BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.staging.osgeo.org//foss4g-2022//speaker//JB8MU3 BEGIN:VTIMEZONE TZID:CET BEGIN:STANDARD DTSTART:20001029T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-2022-EFDUYY@talks.staging.osgeo.org DTSTART;TZID=CET:20220824T121500 DTEND;TZID=CET:20220824T122000 DESCRIPTION:All of us involved in the creation and publication of large amo unts of geodata are familiar with the complexities of data management. In the case of geodata created with GRASS GIS\, we asked ourselves how they c ould 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 direct ly with GeoServer. And why is that? Because this directly links the analyt ical capabilities of GRASS GIS with the exceptional geo service & publishi ng capabilities of GeoServer.\n\nOur approach is to use the existing GDAL- GRASS bridge\, and add this bridge as a new extension to GeoServer. To thi s 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. T he new GeoServer GRASS raster datastore allows to use GRASS raster data di rectly 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 da ta from GRASS GIS to GeoTIFF or COG files. This works for both classic ras ter data and also for timeseries which can e.g. be inspected as a WMS Time . DTSTAMP:20260403T233306Z LOCATION:Room 4 SUMMARY:Connecting tribes: how we connected the GRASS GIS database natively to GeoServer - Markus Neteler\, Carmen Tawalika\, Marc Jansen\, Markus Me tz\, Anika Weinmann URL:https://talks.staging.osgeo.org/foss4g-2022/talk/EFDUYY/ END:VEVENT BEGIN:VEVENT UID:pretalx-foss4g-2022-TD3HNC@talks.staging.osgeo.org DTSTART;TZID=CET:20220824T151500 DTEND;TZID=CET:20220824T154500 DESCRIPTION:„Hello again\, my name is actinia. Still new to OSGeo and a C ommunity Project since 2019\, you might have heard about me already. In sh ort I am a REST API on top of GRASS GIS to allow location\, mapset and geo data management and visualization as well as execution of the many GRASS G IS modules and addons. Processing with other tools like GDAL and snappy is supported as well. I can be installed in a cloud environment\, helping to prepare\, analyse and provide a large amount of geoinformation. Besides t hese facts about me there is also a lot to tell about what happened last y ear! Besides vector upload\, citable DOI\, QGIS and python client implemen tations and more\, I can be a Spatio Temporal Asset Catalog myself with th e actinia-stac-plugin\, am able to use data registered in a STAC for proce ssing and after processing register the resulting data. With the ongoing d evelopment of the openeo-grassgis-driver\, you can use this new functional ity either in my native language or via openEO API. To learn about the det ails\, come on over!“ DTSTAMP:20260403T233306Z LOCATION:Room Onice SUMMARY:News from actinia - let's STAC! - Markus Neteler\, Carmen Tawalika\ , Jorge Herrera\, Anika Weinmann URL:https://talks.staging.osgeo.org/foss4g-2022/talk/TD3HNC/ END:VEVENT BEGIN:VEVENT UID:pretalx-foss4g-2022-RU7PYN@talks.staging.osgeo.org DTSTART;TZID=CET:20220825T090000 DTEND;TZID=CET:20220825T093000 DESCRIPTION:The new GRASS GIS version 8.2 is a special edition including al l new features developed during Google Summer of Code 2021. One of the enh ancements is the parallelization of several raster modules by means of Ope nMP\, an implementation of multithreading to speed up massive data process ing. Another exciting new feature is much improved\, the Jupyter notebook support. Here\, a new python package (grass.jupyter) is available which al lows to interactively visualise maps and time series given the integration with [folium](https://github.com/python-visualization/folium). \nThe grap hical user interface in version 8.0 introduced faster and more streamlined startup without a need for a welcome screen. For even more convenience\, version 8.2 adds an experimental single window layout with familiar look-a nd-feel.\nRelated to raster data\, a new metadata class called semantic la bels can now be added to raster maps. Examples of semantic labels are aeri al or satellite spectral bands\, dataset names in remote sensing products (ndvi\, evi\, lst\, etc)\, or any custom names.\nAt community level\, we h ave developed a student grant program and\, thanks to the move to GitHub\, we have welcomed numerous new contributors. DTSTAMP:20260403T233306Z LOCATION:Room Verde SUMMARY:State of GRASS GIS - Anna Petrasova\, Vaclav Petras\, Veronica Andr eo\, Markus Neteler URL:https://talks.staging.osgeo.org/foss4g-2022/talk/RU7PYN/ END:VEVENT BEGIN:VEVENT UID:pretalx-foss4g-2022-PCD8VQ@talks.staging.osgeo.org DTSTART;TZID=CET:20220826T090000 DTEND;TZID=CET:20220826T093000 DESCRIPTION:Globally\, the population living in urban areas is increasing w ith a strong impact on land use patterns\, particularly on the availabilit y and use of green spaces. The impact of green spaces is beneficial to hea lth\, for example\, by reducing mortality or improving mental health. Thes e effects are also related to different ecosystem services provided by gre en spaces\, such as regulating temperature\, modifying air pollution and n oise levels\, and offering more opportunities for physical activity.\n\nGr eenUr is a plugin for QGIS that aims at putting together knowledge and inf ormation on the impacts of green space on health. It is developed as a pro totype representing a work in progress coordinated by the World Health Org anization (WHO) to provide an educational tool to introduce the relation b etween green spaces\, health\, and well-being and raise awareness of the i mportance of green spaces in cities globally. The tool can also be used as ‘quickscan’ for urban spatial planners that would like to orientate o n possible effects of current and new green space design. The plugin has b een tested with different experts and locations\, and it will be downloada ble via the QGIS Plugin manager from the project website.\n\nThe GreenUr t ool 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:\n\n- How much green space is ava ilable for the population of a specific city?\n- Which are the pathways th rough which green spaces relate to health?\n- Where within a city are heal th-related benefits of green spaces the largest?\n- Which are hypothetical ly different land-use scenarios for green spaces?\n- What would be the mag nitude of the change in health impacts if future green space would be chan ged in cities?\n\nAll calculations performed by GreenUr are based on metho dologies established by social\, environmental\, and epidemiological studi es identified by WHO. The computational backend used is GRASS GIS and othe r processing methods available in QGIS. The plugin is running any common o perating system and offers a demo database. DTSTAMP:20260403T233306Z LOCATION:Room Limonaia SUMMARY:The GreenUr project: creating an application in QGIS to manage the impacts of urban green spaces on human health - Markus Neteler\, Marc Jans en\, Markus Metz\, Anika Weinmann URL:https://talks.staging.osgeo.org/foss4g-2022/talk/PCD8VQ/ END:VEVENT END:VCALENDAR