FOSS4G 2022 general tracks

Markus Metz

GRASS GIS developer, GDAL contributor, GIS / RS analysis, cloud and HPC processing


Sessions

08-24
12:15
5min
Connecting tribes: how we connected the GRASS GIS database natively to GeoServer
Markus Neteler, Carmen Tawalika, Marc Jansen, Markus Metz, Anika Weinmann

All of us involved in the creation and publication of large amounts of geodata are familiar with the complexities of data management. In the case of geodata created with GRASS GIS, we asked ourselves how they could be made accessible to GeoServer without duplication. To overcome the previous limitation of GRASS GIS having its own data format, we connected the tribes and let Java and C/Python communicate with each other. So the challenge was to be able to efficiently read the GRASS GIS database directly with GeoServer. And why is that? Because this directly links the analytical capabilities of GRASS GIS with the exceptional geo service & publishing capabilities of GeoServer.

Our approach is to use the existing GDAL-GRASS bridge, and add this bridge as a new extension to GeoServer. To this we add two new GRASS GIS addons (r.geoserver.style + r.geoserver.publish) to easily publish the data from a GRASS GIS session as an OGC service. The new GeoServer GRASS raster datastore allows to use GRASS raster data directly in a GeoServer instance. In this way it is now very easy to publish GRASS data as a web service via GeoServer without having to export the data from GRASS GIS to GeoTIFF or COG files. This works for both classic raster data and also for timeseries which can e.g. be inspected as a WMS Time.

Use cases & applications
Room 4
08-26
09:00
30min
The GreenUr project: creating an application in QGIS to manage the impacts of urban green spaces on human health
Markus Neteler, Marc Jansen, Markus Metz, Anika Weinmann

Globally, the population living in urban areas is increasing with a strong impact on land use patterns, particularly on the availability and use of green spaces. The impact of green spaces is beneficial to health, for example, by reducing mortality or improving mental health. These effects are also related to different ecosystem services provided by green spaces, such as regulating temperature, modifying air pollution and noise levels, and offering more opportunities for physical activity.

GreenUr is a plugin for QGIS that aims at putting together knowledge and information on the impacts of green space on health. It is developed as a prototype representing a work in progress coordinated by the World Health Organization (WHO) to provide an educational tool to introduce the relation between green spaces, health, and well-being and raise awareness of the importance of green spaces in cities globally. The tool can also be used as ‘quickscan’ for urban spatial planners that would like to orientate on possible effects of current and new green space design. The plugin has been tested with different experts and locations, and it will be downloadable via the QGIS Plugin manager from the project website.

The GreenUr tool allows the users to estimate the impacts of green spaces on health in a given population. The main questions addressed by the current version of the GreenUr prototype are the following:

  • How much green space is available for the population of a specific city?
  • Which are the pathways through which green spaces relate to health?
  • Where within a city are health-related benefits of green spaces the largest?
  • Which are hypothetically different land-use scenarios for green spaces?
  • What would be the magnitude of the change in health impacts if future green space would be changed in cities?

All calculations performed by GreenUr are based on methodologies established by social, environmental, and epidemiological studies identified by WHO. The computational backend used is GRASS GIS and other processing methods available in QGIS. The plugin is running any common operating system and offers a demo database.

Use cases & applications
Room Limonaia