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25 November 2021
9:00
Paul Ramsey: Open Source GIS Fights the Three-Horned Monster [2002]
sur Planet OSGeo

This article (PDF) was published in the August 2002 edition of GeoWorld. I came across my hard copy cleaning my desk and thought it might be of historical interest.

They say you can have your software good, cheap or soon, but you can’t have all three. Information technology (IT) project managers have assumed since the dawn of microchips that any improvement in one measure of software quality must inevitably be accompanied by a reduction in others.

Last year, Ross Searle of the Department of Natural Resources and Mines, Queensland, Australia, faced this “three-horned” IT dilemma. He had a problem, and the solution had to be cheap, quick and good. Searle wanted to create an online permitting application that allowed resource officers in his department to quickly evaluate the environmental consequences of tree-clearing permits.

“In Queensland, our state government has legislation controlling the clearing of trees,” says Searle. “If a landholder wishes to clear trees, then he or she has to apply for a permit. A permit will only be issued if the clearing does not cause environmental degradation. The state government has the role of assessing the permits. To do this, officers need access to a broad range of clatasets all generally held in GIS form.”

The three-horned dilemma loomed. The application had to be cheap—budgets for the department were shrinking, no discretionary funding was available, and all the existing licenses for proprietary Web mapping software were tied up in the departmental head office. The application had to be good—data volumes were huge, encompassing several spatial coverages of more than 500MB apiece, so lightweight solutions weren’t going to work. The application had to be ready soon—Searle didn’t have the time or money to program a complex system from scratch.

Searle slew his three-homed dilemma with a combination of “open-source” tools, using the University of Minnesota (LIMN) MapServer to provide Web mapping capabilities and PostGIS/PostgreSQL as the spatial database backend.

“We are using PostGIS to deliver large amounts of natural resource information via a MapServer interface,” adds Searle, “The MapServer/PostGIS application allows users to quickly search for a parcel of land and bring up all the relevant information in a standard format.

“Apart from the cost factors, I believe that the open-source software for this particular purpose is every bit as good—if not better—than the solutions offered by commercial vendors. We have found that the developers of open-source software are responsive to bugs/suggestions/inquiries, etc., more than commercial vendors. In fact, one of the biggest problems we have found in using open source is keeping up with all the improvements.”
What’s Open Source?
Unlike “freeware” or “shareware,” open-source software provides users with more than just a program and some documentation. As defined by the Open Source Initiative, open-source software “must be distributed under a license that guarantees the right to read, redistribute, modify and use the software freely.”

Open-source programs are distributed along with their “source code,” i.e., the programming instructions that control how the software works. Using open-source software is like eating at a restaurant where the recipes are served alongside the meals—you can simply enjoy the food, but you also have the option of taking the recipe home, changing the seasonings and serving the result to your friends.

Successful open-source projects attract developers interested in improving the software. Sometimes their motives are personal, but often they’re professional—the software helps solve a problem, and improvements to the software make doing their job easier. Through time, success breeds success. The projects with the most development activity attract more developers and become more active, improving and addling features at a rapid rate.

After users become accustomed to having complete access to the inner workings of the software they use, proprietary software begins to feel a little limiting, even unnatural. Bob Young, co-founder of the successful open-source company Red Hat, likes to compare purchasing proprietary software to “buying a car with the hood welded shut.”

“We demand the ability to open the hood of our cars, because it gives us, the consumer, control over the product we’ve bought and takes it away from the vendor,” notes Young.

In Young’s view, the software market should be one in which consumers don’t purchase software per se, but instead purchase whatever services they need to effectively use the software they choose.

Rather than purchase a proprietary database system and then purchase support from the proprietary database company, customers instead choose an open-source database and purchase support from an array of support companies with expertise in the chosen database. The net effect is the same—customers have functioning and supported products—but the balance of power is shifted in favor of customers.
An Open-Source Economy
In a healthy open-source economy, every successful open-source software project should have an accompanying set of companies prepared to offer support and consulting to customers who choose to implement systems with the software. DM Solutions Group, for example, is one of the companies supporting the LIMN MapServer—the open-source Web mapping application Searle used to implement his online permitting application. DM Solutions started as a traditional systems integrator, providing consulting services that implement proprietary software packages.

“We were frustrated with the fact that we were dealing with ‘closed boxes’ that magically did all the work for us,” says Dave Mcllhagga, president of DM Solutions, “If it didn’t do it the way we wanted it to, we couldn’t change it or would have to depend and wait on a third party to take care of any problems.

“Now that we are using open-source software, we’re in full control of the situation and can offer not only consulting services, but also free and open software to base it on. We then can guarantee that if there are any problems in the base software, we can fix them. The word ‘workaround’ no longer is part of our vocabulary. If it doesn’t work, we fix it.”

In addition to providing MapServer consulting services, DM Solutions soon became actively involved in MapServer development, adding new features like OpenGIS Web Map Server, Macromedia Flash and GML support. Mcllhagga notes that effort spent on development actually promotes consulting skills, demonstrating that “we are the industry leaders in use of the product, have a high level of expertise and can therefore offer a premium service to our clients.”

Refractions Research occupies a similar position with respect to PostGIS/PostgreSQL, Searle’s other key application component. As the original developers and current maintainers of PostGIS, Refractions Research occupies a market niche and can offer special expertise to the growing community of PostGIS users. Dave Blasby, principal developer of PostGIS, wonders where it’s all leading.

“If you had told me last year that we would be working for clients in Germany, Florida, Montreal and Los Angeles during the next 12 months, I would have thought you were crazy,” says Blasby.
An Unlocked Hood
Products like UMN MapServer and PostGIS/PostgreSQL gain leverage by building on the prior efforts of other open-source projects. For example, by building on the capabilities of PostgreSQL, PostGIS gains all the strengths of an existing industrial-strength database: transactional integrity, write-ahead logs, Structured Query Language (SQL) and standard application programming interfaces.

Similarly, MapServer garners much of its GIS file format compatibility by using OGR and Geospatial Data Abstraction Library (GDAL) file format libraries. Shared code such as software libraries is extremely important to open-source projects, because it allows all projects to improve together in lockstep as enhancements are made to base libraries.

The author of the OGR and GDAL libraries is Frank Warmerdam, an independent contractor in Ontario, Canada. Warmerdam provides customizations of his many geospatial libraries to software companies and system integrators, who bundle the libraries in their products.

“In many cases, the clients gain substantial leverage from building on an existing open-source library, only needing to pay for the specific improvements they require,” explains Warmerdam. “Clients funding initial work on libraries often gain from testing and improvements provided by later users.”

Ironically, Warmerdam’s open-source TIFF image-format library is the basis for TIFF support in several well-known proprietary GIS products as well as many open-source projects. Even proprietary software vendors can take advantage of the group source libraries provide.

Warmerdam has been working in the software industry for many years and says one of the reasons he now works mainly on open-source contracts “is the sense that I’m building something that will outlast the commercial decisions and market success of any one company.”
Future Solutions
As the foundation of several open-source projects, Warmerdam’s libraries will be used for many years. The sheer quantity of open-source GIS projects available can be appreciated by browsing the entries at FreeGIS.org, a clearinghouse Web site for project information.

Unlike Linus Torvalds, the author of Linux, open-source GIS promoters don’t talk of “world domination”—not even in jest as Torvalds did. Instead, they point to the flexibility that’s the hallmark of open-source software and predict increasing ubiquity behind the scenes.

Dave Mcllhagga points to MapServer as an example of open-source GIS infrastructure with strong momentum, and notes the importance of providing a viable alternative to the status quo.

“There’s a reason why MapServer’s user base has been growing,” notes Mcllhagga. “With the availability of user-friendly tools complementing some technically robust technology, there’s reason to believe it can play a substantial role in this business. If open-source alternatives can continue to improve and at least keep commercial vendors honest, they will be successful.”

Regardless of whether open-source OS ever lands on desktops and workstations, it likely will play an increasing role in meeting the specialized needs of the OS community. Wherever people have problems to solve and a willingness to share their solutions with others, open source will continue to flourish.
23 November 2021
17:35
OTB Team: OTB User days 2021
sur Planet OSGeo

OTB User days 2021 will take place in Artilect FabLab from November 29th to December 1st 2021. The detailed program can be found below: Day 1: 09:00 Welcome 09:30 – 12:00 Presentations from users and development team: Introduction New release OTB 8.0: What’s new with OTB 8.0? OTB integration in operational processing chainsBreak pyotb: A […]
10:00
CARTO Blog: Understanding the Impact of Tree Equity in Chicago
sur Planet OSGeo

The Healthy Regions + Policy Lab (or HeRoP) at the University of Chicago integrates innovative GIScience, public health, and statistical approaches to explore, understand, ...
22 November 2021
16:06
GeoSolutions: MapStore Release 2021.02.00 and beyond – Free Webinar
sur Planet OSGeo

Enclosure: [download]

You must be logged into the site to view this content.
1:00
GeoServer Team: GeoServer 2.20.1 Released
sur Planet OSGeo
We are happy to announce GeoServer 2.20.1 release is available with downloads (bin, war, windows), along with docs and extensions.

This is a stable release of the 2.20.x series recommended for production systems. This release was made in conjunction with GeoTools 26.1.
Windows installer
We are pleased to announce the return of the GeoServer windows installer.

Windows installer in action

Thanks to Sander and the GeoCat team for completing this work on behalf of the GeoServer PSC, everyone on the user list who helped test, and Stefan Overkamp for supplying screen snaps for the documentation.

Reference:
- Windows Installer (User Guide)
Improvements and Fixes
New Feature
- GEOS-10228 Wrap the category text values of a legend
Improvements:
- GEOS-10298 OpenSearch REST management API: allow creation of products via PUT
- GEOS-10265 WFS-T Bulk Transaction optimization
- GEOS-10268 Null Support in Features Templating
Fixes:
- GEOS-10299 Reprojection console can now work with AUTO codes
- GEOS-10292 Fixed issue changing worker pool size in raster access
- GEOS-10289 Improve Shapefile Directory performance when working with a huge number of files
- GEOS-10282 GeoServer translations files incorrectly decoded assuming UTF-8 causing translation files like GeoServerApplication_de.properties leading characters represented as question marks
- GEOS-10281 GeoServer log level was not being picked up with during Catalog reload
- GEOS-10277 Add a special keyword for semi-colon as a CSV Separator in WFS request
- GEOS-10273 GeofenceAccesManager index out of bound issue when requesting nested layerGroups
Community Updates
For developers building from source, our community modules are a great place to collaborate on functionality and improvements.
- GEOS-10301 The ogc-api community module resolved conflicting woodstax parser preventing editing of SLD styles
About GeoServer 2.20
Additional information on GeoServer 2.20 series:
- Internationalization of title and abstract
- State of GeoServer 2.20 edition
- Windows Insatller
- Release notes: 2.20.1, 2.20.0, 2.20-RC
19 November 2021
10:21
gvSIG Team: Seminario “Derecho y geomática: el uso de datos espaciales para orientar políticas públicas hacia la justicia social”
sur Planet OSGeo

Como parte de las actividades de la Red JUST-Side, el próximo martes 23 de noviembre a las 12 horas de México, se presentará la ponencia Derecho y Geomática: el uso de datos espaciales para orientar las políticas públicas hacia la justicia social, en el Seminario Institucional del Centro de Investigaciones en Geografia Ambiental (CIGA) de la UNAM.

La transmisión se podrá seguir en directo por Facebook Live y por Youtube.
1:00
EOX' blog: Vector Tiles? That would be great
sur Planet OSGeo

This blog post is about a talk that I held virtually at FOSS4G 2021 in Buenos Aires/Argentina. Our efforts are the continuation of work that we began with LPvis (more info in this blog post). Abstract End of last year we at EOX decided to go all-in on open source vector tiles (MVT). We had two use-c ...
16 November 2021
15:44
GeoSolutions: MapStore Release 2021.02.00
sur Planet OSGeo

Enclosure: [download]

You must be logged into the site to view this content.
10:00
CARTO Blog: Announcing CARTO Spatial Extension for Snowflake
sur Planet OSGeo

At CARTO, our mission is to help customers unlock spatial analytics in the cloud, and today we are excited to announce the general availability of the CARTO Spatial Extensi...
15 November 2021
10:25
gvSIG Team: Guía-T, información urbanística con gvSIG Online
sur Planet OSGeo

El pasado Día Mundial del Urbanismo, la Conselleria de Política Territorial de la Generalitat Valenciana presentó el proyecto Guía-T, desarrollado con gvSIG Online.

Guía-T es una herramienta de agilización de trámites urbanísticos que permite a promotores, redactores y personal técnico funcionario acceder a la información urbanística más relevante de un ámbito y conocer. con carácter previo, cuáles son los condicionantes sectoriales y la documentación necesaria, evitando así, trámites innecesarios.

Os dejo el enlace a la nota de prensa, para los que estéis interesados en este tipo de aplicaciones:

[https:]]
12 November 2021
15:14
Free and Open Source GIS Ramblings: Open source for open spatial data science
sur Planet OSGeo

Thanks to the FOSS4G2021 video team, all talks – including my keynote – are now available online.

I had the honor to be invited to give the closing keynote, talking about how open source can help open science, particularly data science:

I’m convinced that efforts towards more open data science are a worthwhile investment even if current scientific incentive structures are stacked against it.

Until incentive policies catch up, we all can help encourage more people to go the extra mile(s) by properly valuing their efforts, e.g. by celebrating and citing reproducible publications, open research datasets, and open scientific software.
13:20
Jackie Ng: Announcing: mapguide-react-layout 0.14.4
sur Planet OSGeo
This release improves upon the 0.14.3 release with the following fixes and changes:
- The hover highlighting of vector layer features will now only happen if the active map tool is the select tool.
- Fix viewer init of an appdef with static image layers
- Fix support for Map Definitions using arbitrary coordinate systems whose units are not in meters.
- Fix ability to add GeoJSON layers for some WFS services
- A GeoJSON appdef layer can now source data from a browser global variable
- WFS is now supported as an appdef external layer
Download
11 November 2021
19:08
gvSIG Team: GIS Day + III Jornada SIG y Teledetección libre de Costa Rica
sur Planet OSGeo
La próxima semana, del lunes 15 al viernes 19 de noviembre, tendrá lugar la III Jornada SIG y Teledetección libre organizada por la Universidad de Costa Rica. Este año la presencia de gvSIG es considerable, teniendo a vuestra disposición tanto ponencias como un taller.

El evento es gratuito y sin inscripción previa. Se transmitirá vía Facebook-Live en las páginas de Geografía UCR y de la Facultad de Ciencias Sociales.

[https:]]

[https:]]

Respecto al taller denominado “Introducción a las Tecnologías de Información Geográfica y gvSIG Batoví” os dejo la información detallada del mismo:

El taller pretende, mediante un sencillo ejercicio, ilustrar al asistente sobre parte de las herramientas con que cuenta gvSIG Batoví (adaptación del software libre SIG para su uso como herramienta educativa). En el mismo los asistentes realizarán diferentes acciones, a través de un recorrido por diferentes Tecnologías de Información Geográfica (SIG, geoservicios IDE, visualizadores, globos virtuales):
- Manejar herramientas de navegación, selección y consulta.
- Cargar información geográfica a través de geoservicios.
- Crear información geográfica con gvSIG Batoví y con Google Maps.
- Comparar información geográfica histórica.
- Crear un mapa con todos sus elementos.
- Exportar un mapa a pdf para compartir o imprimir
La cartografía a utilizar, proveniente de diversas fuentes, permitirá realizar un análisis temático de la información, con el fin de demostrar el uso de gvSIG Batoví como herramienta de enseñanza. Se requiere contar con laptop personal (Windows o Linux), debiendo tener ya instalado gvSIG Batoví (se descarga de aquí. Luego se descomprime y se ejecuta el archivo gvsig-desktop.exe -en Windows- o el gvsig.sh -en Linux-, debiendo tener abierto el software al momento de comenzar el taller).
17:08
gvSIG Team: Taller de gvSIG Online en las JIIDE
sur Planet OSGeo

Aparte de las numerosas ponencias con tecnología gvSIG, en las Jornadas Ibéricas de Infraestructuras de Datos Espaciales de este año podéis inscribiros a un taller gratuito de gvSIG Online, titulado “Generación de geoportales y administración de una Infraestructura de Datos Espaciales con gvSIG Online”.

Es buen momento para descubrir todo el potencial de esta solución, implantada cada vez en más organizaciones de todo el mundo.

El taller tendrá lugar el próximo jueves 18 de noviembre, a las 16:30 (hora de España)

Podéis registraros aquí.
09 November 2021
10:16
gvSIG Team: gvSIG en las Jornadas Ibéricas de Infraestructuras de Datos Espaciales
sur Planet OSGeo
La próxima semana, en modalidad online, podremos asistir a las JIIDE (Jornadas Ibéricas de Infraestructuras de Datos Espaciales), que este año nos traen numerosas ponencias en las que la base tecnológica de las soluciones es la Suite gvSIG. Esto es, en gran parte, un indicador de como soluciones como gvSIG Online se están convirtiendo en un referente a la hora de poner en marcha Infraestructuras de Datos Espaciales con software libre.

Os indicamos aquí el horario de las ponencias relacionadas con gvSIG:

15 de noviembre: Sesión 2. Perspectivas de la información geográfica. Hora ES: 15.30-17.00
- Control de versiones y edición de cartografía multiusuario con software libre. Producción cartográfica avanzada con geomática libre
- La geomática como herramienta en el descubrimiento del lugar de El Quijote. Análisis geográfico en el ensayo «Un lugar de la Mancha. La patria de don Quijote al descubierto»
17 de noviembre: Sesión 6. Implementación local. Hora ES: 12.00-14.00
- Infraestructura de Datos Espaciales de la Diputación de Albacete. Primeros pasos y evolución hacia su aplicación a la gestión de procedimientos administrativos
- Infraestructuras de Datos Espaciales en la Administración Local con gvSIG Online, de Xàtiva a la Intendencia Departamental de Durazno. Optimizando la gestión territorial municipal con geomática libre
- Evolución y usos de la Infraestructura de Datos Espaciales en el Consorcio Provincial de Bomberos de Valencia. Avances en la plataforma cartográfica para la prevención y gestión de emergencias
19 de noviembre: Sesión 12. Redes de transporte (II). Hora ES: 12.00-13-00
- GVEnRuta, plataforma de cálculo de rutas multimodal de la Comunitat Valenciana. Geomática aplicada a la movilidad sostenible
9:59
gvSIG Team: III Congresso Internacional JUST Side
sur Planet OSGeo

El próximo lunes, 15 de noviembre, en modalidad online, tendrá lugar el III Congreso Internacional JUST Side, con el lema “TIG para la justicia territorial y efectividad de políticas públicas: obstaculos y retos”.

El Congreso forma parte de las actividades realizadas por la Red JUST Side, asociación conformada por distintos grupos de investigación y desarrollo (I+D) impulsada por CYTED, el Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo, creado por los gobiernos de los países iberoamericanos para promover la cooperación en temas de ciencia, tecnología e innovación para el desarrollo armónico de Iberoamérica.

La Asociación gvSIG forma parte de los grupos de investigación, aportando su conocimiento en tecnologías para la gestión de información geográfica y las soluciones para Infraestructuras de Datos Espaciales basadas en gvSIG Online, plataforma utilizada en distintos proyectos de la Red JUST Side.

El programa lo podéis consultar aquí.

El formulario de inscripción al congreso lo podéis encontrar aquí.
08 November 2021
18:43
gvSIG Team: Program of the 17th International gvSIG Conference (online) is now available, and registration (free of charge) period is open
sur Planet OSGeo

Free registration period for the 17th International gvSIG Conference is now open. The Conference is an online event again, and it will be held from December 1st to 3rd.

The full program of the Conference is available on the event website, where registration to the different sessions can be done.

The webinar platform allows to connect to the webinars from any operating system, and in case you can’t follow them, you will be able to watch them at the gvSIG Youtube channel later.

In reference to workshops, all the information about cartography and gvSIG version to install will be published at the gvSIG blog before the conference.

Don’t miss it!
18:35
gvSIG Team: Ya está disponible el programa de las 17as Jornadas Internacionales gvSIG (online), con inscripciones gratuitas abiertas
sur Planet OSGeo

Ya están abiertas las inscripciones gratuitas para las 17as Jornadas Internacionales gvSIG, que serán de nuevo de forma online, del 1 al 3 de diciembre.

Podéis consultar el programa completo en la página web del evento, desde donde podéis realizar la inscripción a cada una de las ponencias.

La plataforma de webinar permite conectarse desde cualquier sistema operativo, y en caso de no poder seguirlos en directo podréis verlos a posteriori, ya que se publicarán en el canal de Youtube del proyecto al igual que en años anteriores.

Respecto a los talleres, en el blog de gvSIG informaremos unos días antes de las jornadas sobre la cartografía a descargar para seguir los talleres, así como de la versión de gvSIG a instalar.

¡Os esperamos!
10:00
CARTO Blog: Fuel Shortage UK Maps & What Location Data Can Tell Us
sur Planet OSGeo

In September 2021 many petrol stations across the UK ran out of fuel. Panic buying was attributed to media reports of a leaked government briefing outlining the shortage of...
03 November 2021
10:00
CARTO Blog: CARTO presenting at GEO Business 2021, UK’s largest geospatial event
sur Planet OSGeo

We’re excited to announce that we’ll be attending and presenting at this year’s GEO Business 2021, taking place on November 24 - 25 at ExCeL London. GEO Business is the UK’...
02 November 2021
15:00
Narcélio de Sá: Novembro / 2021
sur Planet OSGeo
Como não participo ativamente das redes sociais, esta é minha maneira de compartilhar e documentar publicamente o que tenho feito.
Última atualização Nov 14, 2021.
Leitura:
Terminado recentemente:
- A Ilha do Doutor Moreau – H. G. Wells
Meu perfil no Skoob

Nota de transparência: os links dos livros acima têm código de afiliado. Clicando neles, os preços não mudam, mas posso ganhar uma comissão da Amazon.
Assistindo:
Concluído / atualizado recentemente:
- Batalha Bilionária: O Caso Google Earth – Netflix
Cinema
No dia 4 de novembro eu e minha esposa fomos ao Cine Teatro São Luiz para assistir o INCRÍVEL Marighella. Essa foi a primeira vez que fomos ao cinema, ou qualquer outro evento, desde o início da pandemia. A última vez no cinema foi no final de 2019 para assistir o também fantástico Bacurau.
Teatro
No dia 13 de novembro retornamos ao Cineteatro São Luiz para acompanhar a estreia do espetáculo “O Pior de Mim” de Maitê Proença.
Ouvindo:
- Meu Coco – Caetano Veloso (2021)
- Rodger e Teti do Pessoal do Ceará Chão Sagrado – Teti e Rodger Rogério (2019)
Trabalho, projetos e outras coisas
Recentemente comprei alguns pinceis e guache, dessas escolares mesmo, e estou voltando a desenhar e pintar como um hobbie. Desenhei bastante quando criança, mas já tem alguns 15 anos que não desenhava nada. Estou gostando, pois, além de me fazer estudar novamente a teoria das cores, a pintura me tira de frente do computador.
Frase do momento
“Toda vez que vejo um adulto em uma bicicleta, eu já não me desespero quanto ao futuro da raça humana”
— H. G. Wells, escritor

The post Novembro / 2021 appeared first on Narcélio de Sá.
10:00
CARTO Blog: Explore Open Buildings with CARTO Spatial Extension for BigQuery
sur Planet OSGeo

Google recently released the Open Buildings dataset, including 516 million building footprints covering 64% of the African continent. Each building is described as a polygo...
7:00
Lutra consulting: Crowdfunding: Enhancing elevation data and point cloud in QGIS
sur Planet OSGeo

The next round of crowdfunding to improve point cloud and elevation data in QGIS is here! Similar to the previous crowdfunding campaign, we have teamed up with North Road and Hobu to improve elevation and point cloud data in QGIS.

Buildings extracted from lidar, overlaid on top of a cadastral map from 1890. Made by Tibor Lieskovsky, data UGKK SR.

Last year, we added point cloud data to QGIS, thanks to the great support from the community. Based on numerous feedback and suggestions we had over the past year, we have decided to run another campaign to introduce some new tools and enhance user experience when dealing with elevation and point cloud data. Below is a list of those features we intend to introduce. For more details see the crowdfunding page.
Profile tool
A tool for drawing profiles of elevations is essential when working with 3D data, yet it has long been missing from QGIS. While there are several plugins for QGIS that add this missing functionality, unfortunately they all have limitations when it comes to ease of use, performance, integration with the rest of the user interface and wealth of functionality. The goal is to add a profile tool that would cover a wide variety of use cases, and be available immediately out-of-the-box for all QGIS users.

An example of a cross-section: view from the top including the profile line with a buffer, and the profile with two different ways of styling (classification / elevation-based).
Enhanced 2D visualisation of point cloud
A technique that is extremely useful for visualization of point clouds in the 3D map view is the Eye Dome Lighting effect, which adds subtle shading and silhouettes (when there is a greater change of elevation) making it much easier to identify various features of interest that could be otherwise hard to see. To date this feature is only available in 3D QGIS map views, but we would like to introduce it to 2D map view as well! Many GIS workflows and products are still entirely based around 2D views of data (such as digitizing of vector data), so having the extra visual clues which Eye Dome adds is also highly desirable in 2D views.

Top-down 2D view of a classified point cloud. Left: rendering without Eye Dome Lighting (EDL) effect. Right: rendering with EDL.
Filtering point clouds for visualisation
A common requirement of analysts when working with point clouds to work with just a subset of the dataset. This could be as simple as showing only one class of a classified dataset, using only a limited range of elevations, viewing just a particular flight line, or looking at just the first/last returns. Currently, QGIS only provides basic class-based filtering when using rendering based on classification.
Improve 3D map views
One of the limitations is the 3D map view’s window: when it gets closed the configuration of the 3D map view is discarded and any newly opened 3D map view needs to be re-configured again. This is frustrating for users and results in a lot of wasted time! We would like to fix this by keeping 3D views stored in QGIS projects, even when they are not currently being shown. Another issue related to 3D map views is the fact that they are currently only “dock widgets” that can be embedded within the main window. However, often it is preferable to be able to see the 3D view content in a big window, which is quite tricky to do in current QGIS versions (especially when the user does not have multiple displays).
Cloud-optimized point clouds
The new specification of cloud-optimized point clouds (COPC) is current being finalized (October 2021) and it is a very exciting innovation! Inspired by the hugely successful cloud-optimized GeoTIFF (COG) format, the idea is to reuse the existing LAZ format (widely used by the lidar community) and add the improvements which make the format more useful.
More point cloud data formats & more robust loading
While LAS and LAZ files (currently supported by QGIS) are the most common formats for point clouds nowadays, they are not the only ones. In order to support more formats in QGIS we do not need to worry about technical details of each format thanks to the PDAL library. It comes with a multitude of drivers for various formats and services - see [https:] . In QGIS we need to provide a user interface to allow people to get other additional formats to work. Some drivers are always available in PDAL, others are optional and may need extra third-party libraries in order to work. We welcome feedback from the community regarding drivers they consider important.
About the crowdfunding campaign
Please visit the crowdfunding page for more details about the campaign!
You may also like... Input, a field data collection app based on QGIS. Input makes field work easy with its simple interface and cloud-based sync. Available on Android and iOS.
01 November 2021

20:54

Martin Davis: JTS Polygon Triangulation, at last

sur Planet OSGeo

A (long) while ago I posted about "soon-to-be-released" JTS code for polygon triangulation using Ear Clipping. It turned out it was actually in the category of "never-to-be-released". However, later I worked with a student, Dan Tong, on a coding exercise sponsored by Facebook. We decided to tackle polygon triangulation. By the end of the project he implemented a functional algorithm, including handling holes (via the hole-joining technique described by Eberly). To make it release-ready the code needed performance and structural improvements. This has finally happened and the code is out!

Polygon Triangulation

The new codebase has been substantially rewritten to improve modularity and the API. A new data structure to represent triangulations has been introduced, called a Tri It is simpler, more memory efficient, and easier to work with than the QuadEdge data structure previously used in JTS. It provides an excellent basis for developing further algorithms based on triangulations (of which more below)

Most of the reworking involved implementing key performance optimizations, utilizing existing and new JTS spatial index structures:

the Hole Joining phase now uses a spatial index to optimize the test for whether a join line is internal to a polygon
the Ear-Clipping phase has to check whether a candidate ear contains any vertices of the polygon shell being clipped. This has been made performant by using a new spatial index structure called the VertexSequencePackedRtree

Performance must be benchmarked against an existing implementation. Geometry maestro Vladimir Agafonkin has developed an Ear Clipping algorithm in Javascript called Earcut. It's claimed to be the fastest implementation in Javascript. Indeed the performance comparison shows Earcut to be over 4 times faster than some other Javascript triangulation implementations. Earcut has been ported to Java as earcut4j, which allows comparing JTS to it.

Dataset	Size	JTS Time	Earcut4j Time
Lake Superior	3,478 vertices / 28 holes	18 ms	13 ms
Canada	10,522 vertices	35 ms	26 ms
Complex polygon	44,051 vertices / 125 holes	1.1 s	0.64 s
North America with Lakes	115,206 vertices / 1,660 holes	13.3 s	5.4 s

So JTS ear clipping is not quite as fast as Earcut4j. But it's still plenty fast enough for production use!

The triangulation algorithm is exposed as the PolygonTriangulator class (deliberately named after the effect, rather than the algorithm producing it). Here's an example of the output:

Ear-Clipping Triangulation of Lake SuperiorConstrained Delaunay Triangulation

The output of PolygonTriangulator is guaranteed to be a valid triangulation, but in the interests of performance it does not attempt to produce a high-quality one. Triangulation quality is measured in terms of minimizing the number of "skinny" triangles (or equivalently, maximizing the sum of the interior angles). Optimal quality is provided by Constrained Delaunay Triangulation (CDT). In addition to being optimal in terms of triangle shape, the CDT has the nice properties of being (essentially) unique, and of accurately representing the structure of the input polygon. It also removes the influence that Hole Joining holes has on the raw triangulation provided by Ear-Clipping.

I originally proposed that a CDT can be achieved by a Delaunay Improvement algorithm based on iterated triangle flipping. It turned out that this technique is not only effective, but also pleasingly performant. This is implemented in the ConstrainedDelaunayTriangulator class. Running it on the example above shows the improvement obtained. Note how there are fewer narrow triangles, and their arrangement more closely represents the structure of the polygon.

Constrained Delaunay Triangulation of Lake Superior

This code will appear in the next JTS version (1.18.3 or 1.19), and has already been released in GEOS 3.10.

Future Work

It seems possible to adapt the machinery for Ear Clipping to provide two other useful constructions:

Polygon Concave Hull ("Outer Hull") - this requires a triangulation of the area between the polygon and its convex hull. That can be obtained by running Ear Clipping outwards, rather than inwards. A Concave Hull can be constructed by limiting the number of triangles generated based on some criteria such as area, longest edge, or number of vertices. The result is a simplified polygon with fewer vertices which is guaranteed to contain the original polygon.
Polygon Inner Hull - the triangulation constructed by Ear Clipping can be "eroded" to provide a simpler polygon which is guaranteed to be contained in the original.

The property of the Constrained Delaunay Triangulation of representing the structure of the input polygon could provide a basis for computing the following constructions:

Approximate Skeleton construction (also known as the Medial Axis) by creating edges through the CDT triangles
Equal-Area Polygon Subdivision, by partitioning the graph induced by the CDT

The Tri data structure provides a simple representation of a triangulation. I expect that it will facilitate the development of further JTS triangulation algorithms, such as:

Concave Hull of Point Set
Constrained Delaunay Triangulation of Lines and Points

15:58
Free and Open Source GIS Ramblings: Exploring ZAMG’s new open weather data
sur Planet OSGeo

The Central Institution for Meteorology and Geodynamics (ZAMG) is Austrian’s meteorological and geophysical service. And as such, they have a large database of historical weather data which they have now made publicly available, as announced on 28th Oct 2021:

Ab sofort sind hochwertige #Wetter–#Daten der ZAMG für zahlreiche Wetterstationen Österreichs seit Messbeginn kostenlos abrufbar (im Rahmen der Public Sector Information Richtlinie der #EU). Infos und Zugang auf [https:]]
— zamg.at (@ZAMG_AT) October 28, 2021

The new ZAMG Data Hub provides weather and station data, mainly in NetCDF and CSV formats:

I decided to grab a NetCDF sample from their analysis and nowcasting system INCA. I went with all available parameters for a period of one day (the data has a temporal resolution of one hour) and a bounding box around Vienna:
[https:]]
The loading screen of QGIS 3.22 shows the different NetCDF layers:

After adding the incal-hourly layer to QGIS, the layer styling panel provides access to the different weather parameters. We can switch between these parameters by clicking the gradient icon next to the parameter names. Here you can see the air temperature:

And because the NetCDF layer is time-aware, we can also use the QGIS Temporal Controller to step through the hourly measurements / create an animation:

Make sure to grab the latest version of QGIS to get access to all the functionality shown here.
13:19
Free and Open Source GIS Ramblings: MovingPandas v0.8 released!
sur Planet OSGeo
The latest v0.8 release is now available from conda-forge.

New features include:
- More convenient creation of TrajectoryCollection objects from (Geo)DataFrames (#137)
- Support for different geometry column names (#112)
Last week, I also had the pleasure to speak about MovingPandas at Carto’s Spatial Data Science Conference SDSC21:

As always, all tutorials are available from the movingpandas-examples repository and on MyBinder:
30 October 2021
1:08
Tyler Mitchell: Setting up PyQGIS with VSCode+Python on Windows
sur Planet OSGeo

Set up a vscode workspace on Windows to develop with Python 3.8, QT5, and PyQGIS QGIS open source desktop mapping apps.

The post Setting up PyQGIS with VSCode+Python on Windows appeared first on spatialguru.com.
29 October 2021
17:47
Jackie Ng: Announcing: mapguide-react-layout 0.14.3
sur Planet OSGeo
This release improves upon the 0.14.2 release with the following changes:
The viewer now supports static images as a subject layer in an application definition JSON document. This allows the viewer to display any arbitrary image, allowing one to display "maps" that have no real-world geographic basis. For example, you can now use the viewer to view the fictional map of Los Santos

Or if fantasy is your thing, maybe a map of Middle Earth

Because static image layers have no real-world geographic basis, it is incompatible with layers and widgets that assume your map is based on a real-world coordinate system, so things such as:
- XYZ, OSM or Bing Maps Layers
- Coordinate Tracker widget
Will not work with static image layers and will be disabled if you load in an appdef document that has a static layer and one or more of these layers/widgets specified. A viewer static image subject layer will also be operating in stateless mode, so all the caveats and limitations of stateless mode also apply.
On the same topic, the viewer now also supports MapGuide Map Definitions based on arbitrary unit coordinate systems. Map Definitions based on arbitrary coordinate systems are typically things like internal building floor plans or maps whose layers are sourced from non-georeferenced CAD drawings. Again, the same limitations as static image subject layers apply (no XYZ/OSM/Bing backdrops, etc, etc)
For this release we've also extracted the layout-template-specific CSS out to their respective stylesheets. This means that the HTML content for all the viewer template files are now 99% identical with the difference being the template stylesheet reference and the template name to init the viewer with.
The HTML is such that you could now conceivably create a server-side wrapper that can generate the viewer HTML for any template given the name of the template to use. This release includes a new optional index.php entry point that pretty much demonstrates this idea. The index.php entry point takes a template query string parameter in addition to all the other query string parameters and will render out the viewer in your chosen template.
This release also fixes the following issues:
- Init warnings now display again on startup
- Transparency is now properly applied for non-MapGuide subject layers
Download
28 October 2021
11:00
CARTO Blog: Announcing the Spatial Data Scientist of the Year 2021
sur Planet OSGeo

What a week it has been! Thousands of you attended this year’s Spatial Data Science Conference 2021 (#SDSC21), featuring 53 speakers across 35 interactive talks, workshops,...
27 October 2021
2:00
GeoServer Team: GeoServer 2.19.3 Released
sur Planet OSGeo
GeoServer 2.19.3 Released
The GeoServer team are happy to announce GeoServer 2.19.3 release is available for download (zip and war) along with docs and extensions.

This GeoServer 2.19.3 release was produced in conjunction with GeoTools 25.3, this is a maintenance release recommended for production systems.

Thanks to everyone who contributed, and to Ian Turton (Astun Technology) for making this release.
Improvements and Fixes Bug
- [GEOS-9937] - Name of styles with colons are incorrect in REST API
- [GEOS-10072] - WMS dimension default values and nearest match can pollute caches (in GWC and beyond)
- [GEOS-10132] - Deadlock at org.geotools.xsd.XSD.getSchema
- [GEOS-10133] - Connecting to WMS Service via Http Proxy
- [GEOS-10158] - POST request -> j_spring_security_check is in http plain even if proxy base url is in [https]
- [GEOS-10161] - Smart data loader missing PostgreSQL type in DomainModelBuilder
- [GEOS-10162] - GeoServerOAuthAuthenticationFilter creates Anonymous authentication when preAuthenticated principal is not present
- [GEOS-10173] - CoverageViewReader’s format not being secured with Geofence-Geoserver
- [GEOS-10188] - Features templating when deleting a templateInfo all the template contents will be deleted
- [GEOS-10193] - Indirect imports will drop the target table if there is any failure during the import process
- [GEOS-10198] - Features Templating - TemplateRuleService save rule bug
- [GEOS-10200] - GetLegendGraphic can fail if SCALE removes all rules
- [GEOS-10208] - Broken link in DDS/BIL community plugin documentation
- [GEOS-10213] - WMS requests fail on LayerGroup default style names, when used in GetMap/GetFeatureInfo/GetLegendGraphics
- [GEOS-10215] - Layers nested inside a group maintain their prefix even in workspace specific services
- [GEOS-10227] - Features Templating - Included templates are not reloaded on file modifications
- [GEOS-10266] - Features Templating makes getfeatureinfo fail for raster data
- [GEOS-10273] - GeofenceAccesManager throws index out of bound when requesting nested layerGroups
New Feature
- [GEOS-10063] - Add XML templating support to features-templating community plug-in
- [GEOS-10118] - Features templating add include directive in xml templates
- [GEOS-10153] - Features templating UI
- [GEOS-10154] - Feature templating - Add HTML template support
- [GEOS-10165] - Features templating add Rest API
- [GEOS-10166] - Features templating - Add CQL profile field in template rule UI
- [GEOS-10217] - Features templating add GetFeatureInfo support
Improvement
- [GEOS-10080] - Features-templating allows the possibility to reference domain attribute in templates
- [GEOS-10081] - Features-templating allow the encoding of xml attribute in nodes encoded from a Static or Dynamic builder
- [GEOS-10119] - Features templating add managed support and allow simplified templates structure
- [GEOS-10172] - Add support for GeoPackage output in WPS download
- [GEOS-10194] - Improve importer LOGGING
- [GEOS-10265] - WFS-T Bulk Transaction optimization
For details check the 2.19.3 release notes.
About GeoServer 2.19
Additional information on GeoServer 2.19 series:

• WMS GetFeatureInfo includes labels from ColorMap

• Promote WMTS multidim to extension

• Promote WPS-Download to extension

• Promote params-extractor to extension

• Promote GWC-S3 to extension

• Promote WPS-JDBC to extension status

• Promote MapML to extension status

• GeoServer repository transition to main branch

Release notes ( 2.19.3| 2.19.2| 2.19.1 | 2.19.0 | 2.19-RC )
26 October 2021
14:40
Oslandia: (Fr) Oslandia recrute : Ingénieur(e) développement d’applications SIG ( Python / SQL / QGIS ) – OSL2110A
sur Planet OSGeo

Sorry, this entry is only available in French.
11:00
Lutra consulting: Scoped storage in Input for Android
sur Planet OSGeo
Android has forced app to use Scoped Storage for all app related data. If you are using Input app on Android please read carefully for the upcoming update (1.1) of the app in the Google Play Store.
What is Scoped Storage?
In summary, apps need to use a specific part of folders on Android devices to store app related data.

Currently, Input stores your QGIS project and some other settings (e.g. grid shift projection) on /Internal storage/INPUT. With the new Android requirements, the app related data should be stored on /Internal storage/Android/data/uk.co.lutraconsulting.
Update process
For the 1.1 release of Input on Android, there will be an extra process. This process will be a on-off action. When you launch the app after the upgrade, it will copy the data from /Internal storage/INPUT to /Internal storage/Android/data/uk.co.lutraconsulting. Depending on the size of your projects, this can take a couple of minutes. During the process you will see a screen similar to this one:
Best practices
The upgrade and copy process should work smoothly. But we suggest to take the following actions to ensure you will not lose any data during the process:
- Sync all you changes: before upgrading the app, open Input and sync all your local changes to Mergin.
- Storage space: if you work with several projects and large volume of data, make sure you have enough storage. The process will make a copy of your existing /Internal storage/INPUT without deleting it. So, you need at least the size of /Internal storage/INPUT storage available.
Troubleshooting
In case you have encountered any issues, you can take the following steps to fix the problem manually:
- Lack of storage space:
  - Transfer the data through USB cable to your PC.
  - Make a back up of data on your PC.
  - Delete /Internal storage/INPUT on your Android phone/tablet
  - Transfer the data from PC through USB to /Internal storage/Android/data/uk.co.lutraconsulting
- Missing data: the migration process does not delete /Internal storage/INPUT folder. It will rename it /Internal storage/INPUT_migrated. Similar to step above, you can copy the data to the PC and move them to /Internal storage/Android/data/uk.co.lutraconsulting. Alternatively, you can use a file browser app on your device to copy files around.
- If you use Input app on a shared device, the migration process will transfer all the project data from /Internal storage/INPUT and marks the folder as /Internal storage/INPUT_migrated. Therefore, when the next user starts up the app, no data will be present. To fix the issue, you need to manually move the data from /Internal storage/INPUT_migrated to /Internal storage/Android/data/uk.co.lutraconsulting (as described above) for the other users on the device.
Need help
If you need further help, please join us on the community chatroom and we will be able to help you with the upgrade issue (or other Input/Mergin related problems.)
9:49
GeoTools Team: GeoTools 25.3 Released
sur Planet OSGeo

The GeoTools team is pleased to announce the release GeoTools 25.3: geotools-25.3-bin.zip geotools-25.3-doc.zip geotools-25.3-userguide.zip geotools-25.3-project.zip GeoTools 25.3 is published to repo.osgeo.org for direct build integration. This release is made in conjunction with GeoServer 2.19.3. The GeoTools team is grateful to Astun Technology for allowing Ian Turton the time
25 October 2021
14:24
Just van den Broecke: Deploying OSGeo Software using GitOps
sur Planet OSGeo
I use Ansible already for years to provision server instances and for subsequent CI/CD. A recent example is the Geonovum OGC API Testbed . Here (selective) Docker Containers are automatically deployed on GitHub pushes using Ansible called from within a GitHub Workflows.

Now investigating how Terraform could play a key role in (Cloud) infrastructure management. There is a small overlap between Ansible and Terraform but that is a matter of how they are applied in concert.

Ansible is more geared towards maintaining the OS and its running components e.g. Docker Containers on VM-instances. Terraform is more geared to maintaining a Cloud infrastructure, "in the large": acquiring VM-instances, networks, DNS. If you are familiar with AWS, Google Cloud Platform, or in our case Hetzner Cloud , it is what you can do by clicking in their respective UIs or via their APIs like Hetzner's hcloud . And btw: both Ansible and Terraform are Open Source.

Quote from random web-search : "Terraform is designed to provision different infrastructure components. Ansible is a configuration-management and application-deployment tool. It means that you'll use Terraform first to create, for example, a virtual machine and then use Ansible to install necessary applications on that machine."

Both Ansible and Terraform are "declarative", i.e. configuration-based, where the configuration describes a desired state. ctions are "idempotent", i.e. the same action can be applied multiple times, but when the desired state is reached it won't have effect.

As I plan to apply Terraform in other projects as well, I took a deep dive, following hands-on tutorials from the Terraform website. In a very short time I was amazed by Terraform's power and elegance! My ultimate goal was to manage (acquire, configure, access, destroy) the lifecycle of Hetzner Cloud Virtual Machines (VMs, VPS's). This all took about less than two hours, documenting my steps along the way.

I started at the Getting Started page. While there is a lot of stuff on AWS, Terraform Cloud, I basically stuck to these four steps. You may even skip the third (GCP) step. Important is to learn the terminology and config conventions.
1. Installation
2. Using Docker Provider
3. Using GCP Provider
4. Using Hetzner Cloud Provider
  Tip: in IntelliJ IDEA install the Terraform plugin. It will recognise/help with Terraform files!
Step 1 - Installation
learn.hashicorp.com/tutorials/terraform/install-cli

On a Mac with Homebrew install the Terraform CLI:
```
1$ brew tap hashicorp/tap
2
3$ brew install hashicorp/tap/terraform
4
5$ terraform -version
6
7Terraform v1.0.2
8on darwin_amd64
```
That's it!
Step 2 - Using Docker Provider
learn.hashicorp.com/collections/terraform/docker-get-started

I started project dirs under ~/project/terraform/learn/.
```
1$ mkdir -p ~/project/terraform/learn/terraform-docker-container
```
Create a file called main.tf:
```
 1terraform {
 2  required_providers {
 3    docker = {
 4      source  = "kreuzwerker/docker"
 5      version = "~ 2.13.0"
 6    }
 7  }
 8}
 9
10provider "docker" {}
11
12resource "docker_image" "nginx" {
13  name         = "nginx:latest"
14  keep_locally = false
15}
16
17resource "docker_container" "nginx" {
18  image = docker_image.nginx.latest
19  name  = "tutorial"
20  ports {
21    internal = 80
22    external = 8000
23  }
24}
25
```
This defines that we will use the Terraform Provider plugin named "docker" with source kreuzwerker/docker . `Terraform has a registry of official (Provider) plugins.

Now initialize and install the plugin:
```
 1$ terraform init
 2
 3 **Initializing the backend...**
 4
 5 **Initializing provider plugins...**
 6
 7- Finding kreuzwerker/docker versions matching "~ 2.13.0"...
 8
 9- Installing kreuzwerker/docker v2.13.0...
10
11- Installed kreuzwerker/docker v2.13.0 (self-signed, key ID **24E54F214569A8A5**)
12
13. etc
14
```
You may validate your config:
```
1$ terraform validate
```
Moment of truth: create the resources:
```
1$ terraform apply
```
Verify the existence of the NGINX container by visiting localhost:8000 in your web browser or running docker ps to see the container.

That's it for Docker. Next is to use a real Cloud Provider.
Step 3 - Using GCP Provider
learn.hashicorp.com/collections/terraform/gcp-get-started

This was actually more elaborate than the Hetzner Cloud exercise. I had a GCP account, so this went smooth: first creating a Network and later a VM Instance. In this step also learned about using Terraform Providers, Resources, Variables(-files.) I leave this as an option and skip to Hetzner Cloud which is the goal of this post.
Step 4 - Using Hetzner Cloud Provider
The Hetzner Cloud plugin provider was not in the tutorials, but it was still not too hard to extrapolate from Step 3, from various Hetzner tutorials and from the hetznercloud/hcloud Terraform Provider.

Links:
- hcloud Provider: [https:]]
- [https:]]
- [https:]]
- using TF-hcloud with Docker: github.com/insekticid/docker-terraform-hcloud-example
Prerequisite is to have a Hetzner Cloud account and thus login access to console.hetzner.cloud .

Steps:
- create a new Project in [https:]] e.g. TerraformLearn
- add your SSH public key to this project via "Security" menu link left
- generate and copy an API Token for the project
My goal was to create a Debian VM, login there with root and SSH key and destroy it afterwards.
```
1$ mkdir -p ~/project/terraform/learn/terraform-hetzner
```
Create main.tf as follows:
```
 1terraform {
 2   required_providers {
 3     hcloud = {
 4       source  = "hetznercloud/hcloud"
 5       version = "1.27.2"
 6     }
 7   }
 8 }
 9 
10 provider "hcloud" {
11   token = var.hcloud_token
12 }
13 
14 resource "hcloud_server" "node1" {
15   name        = "node1"
16   image       = "debian-9"
17   server_type = "cx11"
18   ssh_keys = ["just@sunda.lan"]
19 }
20 
```
Create a file variables.tf:
```
1 # Set the variable value in *.tfvars file
2 # or using the -var="hcloud_token=..." CLI option
3 variable "hcloud_token" {
4   sensitive = true # Requires terraform = 0.14
5 }
6 
```
Then a file called terraform.tfvars. This is a file with "secrets" normally not checked-in a repo but there are many other possiblities to deal with secrets/credentials:
```
1 hcloud_token = "the token string from Hetzner Cloud API Token"  
```
Moment of truth: apply!
```
1$ terraform init
2
3$ terraform apply -auto-approve
```
Using -auto-approve you skip the interactive approval-step.

Next check the Hetzner Cloud Console project page and see the new VM running!

Try to login on your new VM (IP may also be gotten from output.tf, another exercise):
```
1$ ssh root@<Your VM IP>
```
Then destroy your VM:
```
1$ terraform destroy -auto-approve`
```
There is much more one can do with the Hetzner Provider: basically everything that is available in the console UI and hcloud API: creating Volumes, managing networks, adding SSH-keys, snapshots, using cloud-init etc. See the manpage in particular the Resources drop-down menu: registry.terraform.io/providers/hetznercloud/hcloud/latest/docs

Beware that some Terraform actions are destructive: e.g. upgrading the OS will destroy the existing VM and create a new. For those cases Floating IPs and auto-provisioning with Ansible will help. But in that case Ansible would be more suited to upgrade the OS. One can always execute terraform plan first to see the execution plan. My recommendation is to let Terraform handle the basics, and have Ansible manage the details on VMs.

Alternatives: TF with DigitalOcean using the DO Provider: registry.terraform.io/providers/digitalocean/digitalocean/latest/docs .

All in all: Terraform can form a nice partnership with Ansible.
11:00
CARTO Blog: Today Thousands of Spatial Leaders Gather for #SDSC21
sur Planet OSGeo

Starting today, the Spatial Data Science Conference Online 2021 (#SDSC21) is bringing together thousands of data scientists, developers, academics, and business leaders for...
23 October 2021
2:00
PostGIS Development: PostGIS 3.2.0beta1 Released
sur Planet OSGeo

The PostGIS Team is pleased to release the first beta of the upcoming PostGIS 3.2.0 release.

Best served with PostgreSQL 14. This version of PostGIS utilizes the faster GiST building support API introduced in PostgreSQL 14. If compiled with recently released GEOS 3.10.0 you can take advantage of improvements in ST_MakeValid and numerous speed improvements. This release also includes many additional functions and improvements for postgis_raster and postgis_topology extensions.
Continue Reading by clicking title hyperlink ..
21 October 2021
19:37
BostonGIS: FOSS4G 2021 Bueno Aires Videos are out
sur Planet OSGeo

The Free and Open Source for GIS conference : FOSS4G 2021 Buenos Aires Online took place September 27th to October 2nd, 2021 online. Many of the videos from the conference (including mine on PostGIS) are at FOSS4G 2021 Playlist viewable online.
Continue reading "FOSS4G 2021 Buenos Aires Videos are out"
11:00
CARTO Blog: PMI, Litterati, & Clear Channel Win Geospatial Excellence Awards
sur Planet OSGeo

Initiated in 2007, Geospatial World Awards are internationally-acclaimed premium awards recognizing exemplary practices in the global geospatial industry. With the ceremony...
20 October 2021
22:50
Fernando Quadro: Curso de GeoServer em Novembro
sur Planet OSGeo
Caros leitores,

Gostaria de informá-los que estão abertas as inscrições para mais uma turma do Curso Online de GeoServer que estarei ministrando pela GEOCURSOS. O objetivo do curso é que você aprenda a configurar e compartilhar dados geográficos na internet com o GeoServer. Veja abaixo a ementa:
- Introdução aos padrões OGC
- Instalação e configuraç&ao
- Publicação de dados vetoriais
- Publicação de dados PostGIS
- Formatos de saída
- Instalação de Plugins
- Como realizar upgrade de versão
- Cache
- Estilos utilizando SLD
- Substituição de variáveis no SLD
- Utilização da API Rest
- Criação de camadas com SQL View
- Segurança
- Boas práticas
- Preparação do GeoServer para ambiente de produção
- Gerar HeapMap com o padrão WPS
- Como utilizar o plugin Importer
- Aplicação prática com OpenLayers
O curso ocorrerá entre os dias 29 de novembro e 03 de dezembro das 19:00 as 22:00 (horário de Brasília).

Aqueles que poderem divulgar para seus contatos, agradeço. Quem quiser saber mais informações sobre o curso, pode obtê-las nos seguintes links:
- Site do curso ( [www.geocursos.com.br] )
- Twitter ( [twitter.com] )
- Facebook ( [www.facebook.com] )
- Instagram ( [www.instagram.com] )
22:44
Fernando Quadro: Como corrigir o problema do idioma do GeoServer no Linux
sur Planet OSGeo
Prezados leitores,

Se você costuma utilizar o GeoServer, já deve ter se deparado com o problema do idioma Português Brasileiro, que acontece desde a versão 2.8.x. Você sabe como corrigir esse problema?

Em 2016 eu já escrevi um post sobre isso, ensinando como é possível fazer isso, porém se você estiver utilizando o sistema operacional Linux, é possível fazer isso de uma forma muito mais rápida e fácil. E é isso que vou relatar nos passos abaixo:

1) Verifique se o seu Linux tem o pacote zip instalado
```
$ sudo apt-get install zip
```
2) Vá até a pasta WEB-INF/lib do seu GeoServer e digite os seguintes comandos, um a um:
```
$ zip -d gs-web-core-2.18.2.jar GeoServerApplication_pt_BR.properties
$ zip -d gs-web-demo-2.18.2.jar GeoServerApplication_pt_BR.properties
$ zip -d gs-web-sec-core-2.18.2.jar GeoServerApplication_pt_BR.properties
$ zip -d gs-web-gwc-2.18.2.jar GeoServerApplication_pt_BR.properties
$ zip -d gs-web-wcs-2.18.2.jar GeoServerApplication_pt_BR.properties
$ zip -d gs-web-wfs-2.18.2.jar GeoServerApplication_pt_BR.properties
$ zip -d gs-web-wms-2.18.2.jar GeoServerApplication_pt_BR.properties
```
Lembre-se de substituir nos comandos o número da versão do GeoServer que você está utilizando, que no meu caso foi a 2.18.2

3) Após executar os comandos, reinicie o seu GeoServer, e ele voltará para o idioma inglês.

Espero que tenham gostado da dica!

Você já fazia dessa forma? Responda nos comentários.
22:30
Fernando Quadro: Configurando a inicialização do GeoServer no SystemCtl
sur Planet OSGeo
Prezados leitores,

Se você já instalou o GeoServer em ambiente Linux, sabe que é de suma importância colocá-lo para ser inicializado juntamente com o sistema operacional.

Existe mais de uma forma para se fazer isso, eu mesmo já escrevi um outro post há bastante tempo que ensino como fazer isso adicionando um script de inicialização na pasta /etc/init.d/, porém, hoje vou ensinar a fazer de uma outra forma, utilizando o systemctl.

Para isso, você deve seguir os seguintes passos:

1) Criar um arquivo chamado geoserver.service

2) Inserir o seguinte conteúdo nesse arquivo:
```
[Unit]
Description=GeoServer service
After=network.target

[Service]
Environment=GEOSERVER_HOME=/usr/share/geoserver
Environment=GEOSERVER_DATA_DIR=/usr/share/geoserver/data_dir
Environment=JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64
ExecStart=/bin/bash /usr/share/geoserver/bin/startup.sh
ExecStop=/bin/bash /usr/share/geoserver/bin/shutdown.sh

[Install]
WantedBy=multi-user.target
```
PS: Altere os caminhos das variáveis para a sua realidade, nesse caso o meu GeoServer está instalado na pasta /usr/share/geoserver/

3) Torne o arquivo executável
```
$ sudo chmod +x geoserver.service
```
4) Copie esse arquivo para a pasta /etc/systemd/system/
```
$ sudo cp geoserver.service /etc/systemd/system/geoserver.service 
```
5) Altere a permissão do arquivo para 644
```
$ sudo chmod 644 /etc/systemd/system/geoserver.service
```
6) Habilite o serviço no systemctl
```
$ sudo systemctl enable geoserver.service
```
Agora o serviço já está habilitado, e você deve usar os seguintes comandos para inicializar, parar e reiniciar o serviço do GeoServer
```
$ sudo systemctl start geoserver
$ sudo systemctl stop geoserver
$ sudo systemctl restart geoserver
```
Espero que tenham gostado da dica!

Você já fazia a inicialização do seu GeoServer dessa forma? Responda nos comentários.
7:05
Lutra consulting: Pecan Precision Farming with Input App
sur Planet OSGeo

Precision farming opens an opportunity to increase the gain for a farmer up to 20% with fewer trees.

Making a sustainable profit from farming can be something like tossing a coin. However, today the advancements in digital technology provide the incredible benefit of reducing the unpredictability of farming in general. In pecan farming in particular, the proper know-how of a combination of multiple factors such as soil composition, environmental impact, climate, irrigation and sunlight management are vital for success. Hard data is essential for innovating key decisions. Riaan Burger, a South African farmer, successfully uses open source GIS software to tackle the issues of collecting and utilising such vital data.

Riaan Burger on his pecan farm.
Becoming a Farmer
Riaan Burger’s journey started back in 2017 when, after 20 years’ working as an electrical engineer, he decided to embark on his own business in pecan nut farming. He is a self-taught farmer and co-owner of one of the biggest pecan farms in the district of Weenen, South Africa. At first, Riaan had only a rough idea of how to improve his newly bought 24 hectares of planted orchard.

After reading books on soil structure, type, depth and chemical analyses, he had soil samples taken to create a soil sample map. In his orchard, the trees were planted in 10x10 metres geometric layouts. After 20 years, the trees were already creating shade. Riaan knew that sunlight penetration is important and that pecan trees are susceptible to fungus, so he decided to take a closer look.

“The previous owner of the farm had already started chopping out every second tree. I was in the position where I could compare the yield from areas where trees had been chopped down, to areas where they had not been felled,” explains Riaan.

A photo of the farm taken by drone and initial stage of farming - soil maps.

Riaan realised that understanding the ambient conditions and mapping them to yield results was the right way to go. This was the beginning of his exciting journey in precision farming.
Collecting Data from the Field
It was no easy task for Riaan to get a complete picture. For two years, he only recorded the yield per day, and the relevant orchard block. Later, he used the services of a local consulting company which provided him with surveying applications to help him to set up a basic workflow.

“I record the weight of pecan nuts from each individual tree and I plot it on the map,” Riaan says. “And then afterwards I can see the different cultivars of trees, the weight of nuts they produced and the area in which they were produced. I previously had soil samples taken, so I’ve got soil sample maps. Now I can overlay a yield map over the soil sample map and correlate them”

Despite working well with the surveying app, Riaan was still in need of assistance to prepare data tables and then to export them to Excel sheets and to request map creation. After the consulting company moved from a third-party app to the in-house build solution, things got worse for Riaan: “It was a generic tool and a difficult app to work with. Displaying data was cumbersome. I wanted something that was quick and easy again. Ideally, I would like to capture data on the iPad and have it directly linked to my laptop – that is how I think it should work.”

So Riaan discovered the Input and Mergin suite, a surveying app based on QGIS and a cloud service for data synchronisation, respectively. Despite only a basic knowledge of QGIS and the necessity to learn and experiment, the effort immediately paid off!

“I’ve got Input, I’ve got a Mergin account and I’ve got QGIS. I now have full control of the process. I don’t need to fund a consultant and find that by 8 o’clock at night he has not yet responded to my query, and so I have to back it up with a WhatsApp call,” Riaan explains. “This is something I created entirely myself. I don’t need to ask someone to change this map, or add that icon, modify the legend or change the styling, I am in control of all of it! And I think there is a sense of satisfaction when one gets things going for oneself.”

A farming project in QGIS desktop and Input app UI.

With the Input app, Riaan has gained control of the workflow – something not before experienced. He has gained the freedom to set the project according to his own individual needs. Without much effort, not only the data but the styling, an important factor for him, are synchronised.

“In QGIS I created a style where each bubble represents the kilograms of the yield and the colour represents the variety,” says Riaan. “Then I saw in Input that there is suddenly an extra page on my iPad. So now I have the bubbles and bubble colours on the iPad instantly, which I did not have in previous apps. Previously, I had to create it the long way around, but now it is suddenly on the iPad automatically. I enjoy having that available! In the past, I only had that information by the end of the harvest.”
Cutting Down Trees
The energy invested in creating workflow, capturing and analysing data paid off handsomely for Riaan. All his initial doubts were suddenly eliminated. He has all the information essential for making any important decision right at his fingertips.

“The first time you fell trees, you have nightmares! How on earth you can be cutting your income and destroying 20 years of growth? Now, with the necessary proof at hand, it is easier in your mind to motivate that tree felling is actually your source of income, that it is the right thing to do,” says Riaan. “You can see that the yield from the remaining trees is more than double than before. The trees are healthier, because of allowing sunlight in. Moreover, you also get less pressure from fungus, because pecan trees are easily susceptible to fungus. Now that you have good ventilation, because you have a draught through your orchard, you can see on the map what your exposure to fungus is.”

Orchard with higher density of trees (top) and lower density (bottom).

Riaan continues: “I am not a sole owner, I have a partner. Now I have the data available, so that when we have a meeting I can explain to him this is what I did, this is what happened and this is the result. If you go to a bank manager for a loan, I mean, he really frowns at you when you tell him you are cutting down your trees which produce your income. Then you can explain to him why it is for the better.”

Increase in yield per tree after reduction of tree density.
Harvest Data Analysis and Beyond
The benefits of collecting and interpreting data carefully are limitless. Cutting down trees is just one example of the many advantages of careful data gathering and interpretation.

“Now I see that certain cultivars perform better than others this year,” adds Riaan. “So I can see if they consistently perform better or worse. I can decide, based on these results, what to do: if I need to add more nitrogen or improve soil pH, or whatever the case may be.”

User-friendly tools tailor-made to specific needs, such as the Input and Mergin suite, provided Riaan a way of collecting and analysing his specific type of farming data. His insights for necessary improvements also developed over the past few years.

“At first I did not have the distinction between individual trees and I even said to my partner” continues Riaan, “if only I’d started doing this in the very first season, I would have had 5 years of data to compare – but I didn’t. I will definitely continue to use this suite. It is valuable and I have been using it only for harvest. However, I see now that I can start recording where I have cut down a tree, so I have a record of when and where the tree was cut. I can also record my irrigation data.”

In spite of initial teething problems and the difficult decisions he had to take, Riaan’s success is proof that he has found the right way to go for his own specific pecan farming needs. He has even become an evangelist within the local farming community.

“I am not the only pecan farmer in our district. I am the biggest pecan farmer, but not the only one. I am trying to spread the word around. For example, my neighbour still does not want to cut down his trees. But I am getting there, showing him photos, proving that you have to be aggressive to open up the orchard to get sunlight in – and here is the proof that it has been working for me!”
Download Input Today
19 October 2021
11:00
CARTO Blog: CARTO Spatial Features, now with global urbanity, climatology, & elevation data
sur Planet OSGeo

In late 2020, we released our first derivative data product, CARTO Spatial Features, providing global demographic data and Point of Interest (POI) aggregations by category....
18 October 2021
11:00
CARTO Blog: CARTO & Havas Media Group present at Big Data & AI World Madrid 2021
sur Planet OSGeo

We’re excited to announce that we’ll be presenting alongside Havas Media Group at this year’s Big Data & AI World 2021 (part of the Madrid Tech Show), taking place on O...
10:41
GeoTools Team: GeoTools 26.0 released
sur Planet OSGeo

The GeoTools team is pleased to share the availability GeoTools 26.0 : geotools-26.0-bin.zip geotools-26.0-doc.zip geotools-26.0-userguide.zip geotools-26.0-project.zip This release candidate is also available from the OSGeo Maven Repository and is made in conjunction with GeoServer 2.20 and JTS 1.18.2.UpgradeThere is no specific incompatibilities noted for this release (see User Manual "
2:00
GeoServer Team: GeoServer 2.20.0 Released
sur Planet OSGeo
We are happy to announce GeoServer 2.20 release candidate is available for testing. Downloads are available (bin, war, windows) along with docs and extensions.

This is the first stable release of the 2.20.x series, made in conjunction with GeoTools 26.0 and GeoWebCache 1.20.
Internationalization
The leading feature for this release is the internationalization of Title, Abstract and Contact details for:
- WMS 1.1 and 1.3
- WFS 2.0
- WCS 2.0
See documentation for internationalization support and GSIP-203 proposal for details.

New feature:
- GEOS-10123 Internationalization for title and abstract
- GEOS-10207 Allow creation of internationalized raster legends
- GEOS-10190 i18n support for Contact Information
- GEOS-10185 LayerGroup legend internationalization styles returns multiple values
- GEOS-10177 Allow Default Translation
- GEOS-10129 Add language function for multilingual support in sld
Improvements and fixes:
- GEOS-10205 Layer with i18n title might appear twice in the capabilities, while being contained in a named tree
- GEOS-10204 Default locale is not being used while producing internationalized outputs in Capabilities document
- GEOS-10160 Requested Language in GetCapabilities
Modules Status Information for Extensions
Thanks to Ian for completing a [long outstanding request] [https:] to provide listing everything you have installed:
- The Server Status page now provides a complete list of the loaded modules and extensions
- This extension list can also be checked via REST API (allowing scripts to check if the functionality they require has been installed)
New Feature:
- GEOS-10067 Implement module status in extensions (GISP-143)
Improvements and fixes:
- GEOS-9967 Add Module Status implementation for CSW Extension
Updates and quality assurance
GeoServer continues to be build with the latest open source technologies:
- GeoTools 26-RC
- GeoWebCache 1.20-RC
- JAI-EXT 1.1.20
- ImageIO-EXT 1.3.10
- JTS 1.18.2
- GeoFence 3.5.0
- Flatgeobuf to 3.10.1
The team continues to work with automated code checks, gradually improving the codebase and introducing checks to ensure issues are not re-introduced over time:
- Check system.out.println and printStackTrace statements are not accidentally committed, which can add to logs
- Cognitive complexity checks, start cleaning up methods that are too complex
- Use StandardCharsets when possible, rather than String
- Avoid unnecessary object wrapper creation
- Use short arrays initializers
- Work towards consistent style with checks to avoid C style array declarations, add missing @Override annotations, and check java generics are used
This dedication helps provide confidence in the technology we publish.
WMS
Fixes and improvements:
- GEOS-4939 Coordinate system ISSUE - S-JTSK Krovak East North (EPSG: 5514) - cannot be set up
- GEOS-10032 Group Layer in Catalog Mode Hide not in capabilities when unauthenticated
- GEOS-10013 Mark invalid error while validating or saving a Style
- GEOS-9907 Enable usage of labelPoint function in GetFeatureInfo requests
- GEOS-9759 Set Response Cache Headers in LayerGroups
The following functionality has been removed:
- GEOS-10001 Remove animator and animated GIF support from WMS
  
  Use of WPS Animation process is provided as an alternative
WFS
Fixes and improvements:
- GEOS-10222 WFS CSV OutputFormat delimiter
WPS
Fixes and improvements:
- GEOS-9990 Add GUI and REST API to configure the wps-download module
- GEOS-10073 WPS animation download process should report about eventual time mis-matches
WMTS
Improvements and fixes:
- GEOS-10008 Have GeoServerTileLayer implementing TileJSONProvider
- GEOS-9971 GeoWebCache S3 plugin require AWS creds
INSPIRE Extension
New feature:
- GEOS-10124 Add Language support to INSPIRE extension
Improvements and fixes:
- GEOS-10211 Unable to pass INSPIRE validation: Version is mandatory (WMS)
- GEOS-10192 Inspire extension consistent outputResponse element
- GEOS-10141 Inspire extension better error message on language not found
- GEOS-10163 Incorrect INSPIRE namespace URI
And more!
Fixes and Improvements:
- GEOS-10092 Fix the page description of remote WMS/WMTS connection
- GEOS-10189 I18n improvement using the UTF-8 charset for Chinese translations
- GEOS-10033 Geoserver startup and shutdown shell scripts don’t handle path with spaces
- GEOS-9381 Conversion from boolean true/false in geoserver to SQL Server bit 0/1, is broken
- GEOS-9970 MapML GetFeature bug fix for CRS authority
- GEOS-10201 Geoserver fails to start on Windows 11 beta
- GEOS-10264 Address startup warning File option not set for appender [geoserverlogfile]
- GEOS-9950 MapPreviewPage logs unable to find property: format.wfs.text/csv continuously
- GEOS-10265 WFS-T Bulk Transaction optimization
About GeoServer 2.20
Additional information on GeoServer 2.20 series:
- Internationalization of title and abstract
- State of GeoServer 2.20 edition
17 October 2021
9:00
Paul Ramsey: BC IT Outsourcing 2020/21
sur Planet OSGeo
Public accounts came out at the end of summer, so I have finally gotten around to entering in the central government data (the Health Authorities put out their reports much later) and the results show … the first decline since 2015?

Historically there have been growth pauses every 5 years or so, but the last two were associated with brief phases of government austerity, though that may have been a mirage, since the other thing the pauses all have in common is IBM taking it on the chin.

The loss of a book of Ministry of Health business (twice), then the loss of the desktop support contract, seem to tell the tale of IBM’s decline as an outsourcing juggernaut.

Maximus remains curiously resiliant, even as the MSP program phases out.

And the big shark, the back-office systems contract, which has migrated through a series of corporate names, from EDS (does anyone remember Ross Perot?) to HP Advanced Solutions to ESIT Advanced Solutions is now just … “Advanced Solutions, a DXC Technology Company”.

Looking over the sweep of the curve (which is now 23 years long!) you can see a bunch of interesting moments:
- The initial major privatization around 2005 under the Campbell Liberals, which starts off the whole process.
- The entry of Maximus into the Ministry of Health in 2005 at that same time, which may help explain some of the decline of IBM, as a more nimble competitor gobbles up prospects.
- The entry of Deloitte in 2011, for the Social Services ICM project, which leads to solid growth, but is also the high-water mark, as the planned successor project in Natural Resources around 2015 ends up going more to CGI than Deloitte.
What might the future hold? I have no idea, but unless and until the major backend contract held by “Advanced Solutions” changes (was supposed to run out this year?) I expect the total outsourcing spend to remain in the “holy cow that is a lot of money” range.

Coda: It’s waaaay to early to make any serious statements, but one thing I did notice eyeballing the vendors chart is that while most vendors have been treading water since the NDP took government in 2017, one “vendor” that has notched up 50% growth is my aggregate “local vendors” vendor, which I batch all the smaller companies into so they show up on the chart.

Since one of the NDP platform promises in 2017 was a preference to local companies, this could be sign of progress. Or it could be random! But local companies have gone from about $50M/yr to $75M/yr since 2017, that’s not nothing. Something to keep an eye on for next year.
14 October 2021
16:07
Jackie Ng: Announcing: mapguide-react-layout 0.14.2
sur Planet OSGeo

This release improves upon the 0.14 release with the following changes:
A new XYZDebug base layer type is available to view debug tiles with XYZ coordinates
To add a XYZDebug layer, add a XML fragment like the following to your application definition document.

The purpose of this layer is simply to assist in debugging/identifying XYZ tile coordinates relative to the map you're looking at. It's loaded like any other base layer, so you won't see it overlaid on top of your map. To see it you'll need to change the transparency of the main map in the Viewer Options.
The other noticeable change is that the Select tool now has a flag that toggles whether this tool can pan via mouse drag, as demonstrated in this recording below.

This allows mapguide-react-layout to behave more like the simplified web maps like Google Maps instead of GISes where selection and panning are 2 separately distinct functions.
The final change is that the Refresh Map command no longer tries to request an updated MapGuide runtime map layer/group structure when the viewer is in stateless mode.
Download
12 October 2021
12:00
CARTO Blog: Announcing CARTO Spatial Extension for BigQuery
sur Planet OSGeo

Today we announced at Google’s Cloud Next ‘21 the General Availability of the new CARTO Spatial Extension for BigQuery. Our friends from Google Cloud are showcasing it toda...
11:00
CARTO Blog: CARTO & Google Cloud announce sustainability partnership to fight Climate Change
sur Planet OSGeo

Today we’re excited to announce a further partnership with Google Cloud at the 2021 Google Cloud Next event, supporting their ambitious sustainability program - enabling gl...
10 October 2021
13:38
GRASS GIS: GRASS GIS 7.8.6 released
sur Planet OSGeo

What’s new in a nutshell As a follow-up to the previous GRASS GIS 7.8.5 we have published the new release GRASS GIS 7.8.6 with more than 145 fixes and improvements. This minor release offers new t.downgrade module that allows to downgrade the version of space time datasets created with GRASS development version. Importantly, this release comes with a critical bugfix: the addon extension manager has been updated to match new addon repository structure which solves issues found when installing addons in UNIX-like systems.
11:41
From GIS to Remote Sensing: Major Update: Semi-Automatic Classification Plugin v. 7.10.0
sur Planet OSGeo

This post is about a new update of the Semi-Automatic Classification Plugin v. 7.10.0.
Following the changelog:-added option to Download products for downloading as virtual raster the portion of the image defined with search coordinates (for Landsat and Sentinel-2)-Stack raster bands can now export virtual raster if output extension is .vrt-in Batch the function create_bandset if the option date is 'auto' it tries to get the date of the image from the directory name-in Band set list added button to sort Band sets by date if defined-fixed Scatter plot-fixed Band combination-small fixes to Clip multiple rasters
In particular, the main new feature is the option "Virtual output" in the tab Download products, which allows to download Sentinel-2 and Landsat images as virtual file (i.e. a link to the download url), and also the ability to download only the portion of the image defined by search coordinates. This allows for downloading a subset of the original images reducing the download and processing time, in case the whole image is not needed.
Following a brief tutorial that illustrates this new feature.

For any comment or question, join the Facebook group or GitHub discussions about the Semi-Automatic Classification Plugin.
5:27
Martin Davis: Query KD-trees 100x faster with this one weird trick!
sur Planet OSGeo

Recently a GEOS patch was contributed to change the KdTree query implementation to use an explicit stack rather than recursion. This has been ported to JTS as PR #779 (along with some refactoring).
The change was motivated by a QGIS issue in which a union of some large polygons caused a stack overflow during a KdTree query. The reason is that the poor vertex alignment of the input polygons causes the union overlay process to invoke the SnappingNoder. (For background about why this occurs see the post OverlayNG - Noding Strategies). The snapping noder snaps vertices using a KdTree with a tolerance. The polygon boundaries contain runs of coherent (nearly-monotonic) vertices (which is typical for high-resolution polygons delineating natural areas). When these are loaded directly into a KdTree the tree can become unbalanced.
An unbalanced tree has a relatively large depth for its size. The diagrams below shows the graph of the KdTree for a polygon containing 10,552 vertices. The unbalanced nature of the tree is evident from the few subtrees extending much deeper than the rest of the tree. The tree depth is 282, but most of that occurs in a single subtree.
An unbalanced KD-tree (size = 10,552, depth = 282)
Left: full graph. Right: close-up of graph structure
For large inputs querying such a deep subtree causes the recursive tree traversal to exceed the available call stack. Switching to an iterative implementation eliminates the stack overflow error, since the memory-based stack can grow to whatever size is needed.
However, stack overflow is not the only problem! Unbalanced KD-trees also exhibit poor query performance. This is because deep tree traversals make the search runtime more linear than logarithmic. Increasing the size of the query stack increases robustness, but does not improve the performance problem. The best solution is to build the KD-tree in a balanced way in the first place.
One way to do this is to to break up monotonic runs by randomizing the order of vertex insertion. This is actually implemented in the OverlayNG SnapRoundingNoder, as discussed in the post Randomization to the Rescue. However, using this approach in the SnappingNoder would effectively query the tree twice for each vertex. And in fact it's not necessary to randomize all the inserted points. A better-balanced tree can be produced by "seeding" it with a small set of well-chosen points.
But how can the points be chosen? They could be selected randomly, but true randomness can be quite "clumpy". Also, a non-deterministic algorithm is undesirable for repeatability. Both of these issues can be avoided by using a low-discrepancy quasi-random sequence. This concept has a fascinating theory, with many approaches available. The simplest to implement is an additive recurrence sequence with a constant ? (the notation {...} means "fractional value of"):
R(?) : tn = { t0 + n * ? }, n = 1,2,3,...
If ? is irrational the sequence never repeats (within the limits of finite-precision floating point). The excellent article The Unreasonable Effectiveness of Quasirandom Sequences suggests that the lowest possible discrepancy occurs when ? is the reciprocal of the Golden Ratio ?.
1 / ? = 0.6180339887498949...
Implementing this is straightforward, and it is remarkably effective. For the example above, the resulting KD-tree graph is significantly better-balanced, with lower depth (85 versus 282):
Better-balanced KD-tree (size = 10,552,  depth = 85)
Adding KD-tree seeding to the SnappingNoder gives a huge performance boost to the QGIS test case. For the 526,466 input vertices the tree depth is reduced from 17,776 to 183 and the snapping time is improved by about 100 times, from ~80 s to ~800 ms! (In this case the overall time for the union operation is reduced by only about 50%, since the remainder of the overlay process is time-consuming due to the large number of holes in the output.)
In GEOS the performance difference is smaller, but still quite significant. The snapping time improves 14x, from 12.2 s to 0.82 s, with the union operation time decreasing by 40%, from 31 to 18 secs.
This improvement will be merged into JTS and GEOS soon.
07 October 2021
11:00
CARTO Blog: Spatial Data Science Conference '21: More Speakers Confirmed
sur Planet OSGeo

With just under 3 weeks to go until the 5th annual Spatial Data Science Conference we are very excited to announce new additions to the speaker lineup. Since our first anno...
10:51
Jackie Ng: Announcing: mapguide-react-layout 0.14
sur Planet OSGeo

And here it is! A new major release of mapguide-react-layout.
The release marks a turning point where the map viewer no longer has a hard dependency on a MapGuide Server to function allowing it to be used in more general purpose contexts that may or may not involve a running MapGuide Server.
Not to mention, a whole lot of new features that have already been covered previously.
Download
06 October 2021
11:00
Lutra consulting: Input version 1.0 release
sur Planet OSGeo

Input app has reached a new milestone. Earlier in September, we have released version 1.0 of the app with many new features and enhancements.
Make syncs faster
When you work in a team with several collaborators adding data and photos to the project, the size of the project can get really big. Every time you try to sync your changes, photos from all users will be transferred to your phone. This can take a long while when there are several hundreds of photos collected by other collaborators.

Image below illustrates the difference between having selective sync or the default behaviour (selective sync is disabled):

The configuration file for enabling the selective sync is stored in mergin-config.json which should be placed in the root of your folder. By opening the file in a text editor and adding the following option, the sync will be enabled for photos within your project root folder:

{ "input-selective-sync": true }

Currently, the editing of the file is manual and through the text editor, but we plan to incorporate it within the Mergin plugin for QGIS.

To learn more about how to set up selective sync for your project, you can see the example project. Read more on our help pages for extra configuration options.
One too many!
It is often the case that you have a set of spatial features and you want to record some parameters every now and then. For example, there is a GIS layer representing the manholes and the surveyors carry out regular inspections of the manholes. Instead of duplicating the manhole layer and recording each inspection, you can create a non-spatial table and store each inspection as a new line.

Another use-case for such a feature is that you’d like to attach multiple photos to a single feature.

To learn more about how to configure these types of projects in QGIS you can see the example projects (manhole example and multiple photos example). The documentation pages describes the logic and process in QGIS in more details.
Accuracy metadata
In addition to the display of the accuracy bubble in the app, we have recently added a whole set of new variables to capture the GPS accuracy, e.g. horizontal and vertical accuracy, ground speed and many more. See the help pages to find out how you can set up those variable within your form. Alternatively, you can clone the example project on Mergin website.

In addition to capturing GPS metadata, this feature can be used for geo-fencing: for example, you can only allow users to edit/capture data when they are physically (i.e. their GPS location) within a certain area:

An exciting new feature in the upcoming release of [https:]] : capturing GPS accuracy, speed, position, etc. With this new feature, combined with #QGIS, you can set geofencing rules. pic.twitter.com/zoKsrI29bc
— Lutra Consulting (@lutraconsulting) April 30, 2021
Join our community
If you have any questions, would like to interact with the rest of community or want to give us your feedback, you can join the Slack community channel.

If you would like to add a new feature or have suggestions to improve the app, do not hesitate to contact us on info@lutraconsulting.co.uk
05 October 2021
15:01
GeoSolutions: GeoSolutions Participation at FOSS4G 2021 – an overview
sur Planet OSGeo

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02 October 2021
14:50
Jackie Ng: mapguide-react-layout dev diary part 26: Making the map viewer general purpose
sur Planet OSGeo
Previously, I hinted that the future of mapguide-react-layout besides having a new name (I still haven't come up with a suitable replacement on that front) is to make the map viewer general purpose so that it can be used in contexts that do not require a dependency on a running MapGuide Server.
As I am wrapping up development on the upcoming 0.14 release, I figured it's time for a new dev diary entry that details how we have reached this goal. So strap in. This is going to be a big post with images and embedded webms galore!
MapGuide Support is now optionalTo make our viewer general purpose, we have to be able to load in an Application Definition where the primary Map element does not refer to a MapGuide Map Definition, but instead refers to what I like to call a "subject layer". The "subject layer" is the layer of focus for any given map and can be:
- A WMS layer
- A vector layer
To demonstrate how truly de-coupled we are from requiring a running MapGuide Server, I present to you a new generic viewer template powered by this example application definition document. All the map groups in that example refer to subject layers instead of MapGuide Map Definitions and thus does not require any dependency on a running MapGuide Server.New "generic" viewer templateThe new "generic" viewer template is a minimal and opinionated viewer template geared for use in a general purpose context (without a MapGuide Server).

The template is opinionated in the following sense:
- The commands in the vertical toolbar is pre-defined. You cannot customize the contents through the application definition. This template does offer a configurable context menu.
- The UI is intentionally kept as minimal as possible. There is no Task Pane in this template. Invoke URL commands will load content into floating modal windows. Certain toolbar commands (like the layer manger and selection panel) will load their UI content into drawers.
Although this template is geared for use in a general purpose context, it still can be used with a MapGuide Server as demonstrated below with the Sheboygan dataset

In the MapGuide context, several extra toolbar buttons are enabled. The toolbar differences are outlined below

Supercharged External Layer ManagerFor the upcoming release, the External Layer Manager gets several major enhancements.
Firstly, vector layers now have fully declarative styles with editor support in the External Layer Manager UI. With declarative style support, when adding a new file-based vector layer, you have several choices regarding how the layer is to be added.
You can now choose to create a thematic layer with a pre-defined colorbrewer ramp and optional labeling.

For point-based layers, you may choose to add it as a clustered point layer

Or alternatively, as a heatmap layer

For non-heatmap vector layers, you can view and edit the styles to your liking

General-Purpose-ing various componentsThere are various components that were previously MapGuide-specfic and would be somewhat pointless in a general purpose context. As some of these components are permanent fixtures in some viewer templates, we have to make them somewhat useful in a non-MapGuide context if said template is fed a non-MapGuide appdef.
The Legend component now also displays the list of external layers in its own root category, essentially acting as a compact version of the layer list from the External Layer Manager UI.

The Selection Panel component will now also display attributes of selected client-side vector features.

UTFGrid supportUTFGrid layer support was introduced in the 1st preview release of MapGuide Open Source 4.0. To better advertise this new feature, the viewer supports UTFGrid layers if specified as part of a MapGroup element in an application definition like so

With this XML fragment in place, loading the appdef into the viewer will cause a UTFGrid interaction layer to be created as part of viewer initialization and will manifest as feature tooltips that display on mouse hover.

There is one caveat with UTFGrid support in mapguide-react-layout. You must pair this up with a Map Definition that is in the WGS84.PseudoMercator (aka. EPSG:3857) coordinate system."Stateless" mode for MapGuide mapsUTFGrid layers go nicely with another new feature of mapguide-react-layout: Support for "stateless" mode.
In stateless mode, the viewer:
- Does not create any session ids
- Consequently, it does not issue any CREATERUNTIMEMAP requests on viewer startup
- Will render maps using GETMAPIMAGE instead of GETDYNAMICMAPOVERLAYIMAGE
Because no session id is ever created, the viewer can't use commands that require a SESSION/MAPNAME pair, such as:
- Buffer
- Query
- Theme
- Redline
- Feature Info
- Quick Plot
- Select Within
Such commands if present in the application definition will be permanently disabled in any toolbars and menus where they are referenced in. The viewer will log console warnings about such unsupported commands in stateless mode (as a hint for you to trim out such commands/widgets from your application definition if authoring up a stateless appdef).
Because CREATERUNTIMEMAP requests are not sent in stateless mode, we have a less rich layer/group structure to work with.
Compare the Legend for a stateful version of the Sheboygan map

Versus the stateless version

In the stateless version, we only have the basic layer group structure (computed from the Map Definition resource we fetch on startup) to work with. As a result, we do not have information such as:
- Visible scale ranges for layers
- Style/theme icons for layers
While technically possible, it is currently impractical to fetch all the required Layer Definitions for this information (we would be spamming our MapGuide Server for layer definition requests if loading up a really heavy Map Definition).
Why would you want to use stateless mode? If the caveats listed above are not deal breakers for the type of web map you are trying to serve, stateless mode presents a much more scalable map viewing option in MapGuide as there are zero MapGuide sessions being created or managed, reducing load/memory burden on the MapGuide Server.
Stateless mode is an opt-in feature. You can opt-in to stateless mode by adding a Stateless extension property to the Application Definition like so.

The stateless mode extension property has no effect if your appdef is general-purpose (ie. It does not reference any MapGuide Map Definitions). General-purpose appdefs are implied to be stateless already.
Other notable features/changesClient-side vector layers are now hover-able (to better hint that they're selectable)

The fusion print command/widget is now supported. You will no longer get an error placeholder in toolbars and menus where this command/widget was referenced. This command will export the current map image out to a separate ready-to-print browser tab.

The previous WMS layer selection tool has been incorporated into the regular Select tool, making it the final one-stop-shop for selecting anything, be it MapGuide layers, WMS layers or client-side vector layers. Also when the Select tool is active, you can now still pan via middle-click mouse drag.In ClosingExpect the 0.14 release of mapguide-react-layout to come out soon. I am just finishing up documentation aspects of this release.
30 September 2021
11:00
CARTO Blog: CARTO selected for AI4Cities Phase 2 Sustainable Mobility Project
sur Planet OSGeo

Last year six leading European cities came together to form AI4Cities, an EU-funded Pre-Commercial Procurement (PCP) project. The three-year EU-funded project was establish...
29 September 2021
11:00
CARTO Blog: Climate Change & Extreme Weather: Hurricane, Wildfire, & Flood Maps
sur Planet OSGeo

This summer has witnessed several extreme weather events, including heatwaves, flash floods, and wildfires. With average temperatures having risen by 1.2C since the industr...
2:00
SourcePole: FOSS4G 2021
sur Planet OSGeo
Slides from Sourcepole presentations at the online FOSS4G 2021 conference Buenos Aires.
- Cloud optimized formats for rasters and vectors explained
- The state of Vector tile servers
- Geospatial programming with Rust
- Using game engines for 3D geospatial development
28 September 2021
17:57
gvSIG Team: III Congreso Internacional JUST Side
sur Planet OSGeo

El 15 de noviembre, en modalidad online, tendrá lugar el III Congreso Internacional JUST Side, con el lema “TIG para la justicia territorial y efectividad de políticas públicas: obstaculos y retos“.

El Congreso forma parte de las actividades realizadas por la Red JUST Side, asociación conformada por distintos grupos de investigación y desarrollo (I+D) impulsada por CYTED, el Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo, creado por los gobiernos de los países iberoamericanos para promover la cooperación en temas de ciencia, tecnología e innovación para el desarrollo armónico de Iberoamérica.

La Asociación gvSIG forma parte de los grupos de investigación, aportando su conocimiento en tecnologías para la gestión de información geográfica y las soluciones para Infraestructuras de Datos Espaciales basadas en gvSIG Online, plataforma utilizada en distintos proyectos de la Red JUST Side.

Programa del Congreso:
16:59
Free and Open Source GIS Ramblings: Movement data in GIS #37: “Understanding Movement Data” webinar
sur Planet OSGeo

Two weeks ago, I had the pleasure to speak at SystemX’s seminar series. The talk features a live demonstration of my protocol for exploring movement data, powered by Jupyter, Pandas, Holoviews, Datashader, GeoPandas, and MovingPandas. So if you haven’t read the paper yet, here’s the chance to watch the talk version:
11:00
CARTO Blog: How to Build Scalable Spatial Apps with Vue.js & CARTO
sur Planet OSGeo

Vue.js is one of the fastest growing frameworks for building web applications. It is really versatile and is a reactive framework that provides core libraries and a wealth ...
27 September 2021
11:00
CARTO Blog: Using Location Intelligence to Ease the Supply Chain Crisis
sur Planet OSGeo

Soaring pandemic demand, disruption of trade flows (including port closures in China), along with a shortage of drivers and other labour have combined to create a global su...
26 September 2021
21:16
Even Rouault: Order of GeoJSON properties and graph theory
sur Planet OSGeo

All this story started with this QGIS bug about a crash when a user adds a new field to a GeoJSON file. Who is the culprit between GDAL and QGIS could be debated. Let's look at the GDAL side of things.
Let's consider this simple GeoJSON file:
{ "type": "FeatureCollection", "features": [
{ "type": "Feature", "geometry": null, "properties": { "A": "a", "C": "c" },
{ "type": "Feature", "geometry": null, "properties": { "A": "a", "B": "b", "C": "c" }
]}
GDAL versions up to 3.3.x will expose a layer definition with the fields in the following order, [A, C, B], and this is what confused QGIS, since the C field was appended as the last action, and QGIS expected it to be the last field.
One could also argue that we should not worry about the order of properties since a JSON object such as the "properties" one is unordered. However the JSON parser and writer used by GDAL has the property of respecting the order of appearance of the keys which makes GeoJSON a format that behaves similarly to other formats such as Shapefile, GeoPackage or CSV where the field order is fixed. But in a GeoJSON file where there is no declaration of properties (no "header"), and when properties are omitted in some features, presenting a consistent field order is more challenging.
How does current GDAL in current proceeds to build the list of fields ? That's very simple: iterate over features, for each feature, iterate over its properties, and as soon as a new property is found, append it to the list of properties of the layers. So on our above example, after the first feature, we have [ A, C ]. And when parsing the second feature, we append B to it, hence [A, C, B ]. We can also notice that the order in which features appear in the collections influences the order of properties exposed in the layer definition.
How to fix that ? For that very simple case, we could say "B appears after A, which is already in our list, and before C, which is already in our list and was just after A, so let's insert it in between". Great ! Problem solved ? Unfortunately not.
What if you see features with the following properties:
- [A, D], ==> current consolitated list [A, D]
- then [A, B, D], ==> current consolitated list [A, B, D]
- then [C, D], ==> hum C is before D, but where relatively to A and B ??
- then [A, C], ==> we know now that C is after A. But before or after B ?
- then [B, C], ==> ok, before B. So final list is [A, B, C, D]
Our simple logic of insertion no longer works here, and we can know feel that the problem is much more involved than what it initially looked like. We could also have situations where the dataset is so sparse that the relative order of some fields is indeterminate. Or where fields appear in non consistent order in several features.
My initial though was to use a sorting algorithm, such as std::sort in the standard C++ library, with a custom comparison function that would use the (i, j) apparition order ( (i, j) means that field i immediately appears before j in a feature ). But there are several issues:
- the sort algorithm may invoke the comparison function with any pair of field names, but we have only a knowledge of a subset of those. If we build a graph where the nodes are the field names and a directed edge between i and j means that field i immediately appears before j in a feature, then we can know if there's a path between any tuple of nodes by using standard graph algorithm.
- the comparison function of std::sort implies that we have a strict weak ordering. When there's a path in the graph between 2 nodes, the ordering is clear. We note immediately that the graph should not have cycles, otherwise we would violate the asymmetry property of the strict weak ordering. So when building the graph, we should reject any new edge i->j that would result in a cycle, which boils down to finding if the reverse path j->i already exists. But what to do for nodes that aren't related by a path ? We could decide that they are incomparable. However the "transitivity of incomparibility" property could then be violated. For example if there's no path between A and B, and between B and C (for example B is an isolated node), there might be a path between A and C. So it is far from obvious that we can define a comparison function that respects the strict weak ordering. And if it failed to respect it, then the std::sort() execution is undefined behaviour, meaning that anything can happen: at best, a wrong result; at worse, a crash, infinite loop, etc. Look at this post for other examples of comparision function that subtely violate strict weak ordering
At the end, we want to somewhat "linearize" our graph, by respecting the directed edge.
So given:

We want to get a rresult like [A, F, B, G, D, C, E], or [F, A, B, C, D, E, G], or ...
It appears that this is a known problem in graph theory: computing the topological ordering of a directed acyclic graph. As show in the above example, there are in general several solutions. To try to make the result less "random", we use lexicographical order of field names for the working set S of the Kahn's algorithm, which is an additional sorting rules for nodes that have no direct relationship in the graph.
The result of that work is in [https:]]
25 September 2021
16:15
Free and Open Source GIS Ramblings: Exploring Vienna’s street-level Lidar “Kappazunder” data sample
sur Planet OSGeo
Kappazunder is the city of Vienna’s database created during their recent mobile mapping campaign. Using vehicle-mounted Lidar and cameras, they collected street-level Lidar and street view images.
Slide from the official announcement on Thursday, 23rd Sept 2021. Full slide deck: [https:]]
Yesterday, they published a first sample dataset, containing one trajectory on data.gv.at. The download contains documentation, vector data (.shp), images (.jpg), and point clouds (.laz):
Trajectory
The shapefiles contain vehicle location updates, photo locations, and areas describing the extent of the point clouds. Since the shapefile lack .prj files, we need to manually specify the correct CRS (EPSG:31256 MGI / Austria GK East).

The vehicle location updates and photo locations contain timestamps as epoch. However, the format is a little special:

To display a human-readable timestamp, I therefore used the following label expression:
```
format_date( datetime_from_epoch( "epoch_s"*1000), 'HH:mm:ss')
```
Adding these labels also reveals that the whole trajectory is just 2 minutes long. This puts the download size of over 5GB into perspective. The whole dataset will be massive.
Lidar
The .laz files are between 100 and 200MB, each. There are four .laz files, even though the previously loaded point cloud extent areas only suggested three:

Loading the .laz files for the first time takes a while and there seem to be some issues – either on the user end (me) or in the files themselves. Trying to load content of the ept_ folders only results in very few points and multiple “invalid data source” errors:

For the few point that are loaded, it looks like the height information is available:

Update on 2021-10-01: I’ve reported the data loss issue and Martin Dobias has provided a first work-around that makes it possible to view the data in QGIS:
Images
The street view images are published as cubemaps. Here’s a sample of the side view:
23 September 2021
19:46
gvSIG Team: Las 17as Jornadas Internacionales gvSIG cambian a modalidad online
sur Planet OSGeo

Debido a las restricciones existentes en la movilidad entre países actualmente, las 17as Jornadas Internacionales gvSIG serán finalmente un evento online.

Por este motivo, el periodo de envío de comunicaciones se amplía hasta el 20 de octubre para que las personas que no podían estar presentes y deseen realizar una ponencia puedan presentar sus propuestas. Así mismo, el periodo de inscripción de las Jornadas Internacionales gvSIG comenzará finalmente el 27 de octubre, con la publicación del programa.

Toda la información sobre las normas para la presentación de comunicaciones puede consultarse en el apartado ‘Comunicaciones‘ de la web de las jornadas.
19:43
gvSIG Team: 17th International gvSIG Conference will finally become an online event
sur Planet OSGeo

Due to current restrictions on mobility between countries, the 17th gvSIG International Conference will finally be an online event.

For this reason, the period for sending communications is extended until October 20th so that people who could not be present and wish to make a presentation can present their proposals. Likewise, the registration period for the gvSIG International Conference will finally start on October 27th, when the program is published.

All the information about the rules for submitting proposals can be consulted in the “Communications” section of the conference website.
11:00
CARTO Blog: Spatial Data Science Conference '21: First Speakers Announced
sur Planet OSGeo

The 5th annual Spatial Data Science Conference is just over a month away and we are very excited to announce our first lineup of speakers! #SDSC21 will be available to the ...
10:00
CARTO Blog: Canary Islands Volcano: Mapping La Palma Lava Flow & Damage
sur Planet OSGeo

On Sunday the Cumbre Vieja volcano on La Palma in the Spanish Canary Islands started erupting causing the destruction of 300 homes and forcing the evacuation of more than 6...
9:00
MapTiler: Vector basemaps in QGIS
sur Planet OSGeo
The new version 2.0 of MapTiler QGIS Plugin was released. The first version of the plugin was written in Python and released as open-source last year. We are happy to see that our source code was ported into QGIS C++ core with some improvements.

The new version of the MapTiler plugin takes advantage of the rewritten code and pushes our maps from MapTiler Cloud almost to perfection. Our maps in Cloud contain data of the entire planet, with details down to the street level, thanks to the OpenStreetMap project and community. But you are not limited just to our Cloud.

Load these and many other map styles directly from MapTiler Cloud
Open vector tile style from any URL
MapTiler plugin is the easiest way how to add any complex vector tile map hosted anywhere on the Internet into your QGIS project. Enjoy the comfort of adding your style.json with multiple sources in just a single click.
Add context to your map with icons
Version 2.0 is packed with a lot of visual improvements. Labels, line width, color interpretation, opacity setting, and many other small enhancements make the maps better. However, the biggest improvements are map symbols. The first version suffered from a lack of possibility to display icons. The new version handles them with ease.

Let users understand your map
Having place names in a local language can significantly improve how users understand the map. Use Customize in Cloud option from the MapTiler plugin menu to choose from more than 50 languages and customize the language of the map to suit your needs.

New Outdoor style in QGIS
In MapTiler, we all are outdoor enthusiasts. That’s why we recently announced a new Outdoor map style. Hiking trails, biking routes, points of interest, landcover, hillshade, and contour lines, everything you wish for in a good outdoor map is now available in QGIS as a base map for planning your adventure.

High DPI print as the main benefit of vector maps
The previous version of the plugin brought to QGIS high-quality vector maps. However, few issues were identified when printing in high DPI or on retina displays. The new version solved all those issues and you can print maps in high resolution. Set high DPI, print or export your map to PDF, and zoom in deeply to inspect the level of sharpness. Even though our raster tiles are optimized for serving, you can never get such detail as with vectors.

We also prepared a new basemap allowing attribution-free print-out.

Keep in mind that for printing maps or exporting from MapTiler Cloud you must have a commercial plan, see terms and conditions or contact our sales.
Download/upgrade the plugin for free
Learn more about the plugin or get it by searching maptiler in the plugin service in QGIS. Installing the plugin is straightforward:
1. Open QGIS
2. Click on the menu Plugins ? Manage and Install Plugins…
3. Search for maptiler
4. Click on the Install Plugin (Reinstall, if you already have the old version installed)
5. Restart QGIS
6. Right-click on the MapTiler plugin ? Account…
7. Follow the link after Get a FREE key Now, just add the key and start loading maps.
Open-source code on GitHub
The MapTiler plugin for QGIS is released under an open-source license on GitHub. Feel free to report issues or send pull requests!

Links:
22 September 2021
11:00
CARTO Blog: Capturing the Sensitivity of National Wind Energy Potential to Local Siting Challenges
sur Planet OSGeo

Onshore wind energy is among the fastest growing utility-scale renewable energy technologies in the world. With falling costs, usage is on the rise with wind generation cap...
21 September 2021
11:00
CARTO Blog: A Look Back at 18 Months of COVID Grants & Maps
sur Planet OSGeo

18 months ago, on the same day that the World Health Organization (WHO) declared COVID-19 a pandemic, CARTO announced that it would be making its platform available for fre...
18 September 2021
23:35
Cameron Shorter: Open source peer bonuses
sur Planet OSGeo
Congratulations Alyssa, Angelos and Aiden for your Google's Open Source Peer Bonus award. This cool award enables Google employees to recognize and thank a few valued open source contributors. It includes a token financial contribution - enough to take the family out for dinner at a nice restaurant.
Alyssa Rock
Alyssa has played a pivotal role in growing and expanding, The Good Docs Project. She has been doing this by:
1. Being an excellent technical writer, prolifically writing quality material for the project.
2. Reaching out at conferences and related events, advocating for the project, and attracting scores of new contributors.
3. Pro-actively helping establish a very supportive and inclusive culture, leading by example, being incredibly warm and encouraging in helping to onboard people, and writing our code-of-conduct.
4. Stepping up to do much of the grunt work to establish community processes.
5. Doing the many other small things that help make an open source project successful.
Angelos Tzotsos
Angelos has been a lynch pin contributor to many of the geospatial open source projects. Most notably, he is one of the primary coordinators of the OSGeo-Live linux distribution of open source geospatial software, supporting the 50+ projects represented to get the software up to scratch and compiling on the distribution. He is very competent, always humble, very wise, always supportive of others, and very effective at building open source communities. Notably, he has been voted onto the board of the Open Source Geospatial Foundation.
Aidan Doherty
Aidan has been a steady and reliable contributor to The Good Docs Project, taking on core background tasks, like community building (kicking off an unofficial welcoming committee for new members), and setting up a base template working group (from which all of the rest of our project templates will depend.) He takes on the unglamorous but important work which makes an open source project successful.
15 September 2021
18:55
Jackie Ng: Announcing: FDO Toolbox 1.5.2
sur Planet OSGeo
This release addresses 2 issues:
- The --connect-params switch of the list-connection-params command in FdoCmd is now optional. This means you can now list required connection parameters for a given FDO provider without having to establish a data store connection.
- This release contains updated FDO binaries which include the following changes:
Download
9:51
Free and Open Source GIS Ramblings: Movement data in GIS #46: trucks from space
sur Planet OSGeo

Can we reliably measure truck traffic from space? Compared to private transport, spatiotemporal data on freight transport is even harder to come by. Detecting trucks using remote sensing has been a promising lead for many years but often required access to pretty specialized sensors, such as TerraSAR-X. That is why I was really excited to read about a new approach that detects trucks in commonly available Sentinel-2 imagery developed by Henrik Fisser (Julius-Maximilians-University Würzburg, Germany). So I reached out to him to learn more about the possibilities this new technology opens up.
Vehicles are visible and detectable in Sentinel-2 data if they are large and moving fast enough (image source: ESA)
To verify his truck detection results. Henrik had already used data from truck counting stations along the German autobahn network. However, these counters are quite rare and thus cannot provide full spatial coverage. Therefore we started looking for more complete reference data. Fortunately, Nikolaus Kapser at the Austrian highway corporation ASFINAG offered his help. The Austrian autobahn toll system is gantry-based. It records when a truck passes a gantry. Using the timestamp of these truck passages and the current traffic speed, it is possible to estimate truck locations at arbitrary points in time, such as the time a Sentinel-2 image was taken. This makes it possible to assess the Sentinel-2-based truck detection along the autobahn network for complete Sentinel-2 images.

Overall, Sentinel-2-based detections tend to underestimate the number of trucks. Henrik found a strong correlation (with an average r value > 0.8) between German traffic counting stations and trucks detected by the Sentinel-2 method. These counting stations were selected for their ideal characteristics, including distance from volatile traffic situations such as a high number of highway intersections. This is very different from our comparison which covers autobahn sections in and near Vienna. We therefore expected larger detection errors. However, our new Austrian analysis reaches similar results (with r values of 0.79, 0.70, and 0.86 for three different days 2020-08-28, 2020-09-22, and 2020-11-06).

Thanks to the truck reference locations provided by ASFINAG, we were also able to analyze the spatial distribution of truck detections. We decided to compare ASFINAG data (truth) and Sentinel-2-based detections using a grid based approach with a cell size of 5×5 km. Confirming Henrik’s original results, grid cells with higher detection than ground truth values are clearly in the minority. Interestingly, many cells in Vienna (at the eastern border of the image extent) exhibit rather low relative errors compared to, for example, the cells along Westautobahn (the east-west running autobahn in the center of the image extent).

Some important remarks: The Sentinel-2-based detection method only works for large vehicles moving around 50km/h or faster. It is hence less suited to detect trucks in city traffic. Additionally, trucks in tunnel sections cannot be detected. To enable a fair comparison, we therefore flagged trucks in the ground truth dataset that were located in tunnels and excluded them from the analysis. Sentinel-2 captures the region around Vienna around 10:00 o’clock in the morning. As a result, it is not possible to assess other times of day. Finally, cloud cover will reduce the accuracy. Therefore we picked images with low reported cloud cover percentage (< 5%).

It is really exciting to finally see a truck detection method that works with readily available remote sensing data because this means that it is potentially transferable to other areas of the world where no official traffic counts are available. Furthermore, this method should be in line with data protection regulations (avoiding identification of individuals and potential reconstruction of movement trajectories) thus making it possible to use and publish the resulting data without further anonymization steps.

This post was written in collaboration with Henrik Fisser (Uni Würzburg / DLR) and Nikolaus Kasper (Asfinag MSG). Keep your eyes open for upcoming detailed publications on the Sentinel-2-based method by Henrik.

This post is part of a series. Read more about movement data in GIS.
14 September 2021
19:17
GeoTools Team: GeoTools 26-RC Release Candidate
sur Planet OSGeo

The GeoTools team is pleased to share the availability GeoTools 26-RC : geotools-26-RC-bin.zip geotools-26-RC-doc.zip geotools-26-RC-userguide.zip geotools-26-RC-project.zip This release candidate is also available from the OSGeo Maven Repository and is made in conjunction with
17:03
Even Rouault: The ultimate guide for successful contribution to open source
sur Planet OSGeo

(This is a post I started on December 2019 and didn't publish because I felt it was too negative. But recent events show that it is still a current topic, and at least this will document my own preception of things)
We have lately stumbled upon a few clumsy attempts of corporations at contributing to open source software. Needless to say this is a bumpy ride not for the faint of heart, from both side of the equation.
If you just want to stop your reading here, just remember that good old motto: When in Rome, do as the Romans do. And be prepared to become a Roman citizen.

Us, open source developers have our own hard-to-decipher customs. We pay tribute to the Allmighty Git (*), preferably his most revered (often with awe) incarnation called GitHub. You may also find followers of GitLab, gitea, gitorious.In that case, never pronounce the word 'GitHub' before them. It is also said that some might still use email patches: be sure to set a 80 character limit to lines, use LF line endings and refrain from using PNG signatures. Be sure to stay away from SourceForge followers. They will continuously impose on you advertising messages that will destroy your sanity.
You should subscribe to mailing lists. Be wary of trolls. We may occasionally engage into flame wars, generally sanctionned by motions. We are structured into groups that defer to a Project Steering Committee to decide (or not) which way to follow. Our groups regularly gather at solstice time in dark rooms for a week-long trance (note: was written pre-pandemic), known as a hackfest, hackathon or code sprint. For the tribes involved in geospatial, we have an annual Pow-Wow, called FOSS4G, during which we temporarily bury the hatchet and occasionaly thank our sponsors. You may stumble upon a C89 developer sharing a beer with a Java 11 one, or an adorer of Leaflet trying to convert a OpenLayers follower. If you want to join the Pow-Wow, remove your tie and suit, wear a t-shirt and sandals, and make sure to display a prominent "I Love Open Source" sticker on your laptop. You may also add a "I Love Shapefile" or "I Love GeoPackage" sticker, but only if you are confident to which one the group pays tribute. Failure to display the appropriate sticker will expose you to terrific insults about 10-character limits or obscure write-ahead log locking issues. If unsure, use the "I ? Shapefile" sticker.
We have taboo words. Thou Should Not Talk about business plan, intellectual property, patent portfolio, customer demand, strategy, costless SDK, CVE number, internal policy, consolidated codebases, education license fees. Planning and roadmap should also be pronounced with care, as some tribes will probably not have even the slightest idea of what you talk about.
If despite all those strange habits, you want to join with us, be prepared to follow a long and demanding initiation path. You will have to demonstrate your (possibly affected) adoration to our principles. As strange as it can be, we abhor being offered large presents that we cannot prevent ourselves from seeing as Trojan horses. You will rather have to locate a long list of problems pinned on a wall called bug tracker where each member of the community has written an issue or a wish he has. Start by the modest one that makes sense to you, solve it and offer its resolution to the Reviewer in a sufficiently argumented Pull Request. The Reviewer, which often equates to the Maintainer, will scrutinize at your gift, often at night time after Day Job. He may decide to accept it right away, or return it to you with a comment requesting a change, or just ignore it with the highest contempt. Be humble and obey to his command. You may beg for enlightenment, but never object even if you cannot make sense of his rebutal. He is the allmighty after the Allmighty. Never Rebase if asked to Merge; never Merge if asked to Rebase. Refactor when asked, but don't when not ! You should rewrite history before submitting, or maybe not. If unsure, consult Contributing.md, or be prepared that RTFM will be yelled at you (only for the tribes that don't have yet written CodeOfConduct.md). Do not even consider objecting that you have not been tasked to address his demands. You must also make sure to listen to the complaints of the Continuous Integration (CI) half-gods: the Reviewer will probably not even look at your gift until CI has expressed its satisfaction. Retry as many times as needed until they are pleased. You may attempt at submitting a RFC, but be prepared for lengthy and lively discussions. Listen, correct or you may not survive to your first "-1" spell !
We praise especially gifts that have no direct value for you: improved test suite (e.g. [https:]] ), documentation addition and fixes, answering to users on the mailing list. Only when you feel that you have built enough trust, you might try to offer your initial gift. But, even if it is accepted, the most surprising habit is that your gift will remain yours. You will have to make sure you regularly remove the dust that accumlates on it over time, so it remains constantly shiny. While removing dust on your gift, never neglect from removing it also from nearby gifts offered by others. Otherwise the Maintainer might threaten at invoking the terrible Revert incantation on you. Also consider that existing contributors to a project might see your new code, they won't have directly use of, as an extra burden to their daily tasks (studying the commit history of [https:]] , or even more crudly at [https:]] , demonstrates that)

Ready for a ride, and possibly enjoying the feeling that "our" code can also become "yours" ?

(*) some tribes, cut off from the rest of the world, are said to still pursue their adoration of more ancient divinities sometimes known as SVN or CVS. We cannot confirm and have eradicated the last remains of those old cults.
2:00
EOX' blog: EOxServer 1.0
sur Planet OSGeo

With the release of version 1.0 of the EOxServer achieved it is a good time to shed some light on this workhorse software more than ten years in active development. Even before this milestone, EOxServer was and is used in quite a number of operational deployments, most notably in the VirES line of p ...
2:00
GeoServer Team: GeoServer 2.20-RC Released
sur Planet OSGeo
We are happy to announce GeoServer 2.20-RC release candidate is available for testing. Downloads are available (zip and war) along with docs and extensions.

This is a GeoServer release candidate made in conjunction with GeoTools 26-RC and GeoWebCache 1.20-RC.
- Release candidates are a community building exercise and are not intended for production use.
- We ask the community (everyone: individuals, organizations, service providers) to download and thoroughly test this release candidate and report back.
- Testing priority is the new internationalization support
- Participating in testing release candidates is a key expectation of our open source social contract. We make an effort to thank each person who tests in our release announcement and project presentations!
- GeoServer commercial service providers are fully expected to test on behalf of their customers.
Release Candidate Testing Priorities
This is an exciting release and a lot of great new functionality has been added. We would like to ask for your assistance testing the following:
- The number one testing priority is to try out GeoServer with your data! Mass market open source thrives on having many people to review. Scientific open source like GeoServer thrives on exposure to many datasets.
- The rest of this blog post highlights new features for GeoServer 2.20, please try out these features, read the documentation links, and ask questions.
Known Issues:
- No issues reported at this time, you could be the first!
Internationalization
The leading feature for this release is the internationalization of Title, Abstract and Contact details for:
- WMS 1.1 and 1.3
- WFS 2.0
- WCS 2.0
See documentation for internationalization support and GSIP-203 proposal for details.

New feature:
- GEOS-10123 Internationalization for title and abstract
- GEOS-10207 Allow creation of internationalized raster legends
- GEOS-10190 i18n support for Contact Information
- GEOS-10185 LayerGroup legend internationalization styles returns multiple values
- GEOS-10177 Allow Default Translation
- GEOS-10129 Add language function for multilingual support in sld
Improvements and fixes:
- GEOS-10205 Layer with i18n title might appear twice in the capabilities, while being contained in a named tree
- GEOS-10204 Default locale is not being used while producing internationalized outputs in Capabilities document
- GEOS-10160 Requested Language in GetCapabilities
Modules Status Information for Extensions
Thanks to Ian for completing a [long outstanding request] [https:] to provide listing everything you have installed:
- The Server Status page now provides a complete list of the loaded modules and extensions
- This extension list can also be checked via REST API (allowing scripts to check if the functionality they require has been installed)
New Feature:
- GEOS-10067 Implement module status in extensions (GISP-143)
Improvements and fixes:
- GEOS-9967 Add Module Status implementation for CSW Extension
Updates and quality assurance
GeoServer continues to be build with the latest open source technologies:
- GeoTools 26-RC
- GeoWebCache 1.20-RC
- JAI-EXT 1.1.20
- ImageIO-EXT 1.3.10
- JTS 1.18.2
- GeoFence 3.5.0
- Flatgeobuf to 3.10.1
The team continues to work with automated code checks, gradually improving the codebase and introducing checks to ensure issues are not re-introduced over time:
- Check system.out.println and printStackTrace statements are not accidentally committed, which can add to logs
- Cognitive complexity checks, start cleaning up methods that are too complex
- Use StandardCharsets when possible, rather than String
- Avoid unnecessary object wrapper creation
- Use short arrays initializers
- Work towards consistent style with checks to avoid C style array declarations, add missing @Override annotations, and check java generics are used
This dedication helps provide confidence in the technology we publish.
WMS
Fixes and improvements:
- GEOS-4939 Coordinate system ISSUE - S-JTSK Krovak East North (EPSG: 5514) - cannot be set up
- GEOS-10032 Group Layer in Catalog Mode Hide not in capabilities when unauthenticated
- GEOS-10013 Mark invalid error while validating or saving a Style
- GEOS-9907 Enable usage of labelPoint function in GetFeatureInfo requests
- GEOS-9759 Set Response Cache Headers in LayerGroups
The following functionality has been removed:
- GEOS-10001 Remove animator and animated GIF support from WMS
  
  Use of WPS Animation process is provided as an alternative
WFS
Fixes and improvements:
- GEOS-10222 WFS CSV OutputFormat delimiter
WPS
Fixes and improvements:
- GEOS-9990 Add GUI and REST API to configure the wps-download module
- GEOS-10073 WPS animation download process should report about eventual time mis-matches
WMTS
Improvements and fixes:
- GEOS-10008 Have GeoServerTileLayer implementing TileJSONProvider
- GEOS-9971 GeoWebCache S3 plugin require AWS creds
INSPIRE Extension
New feature:
- GEOS-10124 Add Language support to INSPIRE extension
Improvements and fixes:
- GEOS-10211 Unable to pass INSPIRE validation: Version is mandatory (WMS)
- GEOS-10192 Inspire extension consistent outputResponse element
- GEOS-10141 Inspire extension better error message on language not found
- GEOS-10163 Incorrect INSPIRE namespace URI
And more!
Fixes and Improvements:
- GEOS-10092 Fix the page description of remote WMS/WMTS connection
- GEOS-10189 I18n improvement using the UTF-8 charset for Chinese translations
- GEOS-10033 Geoserver startup and shutdown shell scripts don’t handle path with spaces
- GEOS-9381 Conversion from boolean true/false in geoserver to SQL Server bit 0/1, is broken
- GEOS-9970 MapML GetFeature bug fix for CRS authority
- GEOS-10201 Geoserver fails to start on Windows 11 beta
Find out more in the release notes.
About GeoServer 2.20
Additional information on GeoServer 2.20 series:
- Internationalization of title and abstract
- Release notes (2.20-RC)
13 September 2021
15:24
Just van den Broecke: Terraform - First Steps on Hetzner Cloud
sur Planet OSGeo
I use Ansible already for years to provision server instances and for subsequent CI/CD. A recent example is the Geonovum OGC API Testbed . Here (selective) Docker Containers are automatically deployed on GitHub pushes using Ansible called from within a GitHub Workflows.

Now investigating how Terraform could play a key role in (Cloud) infrastructure management. There is a small overlap between Ansible and Terraform but that is a matter of how they are applied in concert.

Ansible is more geared towards maintaining the OS and its running components e.g. Docker Containers on VM-instances. Terraform is more geared to maintaining a Cloud infrastructure, "in the large": acquiring VM-instances, networks, DNS. If you are familiar with AWS, Google Cloud Platform, or in our case Hetzner Cloud , it is what you can do by clicking in their respective UIs or via their APIs like Hetzner's hcloud . And btw: both Ansible and Terraform are Open Source.

Quote from random web-search : "Terraform is designed to provision different infrastructure components. Ansible is a configuration-management and application-deployment tool. It means that you'll use Terraform first to create, for example, a virtual machine and then use Ansible to install necessary applications on that machine."

Both Ansible and Terraform are "declarative", i.e. configuration-based, where the configuration describes a desired state. ctions are "idempotent", i.e. the same action can be applied multiple times, but when the desired state is reached it won't have effect.

As I plan to apply Terraform in other projects as well, I took a deep dive, following hands-on tutorials from the Terraform website. In a very short time I was amazed by Terraform's power and elegance! My ultimate goal was to manage (acquire, configure, access, destroy) the lifecycle of Hetzner Cloud Virtual Machines (VMs, VPS's). This all took about less than two hours, documenting my steps along the way.

I started at the Getting Started page. While there is a lot of stuff on AWS, Terraform Cloud, I basically stuck to these four steps. You may even skip the third (GCP) step. Important is to learn the terminology and config conventions.
1. Installation
2. Using Docker Provider
3. Using GCP Provider
4. Using Hetzner Cloud Provider
  Tip: in IntelliJ IDEA install the Terraform plugin. It will recognise/help with Terraform files!
Step 1 - Installation
learn.hashicorp.com/tutorials/terraform/install-cli

On a Mac with Homebrew install the Terraform CLI:
```
1$ brew tap hashicorp/tap
2
3$ brew install hashicorp/tap/terraform
4
5$ terraform -version
6
7Terraform v1.0.2
8on darwin_amd64
```
That's it!
Step 2 - Using Docker Provider
learn.hashicorp.com/collections/terraform/docker-get-started

I started project dirs under ~/project/terraform/learn/.
```
1$ mkdir -p ~/project/terraform/learn/terraform-docker-container
```
Create a file called main.tf:
```
 1terraform {
 2  required_providers {
 3    docker = {
 4      source  = "kreuzwerker/docker"
 5      version = "~ 2.13.0"
 6    }
 7  }
 8}
 9
10provider "docker" {}
11
12resource "docker_image" "nginx" {
13  name         = "nginx:latest"
14  keep_locally = false
15}
16
17resource "docker_container" "nginx" {
18  image = docker_image.nginx.latest
19  name  = "tutorial"
20  ports {
21    internal = 80
22    external = 8000
23  }
24}
25
```
This defines that we will use the Terraform Provider plugin named "docker" with source kreuzwerker/docker . `Terraform has a registry of official (Provider) plugins.

Now initialize and install the plugin:
```
 1$ terraform init
 2
 3 **Initializing the backend...**
 4
 5 **Initializing provider plugins...**
 6
 7- Finding kreuzwerker/docker versions matching "~ 2.13.0"...
 8
 9- Installing kreuzwerker/docker v2.13.0...
10
11- Installed kreuzwerker/docker v2.13.0 (self-signed, key ID **24E54F214569A8A5**)
12
13. etc
14
```
You may validate your config:
```
1$ terraform validate
```
Moment of truth: create the resources:
```
1$ terraform apply
```
Verify the existence of the NGINX container by visiting localhost:8000 in your web browser or running docker ps to see the container.

That's it for Docker. Next is to use a real Cloud Provider.
Step 3 - Using GCP Provider
learn.hashicorp.com/collections/terraform/gcp-get-started

This was actually more elaborate than the Hetzner Cloud exercise. I had a GCP account, so this went smooth: first creating a Network and later a VM Instance. In this step also learned about using Terraform Providers, Resources, Variables(-files.) I leave this as an option and skip to Hetzner Cloud which is the goal of this post.
Step 4 - Using Hetzner Cloud Provider
The Hetzner Cloud plugin provider was not in the tutorials, but it was still not too hard to extrapolate from Step 3, from various Hetzner tutorials and from the hetznercloud/hcloud Terraform Provider.

Links:
- hcloud Provider: [https:]]
- [https:]]
- [https:]]
- using TF-hcloud with Docker: github.com/insekticid/docker-terraform-hcloud-example
Prerequisite is to have a Hetzner Cloud account and thus login access to console.hetzner.cloud .

Steps:
- create a new Project in [https:]] e.g. TerraformLearn
- add your SSH public key to this project via "Security" menu link left
- generate and copy an API Token for the project
My goal was to create a Debian VM, login there with root and SSH key and destroy it afterwards.
```
1$ mkdir -p ~/project/terraform/learn/terraform-hetzner
```
Create main.tf as follows:
```
 1terraform {
 2   required_providers {
 3     hcloud = {
 4       source  = "hetznercloud/hcloud"
 5       version = "1.27.2"
 6     }
 7   }
 8 }
 9 
10 provider "hcloud" {
11   token = var.hcloud_token
12 }
13 
14 resource "hcloud_server" "node1" {
15   name        = "node1"
16   image       = "debian-9"
17   server_type = "cx11"
18   ssh_keys = ["just@sunda.lan"]
19 }
20 
```
Create a file variables.tf:
```
1 # Set the variable value in *.tfvars file
2 # or using the -var="hcloud_token=..." CLI option
3 variable "hcloud_token" {
4   sensitive = true # Requires terraform = 0.14
5 }
6 
```
Then a file called terraform.tfvars. This is a file with "secrets" normally not checked-in a repo but there are many other possiblities to deal with secrets/credentials:
```
1 hcloud_token = "the token string from Hetzner Cloud API Token"  
```
Moment of truth: apply!
```
1$ terraform init
2
3$ terraform apply -auto-approve
```
Using -auto-approve you skip the interactive approval-step.

Next check the Hetzner Cloud Console project page and see the new VM running!

Try to login on your new VM (IP may also be gotten from output.tf, another exercise):
```
1$ ssh root@<Your VM IP>
```
Then destroy your VM:
```
1$ terraform destroy -auto-approve`
```
There is much more one can do with the Hetzner Provider: basically everything that is available in the console UI and hcloud API: creating Volumes, managing networks, adding SSH-keys, snapshots, using cloud-init etc. See the manpage in particular the Resources drop-down menu: registry.terraform.io/providers/hetznercloud/hcloud/latest/docs

Beware that some Terraform actions are destructive: e.g. upgrading the OS will destroy the existing VM and create a new. For those cases Floating IPs and auto-provisioning with Ansible will help. But in that case Ansible would be more suited to upgrade the OS. One can always execute terraform plan first to see the execution plan. My recommendation is to let Terraform handle the basics, and have Ansible manage the details on VMs.

Alternatives: TF with DigitalOcean using the DO Provider: registry.terraform.io/providers/digitalocean/digitalocean/latest/docs .

All in all: Terraform can form a nice partnership with Ansible.
2:00
Lutra consulting: Google Summer of Code 2021 : Virtual Raster Provider for QGIS
sur Planet OSGeo
Read the guest post and congratulate Francesco Bursi, who successfully completed GSOC 2021 project to add virtual raster provider for QGIS with help of mentors Martin Dobias and Peter Petrik.

In this year’s Google Summer of Code (GSoC), I decided to work on the native QGIS raster calculator. Martin Dobias and Peter Petrik volunteered to mentor my work. I’ve been studying Civil Engineering and GeoInformatics at the University of Padua; here I had the opportunity to work both with a lot of GIS software including QGIS. I enjoyed working with QGIS almost immediately because of the possibility to perform complex analysis with a few clicks or with few python commands. Being passionate about programming and enthusiastic about Open Source, I realized that having the possibility to work together with some experienced developers and with an active community was really a great and unique opportunity, so I decided to apply to the GSoC.
Virtual Raster Provider
The existing raster calculator is a powerful tool to perform map algebra that outputs a raster layer, before this work it was possible to take advantage of this tool only by saving the output of this operation as a file. The aim of this year GSoC was to allow users to perform their analysis without creating a new derived raster and taking up disk space and therefore have the result as an on-the-fly computational layer.

Let’s jump to an example and let’s say I want to compute the Chanopy Height Model (CHM), subtracting the Digital Terrain Model (DTM) from the Digital Surface Model (DSM).

I also want to perform some other analysis on the DTM since I want to compute the ideal elevation value for a particular tree planting (disclaimer: the elevation value used is example purposes only, moreover when planting trees you should take into account a lot of factors like slope, aspect, latitude. QGIS, by the way, can really be helpful in this kind of analysis). To do so I will start from the same data and I will create different on-the-fly layers for each calculation, in order to avoid the creation of different files I can take advantage of the new checkbox added to the raster calculator dialog. The computation of CHM is performed in the next screencast and the output layer name is, of course, CHM.

I’ll end up with a new raster layer (CHM) that can be styled as a normal raster and that is not written as an output file to the disk. For some further analysis, from the DTM, I want to obtain the portion of the area with an elevation between 150 and 350 metres above the datum. By applying the following expression to DTM I’ll end up with a raster that has a value of 1 where conditions specified by the expression is TRUE and it will have value of 0 otherwise.
```
("dtm@1" > 150) AND ("dtm@1" < 350)
```
I did not select the output layer name intentionally. The resulting layer will be named after the expression used to generate the layer.
Conditional Statement
I also had the opportunity to improve the raster calculator capabilities by adding the possibility to write expressions that involve conditional statements. Taking the already used example, let’s imagine I want to compute the CHM only for the areas of the DTM that are between 150 and 350 metres above the datum. It’s now possible to write an expression as the following one:
```
if ( ("dtm@1" > 150) AND ("dtm@1" < 350), CHM, -10)
```
This expression will output a raster with values of the CHM where the conditions are met and value of -10 if the conditions are not met. Since this is a final result of our analysis I’ll store this output as a file to the disk in the form of a GeoTIFF. I’d like to outline that the CHM used in the expression above and in the next screencast is an onn-the-fly computed raster, so it is possible to:
- Take advantage of the virtual raster provider (on-the-fly computed raster) in other analysis with the raster calculator (and with other analysis tools);
- Store the on-the-fly computed raster as a file.
Conclusion
I had fun and I struggled working with QGIS, but I learned a lot of new and interesting things. My pull requests were met with several constructive comments, suggestions and feedback. Some suggestions can be a starting point for future improvements.
- An enhancement for the feature I’ve developed can be the possibility to take advantage of OpenCL acceleration as it has also been suggested in the dev mailing list;
- Another enhancement that concerns the raster calculator and only partially the virtual raster provider would be the possibility to support the creation of output raster with multiple bands with the declaration of multiple formulas. I hope to continue to contribute to the QGIS project in the future.
11 September 2021
2:00
PostGIS Development: PostGIS 3.2.0alpha1 Released
sur Planet OSGeo

The PostGIS Team is pleased to release the first alpha of the upcoming PostGIS 3.2.0 release.

Best served with PostgreSQL 14 beta3. This version of PostGIS utilizes the faster GiST building support API introduced in PostgreSQL 14. If compiled with the in-development GEOS 3.10dev you can take advantage of improvements in ST_MakeValid. This release also includes many additional functions and improvements for postgis_raster and postgis_topology extensions.
Continue Reading by clicking title hyperlink ..
10 September 2021
11:00
CARTO Blog: Uncovering Site Selection Strategies using Point of Interest Data
sur Planet OSGeo

In the U.S. it can cost more than $1 million to open a McDonald’s, Taco Bell, Burger King, or Wendy’s restaurant. With such high levels associated with funding startup cost...
09 September 2021
17:00
3liz: QuickOSM 2.0
sur Planet OSGeo

QuickOSM 2.0.0 Introduction
Je suis Maxime Charzat et je suis étudiant à l’ENSG, École Nationale des Sciences Géographiques.

3Liz m’a engagé pour donner un coup de jeune à l'extension. Outre quelques bugfix et mises à jour, cela faisait des années que le plugin n’avait pas été agrémenté de nouvelles fonctionnalités. C’est tout l’objet de ma venue à 3Liz pour ce stage.
Nouveautés Requête rapide
Ce panneau a bien évolué dans cette nouvelle version. En effet, l’idée était de permettre autant des utilisations simples que plus avancées, et bien sûr d’améliorer ces utilisations.

Du côté des utilisations plus basiques, on a voulu simplifier les connaissances par rapport aux clés/valeurs d’OSM. Dans le contexte de l’utilisation du plugin par une personne novice, on a ajouté un champ contenant des pré-réglages de manière similaire aux autres outils qui utilise OSM tel que Vespucci, JOSM… Ce champ est traduit dans la langue définie dans QGIS et permet donc d’abaisser la barrière que peuvent être les clés/valeurs. En tapant Boulangerie en français, la requête OSM shop=bakery est automatique.

Concernant les utilisations avancées, il y avait une fonctionnalité qui était demandée depuis longtemps. Il s’agit de pouvoir créer des requêtes avec plusieurs clés/valeurs. C’est maintenant possible. L’interface permet de jouer avec un tableau pour choisir les clés/valeurs, en ajouter, en supprimer, choisir les liens entre eux. On peut désormais construire une requête qui demande les boulangeries qui font aussi patisserie (shop=bakery AND pastry=yes) ou alors qui demande et les bars et les refuges animaliers (amenity=bar OR amenity=animal_shelter).

Pour les férus de données OSM, les métadonnées peuvent être demandées en cochant la case à cocher dans le groupe Avancé. Cela permet entre autres d’avoir accès à la version de l’objet et à la dernière personne qui a mis à jour cet objet.

Dernier ajout sur ce panneau : un historique des requêtes. L’extension enregistre maintenant temporairement les dix dernières requêtes effectuées. Cela permet de relancer une requête récente sans avoir à s’embêter à devoir derechef tout remplir.

Fichier OSM
Ce panneau permet de charger un fichier OSM ou PBF dans QGIS, stocké en local sur votre ordinateur. Le problème, c’était que l’on était obligé de charger tout le fichier (qui peut être assez volumineux). Il est désormais possible de ne charger que les données qui répondent à une requête de clés/valeurs.

À partir d’un fichier téléchargé par exemple sur [https:]] , sans utiliser internet, on peut faire des requêtes sur un gros volume de données. Volume pas forcément supporté par l’API Overpass utilisé par le plugin pour télécharger les données OSM.
Boîte à outil Traitement
En réfléchissant à tous les usages du plugin, on a décidé de compléter la gamme d’algorithmes dans la boîte à outil Traitement. En effet, jusqu’alors seuls les algorithmes de construction de requêtes étaient implémentés dans le modeleur graphique de QGIS.

Si vous ne connaissez pas le modeleur de QGIS, c'est le moment de jeter un œil.

On en a donc ajouté équivalent du panneau Requête rapide dans la boîte à outil Processing.
Thème de carte
Voici une grosse nouveauté pour la version 2.0.0 et qui peut-être assez puissante. Sur les bases du panneau Mes requêtes qui existait dans la version QGIS 2, on a implémenté l’option de sauvegarder ses requêtes.

Mais, cela va même au-delà de juste enregistrer, on offre la possibilité de les transformer en un thème de carte. Ainsi, en deux clics, en précisant juste l’étendue ou le lieu voulu, il est possible de télécharger toutes les données, d’effectuer toutes les requêtes qui permettent d’afficher une carte prête à l'emploi. On peut même associer un style aux couches directement.

Concrètement, en lançant le thème Urban ci-dessus, vous téléchargez automatiquement les bâtiments et les routes. De plus un style accompagne les données pour la mise en forme.
Configuration
Les requêtes sauvegardées ont donc un mode d’édition pensé pour être exhaustif. On veut laisser à l’utilisateur le pouvoir de fabriquer son thème en ayant la main sur la majorité des options possibles. Ainsi, dans le thème on peut gérer plusieurs requêtes (qui se lancent les unes à la suite des autres lors du processus), gérer la plupart des paramètres pour chaque requête, définir les champs en sortie.

On a aussi le choix entre deux types de thème : soit basique, soit avancé. La différence se fait dans la requête. En type basique, le processus va construire les requêtes avec les clés/valeurs données. En type avancé, le processus va utiliser la requête écrite par l’utilisateur.

Le plugin ne contient que un seul thème par défaut pour le moment. On va avoir besoin de vous pour étoffer cette liste. Si vous vous sentez l’âme d’un contributeur, que vous pensez qu'un thème est manquant, que vous voulez participer à ce plugin, alors n’hésitez pas à nous proposer vos thèmes sur [https:]] en prévoyant le fichier JSON et les fichiers QML.

On peut très bien imaginer un thème carte randonnée, carte cadastre, carte occupation du sol…
Conclusion
Je suis heureux de pouvoir vous présenter cette nouvelle version de QuickOSM. Cela ouvre et approfondi un champ des possibles que j’ai hâte que vous découvriez. N’hésitez pas à nous faire des retours (Twitter, LinkedIn, GitHub…) et à nous proposer vos thèmes.

Amusez-vous !!!

Maxime Charzat
17:00
3liz: QuickOSM 2.0
sur Planet OSGeo

QuickOSM 2.0.0 Introduction
Hi everyone, I'm Maxime Charzat, student at ENSG, French Engineering school about GIS. I've been interning at 3Liz with the goal to clean up, update and add new features to the QGIS QuickOSM plugin.
What's new Quick query
We had two goals with this panel. Make it simpler for newcomers to download OSM data and our other goal was to make it better for advanced users, so they could get more out of the OSM data.

The first goal was to simplify the way to find OSM keys and values. So we've used prepopulated data as in other OSM tools such as Vespucci, JOSM… These data are available in the language defined in QGIS, so people can easily find keys like bench/highway. By typing Boulangerie in French, the query will be automatically transformed with shop=bakery.

For advanced user, we add the support for multiple key/value. There is now a table to add one or more keys. These different rows are linked by a AND and OR.

For instance, it's now possible to query bakeries that have pastries (shop=bakery AND pastry=yes).

For people familiar with OSM data, metadata can be requested by clicking the checkbox in the advanced settings. This will give you the object version and who contributed to the last version of the said object.

Last but not least, we added the history of queries. The plugin now remembers temporarily the last ten queries, so they can be easily be relaunched.

OSM File
This lets you load a PBF or OSM file in QGIS, stored on your hard drive. Before 2.0, you had to load the full dataset from the file. In 2.0 you can now filter using key/values.

This means that you can now process huge quantities of OSM data offline, without using the Overpass API. Files can be generated by services like [https:]] . It means people working on large dataset won't affect the Overpass API.
Processing toolbox
Until now only construction query algorithm were supported in the QGIS Processing Modeler.

If you don't know yet about QGIS Modeler, it's time to have a look.

We decided to add more QGIS Processing algorithm.

You can now find the equivalent of the Quick query in the Processing toolbox.
Map presets
This is the biggest new feature in this release.

Map presets are a nice way to save queries, like it was possible before in QGIS 2. But we added more features. It's possible to save a set of queries within a single map preset, to have a map out-of-the-box.

You can define one or more queries and associate a QGIS Style file for each layer.

For instance, by clicking on the Urban map preset showed above, you will download automatically buildings and roads with a style.

The plugin comes with a single map preset for now. But we need you to contribute to this list. If you feel like a map maker and contributor and if you think a map preset is missing, feel free to come and share it on [https:]] . We would like to see a hiking map preset, bicyle map preset…
Conclusion
I'm happy that I could make this newer version of QuickOSM available to you. I can't wait to see some feedbacks (Twitter, LinkedIn, GitHub…) and to see more map presets coming in the plugin.

Also we'd love to have more people translating QuickOSM, see [https:]]

Have fun Maxime Charzat
7:05
Lutra consulting: Organising Charitable Collection Routes with Offline Mobile Maps
sur Planet OSGeo
Significant time saved when route maps distributed with Input and Mergin.

This case study was originally written in Czech. The Czech version can be found here.

Every year, teams of volunteers walk door-to-door through the Czech town of Litomyšl collecting charitable donations. Event organisers define routes for the various volunteer teams by marking-up paper maps with pens. The process has a number of issues both in the making and usage of the maps which organisers worked to overcome by making the maps digital using open source GIS software.

Maps were developed using QGIS and made available on volunteers’ phones using the Input app. Volunteers are now able to easily orientate themselves on maps which clearly show their routes. Organisers have reduced the time it takes to update routes and distribute these to volunteers.

Veronika Peterková works for the Litomyšl Parish Charity, a non-profit organisation providing health and social services to people in need since 1993.

Veronika describes the charity’s activities: “We provide home medical services and nursing care to the residents of Litomyšl and its surrounding villages. This includes helping families where the healthy development of a child is at risk and providing respite stays for clients who are otherwise cared for by their families at home. We provide care for about 1000 clients a year.”

She added: “We also coordinate the activities of volunteers who visit the elderly, help with tutoring children and with various leisure and cultural activities.”

One of the parish charity’s biggest fundraising events is the “T?íkrálová sbírka” (Three Kings Collection), a door-to-door carol-singing collection taking part around the 6th of January each year.

Volunteers participating in the Three Kings Collection.

“The Three Kings Collection is the largest national volunteer event in the Czech Republic. In the Litomyšl region alone, nearly 300 volunteers are involved each year with the carol-singers collecting over 500,000 Czech crowns (~20,000 EUR) in sealed boxes. The proceeds are intended to help the sick, the disabled, the elderly, mothers with children in need and other in-need groups in the local area.” Veronika explains.

The Three Kings Collection is organised by Caritas Czech Republic and at least 10% of its proceeds are allocated for humanitarian aid abroad.
The Challenge
Veronika is responsible for planning routes for the carol-singers so they efficiently visit households in the Litomyšl area. Singers are split into groups and paper maps are provided which show groups which households to visit.

An example of previous paper maps, image courtesy of Farní charita Litomyšl.

The above maps were produced by printing screenshots from a national web mapping provider and marking-up printouts for each of the 50 teams using marker pens.

This method proved to have a number of issues as Veronika describes: “On maps of larger areas, house numbers were not always visible due to the scale. This made it even harder for coordinators not familiar with the area to orient themselves, leading to confusion. Coordinators also found it hard to keep the maps dry and undamaged during unfavourable weather. If new groups signed-up afterwards or others opted-out, we’d have to redo/redivide the areas which would be very time-consuming as the maps would need to be marked-up manually once again.”
The Solution and Implementation
Veronika wanted to try a new solution for organising the 2021 Three Kings Collection with the goal of making volunteer tasks clearer and less reliant on paper maps. She wanted the new solution to allow her to:
- reduce work through the reuse of maps in future Three Kings Collection events
- easily update maps if new groups sign in/out and areas need editing
- allow carol singers to see exactly where they are on the map
- gradually replace paper maps while still allowing the use of paper maps where preferred
- group and colour buildings to be visited on the computer
- record a building’s use (e.g. commercial) to direct volunteers more effectively
- clearly show how areas are assigned so anyone can see who is responsible for a given area
In addition, Veronika wanted the solution to be affordable and work offline without volunteers needing internet connectivity in the field.

Peter Petrík, a regular participant of the Litomyšl Three Kings Collection suggested Veronika try using the Input app for coordinating the collection in 2021. Peter works for Lutra Consulting, the company behind Input and Mergin.

He showed Veronika how to create the maps in QGIS, a free and open source mapping software. Using map data from OpenStreetMap, they created a project showing the buildings to be visited, coloured by their associated volunteer group number.

Houses grouped by team in QGIS, image courtesy of Farní charita Litomyšl.

The styled map was uploaded to Mergin, a collaborative mapping platform, making it readily available for viewing interactively on volunteer’s phones using the Input mobile app. Both QGIS and Input integrate closely with Mergin which meant that maps could be adjusted in QGIS with the resulting changes being visible to volunteers shortly thereafter.
Outcomes
Veronika reflects on the solution: “The solution met all our requirements and the maps we’ve prepared can easily be reused in upcoming events, saving us time. The fact that the new maps were made publicly accessible means volunteers can just download them using Input which makes distributing and updating them very easy.”

Volunteer routes and position information shown in Input, screenshot courtesy of Farní charita Litomyšl.

She adds: “All the districts we wanted to visit were distinguished from each other by colour and we were also pleased to be able to clearly mark the areas not to be visited like industrial areas by colouring them in grey.”

Unfortunately COVID meant that Veronika’s plans changed as she explains: “Using these new methods we were able to prepare for the 2021 Three Kings Collection in a short time. Unfortunately however, the COVID situation meant we could not go out on the streets to use the new maps as intended. We hope that in 2022 we’ll be able to more closely evaluate the positives and negatives of the field aspect of the project.”

She adds: “We already see it’s now much easier to allocate areas of the town to our volunteers in a clear and fair manner using QGIS. Producing printed maps for those who prefer them is also now easy and the maps look much more professional. Those who only wanted to use the Input app could see the same information as on the paper maps, but had the advantage of being able to pinpoint their exact location and clearly see the house numbers of each building.”

Example printed map created for volunteers wanting also paper maps, image courtesy of Farní charita Litomyšl.

She concludes: “Overall we found the solution user-friendly, and appreciated being able to discuss the process with Lutra Consulting who helped us solve issues as required. About a third of our volunteers are interested in using Input, which I consider positive.”

The Litomyšl Parish Charity are on Facebook and Instagram.
Download Input Today
2:00
SourcePole: QGIS Cloud: Starting a new feature series for QGIS Cloud Pro customers
sur Planet OSGeo

We are pleased to announce that today we have published a new release of QGIS Cloud. Besides a whole bunch of bug fixes, we have also introduced new features for QGIS Cloud Pro customers. Starting with this release, we will be releasing more features for our QGIS Cloud Pro customers in the coming weeks. The following new features are available for QGIS Cloud Pro users starting today. Import Layer: In the Layers & Legend tool you will now find the possibility to import layers.
06 September 2021
2:00
EOX' blog: VirES for (not only) Swarm - 2021 update
sur Planet OSGeo

A few days ago a new release of the VirES for Swarm service has been successfully deployed in production. The V3.6.0 is the first release of the service under the new ESA contract which assures the service operations for another two years, with a possible extension up to four years. Rather than just ...
04 September 2021
2:00
PostGIS Development: PostGIS 3.1.4, 3.0.4 Released
sur Planet OSGeo
The PostGIS development team is pleased to provide bug fix and performance enhancements 3.1.4 and 3.0.4 for the 3.1, 3.0 stable branches.

3.1.4 This release supports PostgreSQL 9.6-14.
- source download
- NEWS
- PDF docs en
- html doc download
- html online en
- epub doc download
3.0.4 This release works with PostgreSQL 9.5-13 and GEOS >= 3.6 Designed to take advantage of features in PostgreSQL 12+ and Proj 6+
- source download
- NEWS
- PDF docs en
- html doc download
- epub doc download
View all closed tickets for 3.1.4, 3.0.4.

After installing the binaries or after running pg_upgrade:

For PostGIS 3.1, 3.0, 2.5 do below which will upgrade all your postgis extensions.
```
SELECT postgis_extensions_upgrade();
```
For PostGIS 2.4 and below do:
```
ALTER EXTENSION postgis UPDATE;
```
— if you use the other extensions packaged with postgis — make sure to upgrade those as well
```
ALTER EXTENSION postgis_sfcgal UPDATE;
ALTER EXTENSION postgis_topology UPDATE;
ALTER EXTENSION postgis_tiger_geocoder UPDATE;
```
If you use legacy.sql or legacy_minimal.sql, make sure to rerun the version packaged with these releases.
03 September 2021
17:19
OTB Team: OTB release 7.4.0
sur Planet OSGeo

We are happy to announce that OTB 7.4.0 has been released! Ready to use binary packages are available on the package page of the website: OTB-7.4.0-Darwin64.run (Mac OS) OTB-7.4.0-Linux64.run (Linux) OTB-7.4.0-rc1-Win64.zip (Windows 64 bits) It is also possible to checkout the branch with git: git clone [https:] OTB -b release-7.4 The documentation for OTB 7.4.0 […]
01 September 2021
10:00
Paul Ramsey: GeoMob Podcast - PostGIS
sur Planet OSGeo
I neglected to post about this at the time, which I guess is a testament to the power of twitter to suck up energy that might otherwise be used in blogging, but for posterity I am going to call out here:
- I got to go on the GeoMob podcast and talk with Steven Feldman this spring.
- It was cool, Steven is a fellow “FOSS4G Chairpersons” alumnus, having chaired the 2013 edition.
- We covered PostGIS, open source, and even a bit of electoral data and field ops.
Have a listen.
31 August 2021
16:39
Even Rouault: Analyze of OSS-Fuzz related data on GDAL
sur Planet OSGeo
GDAL has now been put under the continuous scrutinity of OSS-Fuzz for more than 4 years. To keep it simple, OSS-Fuzz is a continuous running infrastructure that stresses a software with (not-so-)random data to discover various flaws, and automatically files issues in a dedicated issue tracker, with reproducer test cases and stack traces when available. It is time to use a bit the data accumulated to give a few trends.
First, we can see a total of 1787 issues having been found, which represents on average a bit more than one per day. Out of those, only 38 are still open (so 97.8% have been fixed or are no longer reproducible). Those 1787 issues are out of a total of 37 769 filed issues against all 530 enrolled software, hence representing 4.6 % (so significantly higher than the naive 1 / 530 = 0.2 % proportion that we could expect, at least if all software were of the same size, but GDAL is likely larger than the average). Does that mean that the quality of GDAL is lower than the average of enrolled software, or that it is stressed in a more efficient way... ? Most of GDAL code being about dealing with a lot of file formats, it is the ideal fit for fuzz testing.
We should mention that a number of issues attributed to GDAL actually belong to some of its dependencies: PROJ (coordinate transformation), Poppler (PDF rendering), cURL (network access), SQLite3 (embedded database), Xerces-C (XML parsing), etc. And we reguarly report or fix those issues to those upstream components.
Addressing those issues is now facilitated with the sponsorship program which allows us to spend funded time on such unsexy and usually hard to fund topics, but important to enhance the robustness of the software.
We have run a script that parses git commit logs to identify commits that explicitly reference an issue filed by ossfuzz and tried to analyze the commit message to find the category of the issue that it addresses.
Here's its output:
Category                                                Count Pct
----------------------------------------------------------------------
integer_overflow_signed                                  178 14.67 %
excessive_memory_use                                     174 14.34 %
other_issue                                              114   9.40 %
buffer_overflow_unspecified                              105   8.66 %
excessive_processing_time                                102   8.41 %
null_pointer_dereference                                  93   7.67 %
integer_overflow_unsigned                                 68   5.61 %
division_by_zero_integer                                  54   4.45 %
heap_buffer_overflow_read                                 37   3.05 %
unspecified_crash                                         32   2.64 %
stack_call_overflow                                       31   2.56 %
memory_leak_error_code_path                               23   1.90 %
heap_buffer_overflow_write                                22   1.81 %
division_by_zero_floating_point_unknown_consequence       19   1.57 %
stack_buffer_overflow_unspecified                         19   1.57 %
invalid_cast                                              14   1.15 %
invalid_shift_unspecified_dir                             14   1.15 %
memory_leak_unspecified                                   13   1.07 %
assertion                                                 13   1.07 %
invalid_enum                                              11   0.91 %
division_by_zero_floating_point_harmless                  10   0.82 %
infinite_loop                                             10   0.82 %
integer_overflow_unsigned_harmless                         8   0.66 %
invalid_memory_dereference                                 7   0.58 %
undefined_shift_left                                       7   0.58 %
double_free                                                6   0.49 %
stack_buffer_overflow_read                                 6   0.49 %
use_after_free                                             6   0.49 %
integer_overflow_harmless                                  5   0.41 %
undefined_behavior_unspecified                             3   0.25 %
negative_size_allocation                                   3   0.25 %
unhandled_exception                                        2   0.16 %
invalid_shift_right                                        2   0.16 %
unsigned_integer_underflow                                 1   0.08 %
uninitialized_variable                                     1   0.08 %
----------------------------------------------------------------------
Total                                                   1213

So 1213 commits for 1787-38 fixed issues: the difference is duplicated issues, non-reliably reproducing issues that end up being closed or issues fixed in other code bases than GDAL.
Let's dig into those categories, from most frequently hit to lesser ones:
- integer_overflow_signed: an arithmetic operation on a signed integer whose results overflows its size. This is a undefined behavior in C/C++, meaning that anything can happen in theory. In practice, most reasonable compilers and common CPU architectures implementing complement-to-two signed integers will have a wrap around behavior, and not crash when the overflow occurs. However this has often later consequences, like allocating an array of the wrong size, and having out-of-bounds access.
- excessive_memory_use: this is not a vulnerability by itself. This issue is raised because processes that run under OSSFuzz are limited to 2 GB of RAM usage, which is reasonable given than OSSFuzz manipulates input buffers that are generally large of a few tens of kilobytes. It is thus expected that for those small inputs, RAM consumption should remain small. When that's violated, it is because the code generally trusts too much some fields in the input data that drive a memory allocation, without checking that against reasonable bounds, or the file size. However for some file formats, it is difficult to implement definitive bounds because they allow valid small files that need a lot of RAM to be processed. Part of the remaining open issues belong to that category.
- other_issue: issues that could not be classified under a more precise category. Bonus points for anyone improving the script to analyze the diff and figure from the code the cases where the commit message lacks details! Or perhaps just parse the OSSFuzz issue itself which gives a categorization.
- buffer_overflow_unspecified: an access outside the validity area of some buffer (string, array, vector, etc.), and we couldn't determine if it is a heap allocated or stack allocated, or a read attempt or write attempt. Potentially can result in arbitrary code execution.
- excessive_processing_time: this is when a program exceeds the timeout of 60 second granted by OSS-Fuzz to complete processing of an input buffer. This is often due to a sub-optimal algorithm (e.g. quadratic performance whereas linear can be met), or a unexpected network access. Most of the remaining open issues are in that category. A significant numbers are also in a out-of-memory situation hit by the fuzzer while iterating over many inputs, but often that cannot be reproduced on a individual test case. We suspect heap fragmentation to happen in some of those situations.
- null_pointer_dereference: a classic programming issue: accessing a null pointer, which results in a immediate crash.
- integer_overflow_unsigned: this one is interesting. Technically in C/C++, overflow of unsigned integers is a well-defined behavior. Wrap around behavior is guaranteed by the standards. However we assumed that in most cases, the overflow was unintended and could lead to similar bugs as signed integer overflow, hence we opted in for OSSFuzz to consider those overflows as issues. For the very uncommon cases where the overflow is valid (e.g when applying a difference filter on a sequence of bytes), we can tag the function where it occurs with a __attribute__((no_sanitize("unsigned-integer-overflow"))) annotation
- division_by_zero_integer: an integer divided by zero, with zero being evaluated as an integer. Results in immediate crash on at least x86 architecture
- heap_buffer_overflow_read: read access outside the validity area of a heap allocated data structure. Results generally in a crash.
- unspecified_crash: crash for a unidentified reason. Same bonus point as above to help better categorizing them.
- stack_call_overflow: recursive calls to methods that ends up blowing the size limit of the stack, which results in a crash.
- memory_leak_error_code_path: memory leak that is observed in a non-nominal code path, that is on corrupted/hostile datasets.
- heap_buffer_overflow_write: write access outside the validity area of a heap allocated data structure. Results generally in a crash. Could also be sometimes exploited for arbitrary code execution.
- division_by_zero_floating_point_unknown_consequence: a variable is divided by zero, and this operation is done with floating point evaluation. In C/C++, this is undefined behavior, but on CPU architectures implementing IEEE-754 (that is pretty much all of them nowadays) with default settings, the result is either infinity or not-a-number. If that result is cast to an integer, this results in undefined behavior again (generally not crashing), and various potential bugs (which can be crashing)
- stack_buffer_overflow: a read or write access outside of a stack-allocated buffer. Often results in crashes, and if a write access, can be sometimes exploited for arbitrary code execution.
- invalid_cast: this may be an integer cast to an invalid value for an enumeration (unspecified behavior, which can results in bugs due to not catching that situation later), an instance of a C++ class cast to an invalid type (unspecified behavior, crash likely)
- invalid_shift_unspecified_direction: a left- or right-shift binary operation, generally on a signed integer. For left-shift, this is when this results in setting the most-significant-bit being set (either shifting too much a positive value, which results to a negative value, or shifting a negative value), or shifting by a number of bits equal or greater than the width of the integer. For rigth-shift, this is when shiting by a number of bits equal or greater than the width of the integer. Those undefined behaviors do not result in immediate crashes on common compilers/platforms, but can lead to subsequent bugs.
- memory_leak_unspecified: self explanatory.
- assertion: an assert() in the code is hit. A lot of what we initally think as programming invariants can actually be violated by specially crafted input, and should be replaced by classic checks to error out in a clean way.
- invalid_enum: a particular case of invalid_cast where an invalid value is stored in a variable of a enumeration type.
- division_by_zero_floating_point_harmless: a floating-point division by zero, whose consequences are estimated to be harmless. For example the NaN or infinity value is directly returned to the user and does not influence further execution of the code.
- infinite_loop: a portion of the code is executed in a endless way. This is a denial of service.
- integer_overflow_unsigned_harmless: an example of that could be some_string.substr(some_string.find(' ') + 1) to extract the part of a string after the first space character, or the whole string if there's none. find() will return std::string::npos which is the largest positive size_t, and thus adding 1 to it will result in 0.
- invalid_memory_dereference: generally the same as a heap_buffer_overflow_read.
- invalid_shift_left: mentioned above.
- double_free: a heap-allocated buffer is destroyed twice. Later crash is likely to occur. Could potentially be exploited for arbitrary code execution.
- stack_buffer_overflow_read: mentioned above
- use_after_free: subcase of heap_buffer_overflow_read where one accesses some buffer after it has been freed.
- integer_overflow_harmless: mentioned above, but here, if we exclude the undefined behavior aspect of it, consequences are estimated to be harmless.
- undefined_behavior_unspecified: some undefined behavior of a non identified category, restricted to those caught by the UBSAN analyzer of clang
- negative_size_allocation: a negative size (actually a unsigned integer with its most significant bit set) is passed to a heap memory allocation routine. Not a bug by itself, but often reflects a previous issue.
- unhandled_exception: a C++ exception that propagates up to the main() without being caught. Crash ensured for C code, or C++ callers not expecting it. As the fuzzer programs used by GDAL use the C API, such exception popping up is definitely a bug.
- invalid_shift_right: mentioned above.
- unsigned_integer_underflow: similar as the overflow but going through the negative values. Well defined behavior according to the standards, but often undesirable.
- uninitialized_variable: access to a variable whose content is uninitialized. There are very few instances of that. The reason is probably that we use extensively strict compiler warnings and static code analyzers (cppcheck, clang static analyzer and Coverity Scan), that are very good to catch such issues.
Despite the big number of categories caught by the sanitizers run by OSS-Fuzz, there are some gaps not covered. For example casting an integer (or floating point value) to a narrower integer type with a value that does not fit into the target type. Those are considered as "implementation defined" (the compiler must do something, potentially different from another one, and document what it does), and thus do not enter into what is caught by undefined behavior sanitizers.
PS: For those interested in academic research analyzing outputs of OSSFuzz, you can find this paper (where GDAL actually appears in one figure)
30 August 2021
15:57
GeoSolutions: DHI Announcement
sur Planet OSGeo

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2:00
Ecodiv.earth: Playing with animal tracking data in QGIS
sur Planet OSGeo
I am currently looking for data I can use in my classes about spatial data analysis. A great source of data I found is the Movebank, a free, online database of animal tracking data hosted by the Max Planck Institute of Animal Behavior. The aim is to help animal tracking researchers to manage, share, protect, analyze and archive their data. This short article provides a nice short introduction to the type of data available on this site.

The data is great for something else I have wanted to do for some time now. That is, trying out the temporal controller in QGIS. This tool offers native temporal support to QGIS. It is the successor of the celebrated TimeManager plugin, and is available since version 3.14. The main developer, Nyal Dawson, made a video demonstrating some of the capabilities of this new tool. Definitely something to check out. Below you can find the steps I followed to create the animated map (you can find the map at the end of this post). Note, click on an image to enlarge it.
Cattle movements
To use the temporal controller, you obviously need temporal data. This can be raster or vector data. The animal tracking data available in the Movebank database is a .csv data layer with a number of columns, including the coordinates and the date-time column. This can be imported as a vector point layer in QGIS.

Study area with the 33 animal tracks. Background image, Bing satellite via the Quickmap services plugin for QGIS. In this study, we’ll focus on the eastern tracks along the main river.

For this post, we use a dataset collected by Moritz et al.¹ for a study about grazing pressure in pastoral systems in the Logone Floodplain in Cameroon². I particularly liked this study because of how it combines different approaches and methods (GPS/GIS, video recordings of animal behavior, and ethnographic methods). But that is something for another time.

The GPS data set consists of 33 tracks, representing the daily movement of individual animals during the day (21 tracks) or night (12 tracks) in three different locations. As mentioned above, the data comes as a .csv file, which we import and subsequently save as a vector layer in a new Geopackage.
Import csv and save in geopackage

Import the csv file in QGIS.

Save the data as the layer cattlemovement in the (new) Geopackage cattlemovementdata.gpkg.

Define the symbology, assigning random colors to each of the tracks. Tracks are identified by the categories in the ‘individual-local-identifier’ column.

Data preparation
The locations of the animals were recorded at 3-second intervals (only if the animal was moving)². However, the date-time stamps provided in the Movebank data file are rounded to whole minutes. Information about the seconds between consecutive measurements is provided separately in the column ‘study-specific measurement.’

Because there are some missing observations, creating complete time-stamps based on this information is a bit tricky. So I will leave that as a challenge for you. For the visualizing of the animal movements, a one-minute time interval is good enough. It does mean we need to compute the average locations per minute first.
Calculate average position per minute
First step is to create a new column tracktime with the combined track ID and date-time stamp. This makes for a unique ID that can be used to group the location points that need to be averaged. Combining the two columns can be done using the expression "individual-local-identifier" || '_' || to_string( "timestamp" ) in the Field calculator. Note that we add the underscore to make it easier later on to split the created strings back in two columns with the original track identifiers and the date-time stamps.

Concatenate the columns with the track ID and the timestamp.

To speed up subsequent calculations, we create an index on the newly created field, using the function Create attribute index in the processing toolbox.

Create an index on the column track_time.

To calculate the arithmetic mean of the coordinates of each tracktime category, we use the Mean coordinates function from the processing toolbox.

Create new layer with average position per track_time category.

The resulting layer does not contain the track ID and date-times. To get this ‘back,’ we need to split the tracktime ID’s we created earlier back into two columns with the track ID’s and the date-time records. To do so, we use the string_to_array() function in the Field calculator; string_to_array("tracktime", "_")[0] to get the track ID’s and string_to_array("tracktime", "_")[1] to get the date-time values.

Extract the track ID’s from the column tracktime.

Extract the date-time records from the column tracktime.

We now have a vector layer cattlemovement_perminute with the location data per minute. The tracks were recorded over a 15-day period, with some longer periods between tracks. To speed things up, and to reduce the length of the animated map, we use a subset of the recorded tracks, e.g., those for the tracks in the Cubuna.
Select and save tracking data for Cubunu

Select features using the ‘select features’ option.

Save the selected features as a new layer using the context menu: right click on the layer cattle movement, and in the context menu, select ‘Export > Save selected Features as’.

Save the new vector layer ‘Cubuna’ in the (existing) Geopackage ‘cattlemovementdata.gpkg’ (of course, you can also save it in a new Geopackage if you prefer that).

Symbologies
In the Layers windows, we duplicate this layer (right-click the layer, and in the context menu, select duplicate layer) and rename this Cubuna_background. The idea is to use the Cubuna layer to show the moving points, and the Cubuna_background layer to keep the points visible, but in another color. To this end, we assigned random fill colors to each of the tracks in Cubuna layer, with white borders for the day tracks, and black borders for the night tracks. For the Cubuna_background day tracks, we assign a semi-transparent white color to the day tracks and a semi-transparent black color to the night tracks.
Define the symbology

Symbology for the point layer that symbolizing the point locations.

Symbology for the point layer symbolizing the tracks.

Temporal controller
The next step is to enable the Dynamic temporal control under the Temporal tab of the Layer Properties window. With the dynamic temporal control enabled, QGIS will display features/points at certain times or time intervals. Depending on the data, there are different configuration options. We use the Single field with Date/Time option with the date_time column as input. We furthermore set the event duration to 1 minute. This defines how long the points will be visible after the start.
Enable the temporal control
The Temporal tab can be found in the Layer properties 1. The date and time for each location is determined by the values in the field date_time. We select the Single Field with Data/Time from the configuration drop down menu 2, and the field date-time to define the date and time 4. Finally, we set the event duration to 1 minute 3.

Endable the dynamic temporal control for the ‘Cubuna’ layer in the Layer properties Window.

We do the same for the ‘Cubuna_background’ layer. Only this time, we select the ‘Accumulate features over time’ option 5. With this option enables, the points will remain visible after activation.

Endable the dynamic temporal control for the ‘Cubuna’ layer in the Layer properties Window.

We can now open the Temporal Control Panel to preview the animated map, change the animation speed, or change the temporal range to be animated.
Preview animated map
The layers under temporal control have a clock symbol next to the layer name in the Layer window 1. The Temporal Control Panel can be opened by clicking on the Clock icon on the Map Navigation Toolbar 2 or through View ? Panels ? Temporal Controller. In the Temporal Controller window, we can now click on the Animated Temporal Navigation (play icon 3) to activate the animation controls. Click the Set to Full Range (refresh icon 4) to automatically set the time range to the match the dataset. Set the step to 1 minute 5. Now we can preview the animation by clicking the Play button 6.

Preview of the animated map with the Temporal controller.

Note that if the animation is too fast, or too slow, you can adjust the frame rate by clicking Temporal Settings (yellow gear icon 7). Decreasing the the frame rate (frames per second) will slow down the animation.

It would be nice if we can add a label that displays the time frame on the map. We can do that using the built in Title Decoration.
Add label with time stamp
The following is based on the tutorial by Ujaval Gandhi³. Go to View ? Decorations ? Title Label.

Adding a title label to the map.

Click the checkbox to enable it and click Insert an Expression button and enter the following expression to display the date and time.

[%format_date(@map_start_time, 'dd MMMM yyyy hh:mm:ss')%]

Here, the variable @map_start_time contains the timestamp of the current time slice being displayed. So we can use that timestamp and format it to display the date and time of occurrence. See the QGIS documentation for more information about the syntax and options.

Define the title label text.

The font type and size, background color and placement can all be adapted to your likening. In the example, I used a white font (Noto Sans Georgian, 22pt) on a 43% transparent black background.

Export the animated map
So now we have an animated map that we can view and explore in QGIS. But what if we want to share the map? The Time Controller has the option to export the frames of the animations as individual png files.
Export the animated map
The first step is to export the map animation. To do so, we select the Export Animation (save icon) in the Temporal control window. In the Export Map Animation dialog, we click on the ... Output directory 1 to choose the directory in which the images will be saved. We use Calculate from layer 2 to set the extent to match that of the Cubuna point layer. Activate the little lock 4, and set the output height (the width will be automatically adjusted) 3. Optionally, the time range can be set, e.g., to limit the video to the first day.

Export map animation.

Once the export finishes, we have a large number of PNG images, each representing a 1-minute step, in the output directory. We can now convert these into an animated image (gif) or a video. Given the large number of png files we just created, the gif file will be very large, and it takes a long time to generate. Creating a video is therefore the better option.

There are various tools, but below we are going to use FFmpeg, a cross-platform solution to record, convert and stream audio and video.
From pngs to video
FFmpeg is a command-line tool. If you are on Windows, you can use the command line (cmd) or Windows PowerShell. Either way, first we need to go to the working directory with the png images. In the console, you type in:
```
cd C:\users\brp\Desktop\movementdata
```
Now we use the FFmpeg function to convert the png files in that folder to a video. With the command below, we create two video’s, one in the popular mp4 format, the other in the mkv format. The most important parameter is the -i, which stands for input, followed by the cattlemovement%04d.png. This part of the code identifies the input files as all the png files in the folder which names start with ‘cattlemovement,’ followed by a 4 digit number.
```
ffmpeg -framerate 60 -i cattlemovement%04d.png -crf 20 cattlemovement2.mp4
ffmpeg -i cattlemovement%04d.png -c:v libx264 -preset slow -crf 22 -c:a copy cattlemovement.mkv
```
I leave it up to you to find out more about the other parameters. This page provides an overview of some of the main options. And on this page is more specifically about the various encoding options. And there is of course the official documentation.

The resulting video is around 8 MB. Which is pretty good, given that all the input png files together were 6.45 GB. An in case you are curious, a gif file would have been around 218 MB large, and it takes a lot more time to create. So, yes, creating a video definitely is a good choice here. But the video, that was what it was all about. Check it out below (if it doesn’t automatically play, hit the play button).
Your browser does not support the video tag. You can watch the video on Youtube.
So how useful is a video like the one above? Not sure to be honest. It does raise some interesting questions. Like, how do the pastoralists decide where to go? They must know the area pretty well given that they need to water their animals (i.e., reach the water holes, here marked by blue dots) on time. And what about those night tracks? I guess that is exactly what I like about this kind of maps, they make you curious about what is going on ?. And check out the article for some answers.
Afterword
Hope you enjoyed reading the post. Want to see more examples? Check out this post by Topi Tjukanov and this tutorial by Ujaval Gandhi, both of which served as inspiration for this post. And there are a lot of inspiring video tutorials on Youtube. And last but not least, thanks to Moritz et al. for providing the data and providing feedback on questions, and the Movebank for the answers to my inquiries.

References 1. Moritz M. Data from: An integrated approach to modeling grazing pressure in pastoral systems: the case of the Logone Floodplain (Cameroon). Published online 2018. doi:10.5441/001/1.J682DS56 2. Moritz M, Soma E, Scholte P, et al. An Integrated Approach to Modeling Grazing Pressure in Pastoral Systems: The Case of the Logone Floodplain (Cameroon). Human Ecology. 2010;38(6):775-789. doi:10.1007/s10745-010-9361-z 3. Gandhi U. Animating time series data (QGIS3). Published online 2019. [https:]]
27 August 2021
19:59
From GIS to Remote Sensing: New publication about the Semi-Automatic Classification Plugin in the Journal of Open Source Software
sur Planet OSGeo

I am very glad to announce that the paper "Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS" has been published in the prestigious Journal of Open Source Software.The paper is freely available at this link.

I am very grateful to the reviewers and editors of the Journal for their valuable work, making an exceptional contribution to the open source initiative.I also invite you to contribute to the Journal, for instance volunteering to review.
This paper is very important as it describes the purpose and characteristics of the Semi-Automatic Classification Plugin.
If you are using the Semi-Automatic Classification Plugin in your research please cite as:Congedo, Luca, (2021). Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS. Journal of Open Source Software, 6(64), 3172, [https:]]
For any comment or question, join the Facebook group or GitHub discussions about the Semi-Automatic Classification Plugin.
26 August 2021
16:58
Fernando Quadro: Lançamento: Combo Python com GIS do Zero
sur Planet OSGeo

Prezado leitor,

Você trabalha com dados geográficos, domina o QGIS, tem vontade de automatizar os seus processos mas não sabe programar?

Então essa é a sua chance, pois a Geocursos acaba de lançar um novo curso que vai ter ensinar a programar em Python do Zero e te levar a automação dos seus processos GIS, criação de plugins, interpolação e muito mais.

Ficou interessado?

Acesse o site e matricule-se!
?
[https:]]
11:00
CARTO Blog: How to do Route Optimization at Scale with CARTO & BigQuery
sur Planet OSGeo

Computing distance metrics is a challenging problem in spatial analysis. When studying urban travel, calculating distances between two locations as the crow flies is the mo...
24 August 2021
10:27
Andrea Antonello: SMASH 1.7.0 is out!
sur Planet OSGeo
We just released version 1.7.0 of SMASH to the stores. This was initially thought as a bugfix release but then we got caught up in the vortex of some advanced users and their well formulated comments, feature requests and bugfix ideas. This lead to a set of new features:
Form enhancements:
Probably the most important feature. Forms can now be used also for postgis and geopackage data sources. Until now it was possible only for project notes.

Autocomplete combos for very long lists of choices:

Sketches are back (well, for those that came from geopaparazzi):

String combos in forms can now be encoded. This means that each item of a combo can have a label and a value. That is another nice feature brought in by the Georepublic people.

Export project images to folder
Another feature asked by geopaparazzi lovers. And here it is:

Contour lines
Mapsforge (or better andromap) maps can now be displayed with contour lines.

Other fixes and little enhancements:
- it is now possible to add points by GPS and map center when editing geopackage/postgis layers
- geopackage layer selection has been improved
- zoom-in when notes are very near has been enhanced
- when selecting multiple notes, previous popups are properly disposed
- tile based layer images now properly update when switching layers
- camera setting, speak resolution) are properly applied
- form notes now always show the label. They didn't when exporting to gpx/kml and in the notes list
- log merging now uses the right master log (the first)
This version is aligned with version 3.2 of the Geopaparazzi Survey Server.

Enjoy!!!

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