| hasData_Center_Short_Name |
- Deutsches GeoForschungsZentrum GFZ
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| hasDataset_Online_Resource |
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| hasDataset_Release_Date |
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| hasDataset_Title |
- Berlin-Urban-Gradient dataset 2009 - An EnMAP Preparatory Flight Campaign (Datasets)
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| hasEntry_ID |
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| hasKeyword |
- EnMAP
- HyMap
- classification
- hyperspectral
- imaging spectrometry
- multi-scale
- regression
- support vector machines
- unmixing
- urban land cover
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| hasSummary |
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Berlin-Urban-Gradient is a ready-to-use imaging spectrometry dataset for multi-scale unmixing and hard classification analyses in urban environments. The dataset comprises two airborne HyMap scenes at 3.6 and 9 m resolution, a simulated spaceborne EnMAP scene at 30 m resolution, an im-age endmember spectral library and detailed land cover reference information. All images are pro-vided as geocoded reflectance products and cover the same subset along Berlin’s urban-rural gradient. The variety of land cover and land use patterns captured make the dataset an ideal play-ground for testing the transfer of methods and research approaches at multiple spatial scales.
Version HIstory:
This version of the Berlin-Urban-Gradient-Dataset was updated to account for errors in the spatial referencing. The following files were updated:
Folder “BerlinUrbGrad2009_01_image_products\01_image_products”
Replacement of header files of the four image products: (1) EnMAP01_Berlin_Urban_Gradient_2009.hdr, (2) EnMAP02_Berlin_Urban_Gradient_2009.hdr, (3) HyMap01_Berlin_Urban_Gradient_2009.hdr, (4) HyMap02_Berlin_Urban_Gradient_2009.hdr.
Folder “BerlinUrbGrad2009_02_additional_data\02_additional_data\land_cover”:
Replacement of header files of the two reference land cover images (Land-Cov_Layer_Level1_Berlin_Urban_Gradient_2009.hdr, Lan d-Cov_Layer_Level2_Berlin_Urban_Gradient_2009.hdr).
Replacement of the shapefile (incl. extensions) representing the references polygons (LandCov_Vec_polygons_Berlin_Urban_Gradient_2009.shp, *.dbf, *.prj, *.sbn, *.sbx, *.shp.xml, *.shx).
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| GCMD Sciencekeywords describing the dataset. Click on Keyword to find similar datasets | |
