About
OSM Landuse Landcover is a WebGIS application to explore the OpenStreetMap database specifically in terms of landuse and landcover information.
Land use tags were predicted when absent using belows (Schultz et al. 2020 in prep, Schultz et al. 2017) method. This was first addressed for Germany (2017) and now (2020) - with the improved methods - for all EU countries.
Currently the map is still under development.
Info
- Project lead - Alexander Zipf, Michael Schultz
- Website - Michael Auer
- Cartographic styling of landuse/landcover overlay - Michael Auer, Janek Voss
- Data of landuse/landcover overlay by OpenStreetMap contibutors, under ODbL.
Missing OSM data (gaps) were filled for Europe (ongoing) using data derived from Sentinel-2 10m RGB imagery provided through Daniel Weill of Food and Agriculture Organization (FAO) and Deep Learning Methods developed by Michael Schultz, Hao Li and Zhaoyan Wu - Geoserver WMS & MapProxy tilecache maintanance - Michael Auer (HeiGIT gGmbH)
- PostgreSQL/PostGIS Database with OpenStreetMap Data - Enrico Steiger, Maxim Rylov, Johannes Lauer, Markus Götz, Michael Auer
- Background map - © OpenStreetMap contributors under CC BY-SA 2.0
- Place Search - powered by Nominatim
OSM keys used for classification
Classification of the landuse/landcover classes are similar to the classification level 2 of the CORINE Landcover classes.
The following OSM keys were used to form the respective class:
residential, garages
1.2. Industrial, commercial and transport unitsrailway, industrial, commercial, retail, harbour, port, lock, marina
1.3. Mine, dump and construction sitesquarry, construction, landfill, brownfield
1.4. Artificial, non-agricultural vegetated areasstadium, recreation_ground, golf_course, sports_center, playground
pitch, village_green, allotments, cemetery, park, zoo, track, garden, raceway
greenhouse_horticulture, greenhouse, farmland, farm, farmyard
2.2. Permanent Cropsvineyard, orchard
2.3. Pasturesmeadow
3.1. Forestsforest, wood
3.2. Shrub and/or herbaceous vegetation associationsgrass, greenfield, scrub, heath, grassland
3.3. Open spaces with little or no vegetationcliff, fell, sand, scree, beach, mud, glacier, rock
4.1. Inland wetlandsmarsh, wetland
4.2. Coastal wetlandssalt_pond, tidal
5. Water bodieswater, riverbank, reservoir, basin, dock, canal, pond
Acknowledgements
This work is supported by 
.
Terms of use
Overlay tiles of "OSM Landuse Landcover" can be used freely and without charge by any individuals through this website.
If you intend to use tiles or statistics from "OSM Landuse Landcover" services in your own applications please contact us.
Commercial usage of the services provided by "OSM Landuse Landcover" does need approval!
OpenStreetMap data is available under the Open Database License.
Related Project & Literature
- LandSense: A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring
- Schultz, M., Voss, J., Auer, M., Carter, S., & Zipf, A. (2017). Open land cover from OpenStreetMap and remote sensing. International Journal of Applied Earth Observation and Geoinformation, 63, 206–213. https://doi.org/10.1016/j.jag.2017.07.014
- Voß, J., Auer, M., Schultz, M. & Zipf, A. (2017): Einsatz von OpenStreetMap Daten zur Erstellung von Landnutzungsprodukten am Beispiel von OSM Landuse Landcover. Symposium für Angewandte Geoinformatik AGIT 2017. Salzburg
Contact
GIScience Research Group
Institute of Geography
Heidelberg University, Germany
http://www.geog.uni-heidelberg.de/giscience.html
Email:
zipf[at]uni-heidelberg.de
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