Le portail francophone de la géomatique

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11749 items (7 unread) in 53 feeds

Dans la presse (2 unread)

• Décryptagéo, l'information géographique
• Cybergeo
• Revue Internationale de Géomatique (RIG)
• SIGMAG & SIGTV.FR - Un autre regard sur la géomatique (2 unread)
• Mappemonde

Du côté des éditeurs

• Imagerie Géospatiale
• Toute l’actualité des Geoservices de l'IGN
• arcOrama, un blog sur les SIG, ceux d ESRI en particulier
• arcOpole - Actualités du Programme
• Géoclip, le générateur d'observatoires cartographiques
• Blog GEOCONCEPT FR

Toile géomatique francophone (5 unread)

• Géoblogs (GeoRezo.net)
• Geotribu
• Les cafés géographiques
• UrbaLine (le blog d'Aline sur l'urba, la géomatique, et l'habitat)
• Séries temporelles (CESBIO)
• Datafoncier, données pour les territoires (Cerema)
• Cartes et figures du monde
• SIGEA: actualités des SIG pour l'enseignement agricole
• Data and GIS tips
• Neogeo Technologies
• ReLucBlog
• L'Atelier de Cartographie
• My Geomatic
• archeomatic (le blog d'un archéologue à l’INRAP)
• Cartographies numériques (5 unread)
• Veille cartographie
• Makina Corpus
• Oslandia
• Camptocamp
• Carnet (neo)cartographique
• Le blog de Geomatys
• GEOMATIQUE
• Geomatick
• CartONG (actualités)

Géomatique anglophone

• Planet Geospatial - http://planetgs.com
• Google Maps Mania
• All Points Blog
• Directions Media - Podcasts
• Navx
• James Fee GIS Blog
• Open Geospatial Consortium (OGC)
• Planet OSGeo

Blogs GeoRezo.net

• Parcell'air
• Le coin de l'open-source géospatial
• INSPIRE by clouds
• Les GéoBlogs
• Infobulle
• Le blog SIG & URBA
• Blog Interopérabilité & GéoInformation

Géomatique anglophone

• 13 June 2023
• 17:48

  GeoSolutions: GeoSolutions presence at FOSS4G 2023 in Prizren (Kosovo)

  sur Planet OSGeo

  You must be logged into the site to view this content.

• 15:00

  Chronotube

  sur Google Maps Mania
  NYC Subwaysheds visualizes how far you can get in "40 minutes from each subway station in New York City". Hover over a subway station on this map and an isochrone layer shows the accessible areas around that station in ten minute intervals (traveling by subway and by foot).Mapbox's Chris Whong was inspired to make the map by the ever popular Chronotrains map. Chronotrains visualizes the travel
• 9:38

  Where You Can't Afford to Live

  sur Google Maps Mania
  The Guardian has published an interactive map which visualizes where you can't afford to live or rent in the UK. Unfortunately the newspaper has mistakenly mistitled the map Find out where you can afford to buy or rent in Great Britain rather than the presumably intended 'Find out where you can't afford to buy or rent in Great Britain'.The Guardian map allows you to enter your annual salary to

• 8:11

  gvSIG Team: gvSIG Desktop aplicado al riesgo de impacto paisajístico

  sur Planet OSGeo
  

  Hoy os traemos una presentación de la empresa Geoscan, una consultora con muchos años de experiencia en áreas como la de la ingeniería geológica y el medio ambiente. En este caso nos muestran el uso de gvSIG Desktop para analizar el impacto paisajístico de las instalaciones de una empresa de producción y comercialización de semillas.

• 7:42

  OPENGIS.ch: Unterstützung für WMTS im QGIS Swiss Locator

  sur Planet OSGeo
  

  Das QGIS swiss locator Plugin erleichtert in der Schweiz vielen Anwendern das Leben dadurch, dass es die umfangreichen Geodaten von swisstopo und opendata.swiss zugänglich macht. Darunter ein breites Angebot an GIS Layern, aber auch Objektinformationen und eine Ortsnamensuche.

  Dank eines Förderprojektes der Anwendergruppe Schweiz durfte OPENGIS.ch ihr Plugin um eine zusätzliche Funktionalität erweitern. Dieses Mal mit der Integration von WMTS als Datenquelle, eine ziemlich coole Sache. Doch was ist eigentlich der Unterschied zwischen WMS und WMTS?

  WMS vs. WMTS

  Zuerst zu den Gemeinsamkeiten: Beide Protokolle – WMS und WMTS – sind dazu geeignet, Kartenbilder von einem Server zu einem Client zu übertragen. Dabei werden Rasterdaten, also Pixel, übertragen. Ausserdem werden dabei gerenderte Bilder übertragen, also keine Rohdaten. Diese sind dadurch für die Präsentation geeignet, im Browser, im Desktop GIS oder für einen PDF Export.

  Der Unterschied liegt im T. Das T steht für “Tiled”, oder auf Deutsch “gekachelt”. Bei einem WMS (ohne Kachelung) können beliebige Bildausschnitte angefragt werden. Bei einem WMTS werden die Daten in einem genau vordefinierten Gitternetz — als Kacheln — ausgeliefert. 

  Der Hauptvorteil von WMTS liegt in dieser Standardisierung auf einem Gitternetz. Dadurch können diese Kacheln zwischengespeichert (also gecached) werden. Dies kann auf dem Server geschehen, der bereits alle Kacheln vorberechnen kann und bei einer Anfrage direkt eine Datei zurückschicken kann, ohne ein Bild neu berechnen zu müssen. Es erlaubt aber auch ein clientseitiges Caching, das heisst der Browser – oder im Fall von Swiss Locator QGIS – kann jede Kachel einfach wiederverwenden, ganz ohne den Server nochmals zu kontaktieren. Dadurch kann die Reaktionszeit enorm gesteigert werden und flott mit Applikationen gearbeitet werden.

  Warum also noch WMS verwenden?

  Auch das hat natürlich seine Vorteile. Der WMS kann optimierte Bilder ausliefern für genau eine Abfrage. Er kann Beispielsweise alle Beschriftungen optimal platzieren, so dass diese nicht am Kartenrand abgeschnitten sind, bei Kacheln mit den vielen Rändern ist das schwieriger. Ein WMS kann auch verschiedene abgefragte Layer mit Effekten kombinieren, Blending-Modi sind eine mächtige Möglichkeit, um visuell ansprechende Karten zu erzeugen. Weiter kann ein WMS auch in beliebigen Auflösungen arbeiten (DPI), was dazu führt, dass Schriften und Symbole auf jedem Display in einer angenehmen Grösse angezeigt werden, währenddem das Kartenbild selber scharf bleibt. Dasselbe gilt natürlich auch für einen PDF Export.

  Ein WMS hat zudem auch die Eigenschaft, dass im Normalfall kein Caching geschieht. Bei einer dahinterliegenden Datenbank wird immer der aktuelle Datenstand ausgeliefert. Das kann auch gewünscht sein, zum Beispiel soll nicht zufälligerweise noch der AV-Datensatz von gestern ausgeliefert werden.

  Dies bedingt jedoch immer, dass der Server das auch entsprechend umsetzt. Bei den von swisstopo via map.geo.admin.ch publizierten Karten ist die Schriftgrösse auch bei WMS fix ins Kartenbild integriert und kann nicht vom Server noch angepasst werden.

  Im Falle von QGIS Swiss Locator geht es oft darum, Hintergrundkarten zu laden, z.B. Orthofotos oder Landeskarten zur Orientierung. Daneben natürlich oft auch auch weitere Daten, von eher statischer Natur. In diesem Szenario kommen die Vorteile von WMTS bestmöglich zum tragen. Und deshalb möchten wir der QGIS Anwendergruppe Schweiz im Namen von allen Schweizer QGIS Anwender dafür danken, diese Umsetzung ermöglicht zu haben!

  Der QGIS Swiss Locator ist das schweizer Taschenmesser von QGIS. Fehlt dir ein Werkzeug, das du gerne integrieren würdest? Schreib uns einen Kommentar!

• 12 June 2023
• 11:17

  The Map of Roman Amphitheaters

  sur Google Maps Mania
  Roman Amphitheaters is an interactive map of Roman amphitheaters built in Europe and northern Africa during the long reign of the Roman Empire. The map has been created using Sebastian Heath's Roman amphitheaters data.The amphitheater markers on the map are sized by capacity. Select an amphitheater on the map and an information window opens providing details on the amphitheaters's capacity,

• 11:00

  Lutra consulting: Webinar: Processing LiDAR data in QGIS 3.32

  sur Planet OSGeo

  Join this webinar to learn more about the new features in QGIS to process LiDAR data:

  Date: Monday, June 26, 2023 at 14:00 GMT

  Duration: 30 minutes + 15 minutes Q&A session

  Speaker: Martin Dobias, CTO at Lutra Consulting with more than 15 years of QGIS development experience

  

  Description

  Point clouds are an increasingly popular data type thanks to the decreasing cost of their acquisition through lidar surveys and photogrammetry. On top of that, more and more national mapping agencies release high resolution point cloud data (spanning large areas and consisting of billions of points), unlocking many new use cases.

  This webinar will summarize the latest QGIS release 3.32 and the addition of tools for point cloud analysis right from QGIS Processing toolbox: clip, filter, merge, export to raster, extract boundaries and more - all backed by PDAL library that already ships with QGIS, without having to rely on third party proprietary software.

  This work was made possible by the generous donations to our crowdfunding.

  Live on Monday, June 26, 2023 at 14:00 GMT

  Add it to your calendar!

• 8:01

  gvSIG Team: Control de versiones y edición de cartografía multiusuario con software libre

  sur Planet OSGeo
  

  Uno de los desarrollos más avanzados que han llegado a gvSIG Desktop es su control de versiones, VCSGIS, y que lo ha convertido en una herramienta fundamental para resolver las problemáticas de edición avanzada a las que el software libre no tenía respuesta.

  En esta presentación podréis conocer qué es VCSGIS y todo lo que permite hacer

• 10 June 2023
• 10:32

  Global Sunlight Chart

  sur Google Maps Mania
  The ShadeMap: Direct Sunlight Chart is an interactive map which can calculate the number of hours of direct sunlight for any location on Earth. Unlike traditional sun charts, this map actually accounts for shadows cast by buildings and terrain. If a tall building or mountain blocks out the sun for part of the day this is taken into account in the sunlight chart for that location. The

• 09 June 2023
• 17:48

  GeoSolutions: GeoSolutions at WAGIS 2023 in Tacoma, WA 14-15 June

  sur Planet OSGeo

  You must be logged into the site to view this content.

• 10:41

  America's Pink Migration Banana

  sur Google Maps Mania
  The San Francisco Chronicle has published a fascinating map which visualizes net migration in US counties. On this map counties which have seen a net loss in migration are shown in pink and those that have seen a net gain are shown in blue. The map therefore provides a great overview of where Americans are moving to and from.The Where People are Moving map reveals a pink banana running down the

• 7:56

  gvSIG Team: Plataforma de información geográfica del Estado de Tocantins, Brasil

  sur Planet OSGeo
  

  Os traemos la presentación de otro interesante proyecto de implantación de gvSIG Online, en este caso en el Estado de Tocantins (Brasil) y que ha permitido publicar numerosas capas de información geográfica, estructurada en diversos geoportales.

  De este proyecto, además, destacamos el desarrollo de herramientas en gvSIG Online para la generación de dashboards o cuadros de mandos.

• 08 June 2023
• 16:00

  Lutra consulting: Virtual Point Clouds (VPC)

  sur Planet OSGeo

  As a part of our crowdfunding campaign we have introduced a new method to handle a large number of point cloud files. In this article, we delve into the technical details of the new format, rationale behind our choice and how you can create, view and process virtual point cloud files.

  Rationale

  Lidar surveys of larger areas are often multi-terabyte datasets with many billions of points. Having such large datasets represented as a single point cloud file is not practical due to the difficulties of storage, transfer, display and analysis. Point cloud data are therefore typically stored and distributed split into square tiles (e.g. 1km x 1km), each tile having a more manageable file size (e.g. ~200 MB when compressed).

  Tiling of data solves the problems with size of data, but it introduces issues when processing or viewing an area of interest that does not fit entirely into a single tile. Users need to develop workflows that take into account multiple tiles and special care needs to be taken to deal with data near edges of tiles to avoid unwanted artefacts in outputs. Similarly, when viewing point cloud data, it becomes cumbersome to load many individual files and apply the same symbology.

  Here is an example of several point cloud tiles loaded in QGIS. Each tile is styled based on min/max Z values of the tile, creating visible artefacts on tile edges. The styling has to be adjusted for each layer separately:

  

  Virtual Point Clouds

  In the GIS world, many users are familiar with the concept of virtual rasters. A virtual raster is a file that simply references other raster files with actual data. In this way, GIS software then treats the whole dataset comprising many files as a single raster layer, making the display and analysis of all the rasters listed in the virtual file much easier.

  Borrowing the concept of virtual rasters from GDAL, we have introduced a new file format that references other point cloud files - and we started to call it virtual point cloud (VPC). Software supporting virtual point clouds handles the whole tiled dataset as a single data source.

  At the core, a virtual point cloud file is a simple JSON file with .vpc extension, containing references to actual data files (e.g. LAS/LAZ or COPC files) and additional metadata extracted from the files. Even though it is possible to write VPC files by hand, it is strongly recommended to create them using an automated tool as described later in this post.

  On a more technical level, a virtual point cloud file is based on the increasingly popular STAC specification (the whole file is a STAC API ItemCollection). For more details, please refer to the VPC specification that also contains best practices and optional extensions (such as overviews).

  Virtual Point Clouds in QGIS

  We have added support for virtual point clouds in QGIS 3.32 (released in June 2023) thanks to the many organisations and individuals who contributed to our last year’s joint crowdfunding with North Road and Hobu. The support in QGIS consists of three parts:

  1. Create virtual point clouds from a list of individual files
  2. Load virtual point clouds as a single map layer
  3. Run processing algorithms using virtual point clouds

  Those who prefer using command line tools, PDAL wrench includes a build_vpc command to create virtual point clouds, and all the other PDAL wrench commands support virtual point clouds as the input.

  Using Virtual Point Clouds

  In this tutorial, we are going to generate a VPC using the new Processing algorithm, load it in QGIS and then generate a DTM from terrain class. You will need QGIS 3.32 or later for this. For the purpose of this example, we are using the LiDAR data provided by the IGN France data hub.

  In QGIS, open the Processing toolbox panel, search for the Build virtual point cloud (VPC) algorithm ((located in the Point cloud data management group):

  

  VPC algorithm in the Processing toolbox

  In the algorithm’s window, you can add point cloud layers already loaded in QGIS or alternatively point it to a folder containing your LAZ/LAS files. It is recommended to also check the optional parameters:

  • Calculate boundary polygons - QGIS will be able to show the exact boundaries of data (rather than just rectangular extent)

  • Calculate statistics - will help QGIS to understand ranges of values of various attributes

  • Build overview point cloud - will also generate a single “thinned” point cloud of all your input data (using only every 1000th point from original data). The overview point cloud will be created next to the VPC file - for example, for mydata.vpc, the overview point cloud would be named mydata-overview.copc.laz

  

  VPC algorithm inputs, outputs and options

  After you set the output file and start the process, you should end up with a single VPC file referencing all your data. If you leave the optional parameters unchecked, the VPC file will be built very quickly as the algorithm will only read metadata of input files. With any of the optional parameters set, the algorithm will read all points which can take some time.

  Now you can load the VPC file in QGIS as any other layer - using QGIS browser, Data sources dialog in QGIS or by doing drag&drop from a file browser. After loading a VPC in QGIS, the 2D canvas will show boundaries of individual files - and as you zoom in, the actual point cloud data will be shown. Here, a VPC loaded together with the overview point cloud:

  

  Virtual point cloud (thinned version) generated by the VPC algorithm

  Zooming in QGIS in 2D map with elevation shading - initially showing just the overview point, later replaced by the actual dense point cloud:

  

  VPC output on 2D: displaying details when zooming in

  In addition to 2D maps, you can view the VPC in a 3D map windows too:

  If the input files for VPCs are not COPC files, QGIS will currently only show their boundaries in 2D and 3D views, but processing algorithms will work fine. It is however possible to use the Create COPC algorithm to batch convert LAS/LAZ files to COPC files, and then load VPC with COPC files.

  It is also worth noting that VPCs also work with input data that is not tiled - for example, in some cases the data are distributed as flightlines (with lots of overlaps between files). While this is handled fine by QGIS, for the best performance it is generally recommended to first tile such datasets (using the Tile algorithm) before doing further display and analysis.

  Processing Data with Virtual Point Clouds

  Now that we have the VPC generated, we can run other processing algorithms. For this example, we are going to convert the ground class of the point cloud to a digital terrain model (DTM) raster. In the QGIS Processing toolbox, search for Export to raster algorithm (in the Point cloud conversion group):

  

  VPC layer can be used as an input to the point cloud processing algorithm

  This will use the Z values from the VPC layer and generate a terrain raster based on a user defined resolution. The algorithm will process the tiles in parallel, taking care of edge artefacts (at the edges, it will read data also from the neighbouring tiles). The output of this algorithm will look like this:

  

  Converting a VPC layer to a DTM

  The output raster contains holes where there were no points classified as ground. If needed for your use case, you can fill the holes using Fill nodata algorithm from GDAL in the Processing toolbox and create a smooth terrain model for your input Virtual Point Cloud layer:

  

  Filling the holes in the DTM

  Virtual point clouds can be used also for any other algorithms in the point cloud processing toolbox. For more information about the newly introduced algorithms, please see our previous blog post.

  All of the point cloud algorithms also allow setting filtering extent, so even with a very large VPC, it is possible to run algorithms directly on a small region of interest without having to create temporary point cloud files. Our recommendation is to have input data ready in COPC format, as this format provides more efficient access to data when spatial filtering is used.

  Streaming Data from Remote Sources with VPCs

  One of the very useful features of VPCs is that they work not only with local files, but they can also reference data hosted on remote HTTP servers. Paired with COPCs, point cloud data can be streamed to QGIS for viewing and/or processing - that means QGIS will only download small portions of data of a virtual point cloud, rather than having to download all data before they could be viewed or analysed.

  Using IGN’s lidar data provided as COPC files, we have built a small virtual point cloud ign-chambery.vpc referencing 16 km2 of data (nearly 700 million points). This VPC file can be loaded in QGIS and used for 2D/3D visualisation, elevation profiles and processing, with QGIS handling data requests to the server as necessary. Processing algorithms only take a couple of seconds if the selected area of interest is small (make sure to set the “Cropping extent” parameter of algorithms).

  All this greatly simplifies data access to point clouds:

  • Data producers can use very simple infrastructure - a server hosting static COPC files together with a single VPC file referencing those COPC files.

  • Users can use QGIS to view and process point cloud data as a single map layer, with no need to download large amounts of data, QGIS (and PDAL) taking care of streaming data as needed.

  We are very excited about the opportunities that virtual point clouds are bringing to users, especially when combined with COPC format and access from remote servers!

  Thanks again to all contributors to our crowdfunding campaign - without their generous support, this work would not have been possible.

  Contact us if you would like to add more features in QGIS to handle, analyse or visualise lidar data.

• 15:00

  Dr. Jeff de La Beaujardiere receives OGC Lifetime Achievement Award

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC) is excited to announce that Dr. Jeff de La Beaujardiere has been selected as the latest recipient of the OGC Lifetime Achievement Award. The announcement was made last night during the Executive Dinner in the U.S. Space & Rocket Center at the 126th OGC Member Meeting in GeoHuntsville, AL.

  Jeff has been selected for the award due to his long standing leadership, commitment, and support for the advancement and uptake of standards used for the dissemination of Earth Science information.

  “I’m so happy that Jeff has been selected to receive the OGC Lifetime Achievement Award,” said OGC CEO, Dr. Nadine Alameh. “Jeff is more than a champion for standards, more than an OGC Gardels award winner, and more than the WMS editor and promoter: Jeff is a role model for many of us in geospatial circles, and has directly and indirectly influenced generations of interoperability enthusiasts to collaborate, to innovate, and to solve critical problems related to our Earth. From OGC and myself, I offer our congratulations and thank Jeff for his technical work – and for being such an inspiration to so many!”

  For more than 25 years, Jeff’s support of open standards and OGC’s FAIR mission has improved access to Earth science information for countless users and decision-makers around the globe. Since 1995, Jeff has focused on improving public access to scientific data by pushing for it to be discoverable, accessible, documented, interoperable, citable, curated for long-term preservation, and reusable by the broader scientific community, external users, and decision-makers. 

  In the OGC community, Jeff is best known as the Editor of the OGC Web Map Service (WMS) Specification: a joint OGC/ISO Standard that now supports access to millions of datasets worldwide. OGC WMS was the first in the OGC Web Services suite of Standards and is the most downloaded Standard from OGC. But most importantly, the OGC WMS Standard truly revolutionized how geospatial data is shared and accessed over the web. 

  Jeff was also a major contributor to other OGC Standards, including the OGC Web Services Architecture, the OGC Web Map Context, OGC Web Terrain Service, and OGC Web Services Common. 

  Jeff’s journey with Standards – and his engagement with OGC – started back in 1998 when NASA was leading the effort to implement the Digital Earth program. At that time, Jeff championed interoperability standards as fundamental to realizing the Digital Earth vision. As part of his journey, he has provided leadership to the Geospatial Applications and Interoperability (GAI) Working Group of the U.S. Federal Geographic Data Committee and to the OGC Technical Committee. 

  In 2002 and 2003, Jeff served as Portal Manager for Geospatial One-Stop, a federal electronic government initiative. He led a team of experts in defining the requirements, architecture, and competitive solicitation for a Portal based on open standards and led an OGC interoperability initiative in developing and demonstrating a working implementation. This was a fast-paced, high-stakes effort involving many companies and agencies building on what today is the OGC Collaborative Solution & Innovation Program. 

  Jeff has received several awards for his leadership and impact in the many communities that he has participated in throughout his career, including the 2013 OGC Kenneth D. Gardels Award, the 2023 ESIP President’s Award, and the 2003 Falkenberg Award at AGU which honors “a scientist under 45 years of age who has contributed to the quality of life, economic opportunities, and stewardship of the planet through the use of Earth science information and to the public awareness of the importance of understanding our planet.”

  With this lifetime achievement award, OGC recognizes and celebrates Jeff’s lifetime of service, and his steadfast support of FAIR geospatial information for the benefit of open science, and society.

  The post Dr. Jeff de La Beaujardiere receives OGC Lifetime Achievement Award appeared first on Open Geospatial Consortium.

• 9:35

  QGIS Blog: Plugin Update May 2023

  sur Planet OSGeo

  In May 22 new plugins that have been published in the QGIS plugin repository.

  Here’s the quick overview in reverse chronological order. If any of the names or short descriptions piques your interest, you can find the direct link to the plugin page in the table below the screenshot.

  

  Station Offset

  This plugin computes the station and offset of points along polylines and exports those values to csv for other applications

  MGP Connect

  Enable Maxar SecureWatch customers to stream imagery more effectively in QGIS.

  Triple2Layer

  this plugin imports data

  DiscordRPC Plugin for QGIS

  QGIS plugin that enables displaying a Rich Presence in Discord

  ERS

  This plugin determines calculated polluant concentrations around sensible sites’s perimeters

  IPP

  This plugin calculates IPP

  Road Vectorisation

  This plugin is designed to vectorize roads on satellite images

  Image vectorisator

  Plugin for image vectorisation

  H-RISK with noisemodelling

  Sound levels and Health risks of environmental noise

  Non_electrical_vehicle

  This plugins calculates number of non electrical vehicles

  HOT Templates and Symbology Manager

  QGIS plugin for managing HOT map templates and symbology

  Transparency Setter

  Apply the specified transparency value to both vector and raster layers, as well as layers within the selected groups in the Layer Panel

  DBGI

  Creates geopackages that match the requirements for the DBGI project

  StyleLoadSave

  Load or Save active vector layer style

  PixelCalculator

  Interactively calculate the mean value of selected pixels of a raster layer.

  GISTDA sphere basemap

  A plugin for adding base map layers from GISTDA sphere platform ( [https:]] ).

  Adjust Style

  Adjust the style of a map with a few clicks instead of altering every single symbol (and symbol layer) for many layers, categories or a number of label rules. A quick way to adjust the symbology of all layers (or selected layers) consistantly, to check out how different colors / stroke widths / fonts work for a project, and to save and load styles of all layers – or even to apply styles to another project. With one click, it allows to: adjust color of all symbols (including color ramps and any number of symbol layers) and labels using the HSV color model (rotate hue, change saturation and value); change line thickness (i.e. stroke width of all symbols / symbol borders); change font size of all labels; replace a font family used in labels with another font family; save / load the styles of all layers at once into/from a given folder.

  APLS

  This plugin performs Average Path Length Similarity

  qaequilibrae

  Transportation modeling toolbox for QGIS

  QGPT Agent

  QGPT Agent is LLM Assistant that uses openai GPT model to automate QGIS processes

  FuzzyJoinTables

  Join tables using min Damerau-Levenshtein distance

  Chandrayaan-2 IIRS

  Generates reflectance from Radiance data of Imaging Infrared Spectrometer sensor of Chandrayaan 2

• 9:16

  The Privatisation of East Germany

  sur Google Maps Mania
  After the reunification of Germany in 1990 the German Democratic Republic established an agency in order to privatise East German enterprises. The Treuhandanstalt (Trust Institution) was tasked with overseeing the sale of over 8,500 state-owned companies. Under communism nearly half of all East Germans worked for the state or for state-run companies. Privatising all East German enterprises

• 7:59

  gvSIG Team: GeoETL de la plataforma gvSIG Online: Automatizar transformaciones de datos

  sur Planet OSGeo
  

  Una mejora considerable de gvSIG Online respecto a otros productos del mercado es su ETL. Gracias a su ETL, gvSIG Online podrá realizar integraciones con otras fuentes de datos de forma ágil y sin necesidad de desarrollo.

  ETL es un plugin que se utiliza para automatizar tareas de transformaciones de datos, ya sean repetitivas o no, de manera que no sea necesario la manipulación de los datos a través de código. De esta manera, cualquier usuario es capaz de hacer una manipulación de los datos (geométricamente o no) o una homogeneización de datos que provengan de diferentes orígenes y formatos.

  Esto es posible gracias a un canvas que representará gráficamente el proceso de transformación de los datos de una manera fácil e intuitiva.

  Si queréis conocer todo el potencia de GeoETL, no os perdáis el vídeo:

• 07 June 2023
• 8:42

  Wildfires & Smoke Pollution

  sur Google Maps Mania
  Wildfires in Quebec and Nova Scotia are causing high levels of unhealthy air conditions across much of eastern Canada and the northeastern United States. Over 400 fires were reported to be burning in Canada on Tuesday evening resulting in smoke pollution and dangerous levels of particulate matter 2.5 over large areas.FireSmoke Canada has an interactive smoke forecast map which provides

• 8:02

  gvSIG Team: Conociendo gvSIG Mapps

  sur Planet OSGeo
  

  Todo el mundo conoce gvSIG Desktop, el origen de el catálogo de soluciones que denominamos Suite gvSIG. Cada vez más organizaciones de todo el mundo están implantando gvSIG Online como su plataforma de gestión de datos espaciales y geoportales. Y, aunque menos conocido, crece el número de entidades que usan gvSIG Mapps… bien como app para toma de datos en campo, bien como apps desarrolladas con su framework.

  ¿Queréis saber más? Os contamos qué es realmente gvSIG Mapps:

• 06 June 2023
• 18:48

  gvSIG Team: OpenTripPlanner Open Days 2023 in Valencia

  sur Planet OSGeo
  OpenTripPlanner Open Days 2023

  This September 7 and 8, 2023, OpenTripPlanner (OTP) community members (developers, product owners, users, and any other interested party!) from around the world will meet in Valencia, Spain. OTP Open Days is a summit where we can meet up, exchange ideas, and plan for the future of open source trip planning.

  The event is free to attend.

  Who will be there

  OTP Open Days are open to all. The more you’re involved in using or evaluating OTP, the more you’ll get out of this event. But if Valencia is accessible to you and you’re interested in transportation customer information, consider joining us.

  We are also planning to live stream a plenary session – check back on this website for final confirmation.

  What the program will look like

  This two day conference will include at least 12 different small group sessions aimed at OTP developers and product owners. We’ll also have at least one plenary session including an overview of the latest updates to OTP and the roadmap for the next year.

  Where will we meet

  OTP Open Days 2023 will be hosted by the OTP Project Leadership Committee at the Universitat Politècnica de València (UPV).

  Social events and MobilityData European workshop

  Our partner MobilityData–the global steward of GTFS and GBFS–is co-hosting their European workshop with us at UPV! Their workshop will take place on September 5 and 6. Come for both!

  We’ll also have a social event the evening of September 7. Join us for dinner, drinks, and discussion about everything we do besides trip planning technology!

  (OK–we’ll probably talk about trip planning a little bit at dinner, too…)

  Preliminary schedule

  • Plenary: OTP update and roadmap (business track)
  • Discussion: Flex routing (business)
  • Presentation: OTP APIs and their future (technical, business)
  • Working session: Support for Siri 2.1 (technical)
  • Discussion: Developing an OTP business plan (business)
  • Presentation: OTP’s contribution process (technical)
  • Discussion: OTP’s eco system and associated projects (business)
  • Presentation: Performance improvements for large networks (technical)

  Signup

  Please add yourself to the signup form if you want to attend.

  Partners

• 9:16

  Quiz Around the World

  sur Google Maps Mania
  How well do you know the world? Let's find out with Szilvia Berczes' map it! game. The premise of map it! is very simple. All you have to do is point to the location of ten named countries on a 3D globe. To make the game even easier you can choose which region of the world you wish to play in (Europe, Americas, Asia or Africa). You are awarded one point for every country you identify correctly,

• 7:53

  gvSIG Team: Explorando el potencial de las fichas de búsqueda en gvSIG Desktop

  sur Planet OSGeo

  Uno de los desarrollos más interesantes y desconocidos de gvSIG Desktop son las fichas de búsqueda. Las múltiples funcionalidades que engloban las fichas de búsqueda os van a permitir explotar las consultas a los datos de vuestros proyectos mucho más allá de lo que pensáis.

  Si en vuestros proyectos de SIG trabajáis con numerosos datos alfanuméricos, necesitáis ver esta presentación:

• 05 June 2023
• 12:23

  GRASS GIS: R package rgrass7 to be retired in October, 2023

  sur Planet OSGeo
  Users are encouraged to migrate to the succesor rgrass package The R package rgrass7 interfacing R and GRASS GIS will be removed from active availability on the Comprehensive R Archive Network (CRAN) during October 2023; it will be archived on CRAN. This is because the successor rgrass package has been available since mid-2022, and because the rgdal package on which rgrass7 depends for exchanging files between R and GRASS GIS will also be archived in October 2023, as described in R-spatial evolution project reports (latest providing links to earlier).

• 9:18

  Assassination Simulation

  sur Google Maps Mania
  Japanese broadcaster MBS has released a full scale 3D digital recreation of the assassination of Shinzo Abe. In July 2022 the Japanese Prime Minister Shinzo Abe was shot and killed while giving a speech at Yamato-Saidaiji Station, Nara. A Re-creation of former PM Shinzo Abe's Assassination is a shocking full re-enactment of the Prime Minister's assassination, which uses witness accounts and

• 8:00

  gvSIG Team: Desarrollo del Sistema Único de Direcciones de Uruguay

  sur Planet OSGeo
  

  Hay proyectos de geomática que tienen un gran impacto en un país. Un ejemplo de esto es el proyecto del que os traemos una presentación, el desarrollo del Sistema Único de Direcciones de Uruguay.

  Un proyecto de considerable complejidad que ha implicado desarrollos en el geoportal, geocoder, sistemas de sugerencias, validaciones, cargas masivas, soporte de Open Location Code, API de edición, autenticación, rollback de operaciones,… y todo ello con base tecnológica en gvSIG Online, claro.

• 2:00

  Camptocamp: Camptocamp at FOSS4G 2023

  sur Planet OSGeo

  Enclosure: [download]

  In-person event - Prizren, Kosovo - June 26 - July 2, 2023

• 03 June 2023
• 9:13

  Where is the Cheapest McDonalds?

  sur Google Maps Mania
  At the time of writing the most expensive country in which to buy a Big Mac is Switzerland, where a MacDonald's burger will set you back SFr6.70 (around $7.37). The cheapest country to buy a Big Mac, according to the Big Mac Index, is Egypt, where a burger will cost you E£55.00 (around $1.78). According to the index the average cost of a Big Mac in the USA is $5.36.The Economist's Big Mac Index

• 9:00

  QGIS España: 2º QGISes Camp 2023, reunión anual de la Asociación QGIS España (13 de junio de 2023)

  sur Planet OSGeo

  Las Jornadas de SIG Libre de Girona son uno de los eventos anuales de referencia sobre tecnologías geoespaciales y ciencia de datos espaciales que se realizan en España. Organizadas por el Servicio de SIG y Teledetección (SIGTE) de la Universitat de Girona las Jornadas #siglibre2023 se celebrarán este año los próximos días 14 y 15 de junio en la Facultat de Lletres i de Turisme de la Universitat de Girona.

  Este año, aprovechando de nuevo esta cita de eventos, desde la Asociación vamos a celebrar nuestro 2º Reunión anual el día previo (13 de junio) al inicio de las Jornadas SIG Libre de Girona.

  Queremos desde aquí agradecer la colaboración que el SIGTE nos presta para la organización y difusión del evento.

  ¿Cómo está organizado?

  El evento está organizado como una “des-conferencia”, esto significa que no hay un programa cerrado. Si quieres dar a conocer un caso de uso de QGIS de tu empresa u organización o crees que puedes hacer una sesión sobre alguna de las múltiples funcionalidades de este SIG abierto simplemente vente al evento y preséntalo.

  El objetivo principal es hacer comunidad y compartir las experiencias de usuarios y desarrolladores de QGIS con el resto de los usuarios.

  

  Aprovecharemos también para hacer presentación de la Asociación para las personas no asociadas y recopilar ideas y propuestas a futuro tanto para QGIS como para la Asociación.

  Fecha, hora y lugar de celebración.

  Nos veremos el 13 de junio de 2023 de 17h a 20h en el aula A1 de la Facultad de Letras de la Universidad de Girona.

  
  Ver mapa más grande

  Habrá un coffee-break a las 18h de unos 20 minutos.

  

  Coste/Inscripción

  Se trata de un evento abierto y gratuito. No es necesario hacer prescripción.

  Además tenemos “regalitos” ? para los asistentes.

  Ayúdanos a difundir la #QGISesCamp 2023

  Aquí os dejamos enlaces a nuestras redes sociales y sitio web. Anímate a compartir.

  • Página web: [https:]]
  • Twitter: [https:]]
  • Etiqueta #QGISesCamp
  • Instagram: [https:]]

  

• 2:34

  BostonGIS: PostGIS Bundle 3.3.3 for Windows with MobilityDB

  sur Planet OSGeo

  I recently released PostGIS 3.3.3. bundle for Windows which is available on application stackbuilder and OSGeo download site for PostgreSQL 11 - 15. If you are running PostgreSQL 12 or above, you get an additional bonus extension MobilityDB which is an extension that leverages PostGIS geometry and geography types and introduces several more spatial-temporal types and functions specifically targeted for managing objects in motion.

  What kind of management, think of getting the average speed a train is moving at a segment in time or collisions in time, without any long SQL code. Just use a function on the trip path, and viola. Think about storing GPS data very compactly in a singe row /column with time and being able to ask very complex questions with very little SQL. True PostGIS can do some of this using geometry with Measure (geometryM) geometry types, but you have to deal with that craziness of converting M back to timestamps, which mobilitydb temporal types automatically encode as true PostgreSQL timestamp types.

  Anita Graser, of QGIS and Moving Pandas fame, has written several posts about it such as: Visualizing Trajectories with QGIS and mobilitydb and Detecting close encounters using MobilityDB 1.0.

  Continue reading "PostGIS Bundle 3.3.3 for Windows with MobilityDB"
• 02 June 2023
• 15:02

  Jackie Ng: Announcing: mapguide-react-layout 0.14.8

  sur Planet OSGeo

  We've arrived at the next stop on the tour, a new release of mapguide-react-layout

  This release has the following notable changes

  Map Definition with XYZ tileset restriction liftedMapGuide Open Source 4.0 removed the restriction that Map Definitions cannot link to a XYZ tileset definition. This release of mapguide-react-layout takes advantage of this removed restriction by now supporting loading of a Map Definition that links to a XYZ tileset.Support for loading custom projections and app settings from an Application DefinitionThe beauty of the Extension element in an Application Definition document (and why its XML schema has not required a revision since its introduction) is that we can put any content in there.
  With this release, we are taking advantage of this fact by supporting the ability to read custom projections and app settings from an Application Definition if the right elements are present in the root Extension element of the Application Definition.
  By registering custom projections in the Application Definitions, we can register custom projections with the viewer without requiring an epsg.io lookup.
  The next release of Maestro (the next stop on this tour) will have dedicated editors for specifying custom projections and app settings. So stay tuned to see how this feature can be used.Modal dialog size/positioning now preservedThe redux state around modal dialogs has been reworked so that size/positioning is now preserved. This means that if you close a modal dialog and re-open it later on, it will retain the previous size/positioning it had previously, as demonstrated in this video.
  
  MapGuide Base Layers now has its own opacityPreviously the opacity of MapGuide Base Layers was coupled to the opacity of the MapGuide Map. With this release, MapGuide Base Layers now has its own opacity setting.
  
  
  Other Changes

  • OpenLayers updated to 6.15.1
  • Support disabling custom cursors through a new DISABLE_CURSORS app setting (1 to enable, 0 to disable)
  • Fix potential stale legend state from dispatched update action
  • Fix epsg.io lookup
  • Support Coordinate Tracker with only one projection specified
  • Un-break viewer API drawing example
  • Restore selection appending while holding down SHIFT key
  • Fix viewer state not pushing to url

  
  

  Download

  
  

• 9:20

  Tree Maps of the World

  sur Google Maps Mania
  Gieß den Kiez is an interactive map of over 800,000 trees in Berlin. Using the map Berliners can discover what types of trees are growing in their neighborhood and then sign-up to help water individual trees. By clicking on individual trees on the Gieß den Kiez (Water the Neighborhood) map you can get information about a tree's species, its age and its watering requirements. Registered users

• 8:19

  gvSIG Team: GvSIG Batoví: los jóvenes y adolescentes conociendo y transformando su entorno

  sur Planet OSGeo

  En más de una ocasión os hemos hablado de gvSIG Batoví, un curso-concurso desarrollado en Uruguay y que permite aprender a estudiantes de secundaria el potencial de los Sistemas de Información Geográfica del mejor modo: analizando cómo pueden mejorar su entorno más cercano.

  Hoy os traemos una presentación del proyecto realizada por una de las personas que ha formado parte del equipo coordinador estos últimos años:

• 01 June 2023
• 15:00

  Natural Resources Canada receives inaugural OGC Community Impact Award

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC) announces Natural Resources Canada (NRCan) as the inaugural recipient of the OGC Community Impact Award. The newly established Award is given by OGC to highlight and recognize those members of the OGC Community who, through their exceptional leadership, volunteerism, collaboration, and investment, have had a positive impact on the wider geospatial community.

  The OGC Community Impact award highlights the importance of collaboration, volunteering time and energy, advancing technologies and standards, raising awareness, and helping solve critical issues across the geospatial community. Natural Resources Canada exemplifies all of these qualities through their championing of innovation and standards. They consistently go above and beyond as both an OGC Member, and as a member of the wider geospatial community. 

  NRCan has, and continues to, make an impact within the OGC Community through their strong, consistent, and long term support of multiple OGC Working Groups, numerous Collaborative Solutions & Innovation Initiatives, Sprints, and several OGC Member Meetings. This support comes in addition to NRCan’s continued implementation of OGC Standards and technologies for the betterment of Canada and the world. Through all this, NRCan has made positive impacts across multiple areas, most notably in those related to the Arctic, climate, disaster, and marine domains.

  The OGC Community Impact Award will be presented to Natural Resources Canada on the evening of Wednesday, 7 June, at the Executive Dinner in the U.S. Space & Rocket Center at the 126th OGC Member Meeting in GeoHuntsville, AL.

  The post Natural Resources Canada receives inaugural OGC Community Impact Award appeared first on Open Geospatial Consortium.

• 9:26

  Mapping 1,001 American Novels

  sur Google Maps Mania
  1,001 Novels: A Library of America is an interactive literary map of America. A map on which over one thousand novels have been plotted based on the geographical 'heart' of each story. '1,001 Novels: A Library of America' is a project of love created by Susan Straight, a novelist and professor at UC Riverside. Over the course of five years, Susan read and mapped 1,001 novels set in the United

• 8:09

  gvSIG Team: GvSIG en Repsol: Sistemas clave en la gestión de proyectos de energías renovables

  sur Planet OSGeo
  

  En Repsol se selección la Suite gvSIG como parte de las tecnologías relacionadas con la gestión de proyectos de energías renovables. En particular, en la presentación que os traemos hoy y que recomendamos no os perdáis, se muestra el uso que se hace de gvSIG Online.

  La gestión de proyectos de energías renovables implica a muchos departamentos de la empresa, necesitando entre ellos compartir información de manera continua. Gracias a gvSIG Online estos trabajos se han facilitando enormemente.

  Si solo podéis ver una presentación de uso de SIG este mes, es esta:

• 31 May 2023
• 9:51

  The World's Population in 3D

  sur Google Maps Mania
  This 3D Map of world cities with a population over 100k visualizes the global population of the world's cities as 3D towers. Zoom in on Europe and you can see that London dominates western Europe, towering over Paris, Madrid, Berlin and Rome. The data for the map comes from this Wikipedia list of towns and cities with 100,000 or more inhabitants. Wherein lies the problem. The main problem with

• 8:05

  gvSIG Team: Aplicación para identificación de riesgos en desplazamientos de Cascos Azules con gvSIG Mapps

  sur Planet OSGeo
  

  Para MINUSMA (Misión Multidimensional Integrada de Estabilización de las Naciones Unidas en Malí) se ha desarrollado una aplicación con base en gvSIG Mapps e integrada con gvSIG Online para ayudar a mantener la seguridad de los desplazamientos de los Cascos Azules, especialmente en lo referente a evitar ataques con artefactos explosivos y minas por parte de grupos insurgentes.

  Como sabréis gvSIG Mapps es el framework de desarrollo de la Suite gvSIG que permite desarrollar aplicaciones de mapas con componente geográfica y plenamente integradas con gvSIG Online.

  Aunque por razones evidentes no podemos dar demasiada información del proyecto, os compartimos una presentación autorizada por Naciones Unidas que seguro que os puede interesar.

• 1:00

  Lutra consulting: Native point cloud processing in QGIS

  sur Planet OSGeo

  After the addition of support for visualising point clouds in the recent versions of QGIS, the next step was to add the processing tools so users can manage and analyse their data.

  There are several 3rd party QGIS plugins (either proprietary or not fully open source) which allow users to interrogate and analyse lidar data. But with our latest work, we have introduced powerful point cloud algorithms to the QGIS Processing framework. All the algorithms are available out of the box in QGIS 3.32, with no need to install plugins.

  In this blog post, we summarise the initial point cloud algorithms for QGIS Processing toolbox which will be available in QGIS 3.32 (to be released at the end of June 2023). This work was made possible by the generous donations to our crowdfunding.

  Point Cloud algorithms in QGIS

  First off a quick look at the new algorithms as shown in the Processing toolbox in three groups:

  

  Point Cloud algorithms in QGIS processing toolbox

  • Convert formats: this will allow you to convert your point cloud data between LAS and LAZ formats for the time being. Other PDAL supported formats can be added later.
  • Export to raster: with this algorithm you can export point cloud to a regularly gridded raster data. It uses inverse distance weighting to assign raster cell values. Raster cells with no nearby points will get “no data” values (these holes may be removed by using “Fill nodata” raster algorithm).

  

  Input point cloud layer file

  

  Raster output using Intensity attribute of points

  • Export to raster (using triangulation): this allows you to export Z data to a regularly gridded raster by interpolating between the points using triangulation. Note that this can be slower if you are dealing with a large dataset. If your point cloud is dense, you can export your ground points as a raster using the Export to raster algorithm.

  

  Terrain raster output generated by point cloud triangulation

  • Export to vector: to export point cloud to other vector formats. This is useful to export some of your data for software applications which do not support point cloud data and still use formats such as CSV, Shapefile, DXF.

  

  Exporting point cloud (ground points) to Shapefile styled based on the elevation!

  • Assign projection: assigns a projection to a point cloud layer (if it is wrong or missing)
  • Build virtual point cloud (VPC): with this algorithm you can generate a virtual file (based on STAC specification) and load them as a single file in QGIS. There will be a separate blog post detailing this new exciting feature.
  • Clip: clip a point cloud layer by a vector polygon layer.

  

  Input point cloud layer and a polygon coverage

  

  Result of the clipping algorithm

  • Create COPC: when you load a non-indexed point cloud layer in QGIS, it will take a while for the application to create the COPC index for your file. With this algorithm, you can create the index for all your files in a batch mode.
  • Information: displays information from a point cloud layer:

  LAS           1.4
  point format  6
  count         56736130
  scale         0.001 0.001 0.001
  offset        431749.999 5440919.999 968.898
  extent        431250 5440420 424.266
                432249.999 5441419.999 1513.531
  crs           ETRS89 / UTM zone 34N (N-E) (EPSG:3046)  (vertical CRS missing!)
  units         horizontal=metre  vertical=unknown
  
  Attributes:
   - X floating 8
   - Y floating 8
   - Z floating 8
   - Intensity unsigned 2
   - ReturnNumber unsigned 1
   - NumberOfReturns unsigned 1
   - ScanDirectionFlag unsigned 1
   - EdgeOfFlightLine unsigned 1
   - Classification unsigned 1
   - ScanAngleRank floating 4
   - UserData unsigned 1
   - PointSourceId unsigned 2
   - GpsTime floating 8
   - ScanChannel unsigned 1
   - ClassFlags unsigned 1
  

  Output from point cloud information algorithm

  • Merge: join multiple point cloud layers into a single file
  • Reproject: reproject the input file to a different coordinate reference system
  • Thin (by sampling radius): reduces the number of points within a certain radius

  

  Thining point cloud (by sampling radius)

  • Thin (by skipping points): reduces the number of points by skipping nearby points
  • Tile: this algorithm generates a set of tiles based on the input point cloud layer and tile size
  • Boundary: generates a (multi) polygon from your point cloud data. The output file might contain holes depending on the density of your point cloud input data.

  

  Extracting high vegetation and building polygons from an input point cloud layer

  • Density: outputs a raster file based on the number of points within each raster cell - useful for quality checking of point cloud datasets

  

  Point density (number of points per 2x2 m) as a raster

  • Filter: it creates a new file based on the filter set as an expression. Note that most of the algorithms support on-the-fly filtering under the Advanced parameters.

  

  Filtering of high vegetation class from an input point cloud layer Behind the scenes

  All the heavy lifting of the point cloud processing is done by PDAL - a state of the art open source library for processing point clouds. PDAL provides a wide range of “readers”, “filters” and “writers” to build complex pipelines to process point clouds.

  We have built a new standalone command line tool pdal_wrench on top of PDAL. It addresses two major issues that non-expert users typically face when working with PDAL:

  • Ease of use: not everyone finds it easy to manually craft JSON files with pipelines, study manuals of the many stages and read details about file formats involved.
  • Parallel execution: PDAL runs pipelines in a single thread, so only one CPU gets to do the work normally and users need to implement their own parallelism if they want to speed up processing.

  The command line tool provides a simple set of commands that take care of everything. For example, to export a raster layer with elevations (DEM) with 1 meter resolution:

  pdal_wrench to_raster --output=raster.tif --resolution=1 --attribute=Z data.las
  

  The pdal_wrench tool does not depend on QGIS, so it can be easily used separately.

  The commands are designed to run in parallel when there are multiple input files or when the input file is in COPC format. Depending on the algorithm, the work gets split spatially into square tiles (1000x1000 map units by default) for parallel processing, or individual files are processed in parallel. With a single ordinary LAS/LAZ file on input, there is currently no parallelism going on.

  For commands that are sensitive to edge artifacts (such as export to raster), we take care of processing extra points outside of the extent of each tile (referred to as collar or buffer) to make sure the results are correct as if no tiling would be happening (see Martin Isenburg’s article for more details: [https:]

  Future work

  The current list of point cloud algorithms already allows users to do plenty of work. But more could be added to the toolbox - algorithms that are already supported by PDAL, but not exposed in QGIS: classification, noise removal, surface reconstruction, clustering, height above ground, colorizing and many more. If you are interested in more point cloud processing algorithms in QGIS, please contact us and we will be happy to add them to future QGIS releases.

• 30 May 2023
• 9:11

  The World's Most Impressive Mountain

  sur Google Maps Mania
  Every schoolchild knows that Mount Everest is the tallest mountain in the world. But is it the most impressive? Mount Everest has an elevation of 8,848 meters (29,029 feet) above sea level. However, if we measure the height of a mountain from its base to its peak, then the tallest mountain in the world is Mauna Kea, which is an inactive volcano on the island of Hawaii. Mauna Kea has an

• 8:00

  gvSIG Team: Geoportales con gvSIG Online para visibilizar la violencia de género e identidad sexual en El Salvador

  sur Planet OSGeo
  

  Compartimos la presentación de un proyecto consistente en poner en marcha la plataforma gvSIG Online para ayudar a visibilizar, mediante visores de mapas, los datos de violencia de género e identidad sexual en El Salvador.

  En el proyecto se utilizó gvSIG Desktop para generar los distintos mapas a partir de simples hojas de cálculo y gvSIG Online para la creación de geoportales y publicación de los mapas temáticos.

  Aquí tenéis el acceso a los visores públicos:

  [https:]]

• 6:00

  Marco Bernasocchi: QField 2.8: Boosting field work through external sensors

  sur Planet OSGeo

  The latest version of QField is out, featuring as its main new feature sensor handling alongside the usual round of user experience and stability improvements. We simply can’t wait to see the sensor uses you will come up with!

  The main highlight: sensors

  QField 2.8 ships with out-of-the-box handling of external sensor streams over TCP, UDP, and serial port. The functionality allows for data captured through instruments – such as geiger counter, decibel sensor, CO detector, etc. – to be visualized and manipulated within QField itself.

  Things get really interesting when sensor data is utilized as default values alongside positioning during the digitizing of features. You are always one tap away from adding a point locked onto your current position with spatially paired sensor readings saved as point attribute(s).

  Not wowed yet? Try pairing sensor readings with QField’s tracking capability! Head over QField’s documentation on this as well as QGIS’ section on sensor management to know more.

  The development of this feature involved the addition of a sensor framework in upstream QGIS which will be available by the end of this coming June as part of the 3.32 release. This is a great example of the synergy between QField and its big brother QGIS, whereas development of new functionality often benefits the broader QGIS community. Big thanks to Sevenson Environmental Services for sponsoring this exciting capability.

  Notable improvements

  A couple of refinements during this development cycle are worth mentioning. If you ever wished for QField to directly open a selected project or reloading the last session on app launch, you’ll be happy to know this is now possible.

  For heavy users of value relations in their feature forms, QField is now a tiny bit more clever when displaying string searches against long lists, placing hits that begin with the matched string first as well as visually highlighting matches within the result list itself.

  Finally, feature lists throughout QField are now sorted. By default, it will sort by the display field or expression defined for each vector layer, unless an advanced sorting has been defined in a given vector layer’s attribute table. It makes browsing through lists feel that much more natural.

• 29 May 2023
• 17:19

  gvSIG Team: Preparación de modelos de datos en gvSIG Desktop

  sur Planet OSGeo
  

  Cada vez es más frecuente encontrarnos con proyectos con conjuntos de datos alfanuméricos estructurados, repartidos en varias tablas, algunas con componente geográfica y otras no,… en definitiva modelos de datos cada vez más elaborados.

  GvSIG Desktop tiene funcionalidades (que seguro la mayoría no conoce) que le permiten manipular las tablas resultado de materializar un modelo de datos: dispone de herramientas para trabajar con las tablas no como “tablas aisladas” sino como un todo, en el que las distintas entidades están relacionadas entre sí.

  En la siguiente presentación os mostramos cómo podemos trabajar en gvSIG Desktop con modelos de datos.

• 7:39

  Stack Overflown

  sur Google Maps Mania
  Nomic Atlas is an online tool for visualizing and exploring large datasets. It enables users to store, update and organize multi-million point datasets of unstructured text, images and embeddings. Atlas organizes the text and data into interactive maps which can then be explored in a web browser, using the map to run semantic searches of the uploaded data. You can view an example of an

• 2:00

  PostGIS Development: PostGIS 3.3.3, 3.2.5, 3.1.9, 3.0.9 Patch Releases

  sur Planet OSGeo

  The PostGIS development team is pleased to provide bug fixes and performance enhancements 3.3.3, 3.2.5, 3.1.9 and 3.0.9 for the 3.3, 3.2, 3.1, and 3.0 stable branches.

• 27 May 2023
• 10:46

  Bat Virus Jump Zones

  sur Google Maps Mania
  Over a fifth of the human population lives in areas where there is a large risk that a bat bourne disease will spread to humans. Bats carry tens of thousands of viruses. For most of human history we have been in little danger from these viruses because of the minimal contact between bats and humans. Now, because of human incursions into bat habitats the dangers of a virus jumping from bats to

• 26 May 2023
• 11:25

  GeoTools Team: GeoTools 29.1 Released

  sur Planet OSGeo
  The GeoTools team are pleased to announce the release of the latest stable version of GeoTools 29.1     geotools-29.1-bin.zip     geotools-29.1-doc.zip     geotools-29.1-userguide.zip     geotools-29.1-project.zip Improvements and fixes in this release BugGEOT-7325 WMTS multi tile request is not compatible with RESTful serversGEOT-7333 The result of linearization after creating circulararc is

• 9:26

  MapLibre Adds WebGL2 Support

  sur Google Maps Mania
  MapLibre GL JS v3 has been released. Version 3 of the popular mapping library includes significant improvements to Terrain 3D, support for WebGL2, new styling options and improved performance. MapLibre GL JS, a JavaScript mapping library that uses WebGL to render interactive maps from vector tiles and styles. MapLibre was founded in 2015 in reaction to the growing trend of proprietary mapping

• 2:00

  Camptocamp: Implementing an Effective CICD Pipeline for Faster Software Delivery and Enhanced Security Testing

  sur Planet OSGeo

  Enclosure: [download]

  Delivering high-quality software quickly is essential in today's fast-paced digital landscape, and a well-designed continuous integration and continuous delivery (CICD) pipeline can help development teams achieve this goal by enabling faster feedback loops and reducing the time between code changes and deployment.
• 25 May 2023
• 11:05

  gvSIG Team: FONDEA: aplicación para protección de praderas de posidonia de fondos marinos desarrollada con gvSIG Mapps

  sur Planet OSGeo
  

  FONDEA es una aplicación desarrollada con tecnología gvSIG Mapps que tiene como objetivo ayudar a proteger las praderas fanerógamas, la conocida posidonia. Mediante su uso permite ubicar tanto las embarcaciones como las praderas, con el fin de evitar fondear en zonas protegidas.

  Podéis conocer todos los detalles técnicos en el siguiente vídeo:

• 9:15

  Discover Your Earthquake Risk

  sur Google Maps Mania
  CNN has created an interactive map which reveals your risks from earthquake activity. Enter your address into the What's your earthquake risk interactive map and you can discover your earthquake hazard level based on data from the US Geological Survey.CNN's map colors the United States based on seven different levels of earthquake risk. You can also click on a location on the map to reveal the

• 24 May 2023
• 18:00

  Paul Ramsey: Keynote @ CUGOS Spring Fling

  sur Planet OSGeo

  Last month I was invited to give a keynote talk at the CUGOS Spring Fling, a delightful gathering of “Cascadia Users of Open Source GIS” in Seattle. I have been speaking about open source economics at FOSS4G conferences more-or-less every two years, since 2009, and took this opportunity to somewhat revisit the topics of my 2019 FOSS4GNA keynote.

  If you liked the video and want to use the materials, the slides are available here under CC BY.

• 15:49

  OGC SensorThings API for European Green Deal Data Spaces

  sur Open Geospatial Consortium (OGC)

  A critical component of Data Spaces – those supporting the European Green Deal strategy or beyond – will be their management of dynamic data series coming from many different sources, such as various sensors. To enable interoperable communication between such data series, as well as ease their interpretation and (re-)use, the Open Geospatial Consortium (OGC) long ago developed the SensorThings API Standard. In this post, the Standard is introduced together with the planned developments and initial results from two Horizon Europe projects on Green Deal Data Spaces in which OGC is involved: ‘All Data for Green Deal’ (AD4GD) and ‘Urban Data Space for Green Deal’ (USAGE).

  The European Green Deal and digital data strategies

  The European Green Deal aims to transition Europe to a sustainable and resource-efficient economy and governance while improving the well-being of citizens. Several objectives shall contribute to the main goal, including: transforming the economy and societies; making transport sustainable for all; innovating industry; cleaning energy systems; renovating buildings for greener lifestyles; working with nature to preserve the planet; and boosting global climate actions. European Green Deal objectives are, in turn, in line with the United Nations Sustainable Development Goals.

  Data, especially dynamic data from sensors, plays an essential role in monitoring, analysing, and understanding the status and evolution of the aforementioned sectors, the influence of proposed policies and decisions, and when simulating and measuring the effectiveness of newly applied measures, models, or changed conditions.

  Further, using open protocols and data management practices aligned with the FAIR data principles of Findability, Accessibility, Interoperability, and Reusability, increases efficiency and better supports democracy through data transparency and accessibility.

  Digitalisation is recognised as a powerful support to the European Green Deal and Sustainable Development Goals – on the condition that a strategy is followed that ensures efficient and optimised use and management of digital data and associated tools. The European Strategy for Data and the European Data Spaces policies are intended to rule, define, and support such digitalisation towards fair, aware, and efficient data sharing and use.

  OGC SensorThings API: an Open model for sensor data

  The OGC SensorThings API was developed by the OGC SensorThings Standard Working Group as an open Standard that enables the web-based management, storage, sharing, and analysis of Internet of Things (IoT)-based sensor observation data.

  The OGC SensorThings API consists of a data model and an API split across two documents: (1) the Sensing part and (2) the Tasking part (which is currently in the planning phase). The Sensing part allows IoT devices and applications to create, read, update, and delete IoT data and metadata in a SensorThings service.

  The SensorThings entities data model is based on the OGC/ISO Observation and Measurement (O&M) model [OGC 10-004r3 and ISO 19156:2011]. The model can be understood as follows: an “observation” is modelled as a datastream connected to a “sensor” and a “thing” that produces a “result” (aka “ObservedProperty”) whose value is an estimate of a property of the “observation target” (aka “FeatureOfInterest”).

  For example: when measuring the temperature in a room, the “Observation” is each measurement or data value at a certain moment in time; the “sensor” is the thermometer; the “thing” is the device that reads and transmits the measurement from the thermometer; and the “result” (ObservedProperty) is the temperature measured by the sensor. The ObservedProperty is associated with the “observation target” (FeatureOfInterest), in this case, the part of the room that the sensor resides in.

  An Observation instance is classified by its event time, FeatureOfInterest, ObservedProperty, and the procedure used (often a Sensor). Moreover, “Things” are also modelled in the SensorThings API, and its definition follows the ITU-T definition: “an object of the physical world (physical things) or the information world (virtual things) that is capable of being identified and integrated into communication networks” [ITU-T Y.2060]. The geographical locations of Things are useful in almost every application (in particular in remote sensing, where the object measured is far apart from the actual device) and, as a result, are included as well.

  SensorThings API for Green Deal Data Spaces: the USAGE and AD4GD projects

  Recent examples of adoption of the SensorThings API standard include two Horizon Europe projects – in which OGC participates as a consortium partner – that intend to provide solutions for the Green Deal Data Space: ‘Urban Data Space for Green Deal’ (USAGE), and All Data for Green Deal (AD4GD).

  By using standards for data/service interoperability and integration, USAGE will provide solutions that make city-level environmental & climate data Findable, Accessible, Interoperable, and Reusable (FAIR). This means innovating governance mechanisms, consolidated arrangements, AI-based tools, and data analytics to better share, access, and use the city-level data generated from Earth Observation, Internet of Things, authoritative- and crowd-sources.

  USAGE use cases will range from air pollution mobility to mitigation strategies for climate change (such as minimising the impact of urban heat islands and increased floods) as well as smart traffic management. USAGE pilots and use-cases include the cities of Ferrara (Italy), Zaragoza (Spain), Graz (Austria), and Leuven (Belgium). In Ferrara, citizen science initiatives with high schools and volunteers are already scheduled to support USAGE use cases and biodiversity.

  AD4GD aims to co-create a Green Deal Data Space with stakeholders and end-users. One of the main objectives of the project is the integration of Citizen Science data together with in-situ observations, results from artificial intelligence models, and remote sensing data. AD4GD will leverage standards and semantic technologies to reach this objective.

  AD4GD pilots and use cases include water quality in Berlin’s lakes (Germany), biodiversity in the Metropolitan Area of Barcelona (Spain), and air quality with low-cost sensors in Northern Italy.

  The implementation of SensorThings API is a critical part of both projects. Sensors provide essential data for several treated use cases, including for air quality, water quality, traffic status, animal species tracking, weather & environmental parameters, and more.

  By using an open and shared protocol to communicate data, such as the SensorThings API Standard, the data required for the projects can come from different types of sensors from different vendors, and the sensors can be managed by the government, private industry, or single citizens. Additionally, SensorThings API’s capacity to link observations to definitions of variables and units of measurement facilitates the automatic aggregation and integration of data while increasing its semantic interoperability.

  The two projects plan to further develop the SensorThings API Standard by using it in the provided solutions and recommended architecture while experimenting with its integration with other sensors and data within the developed software. In USAGE specifically, the SensorThings API plugin for QGIS will be refactored to embed access to SensorThings API endpoints in the core part of QGIS and extend it to support data analytics.

  Also further implemented and tested in AD4GD and USAGE is SensorThings API Plus. To more effectively manage data produced by multiple actors with different licenses (such as in citizen science data), SensorThings API Plus extends the OGC SensorThings API Part 1: Sensing Version 1.1 (STA) Standard data model and improves the security aspects of the standard. Its development was started in the COS4CLOUD project and was further developed in citiobs.

  Promoting the SensorThings API with stakeholders

  Both AG4GD and USAGE additionally recognise that a fundamental challenge facing the uptake of effective solutions is firstly alerting the stakeholders and end users of its existence, and then training them in its use. Therefore, within the USAGE project, some workshops were organised by OGC and project partner DedaNext.

  Figure 1 – Responses to the question “What obstacles most hinder the SensorThings API uptake in your organisation?”

  The first workshop was organised on February 1, 2023, in Ferrara (and online). The workshop opened with an introduction to the SensorThings API Standard along with several examples of Open Source implementations. Marco Minghini, from the Joint Research Centre group working on the INSPIRE Directive framework and implementation, presented the INSPIRE Good Practice recommendation of OGC SensorThings API. The API4INSPIRE project was also presented, which assessed the implications of using APIs to exchange data, including the SensorThings API. A recording of this initial part of the workshop is available on the OGC YouTube Channel.

  Next up was a round table where stakeholders from national and regional Italian bodies discussed current solutions for sharing dynamic data as well as challenges facing the adoption of SensorThings API for improving data management quality and FAIRness. The audience was prompted to answer two questions through interactive questionnaire tools: 1) What obstacles most hinder the SensorThings API uptake in your organisation? And 2) What could better support the adoption of the Standard?

  To facilitate the participation of a wider audience, the questions and related answers were allowed in both Italian and English. The lack of knowledge about the standard was recognised as a primary reason blocking its adoption, as seen in Figure 1. For this reason, the recording of the first informative part of the workshop was published online and advertised as part of the Location Innovation Academy and beyond. Additionally, a second SensorThings API webinar was held on April 20, 2023, organised by the Italian Agency for Digitalisation (AgID), and held in Italian.

  Figure 2 – Responses to the question “What can mostly support the adoption of the Standard?”

  The second question pointed out that the biggest driver for uptake of the SensorThings API Standard would be in the form of clear policy directives. The following ranked factors – digital skills and human resources, respectively – confirm once again the need for training and new professional skills. This problem is the impetus behind the launch of the Location Innovation Academy, developed in the European GeoE3 project and hosted by OGC.

  The interest around the SensorThings API Standard continues to grow, with more developments, applications, and implementations expected in the future.

  OGC Members interested in staying up to date on the progress of the SensorThings API Standard, or contributing to its development, are encouraged to join the Connected Systems / SensorThings Standads Working Group via the OGC Portal. Non-OGC members who would like to know more about participating in the SWG are encouraged to contact the OGC Standards Program.

  

  The USAGE project has received funding from the European Union’s Horizon Europe Framework Programme for Research and Innovation under the Grant Agreement no 101059950.

  The AD4GD project has received funding from the European Union’s Horizon Europe Framework Programme for Research and Innovation under the Grant Agreement no 101061001.

  The post OGC SensorThings API for European Green Deal Data Spaces appeared first on Open Geospatial Consortium.

• 9:19

  Germany - the Dirty Man of Europe

  sur Google Maps Mania
  A new interactive map shows how CO2 emissions in Germany are once again on the increase. In the first two decades of this century Germany has produced the most carbon dioxide emissions of any country in the European Union. The main reason for this is that Germany is heavily reliant on coal for electricity generation. Germany aims to become carbon-neutral by 2045 however the war in Ukraine has

• 9:13

  gvSIG Team: Culminó con gran éxito la edición 2022 del Curso-Concurso Proyectos con Estudiantes y gvSIG Batoví

  sur Planet OSGeo

  Repescamos un post sobre la edición de 2022 del Curso-Concurso de gvSIG Batoví, sobre la que no os habiamos contado nada. Como siempre decimos, un ejemplo a replicar en cualquier país del mundo… y en esas se está, este 2023 es muy probable que otros países participen.
  Un ejemplo de como llevar la geomática a las aulas. Alumnos utilizándola para analizar su realidad más cercana para intentar mejorarla.

  gvSIG Batovi

  Desde 2017 se realiza el Curso-Concurso Proyectos de Geografía con Estudiantes y gvSIG Batoví, sólo interrumpido el año 2020 por obvias razones. La edición 2022 tuvo su cierre el pasado 7 de diciembre en el IPES (Instituto de Perfeccionamiento y Estudios Superiores), en la ciudad de Montevideo.

  salón de actos del IPES

  Esta es una iniciativa conjunta de la Dirección Nacional de Topografía (MTOP), la Inspección Nacional de Geografía y Geología de la Dirección General de Educación Secundaria (DGES/ANEP) y Ceibal, a la que este año se sumó el Centro de Investigación en Computación del Instituto Politécnico Nacional de México.

  

  Nuevamente la red GeoLIBERO (Red CYTED compuesta por una veintena de grupos de investigación y un centenar de destacados especialistas en geomática libre de Iberoamérica) participó activamente a través de las tutorías que año a año vienen teniendo los proyectos participantes. Estas tutorías brindan apoyo y asesoramiento a los diferentes…

  View original post 985 more words

• 8:05

  gvSIG Team: GuiaT, uso de gvSIG Online para agilizar los trámites administrativos y burocráticos del sector urbanístico

  sur Planet OSGeo
  

  Hoy os traemos una presentación de GuiaT, un proyecto de la Generalitat Valenciana realizado con gvSIG Online que surge con la idea de agilizar los trámites de urbanismo, mejorar los plazos y dotar a los procedimientos de mayor transparencia.

  GuiaT, Impulsos hacia la Agilización Urbanística:

• 2:00

  Camptocamp: Camptocamp participates in the geOcom’s 10th edition

  sur Planet OSGeo

  Enclosure: [download]

  geOcom is the annual meeting of users, administrators and developers of the geOrchestra data infrastructure.
• 23 May 2023
• 18:08

  GeoSolutions: Leveraging Open-Source Geospatial Services for Real-Time Emergency Management Applications: Overwatch Imaging and HURREVAC use cases

  sur Planet OSGeo

  You must be logged into the site to view this content.

• 9:50

  gvSIG Team: SIGCAR: gestión de seguridad vial con gvSIG Desktop

  sur Planet OSGeo
  

  En la Generalitat Valenciana se han desarrollado un conjunto de herramientas muy potentes sobre gvSIG Desktop para la gestión de Seguridad Vial. Estas herramientas, además, pueden aplicarse a otros usos y forman parte del conjunto de funcionalidades disponibles en las últimas versiones de desarrollo de gvSIG Desktop (sí, tenemos pendiente sacar una versión final que contenga las innumerables mejoras que se han aportado desde la última distribución… la idea es tenerla para el segundo semestre de este año).

  Y ahora si queréis conocer cómo se gestionan los datos de accidentalidad, aforos, catálogos de carreteras… os dejamos con la presentación de SIGCAR:

• 9:04

  A Bird's Eye View of America

  sur Google Maps Mania
  The Library of Congress owns a huge collection of panoramic bird's eye maps of American cities, most of which were published in the late nineteenth and early twentieth centuries. You can now browse and explore these vintage panoramic maps of American cities on the library's View from Above interactive map. The map allows you to view over 1,500 panoramic maps of towns and cities across the

• 2:00

  GeoServer Team: GeoServer 2.23.1 Release

  sur Planet OSGeo

  GeoServer 2.23.1 release is now available with downloads (bin, war, windows), along with docs and extensions.

  This is a stable release of GeoServer suitable for production systems, made in conjunction with GeoTools 29.1 and GeoWebCache 1.23.0.

  We are grateful to Ian Turton (Astun Technology Ltd) for making this release.

  Release notes

  Improvement:

  • GEOS-10858 jdbc-config turns off isolated workspace support

  • GEOS-10898 Preserve key order in STAC responses coming from JSONB columns

  • GEOS-10923 Use default writing params on GeoTIFFPPIO

  • GEOS-10940 Update MapML viewer to release 0.11.0

  Bug:

  • GEOS-8162 CSV Data store does not support relative store paths

  • GEOS-10837 geopackage output fails when java.io.tmpdir on network share

  • GEOS-10912 jms-cluster fails to clone grid coverage layer on other nodes

  • GEOS-10920 Excel output format packaging misses dependencies, cannot produce .xls

  • GEOS-10921 Double escaping of HTML with enabled features-templating

  • GEOS-10922 Features templating exception on text/plain format

  • GEOS-10932 csw-iso: should only add 'xsi:nil = false' attribute

  • GEOS-10934 CSW does not show title/abstract on welcome page

  • GEOS-10946 WMS GetLegendGraphic throws FootprintsTransformation cannot be cast to ProcessFunctionException

  • GEOS-10950 Performance regression in DescribeFeatureType across all feature types

  • GEOS-10955 STAC templates are initialised in the wrong location

  • GEOS-10957 Support ResourceAccessManager implementations returning custom subclasess of AccessLimits

  • GEOS-10969 Empty CQL_FILTER parameter should be ignored

  • GEOS-10975 JMS clustering reports error about ReferencedEnvelope type not being whitelisted in XStream

  • GEOS-10985 B/R of GeoServer catalog is broken with GeoServer 2.23.0

  Task:

  • GEOS-10859 OGC API: swagger-api 4.15.5 upgrade

  For the complete list see 2.23.1 release notes.

  About GeoServer 2.23 Series

  Additional information on GeoServer 2.23 series:

  • Drop Java 8
  • GUI CSS Cleanup
  • Add the possibility to use fixed values in Capabilities for Dimension metadata

  Release notes: ( 2.23.1 | 2.23.0 | 2.23-RC1 )

• 22 May 2023
• 13:07

  gvSIG Team: Plataforma de cálculo de rutas multimodal para movilidad sostenible

  sur Planet OSGeo
  

  Llevamos tiempo con el blog parado, fruto de la avalancha de proyectos, actividades, etc. en la que andamos metidos. Pero ya toca reactivar la difusión del huracán de cosas que se están moviendo en el ecosistema gvSIG, así que vamos a empezar por retomar el blog, contándoos en primer lugar diversos proyectos que utilizan la Suite gvSIG… y empezamos con GVEnRuta, donde hemos utilizado la solución que denominamos gvSIG Mobility y que incluye productos como gvSIG Online, gvSIG Mapps y OpenTripPlanner.

  Se trata de una plataforma de cálculo de rutas multimodal para movilidad sostenible que fue presentada en las pasadas Jornadas Internacionales de gvSIG.

  Por cierto, y antes de dejaros con la presentación, la línea de “proyectos de movilidad” es una de las que más está creciendo en el ecosistema gvSIG y más adelante os contaremos alguno de los proyectos en los que se está trabajando. Tanto es así que igual este año se celebra en Valencia cierto evento que… bueno, ya os contaremos cuando sea el momento.

  Vamos con la presentación de GVEnRuta:

  Y si queréis probarlo (además de las Stores de Google e iOS), podéis en:

  [https:]]

• 9:22

  Explore the World with Shadows

  sur Google Maps Mania
  Chee Aun's Deck.GL with Google Maps Photorealistic 3D Tiles Demo is a demonstration of Google's new 3D map tiles with a few added special effects. Using this map you can explore the world in 3D with building shadows, post-processing effects and an interesting ink effect. This month Google released the new Photorealistic 3D Tiles option at its annual I/O conference. It allows developers to

• 21 May 2023
• 19:23

  Free and Open Source GIS Ramblings: Analyzing video-based bicycle trajectories

  sur Planet OSGeo

  Did you know that MovingPandas also supports local image coordinates? Indeed, it does.

  In today’s post, we will explore how we can use this feature to analyze bicycle tracks extracted from video footage published by Michael Szell @mszll:

  • Dataset: [https:]]
  • Data description: [https:]]

  The bicycle trajectory coordinates are stored in two separate lists: xs_640x360 and ys640x360:

  

  This format is kind of similar to the Kaggle Taxi dataset, we worked with in the previous post. However, to use the solution we implemented there, we need to combine the x and y coordinates into nice (x,y) tuples:

  df['coordinates'] = df.apply(
      lambda row: list(zip(row['xs_640x360'], row['ys_640x360'])), axis=1)
  df.drop(columns=['xs_640x360', 'ys_640x360'], inplace=True)
  

  Afterwards, we can create the points and compute the proper timestamps from the frame numbers:

  def compute_datetime(row):
      # some educated guessing going on here: the paper states that the video covers 2021-06-09 07:00-08:00
      d = datetime(2021,6,9,7,0,0) + (row['frame_in'] + row['running_number']) * timedelta(seconds=2)
      return d
  def create_point(xy):
      try: 
          return Point(xy)
      except TypeError:  # when there are nan values in the input data
          return None
  new_df = df.head().explode('coordinates')
  new_df['geometry'] = new_df['coordinates'].apply(create_point)
  new_df['running_number'] = new_df.groupby('id').cumcount()
  new_df['datetime'] = new_df.apply(compute_datetime, axis=1)
  new_df.drop(columns=['coordinates', 'frame_in', 'running_number'], inplace=True)
  new_df
  

  Once the points and timestamps are ready, we can create the MovingPandas TrajectoryCollection. Note how we explicitly state that there is no CRS for this dataset (crs=None):

  trajs = mpd.TrajectoryCollection(
      gpd.GeoDataFrame(new_df), 
      traj_id_col='id',  t='datetime', crs=None)
  

  Plotting trajectories with image coordinates

  Similarly, to plot these trajectories, we should tell hvplot that it should not fetch any background map tiles (’tiles’:None) and that the coordinates are not geographic (‘geo’:False):

  

  If you want to explore the full source code, you can find my Github fork with the Jupyter notebook at: [https:]]

  The repository also contains a camera image of the intersection, which we can use as a background for our trajectory plots:

  bg_img = hv.RGB.load_image('img/intersection2.png', bounds=(0,0,640,360)) 
  

  

  One important caveat is that speed will be calculated in pixels per second. So when we plot the bicycle speed, the segments closer to the camera will appear faster than the segments in the background:

  

  To fix this issue, we would have to correct for the distortions of the camera lens and perspective. I’m sure that there is specialized software for this task but, for the purpose of this post, I’m going to grab the opportunity to finally test out the VectorBender plugin.

  Georeferencing the trajectories using QGIS VectorBender plugin

  Let’s load the five test trajectories and the camera image to QGIS. To make sure that they align properly, both are set to the same CRS and I’ve created the following basic world file for the camera image:

  1
  0
  0
  -1
  0
  360
  

  Then we can use the VectorBender tools to georeference the trajectories by linking locations from the camera image to locations on aerial images. You can see the whole process in action here:

  After around 15 minutes linking control points, VectorBender comes up with the following georeferenced trajectory result:

  

  Not bad for a quick-and-dirty hack. Some points on the borders of the image could not be georeferenced since I wasn’t always able to identify suitable control points at the camera image borders. So it won’t be perfect but should improve speed estimates.

  This post is part of a series. Read more about movement data in GIS.

• 8:26

  Explore the World in 3D

  sur Google Maps Mania
  San Francisco as seen using Google's new Photorealstic 3D Tiles At Google I/O this year the Google Maps team unveiled the release of Photorealistic 3D Tiles. Google Maps' Photorealistic 3D Tiles are a new way to view the world in 3D. In essence the new tiles allow map developers to use Google Earth's 3D buildings and terrain in their interactive maps. The new 3D tiles are ideal for creating
• 19 May 2023
• 9:24

  How big are London, New York & Tokyo?

  sur Google Maps Mania
  Alasdair Rae has used the leaflet-truesize plug-in for the Leaflet mapping platform to create a map which allows you to compare the size of Greater London and the Tokyo metro area with any other location in the world. Alasdair's How big is Greater London map contains two draggable polygons. One polygon represents the size of Greater London (placed over London) the other is the size of the Tokyo

• 18 May 2023
• 12:52

  OGC Forms new GeoDCAT Standards Working Group

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC) is excited to announce the formation of the OGC GeoDCAT Standards Working Group (GeoDCAT SWG)

  The GeoDCAT SWG will revise, publish, and maintain GeoDCAT – a spatio-temporal profile of the W3C DCAT Recommendation – and provide guidance about its use and further specialization. The larger geospatial community will benefit from the standardization of descriptions of geospatial data and access services in DCAT-based data catalogs.

  DCAT, a vocabulary to describe datasets and services, is the primary means to catalog datasets on the web. Some basic temporal and geographic properties have been adopted within DCAT v2 and planned v3, however these do not address the full range of requirements as identified in the 2019 OGC GeoDCAT-AP Discussion paper. 

  GeoDCAT will provide a standardized vocabulary and encoding for spatial dataset descriptions and service descriptions (metadata records), based on general Web standards as described in the OGC/W3C Spatial Data on the Web Best Practices. GeoDCAT could in future be used as an encoding in catalog API standards, such as OGC API – Records and STAC.

  GeoDCAT enables spatial data to abide by FAIR (Findable, Accessible, Interoperable, and Reusable) Principles in a web-native environment, just as so many other datasets do. GeoDCAT’s European profile (GeoDCAT-AP) is used to make spatial datasets, dataset series, and services discoverable on general data portals, thereby making geospatial information better findable across borders and sectors. The EU references GeoDCAT-AP as a “Good Practice”.

  Portals that describe their data catalogs using either GeoDCAT or GeoDCAT-AP will be interoperable with each other as well as with general data catalogs that use DCAT.

  OGC Members interested in staying up to date on the progress of this standard, or contributing to its development, are encouraged to join the GeoDCAT SWG via the OGC Portal. Non-OGC members who would like to know more about participating in this SWG are encouraged to contact the OGC Standards Program.

  The post OGC Forms new GeoDCAT Standards Working Group appeared first on Open Geospatial Consortium.

• 12:50

  OGC Forms new GeoDataCube Standards Working Group

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC) is excited to announce the formation of the OGC GeoDataCube SWG. 

  The GeoDataCube SWG will improve interoperability between existing datacube solutions, simplify the interaction with different datacubes, and facilitate the integration of data from multiple datacube sources. By following a user-centric approach, the SWG will develop solutions that meet the needs of scientists, application developers, and API integrators.

  The goal of the OGC GeoDataCube SWG is to create a new API specifically to serve the core functionalities of GeoDataCubes, such as access and processing, and to define exchange format recommendations, profiles, and a metadata model. The SWG also aims to analyze usability of existing Standards and identify use cases.

  Similar to other OGC APIs, the GeoDataCube SWG will create this new standard from existing building blocks, such as existing geospatial Standards, outputs from previous OGC Collaborative Solutions & Innovation Initiatives, and other developer resources in a very use-case driven approach, i.e., with a small core and possible extensions. This will allow for interoperability across future OGC Standards.

  With regards to existing and emerging OGC standards, the working group may look specifically at:

  • OGC API – Environmental Data Retrieval: A family of lightweight interfaces to access Environmental Data resources.
  • OGC API – Coverages: Defining a Web API for accessing coverages that are modeled according to the Coverage Implementation Schema.
  • OGC Analysis Ready Data SWG products: proposed Standards to describe specific product types that are often implemented as GeoDataCubes.
  • OGC API – Processes: Supporting the wrapping of computational tasks into executable processes that can be offered by a server through a Web API.
  • Zarr: An OGC Community Standard for the storage of multi-dimensional arrays of data.
  • GeoTIFF and Cloud Optimized GeoTIFF: A format used to share geographic image data.
  • Hierarchical Data Format (HDF5): A set of formats designed to store and organize large amounts of data.

  The GeoDataCube SWG will follow an agile methodology with the goal to create a first core Standard within the first year. Subsequent iterations may add additional functionality. The GeoDataCube SWG will start with a use case collection and analysis phase that further informs the selection of additional starting points or other work to be considered. The targeted use cases shall reflect real world scenarios, though should allow for a rapid implementation of the GeoDataCube standards without adding unnecessary complexity.

  OGC Members interested in staying up to date on the progress of this standard, or contributing to its development, are encouraged to join the GeoDataCube SWG via the OGC Portal. Non-OGC members who would like to know more about participating in this SWG are encouraged to contact the OGC Standards Program.

  The post OGC Forms new GeoDataCube Standards Working Group appeared first on Open Geospatial Consortium.

• 12:44

  OGC Forms new Agriculture Information Model Standards Working Group

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC) is excited to announce the formation of the OGC Agriculture Information Model Standards Working Group (AIM SWG).

  The purpose of the AIM SWG is to develop, publish, and maintain an Agriculture Information Model (AIM) to support interoperability of information in the Agriculture Domain, with emphasis on the re-use of generic OGC standards as appropriate.

  AIM will provide a common language for agriculture applications to harmonize and improve data and metadata exchange by defining the required data elements, including concepts, properties, and relationships relevant to agriculture applications, as well as their associated semantics/meaning for information exchange. 

  AIM will be a multi-tier and modular domain model that aligns, profiles, and/or extends well known agriculture-related and generic ontologies, including those published by OGC. Publishing such a domain model as a modular ontology is a new and innovative approach. As such, the SWG will identify best practices for this approach, as well as develop a series of complementary models.

  AIM will be published as both human and implementation-ready machine-actionable resources. Machine-actionable resources include the canonical ontology representation of the AIM in the Web Ontology Language (OWL) as well as other related artifacts to support implementation.

  The SWG will develop implementations of the AIM model compatible with OGC APIs, including:

  • JSON schemas supported by OGC APIs;
  • JSON-LD contexts allowing identification and validation of AIM-compliant data; and
  • SHACL shapes that enable the validation of data against AIM semantics.

  In addition, other forms may be derived or supplied to support the reuse of the AIM model according to requirements identified by the SWG. For example:

  • UML representation of the AIM conceptual model;
  • UML representation of one or more logical models for AIM implementation; and
  • Formal profiles for implementation of AIM using GeoJSON, FG-JSON, CoverageJSON, and other relevant generic schemas.

  In line with OGC policies and FAIR principles, the AIM will be published using persistent and resolvable URI identifiers, consistent with OGC Naming Authority processes for publishing semantic resources.

  OGC Members interested in staying up to date on the progress of the Agriculture Information Model, or contributing to its development, are encouraged to join the AIM SWG via the OGC Portal. Non-OGC members who would like to know more about participating in this SWG are encouraged to contact the OGC Standards Program.

  The post OGC Forms new Agriculture Information Model Standards Working Group appeared first on Open Geospatial Consortium.

• 12:41

  OGC Forms new Analysis Ready Data Standards Working Group

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC) is excited to announce the formation of the OGC Analysis Ready Data Standards Working Group (ARD SWG). 

  The ARD SWG, in partnership with ISO/TC 211, will develop a multi-part Standard for geospatial Analysis Ready Data that builds upon work undertaken in the Committee on Earth Observation Satellites (CEOS) Land Surface Imaging Virtual Constellation (LSI-VC) and Analysis Ready Data (ARD) Oversight Group, OGC Disaster Pilot 2021, and OGC Testbed-16.

  The concept of ARD was initially developed by CEOS, which defines ARD as “satellite data that have been processed to a minimum set of requirements and organized into a form that allows immediate analysis with a minimum of additional user effort and interoperability both through time and with other datasets.” Adopting the CEOS-ARD definition as a starting point, the OGC ARD SWG will extend the scope of ARD from satellite data to all geospatial data. 

  A major strength of geospatial and location technologies is their ability to integrate and analyze data from diverse providers concerning many different phenomena so as to better understand or predict what is happening in a given area. However, this diversity of data means that preparing the acquired data for integration and analysis remains a time-consuming task. Furthermore, many geospatial data users lack the expertise, infrastructure, and internet bandwidth to efficiently and effectively access, preprocess, and utilize the growing volume of geospatial data available for local, regional, and national decision-making. 

  The charter supporters recognize that formal Standardization of the concepts developed through CEOS-ARD is necessary to achieve broad uptake, particularly by the commercial sector. Defining ARD through international standards bodies, such as OGC and ISO, will also help promote the concept and help avoid the divergence that can be caused by various groups working towards different interpretations of the concept.

  As such, the OGC ARD SWG, which includes a number of CEOS representatives, will work jointly with the planned ISO/TC 211 ARD Standard project team to define a multi-part Standard that specifies a set of minimum requirements that a geospatial data product shall meet in order for the product to qualify as an ARD product.

  The CEOS-ARD concept and Specifications were tested, evaluated, and assessed by OGC during Testbed-16, results of which were published in the ARD Engineering Report in 2020. Building on this, space agencies participating in the OGC Disaster Pilot 2021, introduced a number of CEOS-ARD products into the disaster decision-making process, greatly simplifying the use of satellite data in disaster-related decision making. 

  The Disaster Pilot 2021 concluded with a need to broaden the ARD concepts to cover other types of geospatial data and to create international ARD standards through the formal standard-setting processes of ISO and OGC. Therefore, the OGC Disaster Pilot 2022 set an action item to start an OGC ARD Standards Working Group to work jointly with the project team in ISO TC 211 to develop joint ISO-OGC standards on geospatial ARD.

  OGC Members interested in staying up to date on the development of the Analysis Ready Data Standard, or contributing to its development, are encouraged to join the Analysis Ready Data SWG via the OGC Portal. Non-OGC members who would like to know more about participating in this SWG are encouraged to contact the OGC Standards Program.

  The post OGC Forms new Analysis Ready Data Standards Working Group appeared first on Open Geospatial Consortium.

• 9:49

  US Military Bases Around the World

  sur Google Maps Mania
  The United States has over 800 military bases in more than 80 countries around the world. This makes the U.S. the largest operator of military bases in the world. These bases are used for a variety of purposes, including training, logistics, and intelligence gathering. They also play a role in projecting American power and influence around the globe. World BEYOND War has created an interactive

• 17 May 2023
• 15:40

  Jackie Ng: Announcing: FDO Toolbox 1.5.3

  sur Planet OSGeo

  Here's the first stop of the tour, a new release of FDO Toolbox.

  I knew that a new release of FDO Toolbox would be coming when I was using the previous 1.5.2 release and it spectacularly failed in my dogfooding of trying to load some GDA2020 SHP files to SQL Server. The actual problem was actually pretty minor, but this inevitably started a chain of dealing with many other annoyances and reported issues, culminating in this release you see here.

  Here's a summary of notable changes in this release.

  The configuration support check has been fixed so that the configuration doc field is enabled based on actual provider capability check instead of the previously (dumb) approach of checking the provider name. This means the configuration document field is no longer disabled when connecting to PostgreSQL/PostGIS databases and one can finally supply a XML configuration document to apply schema overrides!

  
  

  The data store editor in standalone mode now supports deleting schemas, to support the common FDO schema override use case of trimming out extraneous schemas and feature classes.

  
  

  
  

  The annoyance of loading a saved bulk copy definition file and a whole bunch of connections with "Connection1/Connection2/Connection3" names being created is now fixed. We will now try to use the original name on the definition file if there is no open connection using the same name.

  
  

  Also did you know that FDO Toolbox has a neat little feature to help you easily visualize geometry WKT?

  
  

  You probably didn't know because this feature was hidden in the depths of the FDO Expression Editor when editing FDO expressions or filters and could not be accessed on its own.

  That's why in this release, the Geometry Visualizer is now also accessible from the Tools menu.

  

  Finally, to return back to the original issue motivating the production of this new release, the ExtendedCoordSys.txt support file for the SQL Server FDO provider has been updated to match the copy from current FDO trunk and has been updated with a CS alias mapping for GDA2020, allowing one to create spatial contexts on a SQL Server data store with this particular coordinate system (and many others!)

  Now onto the next tour stop!

  Download

• 15:00

  OGC to host European Innovation Days and more at Data Week Leipzig ‘23

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC), working with Digital Unit of the City of Leipzig, is excited to host several sessions at Data Week Leipzig ‘23, which runs from June 26-30, 2023, in Leipzig, Germany.

  Data Week Leipzig is an innovative networking and exchange event that highlights scientific, economic, and social perspectives of data and its use, and where industry, citizens, science, and public authorities can enter into dialogue. Special topics of Data Week Leipzig 2023 are the European Green Deal, NetZero Cities, and sustainable, resilient development. Digital strategies will be presented and discussed from the European to the local Leipzig City level.

  From Monday to Wednesday, OGC will present across topics such as Data Spaces, The European Green Deal, Urban Platforms, Semantics, FAIR data and services, and some of the numerous EC-funded projects that OGC is involved with.

  In addition to discussions surrounding EU Data Spaces, you are invited to extend your abstract and presentation and submit a scientific paper for a special issue of the open access journal Remote Sensing with the theme “Earth Observation Data in Environmental Data Spaces.”

  Monday at Data Week Leipzig ‘23 has the theme of “European Innovation Day” and will paint the Data Spaces vision that Europe is moving towards with the EU Digital Strategy. Across keynotes, demos, and podium discussions, political frames will be discussed in line with technical possibilities and challenges. Findings of the GeoE3 project will be one of the central topics of this day. Several sessions on Data Spaces and Digital Twins will be held across Monday and Tuesday, while Wednesday will focus on Semantics and the “OGC Rainbow” – which represents the state-of-the-art in the context of semantic interoperability. 

  OGC and the other Data Week Leipzig organisers welcome attendees to Leipzig to learn and share experiences about the concepts and visions of Data Spaces, Urban Platforms, and other technical solutions that follow the FAIR principles that ensure data remains Findable, Accessible, Interoperable, and Reusable.

  A special session is dedicated to the recently launched Location Innovation Academy – a free online training program based on the knowledge and ideas generated by the European GeoE3 project. The academy offers a comprehensive set of modules that support modern and cross-border management, integration, processing, and sharing of geospatial data. Courses are available for beginners through to experienced technical experts who want to deepen their skills in, for example, the OGC API family of Standards. The current content of the modules has been produced by an international team of experts from across Europe.

  See the full event schedule and register at the Data Week Leipzig website.

  

  The post OGC to host European Innovation Days and more at Data Week Leipzig ‘23 appeared first on Open Geospatial Consortium.

• 9:00

  Streets GL

  sur Google Maps Mania
  Streets GL is a new real-time 3D map which shows buildings in 3D and building shadows in real-time, based on the actual time of day.  The map uses OpenStreetMap map and building height data. It also uses real-time flight data.One of my favorite features of Streets GL is that you can view planes flying around the map in real-time. Zoom in on an airport on the map (such as Heathrow or JFK) and

• 2:00

  Paul Ramsey: MapScaping Podcast: Rasters and PostGIS

  sur Planet OSGeo

  Last month I got to record a couple podcast episodes with the MapScaping Podcast’s Daniel O’Donohue. One of them was on the benefits and many pitfalls of putting rasters into a relational database, and it is online now!

  • Rasters In A Database?

  TL;DR: most people think “put it in a database” is a magic recipe for: faster performance, infinite scalability, and easy management.

  Where the database is replacing a pile of CSV files, this is probably true.

  Where the database is replacing a collection of GeoTIFF imagery files, it is probably false. Raster in the database will be slower, will take up more space, and be very annoying to manage.

  So why do it? Start with a default, “don’t!”, and then evaluate from there.

  For some non-visual raster data, and use cases that involve enriching vectors from raster sources, having the raster co-located with the vectors in the database can make working with it more convenient. It will still be slower than direct access, and it will still be painful to manage, but it allows use of SQL as a query language, which can give you a lot more flexibility to explore the solution space than a purpose built data access script might.

  There’s some other interesting tweaks around storing the actual raster data outside the database and querying it from within, that I think are the future of “raster in (not really in) the database”, listen to the episode to learn more!

• 16 May 2023
• 8:41

  AI Street View

  sur Google Maps Mania
  Today I have mainly been creating AI generated Street View scenes of historical locations. The result is AI Time Travel Street View, a little virtual world of 360 degree panoramas which you can wander around in while exploring Medieval France, Renaissance Venice and Victorian London (as dreamed by AI).Navigating around AI Time Travel Street View is fairly intuitive. Just click on the arrow

• 15 May 2023
• 16:20

  W3C Maps for HTML Community Group: Geomob Podcast on Maps for HTML

  sur Planet OSGeo

  Ed Freyfogle, leader of the OpenCage geocoding service, and Peter Rushforth had a chat about the Maps for HTML community and our goals. You can listen to their conversation here, please leave comments below.

  

• 8:35

  The Map of GitHub

  sur Google Maps Mania
  Every now and again I search GitHub for map and IIIF projects. I find that a quick search of GitHub repositories is a handy way to get an overview of new (and old) areas that the developer community is currently working on. My searching of GitHub has now become a lot easier thanks to the Map of GitHub. The Map of GitHub is a network graph of over 400,000 GitHub projects. Each dot on this
• 13 May 2023
• 9:58

  The Great Amazonian Indigenous Land Grab

  sur Google Maps Mania
  A new investigation by InfoAmazonia shows how over 38,000 hectares of Indigenous land in the Amazon has been stolen and developed into farmland between 2018 and 2021. In Expansion of pastures in indigenous lands triples in 4 years and threatens isolated peoples of the Amazon InfoAmazonia use a series of maps to show where rainforest has been deforested and turned into pasture for grazing

• 12 May 2023
• 15:34

  Free and Open Source GIS Ramblings: How to use Kaggle’s Taxi Trajectory Data in MovingPandas

  sur Planet OSGeo

  Kaggle’s “Taxi Trajectory Data from ECML/PKDD 15: Taxi Trip Time Prediction (II) Competition” is one of the most used mobility / vehicle trajectory datasets in computer science. However, in contrast to other similar datasets, Kaggle’s taxi trajectories are provided in a format that is not readily usable in MovingPandas since the spatiotemporal information is provided as:

  • TIMESTAMP: (integer) Unix Timestamp (in seconds). It identifies the trip’s start;
  • POLYLINE: (String): It contains a list of GPS coordinates (i.e. WGS84 format) mapped as a string. The beginning and the end of the string are identified with brackets (i.e. [ and ], respectively). Each pair of coordinates is also identified by the same brackets as [LONGITUDE, LATITUDE]. This list contains one pair of coordinates for each 15 seconds of trip. The last list item corresponds to the trip’s destination while the first one represents its start;

  Therefore, we need to create a DataFrame with one point + timestamp per row before we can use MovingPandas to create Trajectories and analyze them.

  But first things first. Let’s download the dataset:

  import datetime
  import pandas as pd
  import geopandas as gpd
  import movingpandas as mpd
  import opendatasets as od
  from os.path import exists
  from shapely.geometry import Point
  
  input_file_path = 'taxi-trajectory/train.csv'
  
  def get_porto_taxi_from_kaggle():
      if not exists(input_file_path):
          od.download("https://www.kaggle.com/datasets/crailtap/taxi-trajectory")
  
  get_porto_taxi_from_kaggle()
  df = pd.read_csv(input_file_path, nrows=10, usecols=['TRIP_ID', 'TAXI_ID', 'TIMESTAMP', 'MISSING_DATA', 'POLYLINE'])
  df.POLYLINE = df.POLYLINE.apply(eval)  # string to list
  df
  

  

  And now for the remodelling:

  def unixtime_to_datetime(unix_time):
      return datetime.datetime.fromtimestamp(unix_time)
  
  def compute_datetime(row):
      unix_time = row['TIMESTAMP']
      offset = row['running_number'] * datetime.timedelta(seconds=15)
      return unixtime_to_datetime(unix_time) + offset
  
  def create_point(xy):
      try: 
          return Point(xy)
      except TypeError:  # when there are nan values in the input data
          return None
   
  new_df = df.explode('POLYLINE')
  new_df['geometry'] = new_df['POLYLINE'].apply(create_point)
  new_df['running_number'] = new_df.groupby('TRIP_ID').cumcount()
  new_df['datetime'] = new_df.apply(compute_datetime, axis=1)
  new_df.drop(columns=['POLYLINE', 'TIMESTAMP', 'running_number'], inplace=True)
  new_df
  

  

  And that’s it. Now we can create the trajectories:

  trajs = mpd.TrajectoryCollection(
      gpd.GeoDataFrame(new_df, crs=4326), 
      traj_id_col='TRIP_ID', obj_id_col='TAXI_ID', t='datetime')
  trajs.hvplot(title='Kaggle Taxi Trajectory Data', tiles='CartoLight')
  

  

  That’s it. Now our MovingPandas.TrajectoryCollection is ready for further analysis.

  By the way, the plot above illustrates a new feature in the recent MovingPandas 0.16 release which, among other features, introduced plots with arrow markers that show the movement direction. Other new features include a completely new custom distance, speed, and acceleration unit support. This means that, for example, instead of always getting speed in meters per second, you can now specify your desired output units, including km/h, mph, or nm/h (knots).

  This post is part of a series. Read more about movement data in GIS.

• 9:34

  The Folk Music of the World

  sur Google Maps Mania
  Carnegie Hall's Musical Explorers Around the World Map allows you to discover and listen to folk music from all corners of the globe. Using the map you can directly listen to bluegrass music from Appalachia, mbira music from Zimbabwe, calypso from Trinidad & Tabago, and lots of other amazing performances of traditional music in countries around the world.If you click on a marker on the Musical

• 2:00

  Camptocamp: The Open Source Geospatial Community Gathers at Camptocamp for OGC Code Sprint

  sur Planet OSGeo

  Enclosure: [download]

  Over 50 Geospatial developers from around the world gathered in-person for the 3rd annual Open Standards and Open Source Software Code Sprint at Camptocamp’s Basecamp office in Bussigny, Switzerland from April 25 to 27, 2023.
• 11 May 2023
• 16:00

  QGIS Blog: Plugin Update April 2023

  sur Planet OSGeo

  April wasn’t just the month of our wonderful user conference and contributor meeting, it was also a month with a whopping 23 new plugins that have been published in the QGIS plugin repository.

  Here’s the quick overview in reverse chronological order. If any of the names or short descriptions piques your interest, you can find the direct link to the plugin page in the table below the screenshot.

  

  Network Store Plugin
  export layers to kisters network store
  Sphere Basemap Layers
  This plugin let you to add a variety of thailand basemap from GISTDA sphere Open Platform
  Earth, Sun, Moon, and Planets
  Tools to calculate the positions of the sun, moon, and planets when viewed from directly overhead for a particular date and time. It displays solar and lunar information for a coordinate at the specified date and time. (Note the Python library dependencies.)
  Concaveman QGIS
  Makes concave hull for points
  CIGeoE Holes 3D
  Draws holes in polygons (3D)
  AemetOpenDataDownloader
  This Plugin download open data from aemet
  Topography
  The plugin is available in this first version with the functionality to calculate closed polygons using the projections method.
  Green View Index
  A plugin for Green View Index (GVI) operations
  Datos Espaciales de Referencia de Andalucía (DERA)
  Loading of wfs/wms services from DERA Spatial Reference Data.Carga de los servicios wfs/wms de los Datos Espaciales de Referencia DERA
  Lidar Manager
  Manage LiDAR (dtm/dsm) dataset from Tile Index Layer
  OpenCraterTool
  A tool to measure and compare craters
  GeoTrace2
  A QGIS plugin for geological mapping
  TianDiTu Tools
  ???????
  OpenCage Geocoder
  Geocoding using the OpenCage API
  DMP Data Catalogue
  Discover and add layers from the Danish Miljøportal data catalog
  File Management
  Plugin to help with file management from the Layers Panel.
  Bestagon
  Form (mostly Hexagon) generator for point intensities
  Indiana Ortho Imagery
  This plugin provide easy access to Indiana Ortho Imageries
  Adresssuche
  Searching for an adresspoint in Germany based on offical data – ALKIS Adresssuche
  GpuDataChecker
  Plugin pour l’aide au contrôle de la validité géométrique de données pour intégration dans le géoportail de l’urbanisme
  Tile Index Generator
  This plugin creates tile index in vector format for XYZ tiles.
  SeaLevelTool
  Adjust styling on raster layer by a sea level curve.
  DataSud
  Plugin pour QGIS 3 fournissant un accès simple aux flux de données géographiques (WMS, WFS) publiées par la Région Sud sur DataSud.fr.

• 8:38

  Mapping Russian Military Facilities in Crimea

  sur Google Maps Mania
  Ukrainian journalists working for Radio Liberty have released an interactive map which shows the locations of more than 200 military facilities located in Crimea. The map shows over 200 Russian military locations in Crimea categorized into 10 different categories, documented using Planet Labs satellite imagery and terrestrial photography. Ukraine is soon expected to launch a counteroffensive
• 10 May 2023
• 9:54

  Mythical Creatures of the World

  sur Google Maps Mania
  The Mythical Creatures of the World interactive map allows you to learn more about some of the strange and wonderful monsters that exist in cultures around the world. Mythical creatures appear in the folklore of nearly every culture. Some, like Scotland's Loch Ness Monster or Tibet's Abononimable Snowman, you have probably heard of before. Many of the monsters on this map, however, you have

• 2:00

  SourcePole: Integrate a QGIS Cloud Map into a Web Page

  sur Planet OSGeo
  After a beautiful map has been created with QGIS and published on [https:] the desire quickly arises to integrate this map into one’s own website. This way, visitors to the website could access the map directly and without having to go via [https:] With a little HTML, this is easy to do. But let’s start from the beginning. Make a QGIS Cloud Map As always with QGIS Cloud, a map must first be published.

• 09 May 2023
• 8:56

  AI Map Search Finds Atlantis

  sur Google Maps Mania
  Google Maps is very good at finding your nearest pizza restaurants or cafes. It is not so useful if you want to find a list of the winners of the ugliest building awards or the steepest streets in San Francisco.AI Search Map by Map Channels is a new interactive map which allows you to search for any term at any location. The map uses ChatGPT to find the most accurate and relevant search results

• 2:00

  Paul Ramsey: LLM Use Case

  sur Planet OSGeo

  I can only imagine how much AI large language model generated junk there is on the internet already, but I have now personally found one in my blog comments. It’s worth pointing out, since comment link spam is a long time scourge of web publishing, and the new technology makes it just that little extra bit invisible.

  The target blog post is this one from the late 2000’s oil price spike. A brief post about how transportation costs tie into real estate desirability. (Possible modern day tie in: will the rise of EVs and decoupling of daily transport costs from oil prices result in a suburban rennaisance? God I hope not.)

  The LLM spam by “Liam Hawkins” is elegant in its simplicity.

  

  I imagine the prompt is nothing more complex than “download this page and generate 20 words that are a reasonable comment on it”. The link goes to a Brisbane bathroom renovation company, that I am sure does sterling work and maybe should concentrate on word of mouth rather than SEO.

  I need to check my comment settings, since the simplest solution is surely to just disallow links in comments. An unfortunate degredation in the whole point of the “web”, but apparently necessary in these troubled times.

• 1:57

  GeoCat: Open Standard / Open Source Sprint – April 2023

  sur Planet OSGeo

  The GeoCat team had a rewarding experience attending the Open Standard and Open Source Software code sprint near Lausanne. This was a joint Apache / OSGeo / OGC activity.

  We would like to thank our hosts for their hospitality and amazing food selection.

  geonetwork-open source sprint

  The code sprint afforded an opportunity to discuss, plan and inspire the geonetwork team with ideas for the future.

  A hot topic of discussion was a roadmap challenge: planning the migration from AngularJS to Angular.

  Really it was good to see everyone working productively and enthusiastic about what comes next.

  geoserver open standard sprint 

  GeoCat is quite excited by the new suite of open geospatial standards being developed by the OGC.

  GeoServer has been making progress on implementing these OGCAPI  standards for some time with the work occurring as “community modules” until such time as they are ready for review and publication. The challenge is that until these standards are complete; the implementation is subject to change and not stable to share with the public for review and testing.

  To address this gap, the code sprint covered two improvements:

  The first activity was to split the ogcapi modules into individual downloads. This allows modules that are ready, like ogcapi-features, to be finalized without waiting on standards that are still in progress.

  The second activity was to make it much easier to tryout ogcapi services with a docker image available for each nightly build:

  docker pull docker.osgeo.org/geoserver:2.24.x
  docker run -it -p8080:8080 \
    --env INSTALL_EXTENSIONS=true \
    --env COMMUNITY_EXTENSIONS="ogcapi-features" \
    docker.osgeo.org/geoserver:2.24.x

  Go on give it a go :)

  

  ogcapi-features 1.0.1

   

  This improves on the manual process of downloading a nightly build; and manually installing an extension. We hope these changes will help more people tryout ogcapi services and provide feedback and improvements.

  It is a privilege to work on these activities on behalf of our GeoCat Live and GeoServer Enterprise customers.

  The post  Open Standard / Open Source Sprint – April 2023  appeared first on GeoCat B.V..

• 08 May 2023
• 11:24

  GeoTools Team: GeoTools 27.5 Released

  sur Planet OSGeo
  The GeoTools team is pleased to share the availability GeoTools 27.5:geotools-27.5-bin.zipgeotools-27.5-doc.zipgeotools-27.5-userguide.zipgeotools-27.5-project.zipThis release is also available from the OSGeo Maven Repository and is made in conjunction with GeoServer 2.22.3 and GeoWebCache 1.22.2.Improvements and fixes in this releaseBugGEOT-7316 Child feature ClientProperties are replicated on
• 3:24

  Sean Gillies: Quad Rock 50 recap

  sur Planet OSGeo

  I did it! My third Quad Rock 50 mile finish in three tries. My official time was 13 hours, 56 minutes, and 57 seconds, just three minutes under the limit. I prepared less for this race than I have in 2019 and 2021 because I'm aiming to peak at the end of September and looked at it as mainly a long training run that I might finish or not. My longest run so far this year was 18 miles. I joked with the race director afterwards that my plan was to run myself into shape in the first 25 miles and then build on that. I was mentally prepared to not finish and also prepared to push myself if a finish was within reach.

  In the first half of the race, I stayed well within my limits and left the Soldier Canyon aid station, the turn-around, with an elapsed time of 6 hours and 15 minutes. The climb up Timber Trail was warm and I cramped severely on the following descent down Howard Trail. I arrived at Arthurs Rock aid station only seven minutes before the time check. Dropping out at Arthurs had crossed my mind on the descent and the thought was lingering a bit as I hobbled in, but the friendly volunteers filled my tank up with pickles, popsicles, and encouragement, and I found myself good to go again. I headed out towards the Mill Creek climb and was racing, slowly, against the clock all the rest of the afternoon.

  After I got to the top of Mill Creek, I had to resupply quickly and then get over the rest of the Westridge Trail climb and down to and through the Horsetooth aid station in 65 minutes. Again, thoughts of dropping tempted me during the technical part of the descent. I felt better during the runnable last 1.5 miles and made it to the aid station with four minutes to go. Not enough time to change socks and shoes as I'd planned, only enough time to grab more drinks and food and regroup with two other runners.

  The final climb is not as hard as the penultimate climb, and after that it was mostly a matter of managing my effort well. At the last aid station, with 2.3 relatively flat miles to go and 30 minutes left, I was pretty confident I would make it in under 14 hours. I ran the downhills quickly and didn't dawdle on the flats, coasting just a bit to the finish line.

  Honestly, I could have kept going. I was feeling composed and fairly energetic at the finish. I'll be building on this for the next 16 weeks.

• 2:00

  GeoServer Team: GeoServer 2.21.5 Release

  sur Planet OSGeo

  GeoServer 2.21.5 release is now available with downloads (bin, war, windows), along with docs and extensions.

  This is a maintenance release of the GeoServer 2.21.x series, made in conjunction with GeoTools 27.5 and GeoWebCache 1.21.5.

  Thanks to Daniele Romagnoli (GeoSolutions) for making this release.

  Release notes

  Sub-task

  • GEOS-10908 Update spring version from 5.2.22 to 5.2.23

  Bug

  • GEOS-3978 Layer configuration allows admin to enter a zero area bounding box

  • GEOS-6313 Lifecycle handlers not properly called during shutdown

  • GEOS-10006 Seeding GWC doesn’t work for layers with a dot in the name

  • GEOS-10500 WFS-T unable to delete more than 30 features in a single transaction when the data source is PostGIS

  • GEOS-10517 jms-cluster classes missing from XStream security configuration

  • GEOS-10593 Regression: Creating SQL View via REST API and explicit attribute list is no-longer possible

  • GEOS-10611 Uploading application/zip to styles endpoint does not clean up temporary files

  • GEOS-10828 OGC API - Features - Plugin breaks core `/rest` API with JSON payloads

  • GEOS-10837 geopackage output fails when java.io.tmpdir on network share

  • GEOS-10869 Jayway JSON Path libraries not included anymore on GeoServer packages

  • GEOS-10878 wps-multidimensional and wps-jdbc are not being deployed on maven repo

  • GEOS-10896 Missing NULL check in the template backwards mapping

  • GEOS-10899 Features template escapes twice HTML produced outputs

  • GEOS-10912 jms-cluster fails to clone grid coverage layer on other nodes

  • GEOS-10920 Excel output format packaging misses dependencies, cannot produce .xls

  • GEOS-10921 Double escaping of HTML with enabled features-templating

  • GEOS-10932 csw-iso: should only add ‘xsi:nil = false’ attribute

  • GEOS-10946 WMS GetLegendGraphic throws FootprintsTransformation cannot be cast to ProcessFunction Exception

  • GEOS-10950 Performance regression in DescribeFeatureType across all feature types

  • GEOS-10957 Support ResourceAccessManager implementations returning custom subclasess of AccessLimits

  Improvement

  • GEOS-10867 Bump commons-fileupload from 1.4 to 1.5

  • GEOS-10870 Allow importer AttributesToPointGeometryTransform to preserve original geometries, and to configure the name of the target geometry

  • GEOS-10873 Upgrade XStream to 1.4.20

  • GEOS-10940 Update MapML viewer to release 0.11.0

  Task

  • GEOS-10863 Update Oracle JDBC driver to 19.18.0.0

  • GEOS-10904 Bump jettison from 1.5.3 to 1.5.4

  Release notes: ( 2.21.5 | 2.21.4 | 2.21.3 | 2.21.2 | 2.21.1 | 2.21.0 | 2.21-RC )

• 2:00

  Ian Turton's Blog: Drawing a line on a GeoTools Map

  sur Planet OSGeo
  Drawing a line on a GeoTools Map

  As anyone following the dismal news out of the UK recently will know we had some sort of royal extravaganza down south in England this weekend, so with nothing better to do (and an extra day off) I decided to do some playing with GeoTools. This was mostly motivated by the work I had already done in answering this gis.stackexchange.com question about how to draw a line on top of a map. It seems that there isn’t much about how to do this in the GeoTools documentation.

  So I scratched my head and dredged up what I could remember about swing and particularly about the GeoTools swing module and came up with some code that answered the immediate question which was why the OP got many layers in the map rather than one. I decided that this might be useful for other people so I tidied the code up and created a small project that contains a DigitizerAction and a Digitizer class which is the actual tool. It’s pretty simple all it does is place a series of dots on the screen and then generates a LineString which is added to a list, which is then used to generate a new FeatureLayer and removes the old layer (if it exists).

  I finished up by adding a little demo program which adds a draw button to the toolbar and displays the US States for you to draw over.

  

  All you do is click the draw button, then each click on the map will add a point to the current line, a double click finishes the line and forces a redraw of the screen with the line now in red.

  Details

  For anyone who’s trying to create a new tool for their swing application with GeoTools here is a little more on how it works.

  Action

  We need to create an Action to tell swing what we plan to do, I called mine DigitizerAction and made it extend MapAction which Michael Bedward (the original author of the gt-swing module) helpfully provided to save us typing (or pasting) in a lot of boiler plate code. All I have to provide is some code to initialise the action’s icon, name etc and an actionPerformed method to set the tool up to actually do something when the button is clicked.

  Tool

  Again to save time and effort the Digitizer tool extends CursorTool which extends MapMouseAdapter so we don’t need to worry about how to listen to the mouse’s movements or how to get a real world position from a mouse click. Much of the code is either set up or book keeping. For set up we need to generate a FeatureType for the Features we’ll be building later, and a style so they show up on the map (a more advanced tool might let the user override that default style). The only other thing to take care of in the constructor is setting the cursor to a simple cross hair.

     public Digitizer() {
          SimpleFeatureTypeBuilder b = new SimpleFeatureTypeBuilder();
          b.setName("LineFeature");
          b.add("line", LineString.class);
          SimpleFeatureType TYPE = b.buildFeatureType();
          featureBuilder = new SimpleFeatureBuilder(TYPE);
          geometryFactory = JTSFactoryFinder.getGeometryFactory(JTSFactoryFinder.EMPTY_HINTS);
          style = SLD.createLineStyle(Color.red, 2.0f);
  
          ImageIcon imgIcon = new ImageIcon(getClass().getResource(ICON_IMAGE));
          cursor = new Cursor(Cursor.CROSSHAIR_CURSOR);
      }
  

  The class also has some fields that we’ll need later lastX and lastY which is the position of the last click, an ArrayList of Coordinates which are the real world positions of the current line, and a list of SimpleFeatures which hold the lines that we have already drawn. We need to keep track of the previous features as the display layer is recreated every time we add a line.

  The actual interaction with the user all occurs inside the onMouseClicked method which is called each time a mouse button is clicked.

      public void onMouseClicked(MapMouseEvent e) {
  
          if (e.getClickCount() > 1) { // was it a double click
              drawTheLine(positions);
              first = true;
          } else { // add a new point
              DirectPosition2D pos = e.getWorldPos();
  
              positions.add(new Coordinate(pos.x, pos.y));
              // Put a marker at each digitized point
              Graphics graphics = (Graphics2D) ((JComponent) getMapPane()).getGraphics().create();
              int x = e.getX();
              int y = e.getY();
              if (!first) {
                  graphics.drawLine(lastX, lastY, x, y);
              }
              first = false;
              lastX = x;
              lastY = y;
              graphics.fillRect(x - 3, y - 3, 6, 6);
          }
      }
  

  Here we first check if the user has clicked twice within the system time limit (so it is a double click), if it is we call the drawTheLine method on the positions list to add the line to the screen, we’ll look at that in a moment. We also reset the first flag to say that the next click (if there is one) is the first in a line.

  If the user only clicked once (or this is the first click of a double click) we will go through the else branch, where we get the world position of the click and add that to our list of coordinates. We then grab a graphics from our map pane to draw a temporary mark so the user knows we’re listening and have seen their click, here we need the X and Y pixel coordinates. If this is not the first point in the line we draw a line from the last point (lastX, lastY) to the current point (x, y) and then we draw a point at the current point (x, y). We also make a note of this point for next click to be the start of the line and note that we now have previous point by making first false.

  The last remaining step is to draw lines on the map as SimpleFeatures, this is done in drawTheLine where we generate a new LineString using the GeometryFactory, we then add that LineString to the FeatureBuilder and create a new SimpleFeature from it. Note that we leave the id set to null so it generates a new FID for each feature. The feature is then stored in the features list, the existing layer is removed from the map (to prevent us ending up with an ever increasing number of map layers). Then we create a new FeatureLayer using the DataUtilities.collection method to convert our list of SimpleFeatures to a SimpleFeatureCollection and applying the style we made earlier. Finally, we reset the positions list to empty to be ready to store the next line for the user.

  Usage

  If you want to use this in your own map you can simply do the following:

      mapFrame = new JMapFrame();
      mapFrame.enableToolBar(true);
      JToolBar toolBar = mapFrame.getToolBar();
      DigitizerAction d = new DigitizerAction(mapFrame.getMapPane());
      JButton btn = new JButton(d);
      toolBar.addSeparator();
      toolBar.add(btn);
  

  You can then get the list of features by using d.getFeatures() if you want to provide a save function or to send them to some other store.

• 06 May 2023
• 13:18

  The Rise & Fall of the Irish Railway

  sur Google Maps Mania
  Irish Railway Stations 1834-2000 is a simple interactive map which plots all the Irish train stations which are / were open for every year from 1834 to 2000. By scrolling through all 166 years on the map you get a great overview of the rise and fall of the railway in Ireland. The first railway line opened in Ireland was the Dublin and Kingstown Railway (D&KR), which ran between Westland Row in

• 05 May 2023
• 15:18

  GeoTools Team: GeoTools 28.3 Released

  sur Planet OSGeo
  The GeoTools team is pleased to share the availability GeoTools 28.3:geotools-28.3-bin.zipgeotools-28.3-doc.zipgeotools-28.3-userguide.zipgeotools-28.3-project.zipThis release is also available from the OSGeo Maven Repository and is made in conjunction with GeoServer 2.22.3 and GeoWebCache 1.22.2.Improvements and fixes in this release BugGEOT-7238 WFSContentComplexFeatureSource.getFeatures(

• 9:40

  The First Images from EUMETSAT MTG-I1

  sur Google Maps Mania
  The first high quality image from Europe's newest weather satellite has been released. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) operates a fleet of satellites with which it monitors weather, climate, and the environment from space. EUMETSAT's newest satellite, Meteosat Third Generation – Imager 1 (Meteosat-12) was launched in December 2022 and is

• 2:00

  GeoServer Team: GeoServer 2.22.3 Release

  sur Planet OSGeo

  GeoServer 2.22.3 release is now available with downloads (bin, war, windows), along with docs and extensions.

  This is a maintenance release of the GeoServer 2.22.x series, made in conjunction with GeoTools 28.3 and GeoWebCache 1.22.2.

  Thanks to Daniele Romagnoli (GeoSolutions) for making this release.

  Release notes

  Sub-task:

  • GEOS-10908 Update spring version from 5.2.22 to 5.2.23

  Bug:

  • GEOS-3978 Layer configuration allows admin to enter a zero area bounding box

  • GEOS-6313 Lifecycle handlers not properly called during shutdown

  • GEOS-10006 Seeding GWC doesn’t work for layers with a dot in the name

  • GEOS-10500 WFS-T unable to delete more than 30 features in a single transaction when the data source is PostGIS

  • GEOS-10517 jms-cluster classes missing from XStream security configuration

  • GEOS-10593 Regression: Creating SQL View via REST API and explicit attribute list is no-longer possible

  • GEOS-10611 Uploading application/zip to styles endpoint does not clean up temporary files

  • GEOS-10837 geopackage output fails when java.io.tmpdir on network share

  • GEOS-10865 Backwards incompatible change in the XML representation of user roles

  • GEOS-10869 Jayway JSON Path libraries not included anymore on GeoServer packages

  • GEOS-10871 about geoserver page reporting @project.version@ for WAR deploy

  • GEOS-10878 wps-multidimensional and wps-jdbc are not being deployed on maven repo

  • GEOS-10890 Wrong path for the license file in the Windows installer script

  • GEOS-10896 Missing NULL check in the template backwards mapping

  • GEOS-10899 Features template escapes twice HTML produced outputs

  • GEOS-10912 jms-cluster fails to clone grid coverage layer on other nodes

  • GEOS-10920 Excel output format packaging misses dependencies, cannot produce .xls

  • GEOS-10921 Double escaping of HTML with enabled features-templating

  • GEOS-10922 Features templating exception on text/plain format

  • GEOS-10934 CSW does not show title/abstract on welcome page

  • GEOS-10946 WMS GetLegendGraphic throws FootprintsTransformation cannot be cast to ProcessFunction Exception

  • GEOS-10950 Performance regression in DescribeFeatureType across all feature types

  • GEOS-10957 Support ResourceAccessManager implementations returning custom subclasess of AccessLimits

  Improvement:

  • GEOS-10858 jdbc-config turns off isolated workspace support

  • GEOS-10867 Bump commons-fileupload from 1.4 to 1.5

  • GEOS-10870 Allow importer AttributesToPointGeometryTransform to preserve original geometries, and to configure the name of the target geometry

  • GEOS-10873 Upgrade XStream to 1.4.20

  • GEOS-10898 Preserve key order in STAC responses coming from JSONB columns

  • GEOS-10923 Use default writing params on GeoTIFFPPIO

  New Feature:

  • GEOS-10868 Add support for editable description in GeoServer customize feature type table

  Task:

  • GEOS-10863 Update Oracle JDBC driver to 19.18.0.0

  • GEOS-10894 Random control-flow errors on Mac builds

  • GEOS-10904 Bump jettison from 1.5.3 to 1.5.4

  For complete information see 2.22.3 release notes.

  About GeoServer 2.22

  Additional information on GeoServer 2.22 series:

  • Update Instructions
  • Metadata extension
  • CSW ISO Metadata extension
  • State of GeoServer (FOSS4G Presentation)
  • GeoServer Beginner Workshop (FOSS4G Workshop)
  • Welcome page (User Guide)

  Release notes: ( 2.22.3 | 2.22.2 | 2.22.1 | 2.22.0 | 2.22-RC | 2.22-M0 )

• 04 May 2023
• 17:23

  Jackie Ng: The "I haven't forgotten about you $PROJECT" tour

  sur Planet OSGeo

  As I said near the end of my MGOS 4.0 Beta 1 announcement, I will be momentarily stepping away from MapGuide development/maintenance to give some of my sibling projects in the MapGuide/FDO space some long-overdue attention.

  So for the next few weeks, I will be embarking on the "I haven't forgotten about you $PROJECT" tour with stopovers at the following projects:

  mapguide-react-layoutNext Release: 0.14.8
  Objectives: This will be the last release in the 0.14.x series and the last release to officially support Internet Explorer.MapGuide MaestroNext Release: 6.0m12
  Primary Objective: This release will have authoring parity with MapGuide Open Source 4.0 Beta 1Secondary Objective: Assorted fixes and minor enhancementsFDO ToolboxNext Release: 1.5.3
  Objective: Some fixes for bugs and usability problems reported since 1.5.2mapguide-restNext Release: 1.0 RC6
  Yes! I am finally giving this project some very-overdue attention!
  Primary Objective: Make sure it is compatible with PHP 8.1 that is bundled with MapGuide Open Source 4.0 Beta 1. Also doubles as a secondary sanity test of the new vanilla SWIG-generated PHP bindings, which is my main motivator for revisiting this project.
  Secondary Objective: See if we can do this will still being able to support older PHP versions bundled with older MapGuide versions. If this is not tenable, we may need to branch codebases and make separate releases. I hope that this is not the case.
  
  When I finish this tour, then I will be returning to get MapGuide Open Source 4.0 to the final release finish line
  
  
  

• 15:00

  OGC Adopts 3D Tiles v1.1 as Community Standard

  sur Open Geospatial Consortium (OGC)

  The Open Geospatial Consortium (OGC) is excited to announce that the OGC Membership has approved version 1.1 of 3D Tiles for adoption as an official OGC Community Standard. 3D Tiles is used for sharing, visualizing, fusing, and interacting with massive heterogenous 3D geospatial content across desktop, web, mobile – and now metaverse – applications.

  Previously referred to as “3D Tiles Next,” Version 1.1 of the 3D Tiles Community Standard is designed for streaming high-resolution, semantically-rich 3D geospatial data to the metaverse. 3D Tiles 1.1 promotes several 3D Tiles 1.0 extensions to ‘core’ and introduces new glTF™ extensions for fine-grained metadata storage. The OGC Community Standard is identical to the Cesium release of version 1.1 of the 3D Tiles specification.

  “The collective community experience building with 3D Tiles since 2015, combined with the continued growth of 3D geospatial data availability, especially semantic metadata, and increasing user interest in digital twins and the metaverse has led to this next generation of the 3D Tiles specification,” said Patrick Cozzi, CEO of Cesium. “3D Tiles 1.1 being recognized as an OGC Community Standard encourages an open ecosystem for the benefit of all where the community can leverage the open specification to advance the 3D geospatial industry.”

  The primary enhancements in the 3D Tiles version 1.1 include:

  • Semantic metadata at multiple granularities;
  • Implicit tiling for improved analytics and random access to tiles;
  • Multiple contents per tile to support layering and content groupings; and
  • Direct references to glTF™ content for better integration with the glTF™ ecosystem.

  3D Tiles 1.1 is backwards compatible with 3D Tiles 1.0: valid 1.0 tilesets are also valid 1.1 tilesets.

  3D Tiles was first announced at SIGGRAPH in 2015, and was published as an OGC community standard in 2019. Since then, the community has built apps, exporters, APIs, and engines with 3D Tiles to grow an open and interoperable 3D geospatial ecosystem. This collective experience building with 3D Tiles, combined with the continued growth of 3D geospatial data availability, especially semantic metadata, and increasing user interest in digital twins and the metaverse, has led to this revision of the 3D Tiles specification.

  A Community Standard is an official standard of OGC that is developed and maintained external to the OGC. The originator of the standard brings to OGC a “snapshot” of their work that is then endorsed by OGC membership as a stable, widely implemented standard that becomes part of the OGC Standards Baseline.

  As with any OGC standard, the open 3D Tiles v1.1 OGC Community Standard is free to download and implement. Interested parties can learn more about the standard on OGC’s 3D Tiles Community Standard Page.

  The post OGC Adopts 3D Tiles v1.1 as Community Standard appeared first on Open Geospatial Consortium.

• 9:46

  Trees are Moving North

  sur Google Maps Mania
  In the last few years, in response to global heating and climate change, a number of interactive maps have been created which attempt to show how temperatures in your home town will change over the course of the 21st Century. The traumatic climate changes that we are beginning to experience will have a huge impact on our local ecosystems, effecting the natural habitats of our native flora and
• 03 May 2023
• 9:10

  Exploring Mars in 3D

  sur Google Maps Mania
  Traveling along the bottom of the Mamers Vallis canyon on MarsImagine being able to drive through the Mamers Vallis canyon on Mars, traveling along the canyon floor while marveling at the canyon walls which were formed 3.8 billion years ago. Better still don't imagine it. Instead use AreoBrowser to actually explore Mars in 3D.  The AreoBrowser allows you to explore over 2000 Martian locations in