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03 March 2019
21:03
Free and Open Source GIS Ramblings: Stand-alone PyQGIS scripts with OSGeo4W
sur Planet OSGeo
PyQGIS scripts are great to automate spatial processing workflows. Itâ€™s easy to run these scripts inside QGIS but it can be even more convenient to run PyQGIS scripts without even having to launch QGIS. To create a so-called â€œstand-aloneâ€ PyQGIS script, there are a few things that need to be taken care of. The following steps show how to set up PyCharm for stand-alone PyQGIS development on Windows10 with OSGeo4W.

An essential first step is to ensure that all environment variables are set correctly. The most reliable approach is to go to C:\OSGeo4W64\bin (or wherever OSGeo4W is installed on your machine), make a copy of qgis-dev-g7.bat (or any other QGIS version that you have installed) and rename it to pycharm.bat:

Instead of launching QGIS, we want that pycharm.bat launches PyCharm. Therefore, we edit the final line in the .bat file to start pycharm64.exe:

In PyCharm itself, the main task to finish our setup is configuring the project interpreter:

First, we add a new â€œsystem interpreterâ€ for Python 3.7 using the corresponding OSGeo4W Python installation.

To finish the interpreter config, we need to add two additional paths pointing to QGIS\python and QGIS\python\plugins:

Thatâ€™s it! Now we can start developing our stand-alone PyQGIS script.

The following example shows the necessary steps, particularly:
1. Initializing QGIS
2. Initializing Processing
3. Running a Processing algorithm
```
import sys

from qgis.core import QgsApplication, QgsProcessingFeedback
from qgis.analysis import QgsNativeAlgorithms

QgsApplication.setPrefixPath(r'C:\OSGeo4W64\apps\qgis-dev', True)
qgs = QgsApplication([], False)
qgs.initQgis()

# Add the path to processing so we can import it next
sys.path.append(r'C:\OSGeo4W64\apps\qgis-dev\python\plugins')
# Imports usually should be at the top of a script but this unconventional 
# order is necessary here because QGIS has to be initialized first
import processing
from processing.core.Processing import Processing

Processing.initialize()
QgsApplication.processingRegistry().addProvider(QgsNativeAlgorithms())
feedback = QgsProcessingFeedback()

rivers = r'D:\Documents\Geodata\NaturalEarthData\Natural_Earth_quick_start\10m_physical\ne_10m_rivers_lake_centerlines.shp'
output = r'D:\Documents\Geodata\temp\danube3.shp'
expression = "name LIKE '%Danube%'"

danube = processing.run(
    'native:extractbyexpression',
    {'INPUT': rivers, 'EXPRESSION': expression, 'OUTPUT': output},
    feedback=feedback
    )['OUTPUT']

print(danube)
```
18:29
GeoTools Team: GeoTools 21.0 Released
sur Planet OSGeo

The GeoTools is pleased to announce the release of GeoTools 21.0 our first release with both Java 11 and Java 8 compatibility: geotools-21.0-bin.zip geotools-21.0-doc.zip geotools-21.0-userguide.zip geotools-21.0-project.zip maven repository This is a stable release of GeoTools made in conjunction with GeoServer 2.15 and GeoWebCache 1.15. Release highlights: Works with both Java 11 and Java
1:04
Cameron Shorter: Starting build cycle for OSGeoLive 13.0
sur Planet OSGeo

Are you interested in joining our Open Source GIS experience? The build cycle for the next OSGeoLive release 13.0, is going to start. The final version is planned to be ready on 30th July 2019 in time for FOSS4G 2019Â in Bucharest. Have a look at our schedule for the detailed steps.
Till then we have many challenges - from simple to challenging, to help describe and train people in the value of Open Source GIS.
For this release, we hope to help OSGeo Community projects join OSGeoLive, and work out how we can keep within our size constraints.
We'd love to build a cloud version of OSGeoLive for this release. It would make OSGeoLive, and OSGeo software much more accessible. It seems elusively achievable, but we haven't worked it out yet. If you think you could help, we'd love to hear from you.
Get involvedAre you a programmer or packager with experience in one of the Open Source GIS applications. Are you a technical writer interested in making FOSS4G accessible to all? Are you interested in helping updateÂ translations to latest documents on Transifex.
Contact usIf you would like to add a new project, help us to get in the cloud or have another goal you would like to work on and get involved you are very welcome.

Please join the OSGeoLive mailing listÂ or meet us on IRC at ourÂ weekly meeting.
About OSGeoLiveOSGeoLiveÂ is a â€‹Lubuntu based distribution of Geospatial Open Source Software, available via a Live DVD, Virtual Machine and USB. You can use OSGeoLive to try a wide variety of open source geospatial software without installing anything.

02 March 2019
20:00
The Wine Regions of the World
sur Google Maps Mania

Do you know your Bordeaux from your Burgundy? Do you know which grape varieties are grown in which wine regions? Whether you can answer these questions or not, if you care about wine, you should have a look at the Biarritz Wine Academy Map. The Biarritz Wine Academy Map is an interactive map of the wine regions of the world. The Biarritz Wine Academy Map is very much a work in progress. At the
18:00
The Inequality Atlas
sur Google Maps Mania

The Atlas of Inequality is a new interactive map which shows the income inequality of customers who visit stores and establishments in the Boston metro area. The map shows the place inequality score of each establishment. This score shows how unequal the store's customer's incomes are. The atlas reveals some interesting patterns as to which type of establishment are most equal and which are

14:22
Free and Open Source GIS Ramblings: Easy Processing scripts comeback in QGIS 3.6
sur Planet OSGeo
When QGIS 3.0 was release, I published a Processing script template for QGIS3. While the script template is nicely pythonic, itâ€™s also pretty long and daunting for non-programmers. This fact didnâ€™t go unnoticed and Nathan Woodrow in particular started to work on a QGIS enhancement proposal to improve the situation and make writing Processing scripts easier, while â€“ at the same time â€“ keeping in line with common Python styles.

While the previous template had 57 lines of code, the new template only has 26 lines â€“ 50% less code, same functionality! (Actually, this template provides more functionality since it also tracks progress and ensures that the algorithm can be cancelled.)
```
from qgis.processing import alg
from qgis.core import QgsFeature, QgsFeatureSink

@alg(name="split_lines_new_style", label=alg.tr("Alg name"), group="examplescripts", group_label=alg.tr("Example Scripts"))
@alg.input(type=alg.SOURCE, name="INPUT", label="Input layer")
@alg.input(type=alg.SINK, name="OUTPUT", label="Output layer")
def testalg(instance, parameters, context, feedback, inputs):
    """
    Description goes here. (Don't delete this! Removing this comment will cause errors.)
    """
    source = instance.parameterAsSource(parameters, "INPUT", context)

    (sink, dest_id) = instance.parameterAsSink(
        parameters, "OUTPUT", context,
        source.fields(), source.wkbType(), source.sourceCrs())

    total = 100.0 / source.featureCount() if source.featureCount() else 0
    features = source.getFeatures()
    for current, feature in enumerate(features):
        if feedback.isCanceled():
            break
        out_feature = QgsFeature(feature)
        sink.addFeature(out_feature, QgsFeatureSink.FastInsert)
        feedback.setProgress(int(current * total))

    return {"OUTPUT": dest_id}
```
The key improvement are the new decorators that turn an ordinary function (such as testalg in the template) into a Processing algorithm. Decorators start with @ and are written above a function definition. The @alg decorator declares that the following function is a Processing algorithm, defines its name and assigns it to an algorithm group. The @alg.input decorator creates an input parameter for the algorithm. Similarly, there is a @alg.output decorator for output parameters.

For a longer example script, check out the original QGIS enhancement proposal thread!

For now, this new way of writing Processing scripts is only supported by QGIS 3.6 but there are plans to back-port this improvement to 3.4 once it is more mature. So give it a try and report back!
11:16
GeoServer Team: GeoServer 2.15.0 Released
sur Planet OSGeo
The GeoServer team is happy to announce the GeoServer 2.15.0Â release with downloads (zip|war|exe), documentation (html|pdf) and extensions.

This release is production ready and is ready to work with your Java 8 or Java 11 operational environment. This release is made in conjunction with GeoWebCache 1.15.0 and GeoTools 21.0.

The ability to work with Java 11 is the result a dedicated code sprint. Thanks to organizations participating in the code sprint (Boundless, GeoSolutions, GeoCat,Â Astun Technology,Â CCRi) along with sprint sponsors (Gaia3D,Â atol, osgeo:uk, Astun Technology).
Layer Service Settings
To start things off an often requested capability, the ability to control which services are enabled on a layer-by layer basis.

To try it our yourself see Service Settings in our user manual.
GeoFence Internal Server Extension
Originally a standalone service offering fine grain control over GeoServer security this functionality has been packaged up and embedded into a GeoServer extension for easier deployment.
- GeoFence rules provided greater control over security allowing layer by layer service restrictions
- GeoFence rules can provide access to data overriding layer details including CQL filter to limit contents returned and default style used for rendering
- GeoFence rules can limit access to a geographic extent
For more details see GeoFence Internal Server in our user manual.
Style Editor SLD Auto-Complete
To help make editing easier the Style Editor can provide auto-complete suggestions for SLD 1.0. To try it out yourself use control-space for context aware suggestions.

Generate Classified Thematics maps
SLDService is now an official extension, with a number of improvements. SLDService can now be used for the
- classification of raster data too
- equal area classification
- standard deviation filtering
The SLD REST Service extension is used to generate thematic styles based on attribute data:
```
curl -v -u admin:geoserver -XGET
  [localhost:8080]   ?attribute=PERSONS
  &ramp=CUSTOM
  &method=quantile
  &intervals=3
  &startColor=0xFF0000
  &endColor=0x0000FF
  &open=true
```
For more information see SLD Rest Service in our user manual.

WPS GetExecutionStatus and Dismiss Operations
WPS â€œGetExecutionsâ€ vendor operation allows each user to get the list of running processes:
- Users can review all their running processes
- Administrators can see all processes
The Dismiss vendor operation can be used to cancel the execution of one of the listed processes.

For more information see Dismiss in our user guide.
Java 11 Support
The provided binary download works with either Java 8 or Java 11. Tomcat 9 or newer is required for the WAR install.Â The user guide compatibility listÂ will continue to be updated based on your feedback.

The java ecosystem is now being led by the open source OpenJDK project, with long term support available from a range of organizations notably RedHat OpenJDK Â and Adopt OpenJDK. TheÂ GeoTools user guide provides an overview of Java 8 and Java 11 distributions.

The net effect of these changes:
- If you have been using Oracle JDK please review your options
- Java 8 will continue to be available
- The Java ecosystem is now led by the open-source Open JDK project
Java 11 no longer supports the Java 2 extension mechanism used for native JAI and native ImageIO libraries. Â We recommend the use of the pure Java JAI-EXT operations which have been made the default (see the next section).
JAI-EXT operations on by default
The use of the JAI-EXT operations have long been a recommendation, with this release we are making them the default for GeoServer. Â The JAI-EXT library offers a pure java implementation enhanced for geospatial functionality supporting NODATA pixels and support for vector footprints.

GeoServer Codebase
In addition to Java 11 support this release includes:
- Add JSON as a Legend Output format (GISP 173)
- Printing plugin upgrade version of JTS
- Upgrade NetCDF dependencies
- Improvements for vector tile production, both in terms of output correctness and production performance
Thanks to Andrea Aime for steady work on the codebase quality:
- PMD source code analysis, high priority checks, will fail the build in case of issues
- Error Prone byte code analysis, same as above
- Many small bugs fixed
For more details developers are invited to review Automated Quality Assurance checks in our developers manual. Also, work in ongoing on the master (dev) branch to extend the reach of static code checks using SpotBugs and CheckStyle too.
About GeoServer 2.15 Series
Additional information on the GeoServer 2.15 series:
- Release Notes (2.15.0|2.15-RC|2.15-M0)
- Running on Java 11 (User Manual)

01 March 2019
20:00
How Many Miles do You Scroll Online?
sur Google Maps Mania

Have you ever wondered how many miles your fingers scroll when you browse the internet? Digital Detox did so s/he created a Google Chrome extension to track their personal scrolling distance on all the websites they visit. The data is then sent in real-time to a Leaflet map. Marco Land is an interactive map which shows the path of the Camino FrancÃ©s, the most popular pilgrimage route of the Way
18:00
Shopping on Street View
sur Google Maps Mania

Retailers Fred Perry and Raf Simons have released a virtual reality shopping experience. Fred Perry x Raf Simons is a custom Street View scene which you can navigate around just like you can move around in Street View on Google Maps. However, unlike Google Maps, on these virtual panoramas you can click on the people and buy their clothes. All the models that appear in Fred Perry x Raf Simons
28 February 2019
18:00
The Language of Data Visualization
sur Google Maps Mania

Last year the Financial Times released a poster designed to help people create data visualizations. The FT's poster provides a guide to lots of different methods of visualizing data (including different types of mapped visualization) and advice on when each method should be used. The Github page of theÂ Visual Vocabulary poster includes external links to advice elsewhere on the internet on using

17:06
gvSIG Team: Camino a gvSIG 2.5: EnumeraciÃ³n de capas en la Tabla de Contenidos
sur Planet OSGeo

Una de las componentes mÃ¡s utilizadas en un SIG es su Tabla de Contenidos, tambiÃ©n conocida como TOC por sus siglas en inglÃ©s.

En la Tabla de Contenidos se enumeran todas las capas de una Vista y se muestra la leyenda con la que se representan las entidades de cada capa. TambiÃ©n ayuda a administrar el orden de visualizaciÃ³n de las capas en la Vista, a definir las capas que son visibles, las que estÃ¡n seleccionadas, permite el acceso rÃ¡pido a distintas herramientas, etc.

Ya en gvSIG Desktop 2.4 iniciamos las mejoras en el TOC con la existencia de un catÃ¡logo, que permite la carga rÃ¡pida de capas y la gestiÃ³n de favoritos. En la nueva versiÃ³n, gvSIG 2.5, encontrarÃ©is un nuevo plugin â€œTabbed TOCâ€ con el que continuamos estas mejoras.

Mediante este nuevo plugin aÃ±adimos a la Tabla de Contenidos una serie de nuevas opciones para enumerar o agrupar las capas de nuestra Vista.

AdemÃ¡s de la enumeraciÃ³n principal podremos listar las capas segÃºn la fuente, si son o no visibles y si tienen o no elementos seleccionados. El procedimiento es muy sencillo, hacer clic en el icono de la parte superior del TOC que permite acceder a alguno de los mÃ©todos de agrupaciÃ³n.

Para ver cÃ³mo instalar este nuevo plugin y su funcionamiento, os dejamos con este vÃdeo:
16:57
gvSIG Team: Towards gvSIG 2.5: Listing layers at the Table of Contents
sur Planet OSGeo

One of the most used components in a GIS is the Table of Contents, also known as TOC.

All the layers of a View are listed at the Table of Contents, and the legend with which the entities of each layer are represented is shown too. It also helps to manage the display order of the layers in the View, to define the layers that are visible, which layers are selected, it allows quick access to different tools, etc.

In gvSIG Desktop 2.4, we started improvements in the TOC with a catalog, which allows to load layers quickly and manage the favourite ones. In the new version, gvSIG 2.5, you will find a new plugin called â€œTabbed TOCâ€ with which we are continuing these improvements.

Through this new plugin we add a series of new options to the Table of Contents to list or group the layers of our View.

Besides the main list, now we can list the layers according to the source, if they are visible or not, and if they have selected elements or not. The procedure is very simple, you have to click on the icon on the top of the TOC and it allows to access to any of the grouping methods.

Here you have a video about how to install this new plugin and how it works:

Â

16:00
The People's History Map of Paris
sur Google Maps Mania

The history of the world is so often told through the stories of the rich and powerful. LibÃ©ration has decided that it wants to tell the story of Paris' workers, peasants and insurgents. They have therefore released an historical map of Popular Paris from 1830 to 1980. Paris has often been the center of popular movements and protests. From the French Revolution of 1830, through the student and

13:25

Fernando Quadro: IntroduÃ§Ã£o ao Leaflet â€“ Trilhas com GeoJSON

sur Planet OSGeo

Para adicionar uma trilha ao nosso mapa, vamos convertÃª-lo de um shapefile para GeoJSON. HÃ¡ mais de uma maneira de fazer isso â€“ vocÃª poderia usar ogr2ogr, mas optamos por usar o QGIS, pois ele nÃ£o apenas o converteria, mas tambÃ©m transformaria o sistema de coordenadas ao mesmo tempo.

1. Convertendo para GeoJSON

Com o shapefile carregado no QGIS, podemos clicar com o botÃ£o direito na camada e escolher a opÃ§Ã£o â€œExport -> Save Features Asâ€¦â€

Escolhemos o sistema de coordenadas apropriado ( EPSG:4326 â€“ WGS 84) para uso com o Leaflet e o QGIS faz a conversÃ£o enquanto salva no GeoJSON. Isso torna nossa trilha pronta para uso no Leaflet.

2. Adicionando o arquivo

O arquivo GeoJSON precisa ser adicionado ao nosso arquivo HTML como um script, mas primeiro precisamos modificÃ¡-lo adicionando um nome de variÃ¡vel:

var trail = {
"type": "FeatureCollection",
"name": "rails",
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:EPSG::3857" } },
"features": [
...

Adicionando o var trail ao inÃcio do arquivo nos permitirÃ¡ fazer referÃªncia a ele no Leaflet.

Em seguida, adicionamos o script e agora podemos adicionÃ¡-lo ao mapa:

  var trail = L.geoJSON(trail);
  trail.addTo(map);

3. Estilizando a trilha

Podemos mudar a aparÃªncia da trilha adicionando opÃ§Ãµes Ã declaraÃ§Ã£o L.geoJSON:

Â Â varÂ thetrailÂ =Â L.geoJSON(trail,Â {
Â Â Â Â Â Â color:Â '#800000',
Â Â Â Â Â Â weight:Â 3,
Â Â Â Â Â Â dashArray:Â '12Â 8Â 12',
Â Â });

Isso transforma a trilha em vermelho escuro, aumentando sua largura para 3 pixels e criando uma linha tracejada.

4. Adicionando rÃ³tulo

Ao adicionar este rÃ³tulo quando se passa o mouse sobre a trilha o mesmo Ã© apresentado na tela:

thetrail.bindTooltip('Trilha de Brumadinho')

5. Resultado

ApÃ³s nossas mudanÃ§as o resultado do nosso mapa agora Ã© esse:

6. CÃ³digo

ApÃ³s as alteraÃ§Ãµes realizadas acima, o nosso cÃ³digo ficou da seguinte forma:

<!DOCTYPEÂ html>
<head>
Â Â <linkÂ rel="stylesheet"Â href="https://unpkg.com/leaflet@1.4.0/dist/leaflet.css"
Â Â integrity="sha512-puBpdR0798OZvTTbP4A8Ix/l+A4dHDD0DGqYW6RQ+9jxkRFclaxxQb/SJAWZfWAkuyeQUytO7+7N4QKrDh+drA=="
Â Â crossorigin=""/>Â Â 
Â Â <scriptÂ src="https://unpkg.com/leaflet@1.4.0/dist/leaflet.js"
Â Â integrity="sha512-QVftwZFqvtRNi0ZyCtsznlKSWOStnDORoefr1enyq5mVL4tmKB3S/EnC3rRJcxCPavG10IcrVGSmPh6Qw5lwrg=="
Â Â crossorigin=""></script>
Â Â <scriptÂ src="rails.geojson"></script>
<style>
Â Â Â Â #mapDIV{
Â Â Â Â Â Â Â Â height:Â 700px;
Â Â Â Â Â Â Â Â width:Â 700px;
Â Â Â Â Â Â Â Â border:Â solidÂ 1pxÂ black;
Â Â Â Â }
</style>
</head>
<body>
Â Â Â Â <divÂ id='mapDIV'></div>
<script>
Â Â Â Â varÂ mapÂ =Â L.map(document.getElementById('mapDIV'),Â {
Â Â Â Â center:Â [-20.1438,Â -44.1301],
Â Â Â Â zoom:Â 15
Â Â Â Â });
Â Â Â Â varÂ basemapÂ =Â L.tileLayer('http://{s}.tile.osm.org/{z}/{x}/{y}.png',Â {
Â Â Â Â Â Â Â Â });

Â Â Â Â basemap.addTo(map);
	
Â Â Â Â varÂ earthquakeMarkerÂ =Â L.marker([-20.1438,Â -44.1301],
Â Â Â Â Â Â Â Â Â {title:Â 'JaneiroÂ 25,Â 2019Â DesastreÂ deÂ Brumadinho'});
		Â 
Â Â Â Â earthquakeMarker.bindPopup(
Â Â Â Â Â Â Â Â Â "JaneiroÂ 25,Â 2019<br>Â DesastreÂ deÂ Brumadinho");
		Â 
Â Â Â Â earthquakeMarker.addTo(map);
Â 
Â Â Â Â varÂ thetrailÂ =Â L.geoJSON(trail,Â {
Â Â Â Â Â Â Â Â color:Â '#800000',
Â Â Â Â Â Â Â Â weight:Â 3,
Â Â Â Â Â Â Â Â dashArray:Â '12Â 8Â 12',
Â Â Â Â });
	
Â Â Â Â thetrail.bindTooltip('TrilhaÂ deÂ Brumadinho');
Â Â Â Â thetrail.addTo(map);
</script>
</body>
</html>

11:10
Mapping the World's Power Plants
sur Google Maps Mania

Over 50% of electricity in the Asia-Pacific region comes from coal fueled power plants. The next biggest source of electricity is natural gas, which produces 17.9% of the region's electricity. The renewable energy power sources of solar, wind and tide only contribute 3.99% of the region's electricity. The Asia Pacific Energy Portal has released an interactive map which visualizes over 7,000

10:48
gvSIG Team: Towards gvSIG 2.5: New OSM map servers
sur Planet OSGeo
Surely most of you know the OpenStreetMap (OSM) cartography, and almost certainly you have used it in some of your projects with gvSIG Desktop. Now we have added three new servers to the great number of OSM servers that were already available in gvSIG, that we think that will be interesting for certain uses:
- OSM France. Oriented to show the OSM data with the toponymy in French and the most representative symbols of French culture (for example, bakeries are represented with the symbol of a baguette). Surely it will be useful for the growing French-speaking gvSIG Desktop users community.
- Hillshading. It shows the relief of the ground through a representation using grey tones.
- OSM B&W. In this case it shows the OSM cartography, as represented by Mapnik, but without using colours, only using grey tones.
Here you have a video where you can see these three new OSM servers:

And if you donâ€™t want to wait for the new gvSIG Desktop version to use them, you can add them manually filling in these parameters at the â€œOSMâ€ tab of the â€œAdd layerâ€ window:
- OSM France
  - Name: OSM France
  - URL: [a.tile.openstreetmap.fr]
  - Levels: 18
  - Format: png
- Hillshading
  - Name: Hillshading
  - URL: [c.tiles.wmflabs.org]
  - Levels: 18
  - Format: png
- OSM B&W
  - Name: OSM Black & White
  - URL: [tiles.wmflabs.org]
  - Levels: 18
  - Format: png

27 February 2019
20:30
Living and Dying in Texas
sur Google Maps Mania

The average Texan can expect to live until they are 78.5 years old. Of course life expectancy in the state can vary dependent on where you live and your sex and race. Life Expectancy in Texas is an interactive map which allows you to see where people can expect to live longer or shorter lives in Texas. Enter your zip-code into the map and you can view details on life expectancy in your

18:56
GIScussions: Citymapper â€“ Londonâ€™s Uber?
sur Planet OSGeo

Travel Puzzle
Last week Citymapper (one of the poster children of the UKâ€™s OpenData movement) announced the launch of their CityMapper PASS card.

Citymapper started out with a travel app based on the early releases of transport open data by UK public providers, they then launched a hopper bus service for a short while and this morphed into their shared taxi service â€œRideâ€œ. Along the way they raised an enormous amount of funding for a relatively small startup â€“ according to Crunchbase they had a $10m Series A in 2014 and a $40m Series B in 2016 with some pretty serious investors coming on board. Now they have launched their PASS which potentially can save users upwards of Â£4 per week on the cost of an Oyster Card (London Transportâ€™s contactless card). The Guardian explained the basic finances here

â€œWhile the pass will bring in revenue, it will also result in the company losing money, at least in the short term. Technically, it operates as a simple pre-paid debit card, with Citymapper paying TfL for each journey its users take until they hit the standard weekly price cap.
That means that every user who reaches the daily Tube price cap (Â£7.00 for zones one and two) at least five days in seven will result in Citymapper losing money on them that week. The companyâ€™s explicit plan to counter that loss is to expand the pass by bundling in ever more private offerings, where it has more power to negotiate prices, until it offers a bundle that covers everything from dockless bikes, through rental cars, to ridesharing services.â€
https://www.theguardian.com/uk-news/2019/feb/27/citymapper-pass-launch-london-travel-card-with-cheaper-rate-than-tfl

If PASS is going to reach a critical mass (is that 10,000, 100,000 or more users?) they could be losing Â£15-20 per user per month at which point they will burn through their cash resources pretty quickly. The last accounts that Citymapper filed are for 2017 they show cash balances of Â£12.5m after an in year loss of Â£6.3m. It looks as if Citymapper will need another investment round to support an aggressive launch of PASS and the costs of acquiring users until they find ways to make the service profitable.

Does this matter? Just after the launch was announced JA Early said

It's not ever really been clear how Citymapper was supposed to make money. So, I assume, it's been funded by people who understand the immense value of data derived from sitting at the centre of a large network that tracks the travel times and habits of millions of urbanites.
â€” J A Earley (@AlbyEarley) February 21, 2019

The only way Citymapper can make serious money is through wielding the political power it will accrue from its dominant position in the marketplace.

It will eventually turn on the consumer, regulators and the public realm to carve out a lucrative niche.
â€” J A Earley (@AlbyEarley) February 21, 2019

Or as the Guardian concluded

â€œBut the launch of the service has prompted concerns from some that the companyâ€™s end goal is to try and burn its funding to establish a large base of users that it can then wield in political battles with city authorities to gain better terms for itself. That model has brought success for companies like Uber and Airbnb, which have reshaped regulations around their needs in cities including San Francisco, New York and Paris.â€
https://www.theguardian.com/uk-news/2019/feb/27/citymapper-pass-launch-london-travel-card-with-cheaper-rate-than-tfl

Time will tell whether this pivot will work for Citymapper and their backers, Iâ€™m doubtful whether there is enough demand for this all inclusive multimodal public transport payment system. Of course Uber have shown how you can disrupt a market by throwing enough investorsâ€™ money at undercutting existing players, whether that is good in the long term for users of these services remains to be seen.

18:30
Permafrost is Becoming Permanently Lost
sur Google Maps Mania

New lakes have started to appear from nowhere on the Tibet Plateau. These new lakes are being formed from the melting of the plateau's permafrost. The world's permafrost is thawing. This is very bad news. The amount of carbon held in permafrost is four times that of the carbon already released into the atmosphere. Releasing all that compressed carbon and methane into the atmosphere will
16:32
Observing Global NO2 Emissions from Space
sur Google Maps Mania

This animated map uses data from the European Space Agencyâ€™s Sentinel-5P satellite to show NO2 emissions around the world. The Sentinel 5P satellite is dedicated to monitoring air pollution. The satellite is able to sense ultraviolet, visible, near and short-wavelength infrared to monitor the amount of ozone, methane, formaldehyde, aerosol, carbon monoxide, NO2 and SO2 in the atmosphere. This

15:42
gvSIG Team: Camino a gvSIG 2.5: Nuevos servicios de mapas de OSM
sur Planet OSGeo
Seguro que la gran mayorÃa de vosotros conocÃ©is la cartografÃa de OpenStreetMap (OSM), y con casi toda seguridad la habrÃ©is utilizado en alguno de vuestros proyectos con gvSIG Desktop. Al buen nÃºmero de servidores de OSM que ya estaban disponibles en gvSIG hemos aÃ±adido tres nuevos que consideramos que pueden ser interesantes para determinados usos:
- OSM France. Orientado a mostrar los datos de OSM con la toponimia en francÃ©s y simbologÃa mÃ¡s representativa de la cultura francesa (por ejemplo las panaderÃas ser representan con el sÃmbolo de una baguette). Seguramente serÃ¡ de utilidad para la cada vez mayor comunidad francÃ³fona de usuarios de gvSIG Desktop.
- Hillshading. Muestra el relieve del terreno mediante una representaciÃ³n del mismo utilizando tonos de gris.
- OSM B&W. En este caso muestra la cartografÃa de OSM, tal y como la representa Mapnik, pero sin uso del color, utilizando unicamente tonos de grises.
PodÃ©is ver un vÃdeo en el que se muestran estos 3 nuevos servicios de OSM:

Y si no querÃ©is esperar a la nueva versiÃ³n de gvSIG Desktop para utilizarlos, los podÃ©is aÃ±adir manualmente introduciendo estos parÃ¡metros en la pestaÃ±a de OSM de la ventana de â€œAÃ±adir capaâ€:
- OSM France
  - Nombre: OSM France
  - URL: [a.tile.openstreetmap.fr]
  - Levels: 18
  - Format: png
- Hillshading
  - Nombre: Hillshading
  - URL: [c.tiles.wmflabs.org]
  - Levels: 18
  - Format: png
- OSM B&W
  - Nombre: OSM Black & White
  - URL: [tiles.wmflabs.org]
  - Levels: 18
  - Format: png
12:24
gvSIG Team: Towards gvSIG 2.5: New geoprocess, Grid by point density
sur Planet OSGeo
In the previous post we talked about a series of geoprocesses related to criminology made together with Jaume I University (UJI). These geoprocesses can be used in different fields, not exclusively in criminology.

Now we are going to show the â€œGrid by point densityâ€ geoprocess. The main objective of this geoprocess is to perform a fast and efficient count of points contained in a grid, that also is created by the geoprocess. Here it has been raised for crimes, but it can be applied to many other things. It allows to visualize how events are distributed when there is a layer with a large accumulation of them in the same areas quickly.

Crimes in New York (150.000 features)

The input parameters are a point layer and an expression (optional) that would be a filter to run the geoprocess. For example, we could apply a filter by type of crime.

The options make reference to:
- Grid distance: At the distance from the side of each square or hexagon. In relation to the measurements of the View.
- Grid type: It can be squared or hexagonal. And in hexagonal type there are two types: Vertical or horizontal.
- Add empty grids: It doesnâ€™t add grid in areas where there are no specific elements, that is, where their count is zero.
Itâ€™s important to select the grid extension in the Analysis Region tab correctly.

The results of the geoprocess on the starting image layer returns a grid with an attribute table, where we will be able to apply a legend by intervals of values.

Here you can see the results on the complete crime layer with a shorter distance and vertical grid type.

And here applying a filter on a district.

In the attribute table you can see the total count of points within each grid, the total points involved in the initial calculation before filtering, and the percentage of those points in relation to the total.

In addition, we have taken advantage of this during the development of this geoprocess to improve and debug gvSIG to support layers with a larger number of records. One of these tests for this geoprocess was done with a layer with more than 6.7 million records and more than 10 fields.

You can now download and test the new Grid by point density geoprocess in the new distribution candidate to final version. You can download it from Tools -> Add-ons Manager, and search the â€œGeoprocess: Point density gridâ€ geoprocess. Once installed and after restarting gvSIG, it will appear at the toolbox in the â€œScripting â€“ Data Analysis â€“ Grid by density of pointsâ€ section.

If you find any error or you have any recommendation, we encourage you to write to the gvSIG mailing lists.
11:30
Fernando Quadro: IntroduÃ§Ã£o ao Leaflet â€“ Adicionando Marcador
sur Planet OSGeo
Estou começando devagar, então hoje vamos adicionar um marcador com alguns recursos extras. Já que o mapa de ontem já está centralizado no Desastre de Brumadinho, vamos adicionar um marcador lá.

1. Adicionando um Marcador

Para criar um marcador, o Leaflet usa a classe L.marker:
```
var earthquakeMarker = L.marker([-20.1438, -44.1301]);
```
Isso cria o marcador, porém precisa ser adicionado ao mapa:
```
earthquakeMarker.addTo(map);
```
E o nosso mapa fica assim:

Bom até agora, mas olhando para o mapa não nos diz nada sobre o marcador. Vamos mudar isso adicionando um título:
```
var earthquakeMarker = L.marker([-20.1438, -44.1301], 
    {title: 'Janeiro 25, 2019 Desastre de Brumadinho'});
```
Agora, quando passamos o marcador, recebemos um título:

Agora, vamos adicionar um pop-up ao marcador para exibir mais informações no evento do click. Fazemos isso vinculando um pop-up ao nosso marcador existente:
```
var earthquakeMarker = L.marker([-20.1438, -44.1301], 
    {title: 'Janeiro 25, 2019 Desastre de Brumadinho'});
earthquakeMarker.bindPopup("Janeiro 25, 2019
Desastre de Brumadinho");
earthquakeMarker.addTo(map);	
```
Quando clicamos no marcador, o pop-up é exibido.

26 February 2019
20:00
Mapping Countries by Similarity
sur Google Maps Mania

The Grand Prize winner in the World Data Visualization Prize 2019 was an interactive visualization which groups the world's countries using artificial intelligence. This interactive visualization, created by Interacta, shows the connections and similarities between different countries based on a number of different factors. The Country t-SNE map rearranges the countries of the world so that
18:14
Detroit Foreclosures on Street View
sur Google Maps Mania

One in three homes in Detroit has been foreclosed in the last 15 years. The result of all those lost homes is physically evident on the city's streets. It is also very evident when exploring the city on Google Maps Street View. GooBing Detroit uses the historical imagery function in Google Maps Street View to show how Detroit has changed over the years. By juxtaposing Street View images of the

18:01
gvSIG Team: Camino a gvSIG 2.5: Nuevo geoproceso, Rejilla por densidad de puntos
sur Planet OSGeo
Hablamos en el post anterior sobre una serie de geoprocesos relacionados con la criminologÃa realizados junto a la Universidad Jaume I (UJI). Puedes ver el vÃdeo de la ponencia aquÃ. Estos geoprocesos pueden utilizarse en diferentes campos, no ligado en exclusiva a la criminologÃa.

Le toca el turno al geoproceso de Rejilla por densidad de puntos. El objetivo principal de este geoproceso es el de realizar de una forma rÃ¡pida y eficiente un conteo de puntos contenidos en una rejilla que tambiÃ©n crea el geoproceso. En el caso planteado, delitos, pero se puede aplicar a muchas otra cosas. Esto permite visualizar de forma rÃ¡pida cÃ³mo se distribuyen los eventos cuandoÂ hay una capa con una gran acumulaciÃ³n de ellos en unas mismas zonas.

Delitos en Nueva York (150.000 entidades)

Los parÃ¡metros de entrada son una capa de puntos y una expresiÃ³n (opcional) que servirÃa de filtrado para ejecutar el geoproceso. Por ejemplo, podrÃamos aplicar un filtro por tipologÃa de delito.

Las opciones hacen referencia a:
- Distancia de rejilla: A la distancia del lado de cada cuadrado o hexÃ¡gono. En relaciÃ³n con las medidas de la Vista.
- Tipo de rejilla: PuedeÂ ser cuadricular o hexagonal. Y en hexagonal dos tipos: Vertical o horizontal.
- AÃ±adir rejillas vacÃas: No aÃ±adir rejilla en las zonas donde no hay elementos puntuales, o sea, donde su conteo es cero.
Es importante seleccionar correctamente en la pestaÃ±a de RegiÃ³n de anÃ¡lisis cual va a ser la extensiÃ³n de la rejilla.

El resultado del geoproceso sobre la capa de la imagen inicial devuelve una rejilla con una tabla de atributos a la que podemos aplicarle una leyenda por intervalo de valores.

AquÃ un resultado sobre toda la capa de delitos con otra distancia mÃ¡s pequeÃ±a y de tipo rejilla vertical.

AquÃ aplicando un filtro sobre un distrito.

En la tabla de atributos se puede ver el conteo total de puntos dentro de cada rejilla, el total de puntos implicados en el cÃ¡lculo inicial antes del filtrado, y el porcentaje de esos puntos respecto al total.

AdemÃ¡s, hemos aprovechado durante el desarrollo de este geoproceso en hacer mejoras y depurar gvSIG para soportar capas con mayor nÃºmero de registros. Una de estas pruebas para este geoproceso se realizo con una capa con mÃ¡s de 6.7millones de registros y mÃ¡s de 10 campos.

Ya puedes descargarte y probar el nuevo geoproceso de Rejilla por densidad de puntosÂ en la nueva candidata a versiÃ³n final . Puedes descargarlos de Herramientas -> Administrador de complementos y buscar por el geoproceso â€œGeoprocess: Point density gridâ€. Una vez instalado, aparecerÃ¡ junto a los geoprocesos dentro del apartado de â€œScripting â€“ AnÃ¡lisis de datos â€“ Rejilla por densidad de puntosâ€.

Si encuentras cualquier fallo o recomendaciÃ³n te animamos a escribirnos a lasÂ Listas de correo de gvSIG.

11:30

Fernando Quadro: IntroduÃ§Ã£o ao Leaflet â€“ Parte 1

sur Planet OSGeo

Prezados leitores,

Os prÃ³ximos 13 posts, serÃ£o dedicados a uma introduÃ§Ã£o ao framework Leaflet. Estarei comeÃ§ando do zero e cada postagem no blog serÃ¡ adicionado um pouco mais ao projeto. As postagens provavelmente nÃ£o serÃ£o publicadas todos os dias.

Parte 1 â€“ Configurando um Mapa Simples

Para comeÃ§ar, vamos criar um modelo, copiado diretamente dos documentos do Leaflet:

<!DOCTYPEÂ html>
<head>
Â Â <linkÂ rel="stylesheet"Â href="https://unpkg.com/leaflet@1.4.0/dist/leaflet.css"
Â Â crossorigin=""/>Â Â 
Â Â <scriptÂ src="https://unpkg.com/leaflet@1.4.0/dist/leaflet.js"
Â Â crossorigin=""></script>
Â Â <style>
Â Â Â Â Â Â #mapDIV{
Â Â Â Â Â Â Â Â Â Â height:Â 700px;
Â Â Â Â Â Â Â Â Â Â width:Â 700px;
Â Â Â Â Â Â Â Â Â Â border:Â solidÂ 1pxÂ black;
Â Â Â Â Â Â }
</style>
</head>
<body>
Â Â Â Â <divÂ id='mapDIV'>i</div>
</body>
</html>

TambÃ©m criamos um div para manter o id do mapa (mapDIV) na seÃ§Ã£o head, e adicionamos um estilo para definir o tamanho do mapa quando exibido no navegador. Este HTML irÃ¡ â€œcarregarâ€ o Leaflet, mas vocÃª nÃ£o verÃ¡ nada. Precisamos adicionar um script que crie o mapa.

<script>
Â Â Â Â Â Â varÂ mapÂ =Â L.map(document.getElementById('mapDIV'),Â {
Â Â Â Â Â Â center:Â [-20.1438,Â -44.1301],
Â Â Â Â Â Â zoom:Â 15
Â Â Â Â Â Â });
Â Â Â Â Â Â varÂ basemapÂ =Â L.tileLayer('http://{s}.tile.osm.org/{z}/{x}/{y}.png',Â {
Â Â Â Â Â Â Â Â Â Â });
Â Â Â Â Â Â Â Â Â Â basemap.addTo(map);
</script>

Este pequeno script, colocado depois da mapDiv, faz o seguinte:

Adiciona um objeto de mapa
Centraliza em uma latitude/longitude
Define o nÃvel de zoom
Adiciona o mapa base do OpenStreetMap

Se nÃ³s carregarmos o arquivo em nosso navegador, nÃ³s veremos isto:

Este mapa Ã© centrado na localizaÃ§Ã£o do desastre de Brumadinho que ocorreu no dia 25 de janeiro de 2019. Vamos movÃª-lo em um post posterior.

Esse Ã© o nosso primeiro post. A atribuiÃ§Ã£o Ã© importante e vamos adicionÃ¡-la ao mapa, junto com outras novidades no prÃ³ximo post.

Aqui estÃ¡ o arquivo HTML completo:

<!DOCTYPEÂ html>
<head>
Â Â <linkÂ rel="stylesheet"Â href="https://unpkg.com/leaflet@1.4.0/dist/leaflet.css"
Â Â crossorigin=""/>Â Â 
Â Â <scriptÂ src="https://unpkg.com/leaflet@1.4.0/dist/leaflet.js"
Â Â crossorigin=""></script>
Â Â <style>
Â Â Â Â Â Â #mapDIV{
Â Â Â Â Â Â Â Â Â Â height:Â 700px;
Â Â Â Â Â Â Â Â Â Â width:Â 700px;
Â Â Â Â Â Â Â Â Â Â border:Â solidÂ 1pxÂ black;
Â Â Â Â Â Â }
</style>
</head>
<body>
Â Â Â Â <divÂ id='mapDIV'>i</div>
<script>
Â Â Â Â Â Â varÂ mapÂ =Â L.map(document.getElementById('mapDIV'),Â {
Â Â Â Â Â Â center:Â [-20.1438,Â -44.1301],
Â Â Â Â Â Â zoom:Â 15
Â Â Â Â Â Â });
Â Â Â Â Â Â varÂ basemapÂ =Â L.tileLayer('http://{s}.tile.osm.org/{z}/{x}/{y}.png',Â {
Â Â Â Â Â Â Â Â Â Â });
Â Â Â Â Â Â Â Â Â Â basemap.addTo(map);
</script>
</body>
</html>

11:20
A Journey Through Famine in India
sur Google Maps Mania

"All this day our noses were infested and our bodyes almost infected with a most noysome smell, which after search, wee found to come from a great pitt, wherein were throwne 30 or 40 persons, men, weomen and children, old and younge confuseldy tumbled in together without order or Coveringe" - 1630, Peter Munday, Itinerarium Mundii In 1631 around 3 million people died of starvation & disease in

1:28
Martin Davis: Better/Faster ST_PointOnSurface for PostGIS
sur Planet OSGeo

And now for the final chapter in the saga of improving InteriorPoint / PointOnSurface. For those who missed the first two episodes, the series began with a new approach for the venerable JTS Geometry.interiorPoint() for polygons algorithm. Episode 2 travelled deep into the wilds of C++ with a port to GEOS. The series finale shows how this results in greatly improved performance of PostGIS ST_PointOnSurface.

The BC Voting Area dataset is a convenient test case, since it has lots of large polygons (shown here with interior points computed).
The query is about as simple as it gets:

select ST_PointOnSurface(geom) from ebc.voting_area;

Here's the query timings comparison, using the improved GEOS code and the previous implementation:

Data size Time Time
OLD Improvement Time
ST_Centroid
5,658 polygons
(2,171,676 vertices) 341 ms 4,613 ms x 13 369 ms

As expected, there is a dramatic improvement in performance. The improved ST_PointOnSurface runs 13 times faster than the old code. And it's now as fast as ST_Centroid. It's also more robust and tolerant of invalid input (although this test doesn't show it).

This should show up in PostGIS in the fall release (PostGIS 3 / GEOS 3.8).

On to the next improvement... (and also gotta update the docs and the tutorial!)

Data size	Time	Time OLD	Improvement	Time ST_Centroid
5,658 polygons (2,171,676 vertices)	341 ms	4,613 ms	x 13	369 ms

25 February 2019
20:00
The Rise in American Hate Groups
sur Google Maps Mania

Last year the number of hate groups operating in the United States reached another new record. According to the Southern Poverty Law Center there are now 1,020 hate groups in action across the country. Lat week the Southern Poverty Law Center released an updated version of its hate groups interactive map. This updated map provides users with more details, including which states have the most
18:00
Wheelchair Accessible New York
sur Google Maps Mania

The New York Times has created a map of Where the Subway Limits New Yorkers with Disabilities. The map shows all the areas of the city that are within a ten minute walk from a wheelchair accessible subway station. It also shows where the most people with problems walking live in New York. The map reveals that Manhattan is the most easily accessible area of New York for people with disabilities.

17:05
Fernando Quadro: Usando tiles do OpenStreetMap para Machine Learning
sur Planet OSGeo
O OpenStreetMap Ã© uma fonte de dados incrÃvel. O esforÃ§o coletivo de milhares de voluntÃ¡rios criou um rico conjunto de informaÃ§Ãµes que abrange quase todos os locais do planeta.

HÃ¡ um grande nÃºmero de problemas em que as informaÃ§Ãµes do mapa podem ser Ãºteis:
- Urbanismo
- Infraestrutura de transporte pÃºblico
- Campanhas de marketing
- Pontos crÃticos de crimes e trÃ¡fego
No entanto, para cada problema individual, hÃ¡ uma quantidade significativa de pensamento que precisa ser decidida sobre como transformar os dados usados â€‹â€‹para criar o mapa em recursos Ãºteis para a tarefa em questÃ£o. Para cada tarefa, Ã© preciso entender os recursos disponÃveis e escrever cÃ³digo para extrair esses recursos do banco de dados do OpenStreetMap.

Uma alternativa a essa abordagem manual de engenharia de recursos seria usar redes convolucionais nos tiles renderizados do mapa.

1. Como as redes convolucionais poderiam ser usadas?

Se houver um relacionamento forte o suficiente entre as imagens do mapa (tiles) e a variÃ¡vel de resposta, uma rede convolucional poderÃ¡ aprender os componentes visuais do mapa que sÃ£o Ãºteis para cada problema. Os designers do OpenStreetMap fizeram um Ã³timo trabalho ao garantir que a renderizaÃ§Ã£o do mapa expusesse tanta informaÃ§Ã£o quanto o sistema visual pudesse compreender. E as redes de convoluÃ§Ã£o provaram ser muito capazes de imitar o desempenho do sistema visual â€“ por isso, Ã© viÃ¡vel uma rede convolucional poder aprender quais recursos extrair das imagens â€“ algo que seria demorado programar para cada domÃnio de problema especÃfico.

2. Testando a hipÃ³tese

Para testar se redes convolucionais podem aprender recursos Ãºteis do mapa, foi escolhido um problema simples: Estimar a populaÃ§Ã£o de um determinado bloco do mapa. O censo dos EUA fornece dados sobre o nÃºmero da populaÃ§Ã£o no nÃvel do setor censitÃ¡rio, e Ã© possÃvel usar a informaÃ§Ã£o de populaÃ§Ã£o dos setores para aproximar com as informaÃ§Ãµes de populaÃ§Ã£o do mapa.

As etapas envolvidas:
- FaÃ§a o download dos dados da populaÃ§Ã£o no nÃvel do setor censitÃ¡rio do Census Bureau.
- Para um determinado nÃvel de zoom, identifique os tiles do OpenStreetMap que se cruzam com 1 ou mais setores censitÃ¡rios.
- FaÃ§a o download dos tiles de uma instÃ¢ncia local do OpenMapTiles.
- Soma a populaÃ§Ã£o dos tratos dentro de cada tile, e adicione as populaÃ§Ãµes fracionÃ¡rias para trechos que se cruzam com o tile.
Visualizando os setores censitÃ¡rios que se sobrepÃµem aos 3 tiles de exemplo

Isso nos dÃ¡:
- Entrada X : uma representaÃ§Ã£o de bitmap (RGB) do tile do OpenStreetMap
- Meta Y : uma populaÃ§Ã£o estimada do tile
Para reiterar, as Ãºnicas informaÃ§Ãµes usadas pela rede para prever a populaÃ§Ã£o sÃ£o os valores RGB dos tiles do OpenStreetMap.

Para este experimento, gerou um conjunto de dados da CalifÃ³rnia, mas o mesmo processo pode ser feito para todos os estados dos EUA.

3. Resumo

Desempenho da rede ao prever a populaÃ§Ã£o de um determinado ladrilho

No exemplo de estimativa da populaÃ§Ã£o, hÃ¡ informaÃ§Ãµes suficientes nos tiles do OpenStreetMap para superar significativamente um estimador ingÃªnuo de populaÃ§Ã£o.
Para problemas com um sinal forte o suficiente, os tiles do OpenStreetMap podem ser usados â€‹â€‹como uma fonte de dados sem a necessidade de engenharia manual de recursos.

Este post foi traduzido e adaptado do original escrito por Robert Kyle do site Towards Data Science.

15:30
Making Map Quiz Infographics
sur Google Maps Mania

Earlier this month the Berliner Morgenpost posted an infographic of 12 Berlin location using OpenStreetMap building footprint data. It then asked its readers if they could name the 12 locations based purely on these small circular maps.Â Erkennen Sie die Gegend? includes 12 small circular maps and a clue to each location. If you need a little help then the answers are given (upside down) at the

11:00
CARTO Blog: Introducing the new CARTO dashboard ðŸŽ‰
sur Planet OSGeo

The dashboard is one of the core pieces of CARTO. Itâ€™s what users see right after they login to their CARTO accounts. From here, users can manage their datasets, create map...
9:18
gvSIG Team: Towards gvSIG 2.5: Fields importer
sur Planet OSGeo

We continue with a new feature of the next gvSIG Desktop version. In this post we will show you how the new tool to import fields works. Thanks to it you can import the fields that you want from one table to another, through a field that allows to establish a relationship.

This tool allows you to optimize this type of tasks, which otherwise would have to be done by establishing a series of steps: creating a link, exporting to new layer, editing the table if we want to make changes in the configuration of fields â€¦ With the fields importer all these actions are reduced to the use of a single tool, where you can define the fields to be imported and even define how to name them once imported. This is another extremely useful novelty.

Here you have a video where how to install the plugin and how it works is shown:

24 February 2019
23:01
Australia's First Language Maps
sur Google Maps Mania

First Languages Australia is working with regional language centers across the country to build an interactive map of Australian languages. A map that uses the names and groupings favored by the speakers of each language. The Gambay - First Languages Map shows first languages on the map using colored map labels. The first languages are also listed in alphabetical order in the map sidebar. If

9:04
gvSIG Team: Camino a gvSIG 2.5: Importador de campos
sur Planet OSGeo

Seguimos con las numerosas novedades de la prÃ³xima versiÃ³n de gvSIG Desktop. En este post vamos a mostrar como funciona la nueva herramienta de importar campos. Gracias a ella podemos importar los campos que deseemos de una tabla a otra, mediante un campo que permita establecer una relaciÃ³n.

Esta herramienta permite optimizar este tipo de tareas, que de otro modo se tendrÃan que hacer estableciendo una serie de pasos: crear un enlace, exportar a nueva capa, editar la tabla si queremos realizar cambios en la configuraciÃ³n de camposâ€¦

Con el importador de campos todas estas acciones se reducen al uso de una Ãºnica herramienta, donde podemos definir los campos a importar e incluso definir el nombre con el que queremos que aparezcan una vez importados. Otra novedad extremadamente Ãºtil.

Os dejamos un vÃdeo que muestra cÃ³mo instalar el plugin y su funcionamiento:

23 February 2019
20:00
Mapping Real-Time Road Traffic
sur Google Maps Mania

This interactive map of Palo Alto shows the live status of traffic signals. The map also uses live data to show how many vehicles are waiting at different intersections and how many pedestrians are waiting to cross at each intersection. The live traffic data on the map comes from TrafficWare's streaming TidalWave API. The colored traffic approach lanes on the Traffic map show the color of the
18:00
Dissecting Planet Earth
sur Google Maps Mania

Earth Elevation provides an interesting view of the elevation of the Earth along circles of latitude. That sounds more complicated than it actually is. You can see Earth Elevation in action in the screenshot above, which shows the elevation & ocean depth around the world at 30Â° north of the Equator. This cross-section shows the relative height of the Rockies in America and the Himalayas in Asia.
22 February 2019
20:30
Searching for Slums with Machine Learning
sur Google Maps Mania

Machine learning techniques are being increasingly used to detect features in satellite and aerial imagery. Artificial intelligence and machine learning can be used to train algorithms to search for familiar patterns in aerial imagery of the Earth. The reasons for searching satellite imagery can be varied and can be for commercial, environmental or social purposes. One example of machine
18:18
The Map of Science Fiction
sur Google Maps Mania

In a parallel universe '100 Years of Sci Fi' is called '100 Years of Non-Fiction'. In a completely different parallel universe it is known as '100 Years of SYFY'. We don't live in either of those parallel universes so we shall call it by its given name. 100 Years of Sci Fi is an interactive map of science fiction novels listed on Good Reads. All the sci-fi novels on the map are organized by

15:13
gvSIG Team: Towards gvSIG 2.5: New geoprocess, Ring map
sur Planet OSGeo

In the last gvSIG Conferences we talked about a series of geoprocess created for criminology developed with Universidad Jaume I (UJI). You can see the video here (in spanish, if you have any question you can write directly to us and we will help you). This geoprocess can be used in different fields, not only in criminology.

The first geoprocess that we are going to present is the Ring Map. The objective of this geoprocess is to make easy to visualize info that is inside the layer. For example, it will show info in multipleÂ fields in a single map.

In this example, we are going to see a layer with the population on each block for different range of ages. The result of the ring map will be like in the image. Now with this graph, with a quick look, we can analyse quickly how the population is distributed in each block and in different age ranges.

This geoprocess generate a series of rings and sectors. Each ring is a reference for the same field, and each sector is for the same geometry, that is pointed with an arrow. It creates three new layers with the rings, labels and arrows. Each of them can be modified as a normal shapefile. It creates an automatic legend that can also be modified as we need them.

The parameters that we need to execute this geoprocess is, at least one layer, (with any type of geometry) that it has a field with unique values for each geometry. It needed a opened table. If you are going to use layers,Â be sure that you open previously the attributes table, if not, thisÂ table will not appear as an option. If it doesnâ€™t have an unique field, you can create it using the Field Calculator. This option has been createdÂ becouse it is posible to create diferent representations (differents table) to show them over the same vectorial layer.

The fields should be written in the order that we want them to appear. Also, we have multiple options for change the visualization of the rings. We can change sectors, gaps, size, labels..

This is a similar result from the initial image.

As always, you can see more information about this process pressing the help button.

You can test the Ring Map geoprocessÂ at the newÂ distribution candidateÂ to final version. Just go to Tools -> Addons Manager and Search for â€œGeoprocess: Ring Mapâ€.

If you find any error we encourage you to write about it at the users mailing list. It will help us to fix them.
14:45
gvSIG Team: Camino a gvSIG 2.5: Nuevo Geoproceso, Mapa de anillos
sur Planet OSGeo

Ya comentamos en las Ãºltimas jornadas de gvSIG una serie de geoprocesos relacionados con criminologÃa junto a la Universidad Jaume I (UJI). Puedes ver el video de la ponencia aquÃ. Estos geoprocesos pueden utilizarse en diferentes campos, no ligado en exclusiva a la criminologÃa.

El primer geoprocesoÂ que vamos a presentar es el de Mapa de anillos. El objetivo es el de facilitar la visualizaciÃ³n de una capa que dispone de informaciÃ³n en diferentes campos y necesitamos mejorar la visualizaciÃ³n de todos ellos para presentarlos en un mapa.

En el siguiente ejemplo, vamos a ver una capa que contiene la poblaciÃ³n en diferentes campos de la tabla de atributos, para visualizarlo generaremos un mapa de anillos que darÃ¡ como resultado algo similar a la imagen de a continuaciÃ³n. De esta forma podemos ver de un vistazo rÃ¡pido como se distribuye la poblaciÃ³n en diferentes franjas de edades sobre una zona del mapa.

El geoproceso genera una serie de anillos y sectores. Cada anillo hace referencia a un mismo campo y cada sector hace referencia a una misma entidad o geometrÃa, con una flecha que seÃ±ala la geometrÃa de la cual extrae los valores. Vemos que genera una serie de capas sobre la vista que podemos tratarlas como cualquier otra capa de gvSIG. Dispone de una leyenda que se genera de forma automÃ¡tica y de una serie de capas de puntos que sirven para colocar las etiquetas. Todas ellas son modificables para adaptarseÂ a las necesidades que tengamos.

Los parÃ¡metros necesarios para ejecutar este geoproceso es mÃnimo una capa (puede ser de cualquier tipo de geometrÃa) que tenga de forma obligatoria un campo con un valor Ãºnico que identifique cada geometrÃa. Tiene que haber una tabla abierta (si usas solo capas vectoriales asegÃºrate de abrir la tabla de atributos con antelaciÃ³n para poderla seleccionar sino no aparecerÃ¡ en el listado de tablas disponibles). Si no lo tuviera podrÃamos crearle uno desde la calculadora de campos. Este campo Ãºnico tiene el uso de que sobre una misma capa vectorial, podrÃamos tener diferentes resultados a mostrar en diferentes tablas cuyos valores podrÃan ser calculados en otros programas. El geoproceso relacionarÃ¡ esos valores por su valor Ãºnico y los mostrarÃ¡.

Los campos a mostrar deberÃ¡n ser escritos por orden en que queremos que se muestren. TambiÃ©n disponemos de muchas opciones de configuraciÃ³n para la creaciÃ³n de los anillos. Desde posiciÃ³n de los sectores, espacio entre ellos, tamaÃ±o del circulo interior, del grosor de cada sector, creaciÃ³n de etiquetas..

AquÃ puedes ver otra representaciÃ³n similar a la de la imagen inicial.

Siempre puedes ver con mÃ¡s detalle la informaciÃ³n del geoproceso presionando el botÃ³n de ayuda.

Ya puedes descargarte y probar el nuevo geoproceso de mapa de anillos en laÂ nueva candidata a versiÃ³n final . Puedes descargarlos de Herramientas -> Administrador de complementos y buscar por el geoproceso â€œGeoprocess: Ring Mapâ€

Si encuentras cualquier fallo o recomendaciÃ³n te animamos a escribirnos a las Listas de correo de gvSIG.
14:00
Paul Ramsey: Proj6 in PostGIS
sur Planet OSGeo
Map projection is a core feature of any spatial database, taking coordinates from one coordinate system and converting them to another, and PostGIS has depended on the Proj library for coordinate reprojection support for many years.

For most of those years, the Proj library has been extremely slow moving. New projection systems might be added from time to time, and some bugs fixed, but in general it was easy to ignore. How slow was development? So slow that the version number migrated into the name, and everyone just called it â€œProj4â€.

No more.

Starting a couple years ago, new developers started migrating into the project, and the pace of development picked up. Proj 5 in 2018 dramatically improved the plumbing in the difficult area of geodetic transformation, and promised to begin changing the API. Only a year later, here is Proj 6, with yet more huge infrastructural improvements, and the new API.

Some of this new work was funded via the GDALBarn project, so thanks go out to those sponsors who invested in this incredibly foundational library and GDAL maintainer Even Roualt.

For PostGIS that means we have to accomodate ourselves to the new API. Doing so not only makes it easier to track future releases, but gains us access to the fancy new plumbing in Proj.

For example, Proj 6 provides:

Late-binding coordinate operation capabilities, that takes metadata such as area of use and accuracy into accountâ€¦ This can avoid in a number of situations the past requirement of using WGS84 as a pivot system, which could cause unneeded accuracy loss.

Or, put another way: more accurate results for reprojections that involve datum shifts.

Hereâ€™s a simple example, converting from an old NAD27/NGVD29 3D coordinate with height in feet, to a new NAD83/NAVD88 coordinate with height in metres.
```
SELECT ST_Astext(
         ST_Transform(
           ST_SetSRID(geometry('POINT(-100 40 100)'),7406), 
           5500));
```
Note that the height in NGVD29 is 100 feet, if converted directly to meters, it would be 30.48 metres. The transformed point is:
```
POINT Z (-100.0004058 40.000005894 30.748549546)
```
Hey look! The elevation is slightly higher! Thatâ€™s because in addition to being run through a horizontal NAD27/NAD83 grid shift, the point has also been run through a vertical shift grid as well. The result is a more correct interpretation of the old height measurement in the new vertical system.

Astute PostGIS users will have long noted that PostGIS contains three sources of truth for coordinate references systems (CRS).

Within the spatial_ref_sys table there are columns:
- The authname, authsrid that can be used, if you have an authority database, to lookup an authsrid and get a CRS. Well, Proj 6 now ships with such a database. So thereâ€™s one source of truth.
- The srtext, a string representation of a CRS, in a standard ISO format. Thatâ€™s two sources.
- The proj4text, the old Proj string for the CRS. Until Proj 6, this was the only form of definition that the Proj library could consume, and hence the only source of truth that mattered to PostGIS. Now, itâ€™s a third source of truth.
Knowing this, when you ask PostGIS to transform to an SRID, what will it do?
- If there are non-NULL values in authname and authsrid ask Proj to return a CRS based on those entries.
- If Proj fails, and there is a non-NULL srtext ask Proj to build a CRS using that text.
- If Proj still fails, and there is a non-NULL proj4text ask Proj to build a CRS using that text.
In general, the best transforms will come by having Proj look-up the CRS in its own database, because then it can apply all the power of â€œlate bindingâ€ to ensure the best transformation for each geometry. Hence we bias in favour of Proj lookups, then the quite detailed WKT format, and finally the old Proj format.

13:10
Exploring Britain's History from Above
sur Google Maps Mania

You can now explore over 80,000 historical aerial photographs of Britain dating from 1945-2009. Cambridge Universityâ€™s Collection of Aerial Photographs contains thousands of aerial photographs captured by the Universityâ€™s Air Photography Unit since the end of World War II. There are nearly half a million aerial photos in the collection. 80,000 of them have now been digitized and can be found and

8:13
Cameron Shorter: Inspiring techies to become great writers
sur Planet OSGeo
How to attract writers into Open Source communities, have them amplify developers' written impact, reduce tech ramp-up, facilitate growth,Â while having fun improving the world.

Reading time: 8 minutesPresented at Write The Docs - Sydney [slides]
My story starts at the international conference for Free and Open Source Software for Geospatial when it was held here in Sydney, ten years ago. We wanted to build a distribution of the software to hand out to conference attendees. Back then when software was expensive to download, it was a useful handout, and it provided an attractive marketing pipeline for these free software projects.To build the first version of OSGeoLive we followed install instructions, configured applications, resolved dependencies and conflicts, asked questions on email lists, and finally, after much hard work, produced our first release. This was a very important first step as it showed that we had the commitment to follow through and deliver.
However, it also highlighted many of our failings. We had followed a fully manual install process, so when the next software releases came out, we had to start the installation process again, from scratch. It was completely unsustainable. We needed to automate the install process, and we needed projects to show us how.
But our first calls for help were embarrassingly underwhelming. You see, the perceived learning curve for packaging was considered unacceptably high and volunteers were not stepping up.
To fix this, we wrote an example install script along with clear, step-by-step instructions. We then went back to developers with the message of "if you can spend a couple of hours writing a short install script which looks like this, then we will market your application though our OSGeoLive distribution". Small effort / High Value. And it worked! 28 projects packaged their applications for our version 2 release.In following releases, we applied the same process to documentation. Our first docs were written by developers and as such were quite ... variable.Â So we created skeleton outlines for Project Overviews and Quickstarts, along with clear writing instructions. We then asked projects to write documentation in line with theses outlines. We followed up with reviews, and a publishing pipeline, to produce consistent, quality material. So by applying an outline / write / review / publish process, we were able to achieve significant efficiencies by allowing experts to focus only on the bits they do best and thus reduce contribution effort.
Translators later adopted the same formula to create multiple language variants.
Unpacking the storyOk, letâ€™s unpack this story from the perspective of technical writers. Firstly, we should acknowledge the significant efficiencies software enables. Four out of the ten richest people in the world are self made software entrepreneurs.
However, while proprietary businesses centralise captured wealth, open source software, like other creative commons works, is given away for free. This act of sharing has far reaching consequences. Tools and knowledge created can be used and built upon by everyone. This democratises knowledge, wealth and power.
So if you want to positively improve our world, supporting Open Source projects is a good place to start.
The ResearchSo what makes a successful Open Source project; one which is sustained in the long term? Research provides some answers,Â Â An analysis of over 170,000 Open Source projects to identify success factors, and a study of the success factors of episodic volunteering in Open SourceÂ both highlight the importance of:
- Clear utility,
- Lean governance,
- Clear vision and goals,
- Marketing and a quality website,
- Good user and developer documentation,
- Digestible information,
- Guided introductions,
- Simple workspaces,
- Taskâ€“finding dashboards,
- Financial backing,
- Fine scaled task granularity, making it easier for people to contribute.
And on the social side:
- Leaders who lead by doing, by putting in the hard work,
- A virtuous and supportive community,
- Attracting external contributors,
- Advocating broadly, by all involved,
- A sense of collective ownership,
- Hosting of meetups,
- Recognising all forms of contribution,
- Personal invitations for help,
- Showing appreciation.
Notice the prevalence of communication within these characteristics?Communicators Needed
Where Iâ€™m heading here is that while the Open Source story usually focuses on software developers, equally important are communicators and community builders. So for you folks who are technical writers, Open Source communities need you! Your involvement can significantly amplify a projectâ€™s impact, and by extension, your help will be:
- Making the world more egalitarian,Â
- Reducing wealth inequality,Â
- And democratising knowledge and power.Â
Bridging the tech gapIâ€™d like to touch on inflection points. As a projectâ€™s technology and user base matures, community success factors move. An early inflection point with Open Source projects happens when a project attracts external contributors. These contributors increase the size of the workforce and adds extra skills, but they lack the deep domain expertise of the core team.Â To attract contributors, projects should to reduce ramp up time; and good documentation is key. Poetically however, the documenters who are most qualified to help are typically the least technical, and face the greatest ramp up time.To help explain this problem, Iâ€™d like to introduce you to Johanna Botman. She started her working career as an english teacher, then moved into IT, website design, and is now a geospatial officer in local council. I met her at a spatial conferenceâ€™s community day when she joined other volunteers in updating our OSGeoLive documentation. It was a humbling experience for me. I saw such an accomplished person, with oodles of commitment, struggling to use our documentation tools.Johanna reviewed an early draft of this presentation and observed that ...
Some of the issues relating to getting started is about bridging the gap between developers and writers.Â Developers write code in coding tools. They collaborate, they are used to versioning and are at home with unformatted raw text and automation tools. Writers? They work on Windows machines in Word â€“ maybe in Google Docs if they are lucky. They donâ€™t know about running build scripts, running Linux variants, Github, chat programs, HTML, RST, Wikis and the variants of markup languages.
Itâ€™s one thing to work with the Open Source software, another to write about it, and a third thing to work out how to write it so that it fits in with the project. It seems as if the developers have created the writing system in a way that they are used to working, not necessarily in a way that works for writers.
And I think Johanna is right. Iâ€™ve found many users and writers who are keen to help, but feel overwhelmed, donâ€™t know where to start, donâ€™t want to burden the existing community, and so are shy to ask questions.Writers need to be sought out, welcomed, encouraged, supported and publicly appreciated if projects are to attract good documenters to help them grow.In turn, Iâ€™d encourage writers to proactively reach out to development communities. Iâ€™d expect youâ€™ll find them very welcoming and appreciative, especially if you are volunteering to tackle key documentation pain points.And together we need to help bridge the gap between writers and developers.Documentation StrategySo what should writers expect to see when joining a project. Typically, emerging projects have patchy documentation, in various stages of currency, completion, relevance, verbosity, and quality. The challenge is to consolidate it so that it becomes concise, intuitive, accurate, minimises learning and ramp up time, and sustainably maintained to match continually evolving software releases. This is non-trivial and requires good writing skills, planning, leadership, commitment and follow through to do it well.The problems are that:
- Software is complex. Itâ€™s hard to understand, and harder to explain.
- Software continually evolves, meaning documentation needs to be continually maintained.
- Projects have a range of audiences, with differing information needs, technical backgrounds, and attention spans.
It helps toÂ define the characteristics of your different communication mediums.
Raw imageÂ (inÂ draw.ioÂ format)
Your front web page and elevator pitch should be concise, highly polished and target first time visitors, while community forums are good for once off questions and can be rough around the edges.For each medium you should define your:
- Target audience,
- Document structure,
- Technical depth,
- Quality requirements, and
- Maintenance strategy.
Then aim to:
- Write timeless material to minimise maintenance.
- Only write as much as your team has capacity to maintain.
- Help techies become great writers. Provide skeleton docs and writing instructions, then review, mentor and publish.
- Work within a release cycle, which ideally synchronises with the project.Â
Itâ€™s worth noting that most of what Iâ€™m talking about here is relevant to all sorts of technical writing - not just for Open Source communities.
Getting Started?Okay, so maybe youâ€™d like to get involved and are wondering where to start? Iâ€™d suggest:
Image source
- Focus on one project instead of many, as your ramp-up time will likely be high.Â
- Acknowledge the value you bring. Use it as motivation because youâ€™ll have many challenges and the inner motivation will really help.
- Demonstrate commitment. Itâ€™s contagious.
- Ask for help, you will need it, and youâ€™ll likely be surprised how supportive people will be.
- Donâ€™t be daunted by your lack of domain knowledge. Itâ€™s actually an asset when writing to a broad audience.
- Help developers become great writers. Great impact comes from amplifying the effectiveness others.Â
- Be part of the team; help paint the vision; be inspirational.
- And most of all, have fun while you are doing it. Because believe you me, it is hugely rewarding to share the team camaraderie involved in building something that is much bigger and more impactful than you could possibly create by yourself.
21 February 2019
20:52
Martin Davis: Better/Faster Interior Point for Polygons - now in GEOS
sur Planet OSGeo
As a gentle introduction to GEOS development I took on the task of porting the recent improvements to the JTS InteriorPointArea algorithm.Â Â This is a fairly small chunk o'code, but it touches most of the aspects of GEOS development process: build chain, debugging, unit tests, and infra (source control and build farm).Â It also has the advantage that the JTS code was still hot off the keyboard and (almost) unreleased, so it was a chance to see if any cross-fertilization would blossom from working on the two projects jointly.

Skipping lightly over the details of my (somewhat painful)Â GEOS learning curve, I'm delighted to say that the code has landed in master and is basking in the green glow from the build bot badges.

And now the whole point of the exercise: how much better is the new code in GEOS?Â

It exhibits the expected improvement in robustness, since a GEOS test which actually depended on a thrownÂ TopologyExceptionÂ (due to the now-removed call toÂ Geometry::intersection()Â ) had to be modified to handle a successful return.

Most importantly, there is a dramatic improvement in performance.Â Here's some numbers from running the GEOS InteriorPointArea performance test:

Data size Time Time
OLD Improvement Time
Centroid
100 .8 ms 86 ms x 100 1 ms
1000 6 ms 144 ms x 24 12 ms
10,000 55 ms 672 ms x 12 107 ms
100,000 508 ms 6,714 ms x 13 961 ms
1,000,000 5,143 ms 73,737 ms x 14 11,162 ms

Some observations:
- The performance test uses synthetic data (sine stars).Â Real-world datasets are likely to show significantly better times ( 80x better in some cases, based on JTS timings)
- The largest improvement is for small geometries, which is nice since these are more common
- InteriorPoint is now actually faster than the Centroid computation.Â This is also good news, since users were often tempted to try and use centroids instead of interior points, despite the known issues.
Future Work
Running the identical performance test in JTS is still faster, by roughly 5x.Â This may be due to the advantages of JIT compilation and memory management.Â It may also indicate there is room for improvement by making GEOS smarter about data handling.

Data size	Time	Time OLD	Improvement	Time Centroid
100	.8 ms	86 ms	x 100	1 ms
1000	6 ms	144 ms	x 24	12 ms
10,000	55 ms	672 ms	x 12	107 ms
100,000	508 ms	6,714 ms	x 13	961 ms
1,000,000	5,143 ms	73,737 ms	x 14	11,162 ms

20:00
Satellite Remote Sensing Analytics
sur Google Maps Mania

The Earth Observing System's LandViewer application is an online GIS-assistant which provides a set of advanced tools to perform real-time remote sensing data analytics. The site allows you to access and use a constantly updated satellite imagery catalog. One of the coolest features of LandViewer is the ability to create your own time-lapse animations using satellite imagery captured over time.
18:00
The World Map of Shipping Traffic
sur Google Maps Mania

This map of global shipping density reveals the world's major shipping lanes and also the areas of the world that the major shipping companies avoid. The reasons why some areas of the world's seas and oceans don't see as much traffic as others can vary from geo-political reasons to the dangers of piracy and local sailing conditions. The live ship tracking map MarineTraffic includes an option to
16:00
The History of Settlements in Hungary
sur Google Maps Mania

Partly inspired by the New York Times' popular Map of Every Building in America the Atlo data visualization team decided to undertake a detailed examination of the street patterns of urban settlements in Hungary. In Roads, Buildings, Networks Alto looks at the different types of settlement morphology and the history of urban growth and planning in the country. Roads, Buildings, Networks

14:00
gvSIG Team: Towards gvSIG 2.5: Improvements at geoprocessing framework
sur Planet OSGeo

The gvSIG Desktop 2.5 version, that you can test with the new distribution candidate to final version, includes a series of improvements in the geoprocess framework that we explain below.Â
Visual improvements
Now when opening the geoprocessing toolbox, you can see that extra information about the layers and fields appears at the interface.

At layer type parameters, you will be able to see the layer name, the name of the View in which it is, if it has an active selection and how many entities are selected. An icon will also appear indicating the type of geometry of the layer, or if it has a selection (with a background yellow circle).

At field type parameters, you can also see information about the type of field. and in the future you will be able to see an icon identifying that field.

Integration with the new plugin to capture coordinates
Last year we released a new extension to capture coordinates more effectively in the View. At the new version, the integration with the geoprocess framework has been completed, so that the points captured with that tool will appear at the selection of the Point type parameter.

New Filter type parameter
As we have told about and as we will explain in the next posts in detail, gvSIG has a new expression generator. In the geoprocessing framework this functionality has been added, so that new geoprocesses can have a new type of parameter that is expression type.

This parameter can greatly improve the execution of a geoprocess by a filter and it is also much more optimal to use than a selection done with the â€˜Selection by attributeâ€™ tool. It can greatly improve the processing of some geoprocesses.

This parameter, according to the geoprocess, could be used for values calculation tasks, filtering, etc.

The expression type parameter is associated to each layer or table type parameter, so that several of these parameters may exist in the same geoprocess. Each time we run the expression generator we will see that this window is associated with the corresponding initial parameter. Now you can start to test all these improvements at the new distribution candidate to final version and if you find any error we encourage you to write about it at the users mailing list. It will help us to fix them.

Â

20 February 2019
20:00
Navigating the Green Book
sur Google Maps Mania

In the 1930's Victor H. Green started publishing an African-American travel guide (first published as 'The Negro Motorist Green Book' and later as 'The Negro Travelers' Green Book'). In the guides Green reviewed hotels and restaurants which welcomed Black customers during the time of Jim Crow laws and racial segregation. Back in 2013 the University of South Carolina created an interactive
18:00
Mapping the Carbon Costs of Flying
sur Google Maps Mania

Flying is one of the worst things that you can you do for the environment. Aircraft are just about the worst forms of transport in terms of the CO2 cost per passenger kilometer. The UK's Department for Transport claim that flying is responsible for at least 6.3% of the UK's CO2 emissions. Many environmentalists say that this is an underestimation. The Flight Emissions Map allows you to
16:00
Mapping the Approaching Apocalypse
sur Google Maps Mania

MagyarorszÃ¡g HÃºszezer Ã©v MÃºlva (Hungary in 20,000 Years) is a collection of four interactive maps which imagine what a post-apocalyptic Hungary might look like. I have no idea why living under the rule of Viktor OrbÃ¡n would make Hungarians think about the end of the world, but the pessimistic developers of these maps have imagined four different scenarios that could lead to the end of human

14:38
gvSIG Team: Camino a gvSIG 2.5: Mejoras en el marco de geoprocesos
sur Planet OSGeo

La versiÃ³n de gvSIG Desktop 2.5, que ya puedes testear con la nueva candidata a versiÃ³n final, trae una serie de mejoras en el marco de geoprocesos que explicamos a continuaciÃ³n.
Mejoras visuales
Ahora al abrir los geoprocesos, podremos notar que en la interfaz nos aparece informaciÃ³n extra sobre las capas y los campos que antes no tenÃamos.

En los parÃ¡metros de tipo capa, podremos ver rÃ¡pidamente el nombre de la capa, el nombre de la Vista en la que se encuentra, si tiene una selecciÃ³n activa y de cuantas entidades es esa selecciÃ³n. TambiÃ©n aparecerÃ¡ un icono que nos indica el tipo de geometrÃa de la capa o si tiene una selecciÃ³n (con un circulo amarillo de fondo).

En los parÃ¡metros de tipo campo, tambiÃ©n podremos ver informaciÃ³n sobre el tipo de campo que es y a futuro veremos un icono identificativo de dicho campo.

IntegraciÃ³n con el nuevo capturador de coordenadas
El aÃ±o pasado sacamos una nueva extensiÃ³n para capturar coordenadas de manera mÃ¡s efectiva en la Vista. Con la nueva versiÃ³n, se ha completado la integraciÃ³n con el marco de geoprocesos, por lo que los puntos capturados en la herramienta, aparecerÃ¡n en la selecciÃ³n del parÃ¡metro de tipo Punto.

Nuevo parÃ¡metro de tipo Filtro
Como hemos comentado y explicaremos en prÃ³ximos post con mÃ¡s detenimiento, gvSIG tiene un nuevo generador de expresiones. En el marco de geoprocesos hemos aÃ±adido esta funcionalidad para que nuevos geoprocesos puedan tener un nuevo tipo de parÃ¡metro que sea de tipo expresiÃ³n.

Este parÃ¡metro puede agilizar enormemente la ejecuciÃ³n de un geoproceso por un filtro y ademÃ¡s es mucho mÃ¡s optimo de utilizar que una selecciÃ³n realizada con el SelecciÃ³n por atributos, lo que puede mejorar enormemente la velocidad de algunos geoprocesos.

Este parÃ¡metro, segÃºn el geoproceso, podrÃa utilizarse para tareas de cÃ¡lculo de valores, de filtrado, etc.

El parÃ¡metro de tipo expresiÃ³n, va asociado a cada parÃ¡metro de tipo capa o tabla, por lo que en un mismo geoproceso pueden existir varios de estos parÃ¡metros. Cada vez que le demos al generador de expresiones veremos que esa ventana estÃ¡ asociada al parÃ¡metro inicial que corresponde.

Ya puedes comenzar a probar todas estas mejoras en laÂ nueva candidata a versiÃ³n final y si encuentras cualquier fallo o recomendaciÃ³n te animamos a escribirnos a las Listas de correo de gvSIG.

Â

19 February 2019
20:00
Exploring the Moon
sur Google Maps Mania

The LROC Lunar QuickMap is an interactive map of our nearest neighbor. The Lunar Reconnaissance Orbiter Camera (LROC) is a system of three cameras mounted on the Lunar Reconnaissance Orbiter, a robotic spacescraft currently orbiting the Moon. The Lunar Quickmap interactive is created from the high resolution images of the lunar surface captured by the LROC. The LROC QuickMap includes a number
18:00
The Cheapest Flight to Every City in the World
sur Google Maps Mania

Three researchers at MIT Senseable's Lab in Singapore have created an interactive map which shows the cheapest flight to every city in the world on any given date from your nearest airport. Using the Great Escape map you can search for any destination across the globe and find the cheapest flights for when you want to travel. Enter a point of departure into the Great Escape and the interactive

17:23
Just van den Broecke: Emit #6 â€“ AirSensEUR Calibration
sur Planet OSGeo
This is Emit #6, in a series of blog-posts around the Smart Emission Platform,Â an Open Source software component framework that facilitates the acquisition, processing and (OGC web-API) unlocking of spatiotemporal sensor-data, mainly for Air Quality and other environmental sensor-data like noise.

In Emit #5 â€“ Assembling and Deploying 5 AirSensEURsâ€¦, I described how , with the great help of Jan Vonk from RIVM, we placed five AirSensEURÂ (ASE) air quality stations at the RIVM reference site near the A2 Highway at Breukelen. For about 2.5 months raw data was gathered there while the RIVM station was gathering its data to be used as reference for calibration.

Now â€œcalibrationâ€ is a huge and increasingly important topic when using inexpensive sensors for measuring Air Quality. Within the Smart Emission project we have been applying Artificial Neural Networks to calibrate the gas-sensors within the Josene stations. See also the SE documentation. These sensors were so called metaloxide (MICS) sensors from SGX Sensortech Limited.

The AirSensEURs contain electrochemical sensors from AlphaSense. Several sources like RIVM, state that these sensors are more accurate (than metaloxide sensors), but at the same time need per-sensor calibration.

Within the ASE boxes the following four gas-sensors were applied:
- NO2 (Nitrogen Dioxide): the NO2-B43F, see datasheet.
- NO (Nitric Oxide): the NO-B4, see datasheet.
- O3 (Ozone): the OX_A431, see datasheet.
- CO (Carbon Monoxide): theÂ CO-A4, see datasheet.
The Gang of Four Sensors

The calibration to be applied is based on Regression Analysis. This and other calibration-methods have been investigated and evaluated for many types/brands of sensors by the EC-JRC team. Read all in thisÂ landmark articleÂ and other references there.Â

The complete timeline was as follows. Each phase will be expanded below.
1. Aug 1, 2018 â€“ Okt 9, 2018
  Raw ASE and RIVM reference data collection (Breukelen site)
2. Okt 10, 2018 â€“ Nov 2, 2018
  All ASEs deployed at their target locations
3. Nov/dec 2018
  Calibration performed by Michel Gerboles at the EC-JRC labÂ
4. Jan 2019
  Calibration formulas implemented in Smart Emission (SE) platform
5. Feb 2019
  All ASE calibrated gas-data continuously available via SE viewers/APIs
6. Feb 2019
  Analysis of the calibration (SE Python Stetl) implementation results
ad 1) The five ASE Boxes were mounted on a horizontal pole and connected to WIFI and current. As end-result all boxes were publishing their raw data to the SE InfluxDB Data Collector and were visible in the SE Grafana raw data viewer.

Configured for InfluxDB Data Push visualized via Grafana

Reference values for the gases NO,NO2 and O3 were already continuously available from the RIVM reference station via e.g. the RIVM SOS API. A CO-sensor was added to the station by RIVM. CO-data was collected manually.

ad 2) The picture below shows ASE_NL_01 (left above) through _05 clockwise at their deployment sites. ASE_03 and 04 (right below) were at a single location.

ASE_NL 01 was deployed at an RIVM site in Nijmegen. This allowed us to verify its calibration with different reference data as with which it was calibrated! See below.

ad 3)Â The calibration was performed by EC-JRC (M. Gerboles) using R and ShinyR webapp. All sources can be found in this EC-JRC GitHub repo. This process is quite intricate and a bit hard to explain in the context of a blog-post paragraph. Iâ€™ll try a summary:

Sensor values are digital readings (0..65535). This is effected by the electrical circuitry within each ASE, for optimal gain. To calculate back to mV and nA a per-sensor (brand+type) calculation is required first before applying any regression formula. A bit is explained in the image below.

The second outcome is a per-individual-sensor regression formula. This is for most sensors a linear equation. For O3 (OX_A431) the formula is polynomial, as O3 readings are influenced by NO2 concentration. Below is an example as later implemented in Python using SE Stetl ETL (see below).

The main three outcomes of the calibration are:
- the parameters for digital to nA calculation (per sensor brand+type)
- the linear (polynomial) equations for nA to concentration (ug/m3)
- the per-individual-sensor parameters (a0-a3)
Above some scatterplots made for ASE Box 3 NO2 and O3.

ad 4). Knowing all equations and their parameters from step 3 above, I attempted to integrate this in the continuous ETL within the Smart Emission Platform. Up to now the platform supported only a single sensor station type: the Intemo Jose(ne). As the platform is fed by harvesting raw data from a set of remote APIs provided by Data Collectors, it was relatively easy to add sensor(-station)-metadata and extend the Refiner ETL to apply calibration algorithms driven by that metadata.Â

So for Josene stations the existing ANN calibration would still be applied, while for ASE stations per-sensor linear equations would be performed. All parameterization was already configurable using the Device, DeviceDefs, DeviceFuncs abstractions in the SE Stetl implementation. Recently, to allow stations that already send calibrated values, I introduced the Vanilla Device starting with harvesting Luftdaten.info stations (more in a later post).

The formulaâ€™s as applied in Python SE Stetl are as follows:
```
STEP 1a - Digital to Voltage (V)
V = (Ref - RefAD) + (Digital+1) /2^16 x 2 x RefAD
```
```
STEP 1b - Voltage (V) to Ampere (I) as Ri
I = 10^9 V/(Gain x Rload)
```
```
STEP 2 - Ampere (I) to concentration (ug/m3) - Example 
I=a0+a1*NO2+a2*T
```
```
  ==> NO2Â = (I - a0 - a2 * T) / a1
a0-a2 has specific values for each NO2-B43F sensor.
```
Now that these formulas and their parameters were implemented, near-realtime values could be made visible in all SE apps (viewers) and APIs such as the SmartAppÂ and the Heron Viewer.

Within the Heron Viewer we can compare for example NO2, not only with Josene measurements, but also with official RIVM values.

Also the data is available through all SE OGC APIs, for example the SensorThings API.

ad 6) The moment of truth! How well does the SE-based SE Stetl Python calibration results fit with the original RIVM values? One of the advantages of Data Harvesting (opposed to data push) is that we can switch back in time, i.e. restart harvesting from a given date. Harvesting and continuous calibration was restarted from august 1, 2018, the start of the calibration period at the RIVM station. Using a Grafana panel that displays both RIVM and SE-calculated values we can graphically see how well the data aligns.

What we can see from the above image, is that visually the data aligns very well, here for NO2. The purple graph is the official RIVM measurement. Only station ASE NL 02 is not completely aligned.

To also have some numeric proof and a more objective comparison, I dived in scatterplot and numerical analysis in Python. Apart from scatterplots that show calculated (Y) agains RIVM ref values (X) I calculated the â€œR-squaredâ€ and â€œslopeâ€ for fitting indicator values. This was also my first serious use of Python libs like Scipy, Pandas, Seaborn and Numpy (youâ€™re never too old to become a data-scientist!).

As all SE calibrated data is also stored in InfluxDB with RIVM refdata harvested from their SOS, it was easy to fetch values for the plots/calculations..

Objectivity could be effected since station ASE NL 01 was finally deployed (okt 2018) in Nijmegen, also next to an RIVM station. So the calibration calculations from RIVM refdata in Breukelen could be compared to â€œNijmegenâ€. The implementation for making these scatterplots can be found here. Lets look at some results, mainly for NO2, as I consider this one of the most important AQ indicator gasses.

I like this image a lot as it shows an almost ideal alignment with an R2 of 0.976 and slope of almost 1. Mind: calibration was thus done at a very different site (about 80 km west) and AQ condition (highway) as the deployment (city street).Â

Above are plots for the other gasses as well. First row in Breukelen (no ref CO available in RIVM SOS), front row in Nijmegen. Only NO in Nijmegen is a bit problematic.

To close off: this last image above shows NO2 fit at the Breukelen station for all five ASE boxes. Also quite good.

What to conclude? First of all AirSensEUR is a major step forward in affordable accurate AQ sensing. We hope to expand the community.

AlphaSense NO2 electrochemical sensors appear quite accurate, but calibration requires quite some effort, plus calibration formulas apply per individual sensor. Would automatic per-sensor ANN be less time-consuming and still accurate? Something I would like to investigate.

The Smart Emission project and platform is still going strong, running within a Kubernetes Cloud maintained by Dutch Kadaster.

Next emit will discuss how I integrated data from the amazing Luftdaten.info project for the municipality of Nijmegen.

14:51
The 2019 Submarine Cable Map
sur Google Maps Mania

Drum roll please ... the 2019 Telegeography Submarine Cable Map has arrived. Every year Telegeography releases a new updated version of its map of the global network of undersea telecommunication cables. This year's map highlights the huge recent building boom in submarine cables. This boom will see in the next few years around 107 new submarine cables being laid around the world, adding over

14:13
gvSIG Team: gvSIG 2.5 RC1 disponible, primera distribuciÃ³n candidata a final
sur Planet OSGeo
Ya estÃ¡ disponible para descargar la primera distribuciÃ³n candidata a final (RC1) de la nueva versiÃ³n gvSIG 2.5.

Esta versiÃ³n puede descargarse desde el apartado de versiones en desarrollo de la web del proyecto.

Las novedades que incluye esta versiÃ³n son mÃºltiples, desde nuevas funcionalidades hasta mejoras en rendimiento y estabilidad. Muchas de ellas pueden ser consultadas ya en los diferentes post que se estÃ¡n publicando en el blog, como pueden ser:
Seguiremos publicando mÃ¡s posts sobre el resto de novedades durante las prÃ³ximas semanas.

Con la publicaciÃ³n de esta primera RC, pretendemos que la Comunidad gvSIG comience a probarla de forma masiva y que nos vayÃ¡is comunicando los errores que detectÃ©is a travÃ©s de las listas de usuarios para corregirlos.

TambiÃ©n estamos preparando en paralelo la versiÃ³n para MAC OS X, cuya versiÃ³n portable, asÃ como las versiones portables de Windows y Linux, esperamos tenerlas en los prÃ³ximos dÃas.
14:12
gvSIG Team: gvSIG 2.5 RC1 available, first release candidate to final version
sur Planet OSGeo
The first release candidate (RC1) of the new gvSIG 2.5 version is now available to download.

This version can be downloaded from the development versions section of the project website.

The novelties included in this version are multiple, from new functionalities to performance and stability improvements. Many of them can be consulted already in the different posts that are being published on the blog, such as:
We will continue publishing more posts about the rest of the novelties during the next weeks.

Publishing this first RC, we intend that the gvSIG Community start to test it in a massive way and that you send us the errors that you detect through the user mailing lists to be fixed.

We are also preparing the version for MAC OS X in parallel, and its portable version, as well as the portable versions for Windows and Linux, will be available in the coming days.

18 February 2019
20:00
Should Your Maps Talk?
sur Google Maps Mania

Back in 2014 I used the fairly new (at the time) Web Speech API to create a simple Speaking Map. That map used reverse geocoding to speak the address of a location every time someone clicked on the map. What I neglected to add to my Speaking Map was jokes. Which is where Alex wins out. Alex is a talking map which can understand a number of different spoken commands. You can ask Alex to zoom in
18:00
Earth's Light Mountains
sur Google Maps Mania

Last year Jacob Wasilkowski released an interactive map which visualized Nasaâ€™s nighttime lights data as as elevation data. In other words the Earth at Night map shows light pollution around the world in 3D as mountains of light. NASA's so called Black Marble map is made by combining the best cloud-free satellite images of every land mass area of the Earth. The result is a map which shows the
16:00
The UK Child Poverty Map
sur Google Maps Mania

In some areas of the UK over half of all children are now living in poverty. The levels of child poverty are highest in some of the UK's largest cities, particularly in London, Birmingham and Manchester. For example, in London's Bethnal Green 54.18% of children are living in poverty and in Birmingham's Ladywood neighborhood 53.06% of children are growing up in poverty. The End Child Poverty

12:33
gvSIG Team: Towards the new gvSIG 2.5 version: Calling for translators
sur Planet OSGeo

The stabilization phase of the new gvSIG 2.5 version has started, and in order to have the final version with as many languages as possible the update of the translations of the interface are being carried out too.Currently gvSIG has been translated to more than 25 languages, thank to the participation of the Community.

There are two ways of collaboration: updating any of the existing languages, as well as translating gvSIG interface to a new language in which gvSIG is not translated currently.

If you are interested in translating gvSIG interface you can contact the gvSIG Project [info@gvsig.com] and we would send the instructions to do it.

Translations that arenâ€™t finished when the final version is released will be published as a package to be loaded from the gvSIG Add-ons manager. We will inform about these updates at the gvSIG blog.

We expect your collaboration!
12:22
gvSIG Team: Hacia la nueva versiÃ³n gvSIG 2.5: Llamamiento a traductores
sur Planet OSGeo

La nueva versiÃ³n 2.5 de gvSIG Desktop ya se encuentra en fase de estabilizaciÃ³n, para lo cual se ha comenzado tambiÃ©n con la actualizaciÃ³n de las traducciones de la interfaz. El objetivo es el de tener la versiÃ³n final disponible en el mayor nÃºmero de idiomas posible.Actualmente gvSIG se encuentra traducido a mÃ¡s de 25 idiomas, gracias a la participaciÃ³n de la Comunidad.

Existen dos formas de colaboraciÃ³n, bien actualizar cualquiera de los idiomas ya existentes en versiones anteriores, o bien traducir a algÃºn idioma en el que no se encuentre traducido gvSIG actualmente.

Si estÃ¡is interesad@s en traducir la interfaz de gvSIG podÃ©is poneros en contacto con el proyecto [info@gvsig.com], y os indicaremos las instrucciones.

Las traducciones que no estÃ©n finalizadas en el momento de la publicaciÃ³n de la versiÃ³n final se publicarÃ¡n como paquetes que podrÃ¡n ser cargados directamente desde el Administrador de complementos de gvSIG. Iremos informando sobre estas actualizaciones en el blog de gvSIG.

Â¡Esperamos vuestra colaboraciÃ³n!

16 February 2019
20:00
I ðŸ’›ðŸ’—ðŸ’– Maps
sur Google Maps Mania

I saw a few Valentines Day themed maps this week. None of them were that interesting. I did end up writing about Esri's map ofÂ Britain's Most Romantic Roads but that was really only because I wanted to explore the toponym of the 168 Love Lanes on Esri's map - the original meaning of which is maybe not quite as romantic as Esri imagines (John Stow in 1598 said London's 'Love Lane' was "so called
18:00
Amazon's Lord of the Rings Map
sur Google Maps Mania

Amazon is busy creating a Lord of the Rings Prime Video series. Little is known about the television series, as of yet, but there is a Lord of Rings on Prime official Twitter account. On Wednesday that account made it's first Tweet, which was a short Tolkien quote, â€œI wisely started with a mapâ€ â€” J.R.R. Tolkien â€” The Lord of the Rings on Prime (@LOTRonPrime) Yesterday that Tweet was
15 February 2019
20:00
Do You Speak the Queen's English?
sur Google Maps Mania

The most popular interactive page on the New York Times website in 2013 was How Yâ€™all, Youse and You Guys Talk. This interactive feature asked readers to answer questions about the words they use and how they pronounce them. From the answers given to these language questions the NYT was able to create an interactive map showing where the reader was from in the United States. Now the New York
18:00
America's 2018 Oil Spills
sur Google Maps Mania

On average there were around 11 oils spills a month in the United States during 2018. The largest oil spill was in April in Superior, Wisconsin. 11 people were injured in the incident when a storage tank exploded. You can view all the 137 oil spills that occurred in the United States during 2018 on Resource Watch's interactive map. The 2018 Oil Spills MapÂ uses data from NOAA to plot the
12:30
Mapping Asia's Most Powerful Countries
sur Google Maps Mania

According to the Lowy Institute the USA is the most powerful country in Asia. I'm not sure I agree that the United States is in Asia but I'm not going to argue that it exercises a lot of influence in the continent. According to the Institute's Asia Power Index the next most powerful country in Asia is China. The Asia Power Index ranks 25 Asian countries and territories in terms of their power

12:25
gvSIG Team: Towards gvSIG 2.5: Report by point
sur Planet OSGeo

We are going to show you another novelty of the next version of gvSIG Desktop, that is called report by point. It is a configurable multilayer information button, and it is very useful to consult the information of different layers on a concrete location and visualize it in a simultaneous way.

The operation is very simple, you only have to click on a specific point on the View and a report will be shown in a new window on that point with all the attributes of all visible layers. In that report you can select and copy data to the clipboard, being able to paste them in other applications.

In addition, a new tab has been added to the layer â€œPropertiesâ€, that allows to define which fields you want to see in the report, and even you can modify the field name to be shown.

In the following video you can see how it works. Simple and extremely useful.
11:01
gvSIG Team: Camino a gvSIG 2.5: Informe por punto
sur Planet OSGeo

La novedad que os traemos hoy de la prÃ³xima versiÃ³n de gvSIG Desktop la hemos denominado informe por punto. Viene a ser un botÃ³n de informaciÃ³n multicapa y configurable. Â¡Muy Ãºtil para consultar la informaciÃ³n en un punto de distintas capas y visualizarla de forma simultanea!

El funcionamiento es muy sencillo, pulsamos en un punto determinado de la Vista y se nos mostrarÃ¡ en una nueva ventana un informe sobre ese punto con todos los atributos de todas las capas visibles. En este informe podemos seleccionar y copiar los datos al portapapeles, pudiendo asÃ luego pegarlos en otras aplicaciones.

AdemÃ¡s se ha aÃ±adido una nueva pestaÃ±a a las â€œPropiedadesâ€ de la capa que permite definir que campos queremos que se visualicen en el informe, e incluso modificar el nombre con que aparece el campo.

En el siguiente vÃdeo podÃ©is ver su funcionamiento. Sencillo y extremadamente Ãºtil.

14 February 2019
20:30
The Best Brewery Road Trip Ever
sur Google Maps Mania

If you are tired of the usual bog standard Saturday night pub crawl and you want to take on something a little more ambitious then you need Flowing Data's Brewery Road Trip. This map provides you with the shortest possible route that takes in all the best American breweries. If you undertake this mega journey then you will visit all 71 American breweries in RateBeer's list of the top 100
18:00
A Strip Map of Mars
sur Google Maps Mania

In 1675 John Ogilby published Britannia, a series of strip maps of roads in England and Wales. In 2019 the New York Times also published a strip map. Only this strip map shows the journey of a robot on Mars. On Wednesday NASA announced that the Mars Opportunity rover was no longer working. In June Opportunity went into hibernation during a dust storm on Mars. It was hoped that after the
15:40
The UK's Most Romantic Streets
sur Google Maps Mania

There are 168 Love Lanes in Great Britain. You can view them all on Esri Valentine's Day interactive map, Britain's Most Romantic Roads. The Esri map has 1,453 romantic streets in total. As well as showing the location of all 168 Love Lanes Esri's map includes a Kissing Tree Lane in Stratford-upon-Avon, a Partnership Way in Blackburn and a Heartâ€™s Delight Road in Kent. The toponym 'Love Lane'

15:19
gvSIG Team: Free course about Geographic Information Systems applied to archaeology: Certification and links to the complete course
sur Planet OSGeo
The certification of the course about Geographic Information Systems applied to archaeology is now available (this course is also available in Spanish).

This certification starts after publishing the seven modules that form the course, but it will continue open continuously, so that any user can get it at any moment when the modules are finished.

To take the course, that is free of charge, itâ€™s not necessary any registration. You only have to follow the videos of the different modules induicated at the end of this post.

In addition, if you want to get the certification of the course, that is optional, a complete exercise must be completed, which includes some of the contents shown during the course. Likewise, you must have at least 6 of the 9 existing activities correctly, which will validate the knowledge acquired during the course and will be evaluated by a tutor.

Apart from the delivery and passing exercise successfully, the certification will have a minimum cost, necessary to cover the expenses related to the evaluation and certification. This cost will be â‚¬ 25.

The certification will be issued by the gvSIG Association, and will include the Course completion certificate.

The exercise and the cartography to be used at this practical exercise can be downloaded from the following links:
- Practical exercise.
- Cartography.
In the first section of the practical exercise the steps to follow to send it are explained in detail, as well as how to make the payment.

The course is composed of the following modules:
15:11
gvSIG Team: Curso gratuito de Sistemas de InformaciÃ³n GeogrÃ¡fica aplicados a arqueologÃa: CertificaciÃ³n y enlaces al curso completo
sur Planet OSGeo
Ya estÃ¡ disponible la certificaciÃ³n del curso de Sistemas de InformaciÃ³n GeogrÃ¡fica aplicados a arqueologÃa (este curso tambiÃ©n estÃ¡ disponible en inglÃ©s).

Esta certificaciÃ³n se abre tras la publicaciÃ³n de los siete mÃ³dulos que componen el curso, pero seguirÃ¡ abierta de forma continua, por lo que cualquier usuario podrÃ¡ obtenerla en el momento en que finalice los distintos mÃ³dulos.

Para poder realizar el curso, que es gratuito, no es necesario registrarse en ningÃºn portal, solo se deben seguir los vÃdeos de los mÃ³dulos que lo forman, indicados al final de este post.

Por otro lado, si se desea obtener la certificaciÃ³n del curso, que es opcional, se deberÃ¡ completar un completo ejercicio, que incluye algunos de los contenidos impartidos durante el curso. AsÃ mismo, se deberÃ¡ tener correctamente al menos 6 de las 9 actividades existentes en dicho ejercicio, que validarÃ¡ los conocimientos adquiridos durante el curso y serÃ¡ evaluado por un tutor.

Aparte de la entrega y aprobaciÃ³n del ejercicio, la certificaciÃ³n llevarÃ¡ un coste mÃnimo, necesario para cubrir los gastos relativos a la evaluaciÃ³n y certificaciÃ³n. Este coste serÃ¡ de 25 â‚¬.

La certificaciÃ³n serÃ¡ emitida por la AsociaciÃ³n gvSIG, e incluirÃ¡ el Certificado de aprovechamiento del curso.

El ejercicio y la cartografÃa a utilizar en el mismo pueden descargarse desde los siguientes enlaces:
- Ejercicio prÃ¡ctico
- CartografÃa
En el primer apartado del ejercicio prÃ¡ctico se explica con detalle los pasos a seguir para enviar la prÃ¡ctica, asÃ como para la realizaciÃ³n del pago para poder obtener el certificado.

El curso se compone de los siguientes mÃ³dulos:

13 February 2019
20:00
The Weather Forecast for 2080
sur Google Maps Mania

In the year 2080 the climate in Washington D.C. will resemble the current climate experienced in the state of Mississippi. Portland will experience a climate similar to California's current climate. And Los Angeles will have a climate which resembles present day Las Palmas in Mexico. You can find out what kind of climate your city can expect in 2080 on the University of Maryland's new
18:05
1.4 Million New York Collisions
sur Google Maps Mania

Times Square witnessed more pedestrian injuries from motor vehicle collisions between 2012 and 2019 than any other location in New York. The most cyclists injured during that period was on Delancey Street on Manhattanâ€™s Lower East Side. You can explore more motor vehicle collision trends in New York on the Motor Vehicle Collisions Map. The Motor Vehicle Collisions Map uses New York Police

14:24
gvSIG Team: Towards gvSIG 2.5: â€œIndigenous mappingâ€ symbol library
sur Planet OSGeo

Not all the novelties of the next gvSIG Desktop version are new functionalities. We added a new symbol library called â€œIndigenous mappingâ€ that contains an interesting set of point symbols developed by â€œThe Ethnographic Mapping Labâ€ of the University of Victoria and designed by the graphic artist James Gray.

The objective of these icons is to represent the set of activities, resources and locations commonly associated with indigenous mapping projects. We hope that they are useful for you.

Its installation and use is very simple, as you can see in the following video:
14:24
gvSIG Team: Camino a gvSIG 2.5: Biblioteca de sÃmbolos â€œIndigenous mappingâ€
sur Planet OSGeo

No todas las novedades de la prÃ³xima versiÃ³n de gvSIG Desktop son nuevas funcionalidades. AÃ±adimos una nueva biblioteca de sÃmbolos denominada â€œ Indigenous mappingâ€ que contiene un interesante conjunto de sÃmbolos puntuales desarrollados por â€œThe Ethnographic Mapping Labâ€ de la Universidad de Victoria y diseÃ±ados por el artista grÃ¡fico James Gray.

El objetivo de estos iconos es representar el conjunto de actividades, recursos y localizaciones comÃºnmente asociadas a los proyectos de mapeo indÃgena. Esperamos que os resulten de utilidad.

Su instalaciÃ³n y uso es muy sencilla, como podrÃ©is comprobar en el siguiente vÃdeo:

12:51
Delhi - A City Born of Partition
sur Google Maps Mania

After the partition of India in 1947 half a million Hindu and Sikh refugees from Pakistan arrived in Delhi. The arrival of half a million extra citizens changed Delhi for ever. In fact the impact of their arrival on the city itself can be observed by comparing the map of Delhi in 1942 to the map of Delhi in 1956. Delhi - 1942 vs 1956 allows you to directly compare a street map of Delhi in 1942

12:28
Fernando Quadro: GeoCast Live: OpenStreetMap no apoio ao desastre de Brumadinho
sur Planet OSGeo

No dia 14/02 as 19h acontecerÃ¡ uma live promovida pelo Canal GeoCast (YouTube). Nesta live serÃ¡ possÃvel entender como se deu o esforÃ§o colaborativo de mapeamento da comunidade OpenStreetMap (OSM) na montagem de um mapa base prÃ© e pÃ³s desastre da barragem de rejeitos de minÃ©rio de ferro, da mineradora Vale em Brumadinho-MG, com o intuito de auxiliar no planejamento das buscas e do resgate das vÃtimas, bem como na recuperaÃ§Ã£o a longo prazo da cidade de Brumadinho.

Se vocÃª tem interesse de participar, tirar dÃºvidas, ou simplesmente entender como se deu esse esforÃ§o colaborativo, segue abaixo o link para a live:
8:28
gvSIG Team: Camino a gvSIG 2.5: Guardar y cargar un etiquetado
sur Planet OSGeo

Seguimos con mÃ¡s novedades. En este caso os traemos una pequeÃ±a funcionalidad pero muy Ãºtil. Se trata de la posibilidad de guardar una configuraciÃ³n de etiquetado y poder recuperarla para aplicarla posteriormente.

Cualquier usuario de un SIG sabe que en ocasiones puede conllevar un tiempo considerable definir las caracterÃsticas de un etiquetado; una configuraciÃ³n de etiquetado que no es recuperable para otros proyectos. Y tambiÃ©n puede ocurrir que en un mismo proyecto, a una misma capa, nos pueda interesar aplicarle distintos tipos de etiquetado.

Este tipo de necesidades se cubren con esta nueva funcionalidad que permite guardar la configuraciÃ³n del etiquetado y recuperarla siempre que lo necesitemos.

Os dejamos con una pequeÃ±o demo de su funcionamiento:
8:25
gvSIG Team: Towards gvSIG 2.5: Saving and loading labelling
sur Planet OSGeo

We continue with more novelties. In this case it is a simple functionality, but very useful. This new tool allows to save a labelling configuration, being able to recover it later to apply it.

Any GIS user knows that sometimes it can take a considerable time to define the characteristics of a labelling; a labelling configuration that canâ€™t be recovered for other projects. And sometimes we may be interested in applying different types of labelling in a same project to the same layer.

This type of needs are covered with this new functionality that allows to save labelling configuration and recovering it whenever we need it.

Here you have a short demo of this functionality:

Â
12 February 2019
22:03
Martin Davis: Better and Faster Interior Point for Polygons in JTS/GEOS
sur Planet OSGeo
A humble workhorse of geospatial processing is the ability to compute a point which is guaranteed to lie in the interior of a polygon.Â In the OGC Simple Features for SQL specification (and hence in PostGIS) this is known as ST_PointOnSurface.Â In JTS/GEOS it is called getInteriorPoint, for historical reasons [1].

Interior points for country boundaries
There are some important use cases for this capability:
- Constructing a "proxy point" for a polygon to use in drill-down spatial query.Â This has all kinds of applications:
- Cartographic rendering including:
There is a variety of ways that have been proposed to compute interior points: triangulation, sampling via random or grid points, medial axis transform, etc.Â These all involve trade-offs between location quality and performance [2].Â JTS uses an approach which optimizes performance, by using a simple scan-line algorithm:

JTS Scan-Line Interior Point Algorithm
1. Determine a Y-ordinate which is distinct to every polygon vertex Y-ordinate and close to the centre of the vertical extent
2. Draw a scan line across the polygon and determine the segments of intersection
3. Choose the interior point as the midpoint of the widest intersection segment
Locating a polygon interior point along a scan-line
The current code has been in the JTS codebase since the release of the very first version back in 2001.Â It is elegantly simple, but is quite non-optimal, since it uses the overlay intersection algorithm.Â This is overkill for the computation of the scan-line intersection segments.Â It also has a couple of serious drawbacks: slow performance, and the requirement that the input polygon be valid.Â These are not just theoretical concerns.Â They have been noticed in the user community, and have caused client projects to have to resort to awkward workarounds.Â It's even documented as a known limitation in PostGIS.
Thanks toÂ Crunchy DataÂ recognizing theÂ importance of geospatial,Â we've been able to look into fixing this.Â It turns out that a relatively simple change makes a big improvement.Â The scan-line intersections can be computed via a linear-time scan of the polygon edges.Â This works even for invalid input (except for a few pathological situations).
Interior points of invalid polygons(LH invalid polygon shows suboptimal point placement)
Best of all, it's much faster - providing performance comparable to the (less useful) centroid computation.Â The performance results speak for themselves:

Dataset # polys # points Time Prev
time Improvement
World countries 244 366,951 25 ms 686 ms x 27
Land Cover 64,090 366,951 78 ms 6.35 s x 81

This has been committed to JTS.Â It will be ported to GEOS soon, and from there should show up in PostGIS (and other downstream projects like QGIS, Shapely, GDAL, etc etc).

More Ideas

Some further improvements that could be investigated:
- Use the centroid to provide the Y-ordinate.Â This is probably better in some situations, and worse in others.Â But perhaps there's a fast way to choose the best one?
- Use multiple scan-lines (both vertical and horizontal)
- Provide better handling of short/zero-width scan-line intersections
- Support clipping the interior point to a rectangle.Â This would provide better results for cartographic labelling
[1] JTS was based on the original OGC SFS specification (version 1.1).Â The spec actually does include a method Surface.pointOnSurface.Â The reason for the different choice of name is lost to time, but possibly the reasoning was that the JTS function is more general, since it handles all types of geometry.Â (One of the design principles of JTS is Geometric Uniformity, AKA No Surprises.Â Wherever possible spatial operations are generalized to apply to all geometric types. There is almost always a sensible generalization that can be defined, and it's often quite useful.)

[1a] Also, the acronym IPA is much better than the one for PointOnSurface.

[2] Apparently Oracle has decided to provide blazingly fast performance by simply returningÂ a point on the boundary of the polygon.Â Thus proving the maxim that for every problem there is an solution which is simple, fast, and dead wrong.

Dataset	# polys	# points	Time	Prev time	Improvement
World countries	244	366,951	25 ms	686 ms	x 27
Land Cover	64,090	366,951	78 ms	6.35 s	x 81

20:30
Making Building Footprint Posters
sur Google Maps Mania

I have been inspired by Maptime's Street Patterns tool for making street pattern posters to make my own building footprint posters. Maptime's Street Patterns is a wizard for making map posters from street patterns which can be found at different locations around the world. The tool uses data from OpenStreetMap to create small circular images consisting of just the street map of your chosen
18:00
Mapping American Debt
sur Google Maps Mania

Medical debt affects many Americans. Nearly 20% of Americans have delinquent medical debt on their credit reports. Even those with health insurance in America can still be burdened with huge medical debts. In fact around 60% of those with medical debt have health insurance. The Urban Institute's Debt in America visualizes medical debt levels in every county in the USA. The map allows you to
15:30
How Green is London?
sur Google Maps Mania

The Mayor of London has released an interactive map which visualizes London's green infrastructure. The map shows where Londoner's have good or poor access to open green spaces, such as parks, gardens, trees and rivers. The tool is designed to highlight where there is more and less need for investment in London's green infrastructure. The Green Infrastructure Focus interactive map can be used

12:11
gvSIG Team: Towards gvSIG 2.5: Topology
sur Planet OSGeo

Another important novelty of the next version of gvSIG Desktop is the incorporation of a topology framework.

The topology term refers to the spatial relationships between the different entities of a GIS. These special relationships turn into a set of rules (topological rules) that we can apply to our data. The topological rules that can be applied depend mainly on the types of data that we have. There are rules that are applied to polygon layers, point layers, line layers, to the relationship between a polygon layer and a point layer, etc.

gvSIG Desktop 2.5 will have a topology framework where we have already implemented a first set of rules, but it is prepared to grow unlimitedly, allowing as many new rules to be developed as necessary.

With this topology framework, gvSIG Desktop possibilities to edit and manage cartographic information are greatly increased.

At this video you can see its interface and how it works:

Â
11:54
gvSIG Team: Camino a gvSIG 2.5: TopologÃa
sur Planet OSGeo

Otra de las mÃ¡s importantes novedades de la prÃ³xima versiÃ³n de gvSIG Desktop es la incorporaciÃ³n de un marco de topologÃa.

El tÃ©rmino topologÃa se refiere a las relaciones espaciales entre las distintas entidades de un SIG. Estas relaciones especiales se traducen en un conjunto de reglas (reglas topolÃ³gicas) que podremos aplicar sobre nuestros datos. La reglas topolÃ³gicas que se pueden aplicar dependen principalmente de los tipos de datos que dispongamos. Hay reglas que se aplican a capas de polÃgonos, otras a capas de puntos, otras a capas de lÃneas, otras a la relaciÃ³n entre una capa de polÃgonos y otra de puntos, etc.

gvSIG Desktop 2.5 traerÃ¡ un marco de topologÃa al que ya le hemos implementado un primer conjunto de reglas, pero que estÃ¡ preparado para crecer ilimitadamente, permitiendo que se desarrollen tantas nuevas reglas como sea necesario.

Con la incorporaciÃ³n de este marco de topologÃa se amplÃan enormemente las capacidades de gvSIG Desktop para editar y gestionar la informaciÃ³n cartogrÃ¡fica.

Para que veÃ¡is su interfaz y funcionamiento os dejamos con este vÃdeo:
0:49
Gary Sherman: Leaflet Day 14 - Image Overlay and Wrap-up
sur Planet OSGeo

We end our series with a somewhat trivial, though interesting addition to our map and a special offer. Leaflet allows you to add an image that spans a specified region on the map. Here we add a picture of a little lost moose to the map. In this instance, it serves no purpose other than to show we can do it. The JavaScript code needed is: var imageUrl = "/images/calf_moose.png"; bounds = thetrail.

11 February 2019
22:30
Sydney No Harbour Bridge
sur Google Maps Mania

DX Lab's Pano-scope allows you to view some of the vintage historic panoramic photographs in the New South Wales State Library Collection. The library owns historical panoramic photographs taken in Sydney and elsewhere in New South Wales dating back as early as 1876. Pano-scope is a wonderful way to explore the NSW of the late nineteenth and early twentieth century. It allows you to see how
20:00
To the Kuiper Belt & Beyond
sur Google Maps Mania

Josh Worth's If the Moon Were Only 1 Pixel is a scaled model of the Solar System. The model takes you on a 5,906,510,212 km journey from the sun out as far as Pluto. Luckily for us in this model each pixel is 3474.8 km, so we can cut down the journey time a little. If you haven't got the time to travel to Pluto today then perhaps I can interest you instead in a quick journey to Mars.Â How Far is
18:00
How to Make Street Pattern Posters
sur Google Maps Mania

Maptime Amsterdam #5: Street Patterns is a great tool for making map posters of the city street patterns which can be found at different locations around the world. The tool uses data from OpenStreetMap to create small circular images consisting of just the street map of your chosen location. You can see an example of the map images that Street Patterns outputs in my little Tokyo map above.

11:52
gvSIG Team: Towards gvSIG 2.5: Virtual fields
sur Planet OSGeo

We advance one of the (many) novelties that the next gvSIG Desktop version includes and we think that it will be very useful. This new feature is the virtual fields support (also known as calculated or generated fields).

This fields contain values â€‹â€‹that are calculated when executing a certain formula that the user has defined. And, therefore, their values â€‹â€‹are automatically updated each time there is a change that affects that formula.

For example, in the next video, we can see how a virtual field with population density based on the values â€‹â€‹of two other fields (area and population) can be calculated. When changing any of those two values â€‹â€‹- in the video we can see how the population value is modified â€“ we see how the density is calculated automatically again and it shows the new values.

Another example where the usefulness of these fields is shown is when we create a virtual field that calculates the area of â€‹â€‹the geometries. Each time we modify a geometry graphicallyâ€¦ the polygon area will be updated.

In addition, with the new and powerful formula generator that has been implemented in gvSIG Desktop 2.5 (and which we will discuss in the next post), the possibilities are practically unlimited.
10:29
gvSIG Team: Camino a gvSIG 2.5: Campos virtuales
sur Planet OSGeo

Os adelantamos una de las (muchas) novedades que trae la prÃ³xima versiÃ³n de gvSIG Desktop y que pensamos que va a resultar de muchÃsima utilidad. Se trata del soporte a campos virtuales (tambiÃ©n conocidos como campos calculados o generados).

Este tipo de campos contienen valores que se calculan al ejecutarse una determinada fÃ³rmula que hayamos definido. Y, por tanto, sus valores se actualizan automÃ¡ticamente cada vez que hay algÃºn cambio que afecta a esa fÃ³rmula.

Por ejemplo, en el siguiente vÃdeo, vemos como creamos un campo virtual que calcula la densidad de poblaciÃ³n en funciÃ³n de los valores de otros dos campos: Ã¡rea y poblaciÃ³n. Al cambiar cualquiera de esos dos valores â€“ en el vÃdeo vemos como modificamos la poblaciÃ³n â€“ observamos como de forma automÃ¡tica se calcula de nuevo la densidad y nos muestra los nuevos valores.

Otro ejemplo que os puede permitir ver la utilidad de estos campos: crear un campo virtual que calcule el Ã¡rea de las geometrÃas. Cada vez que modifiquemos grÃ¡ficamente una geometrÃaâ€¦su Ã¡rea estarÃ¡ actualizada.

AdemÃ¡s, con el nuevo y potente generador de fÃ³rmulas que se ha implementado en gvSIG Desktop 2.5 (y del que hablaremos en prÃ³ximos post), las posibilidades son prÃ¡cticamente ilimitadas.
10 February 2019
22:59
Gary Sherman: Leaflet Day 13 - Styling with a Plugin
sur Planet OSGeo

Today weâ€™ll take a look at another pluginâ€”one that allows us to interactively change they style of features on our map: Leaflet.StyleEditor. This illustrates how we can customize our map by changing styles on the fly and also serves as a starting point for even more customization. Installing and Referencing the Plugin The web page for the plugin provides information on installing it. This requires getting the css, js, and image files in the proper location, then referencing them in our HTML file:
22:00
Stefano Costa: Reproducible science per archeologi
sur Planet OSGeo
Il 20 febbraio 2019, a Padova, tengo un workshop su Reproducible science per archeologi dentro il convegno FOSS4G-IT 2019. Avete tempo fino a mercoledÃ¬ 13 febbraio per iscrivervi.
Cosa facciamo
Questo workshop guida i partecipanti nella creazione di una analisi di dati archeologici, secondo i canoni della reproducible science sempre piÃ¹ diffusi a livello internazionale e trasversale.

Utilizzando software di elaborazione ben noti come il linguaggio R e lâ€™ambiente di programmazione RStudio, partiremo da alcuni dataset e affronteremo i vari passaggi analitici che vengono trasposti sotto forma di codice: Ã¨ una procedura pensata per rendere esplicito il processo di ricerca con i suoi meccanismi di tentativi ed errori, secondo il principio della ripetibilitÃ sperimentale.

I partecipanti potranno intervenire attivamente con me nella definizione del percorso e del prodotto finale del workshop, esplorando le pratiche piÃ¹ attuali della open science archeologica diffuse a livello internazionale.

Ci colleghiamo ad altri workshop svolti negli anni scorsi negli USA da Ben Marwick e Matt Harris.
Come iscriversi
Vi potete registrare fino al 13 febbraio 2019 su questa pagina [foss4g-it2019.gfoss.it]

Per lâ€™iscrizione Ã¨ richiesto un pagamento di 10 â‚¬ che vanno a coprire i costi organizzativi dellâ€™evento â€“ non serve a pagare il sottoscritto.
Letture e riferimenti

Per partecipare servirÃ avere installato R, RStudio e se possibile anche Git:
Di seguito qualche link a letture utili per prepararsi al workshop:

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