ben-ge/ESAWorldCover: BigEarthNet Extended with Geographical and Environmental Data/Land-use/land-cover Data M. Mommert, N. Kesseli, J. Hanna, L. Scheibenreif, D. Borth, B. Demir, "ben-ge: Extending BigEarthNet with Geographical and Environmental Data", IEEE International Geoscience and Remote Sensing Symposium, Pasadena, USA, 2023. ben-ge is a multimodal dataset for Earth observation (https://github.com/HSG-AIML/ben-ge) that serves as an extension to the BigEarthNet dataset. ben-ge complements the Sentinel-1/2 data contained in BigEarthNet by providing additional data modalities: * elevation data extracted from the Copernicus Digital Elevation Model GLO-30; * land-use/land-cover data extracted from ESA Worldcover; * climate zone information extracted from Beck et al. 2018; * environmental data concurrent with the Sentinel-1/2 observations from the ERA-5 global reanalysis; * a seasonal encoding. This archive contains the land-use/land-cover data of ben-ge, which were extracted from the ESA WorldCover service. Data Land-use/land-cover map tiles matching the Sentinel-1/2 patches were extracted from ESA WorldCover (https://esa-worldcover.org). Relevant tiles were downloaded and reprojected into the coordinate frame of the corresponding Sentinel-1/2 patches. WorldCover data are available both as maps and as class fractions that are aggregated over each patch. Land-use/land-cover map data are provided in a separate geotiff file for each patch. The naming convention for these files uses the Sentinel-2 patch_id to which we append _esaworldcover.tif. Each file contains a single band with 8-bit integer values that map to land-use/land-cover definitions provided by the ESA WorldCover Product User Manual (https://esa-worldcover.s3.eu-central-1.amazonaws.com/v200/2021/docs/WorldCover_PUM_V2.0.pdf) (page 15). The file ben-ge_esaworldcover.csv contains the fractions by which each of the different classes cover the corresponding patch. This product may be useful to generate single-label or multi-label targets for different classification setups. Relevant meta data for the ben-ge dataset are compiled in the file ben-ge_meta.csv. This file resides on the root level of this archive and contains the following data for each patch: * patch_id: the Sentinel-2 patch id, which plays a central role for cross-referencing different data modalities for individual patches; * patch_id_s1: the Sentinel-1 patch id for this specific patch; * timestamp_s2: the timestamp for the Sentinel-2 observation; * timestamp_s1: the timestamp for the Sentinel-1 observation; * season_s2: the seasonal encoding (see below) for the time of the Sentinel-2 observation; * season_s1: the seasonal encoding (see below) for the time of the Sentinel-1 observation; * lon: longitude (WGS-84) of the center of the patch [degrees]; * lat: latitude (WGS-84) of the center of the patch [degrees]; * climatezone: integer value indicating the climate zone based on Beck et al. 2018 (see below for details). File and directory structure This archive contains the following directory and file structure: | |--- README (this file) |--- ben-ge_meta.csv (ben-ge meta data) |--- ben-ge_esaworldcover.csv (patch-wise ben-ge land-use/land-cover data) |--- esaworldcover/ (land-use/land-cover data) |--- S2B_MSIL2A_20170914T93030_26_83_esaworldcover.tif ... To properly conserve the file and directory structure of the ben-ge dataset, please place this archive file on the root level of the ben-ge dataset and then unpack it. Once unpacked, ben-ge/esaworldcover requires 8.7 GB of space. Other data modalities from ben-ge (as well as Sentinel-1/2 data as provided by BigEarthNet, https://bigearth.net/#downloads), may be added as required. For reference, the recommended structure for the full dataset looks as follows: | |--- ben-ge_meta.csv (ben-ge meta data) |--- ben-ge_era-5.csv (ben-ge environmental data) |--- ben-ge_esaworldcover.csv (patch-wise ben-ge land-use/land-cover data) |--- dem/ (digital elevation model data) | |--- S2A_MSIL2A_20171208T093351_3_82_dem.tif | ... |--- esaworldcover/ (land-use/land-cover data) | |--- S2B_MSIL2A_20170914T93030_26_83_esaworldcover.tif | ... |--- sentinel-1/ (Sentinel-1 SAR data) | |--- S1A_IW_GRDH_1SDV_20180219T063851_29UPV_70_43/ | |--- S1A_IW_GRDH_1SDV_20180219T063851_29UPV_70_43_labels_metadata.json (BigEarthNet label file) | |--- S1A_IW_GRDH_1SDV_20180219T063851_29UPV_70_43_VH.tif (BigEarthNet/Sentinel-1 VH polarization data) | |--- S1A_IW_GRDH_1SDV_20180219T063851_29UPV_70_43_VV.tif (BigEarthNet/Sentinel-1 VV polarization data) | ... |--- sentinel-2/ (Sentinel-2 multispectral data) | |--- S2B_MSIL2A_20170818T112109_31_83/ | |--- S2B_MSIL2A_20170818T112109_31_83_B01.tif (BigEarthNet/Sentinel-2 Band 1 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B02.tif (BigEarthNet/Sentinel-2 Band 2 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B03.tif (BigEarthNet/Sentinel-2 Band 3 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B04.tif (BigEarthNet/Sentinel-2 Band 4 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B05.tif (BigEarthNet/Sentinel-2 Band 5 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B06.tif (BigEarthNet/Sentinel-2 Band 6 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B07.tif (BigEarthNet/Sentinel-2 Band 7 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B08.tif (BigEarthNet/Sentinel-2 Band 8 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B09.tif (BigEarthNet/Sentinel-2 Band 9 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B11.tif (BigEarthNet/Sentinel-2 Band 11 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B12.tif (BigEarthNet/Sentinel-2 Band 12 data) | |--- S2B_MSIL2A_20170818T112109_31_83_B8A.tif (BigEarthNet/Sentinel-2 Band 8A data) | |--- S2B_MSIL2A_20170818T112109_31_83_labels_metadata.json (BigEarthNet label file) ... More Information For more information, please refer to https://github.com/HSG-AIML/ben-ge. Citing ben-ge If you use data contained in this archive, please cite the following paper: M. Mommert, N. Kesseli, J. Hanna, L. Scheibenreif, D. Borth, B. Demir, "ben-ge: Extending BigEarthNet with Geographical and Environmental Data", IEEE International Geoscience and Remote Sensing Symposium, Pasadena, USA, 2023.