| _version_ | 1867169159712866304 |
|---|---|
| author | Muro, Javier |
| author_facet | Muro, Javier |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | This geospatial dataset provides an estimation of plant species richness in grasslands across Germany for 2021. Each pixel covers an area of 10 by 10 m and represents the estimated number of herbaceous species per 16m2. It is derived using Sentinel-2 time series from April to October 2021, and a multilayer perceptron model recalibrted following Muro et al. (2022). Two raster files are provided. In the first version the model has been applied to all pixels of Germany, weather grasslands or not, so that users can mask it to their own grassland map. In the second version, the model has been applied only to pixels that are within the feature space of the training dataset, limiting the analysis to (most) grasslands in Germany. Values range between 1 and 70 species per 16m2. The estimated accuracy for these areas has a relative root squared error of 0.28 and a root mean squared error of ±8 species |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_967052 |
| institution | PANGAEA |
| language | en |
| publishDate | 2025 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Plant species richness across grasslands in Germany Muro, Javier Agriculture; Biodiversity; Germany-Sentinel-2_2017-2021; Raster graphic, GeoTIFF format; Raster graphic, GeoTIFF format (File Size); Raster graphic, GeoTIFF format (MD5 Hash); remote sensing; Satellite imagery; SATI This geospatial dataset provides an estimation of plant species richness in grasslands across Germany for 2021. Each pixel covers an area of 10 by 10 m and represents the estimated number of herbaceous species per 16m2. It is derived using Sentinel-2 time series from April to October 2021, and a multilayer perceptron model recalibrted following Muro et al. (2022). Two raster files are provided. In the first version the model has been applied to all pixels of Germany, weather grasslands or not, so that users can mask it to their own grassland map. In the second version, the model has been applied only to pixels that are within the feature space of the training dataset, limiting the analysis to (most) grasslands in Germany. Values range between 1 and 70 species per 16m2. The estimated accuracy for these areas has a relative root squared error of 0.28 and a root mean squared error of ±8 species |
| title | Plant species richness across grasslands in Germany |
| topic | Agriculture; Biodiversity; Germany-Sentinel-2_2017-2021; Raster graphic, GeoTIFF format; Raster graphic, GeoTIFF format (File Size); Raster graphic, GeoTIFF format (MD5 Hash); remote sensing; Satellite imagery; SATI |
| url | https://doi.org/10.1594/PANGAEA.967052 |