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GHS-BUILT (Sentinel-1)

These data contain an information layer on built-up presence as derived from Sentinel1 image collections (2016). Each scene has been processed with SML-based workflow at 20m (local UTM projection).

The final product is delivered in a mosaic (Spherical Mercator).

Download the GHS-BUILT Sentinel-1 dataset.

Product name:
GHS_BUILT_S1NODSM_GLOBE_R2018A
Projection:
Spherical Mercator (EPSG:3857)
Resolutions available:
Approximately 20m
Description:
A global map of built-up presence derived from backscattered information of Sentinel1 images. Both the GHS BUILT-UP GRID (LDS) as derived from Landsat image collections and the GlobeLand30 (GLC30) were used for training of the Symbolic Machine Learning (SML) classifier.
20m of resolution - Spherical Mercator (EPSG:3857)
Dataset name (size):
GHS_BUILT_S12016NODSM_GLOBE_R2016A_3857_20
Legend:
0 = no built-up
1 = built-up
Description:
Built-up presence for Europe derived from backscattered information of Sentinel1 images and a digital surface model (DSM). The European Settlement Map was used for training the Symbolic Machine Learning (SML) classifier.
20m of resolution - Spherical Mercator (EPSG:3857)
Dataset name (size):
GHS_BUILT_S12016_EUROPE_R2016A_3857_20
Legend:
0 = no built-up
1 = built-up