We are currently working on a new workflow for the record publication reviews! 🕵️📑
Are you interested? Please try it on this test system and give us some feedback!

Published January 19, 2021 | Version 1.0
Dataset Open

European Sentinel-1 Forest Type and Tree Cover Density Maps

  • 1. ROR icon TU Wien
  • 2. Earth Observation Data Centre for Water Resources Monitoring, Vienna, Austria

Description

This dataset was generated by the TU Wien Department of Geodesy and Geoinformation.

European Sentinel-1 forest type and tree cover density maps represent first continental-scale forest layers based on Sentinel-1 C-Band Synthetic Aperture Radar (SAR) backscatter data. For the year 2017 they cover the majority of European continent with 10 m and 100 m sampling for forest type and tree cover density, respectively. The maps were derived using the method described in https://www.tandfonline.com/doi/full/10.1080/01431161.2018.1479788.

The forest type map shows the dominant forest type class (coniferous, broadleaf). Tree cover density map shows the percentage of forest canopy cover within the 100 m pixel.

Please be referred to our peer-reviewed article at https://doi.org/10.3390/rs13030337 for details and accuracy assessment accross Europe.

Dataset Record

The forest type and tree cover density maps are sampled at 10 m and 100 m pixel spacing respectively, georeferenced to the Equi7Grid and divided into square tiles of 100km extent ("T1"-tiles). With this setup, the forest maps consist of 728 tiles over the European continent, with data volumes of 3.12 GB and 378.3 MB.

The tiles' file-format is a LZW-compressed GeoTIFF holding 16-bit integer values, with tagged metadata on encoding and georeference. Compatibility with common geographic information systems as QGIS or ArcGIS, and geodata libraries as GDAL is given.

In this repository, we provide each forest map as tiles, whereas two zipped dataset-collections are available for download below.

Code Availability

For the usage of the Equi7Grid we provide data and tools via the python package available on GitHub at https://github.com/TUW-GEO/Equi7Grid. More details on the grid reference can be found in https://www.sciencedirect.com/science/article/pii/S0098300414001629.

Acknowledgements

The computational results presented have been achieved using the Vienna Scientific Cluster (VSC).

Files

ForestType.zip

Files (3.2 GiB)

Name Size
md5:55c643960a6df83a3bf268df7eb85c26
2.9 GiB Preview Download
md5:80c91540ff47366d0d3ecd06f3ec5148
360.8 MiB Preview Download

Additional details

Related works

Is referenced by
Other: 10.3390/rs13030337 (DOI)
Is supplement to
Software: 10.5281/zenodo.3515933 (DOI)
Software: https://github.com/TUW-GEO/Equi7Grid (URL)
References
Other: 10.1080/01431161.2018.1479788 (DOI)
Other: 10.1016/j.cageo.2014.07.005 (DOI)