ben-ge/DEM: BigEarthNet Extended with Geographical and Environmental Data/Elevation Data

ben-ge/DEM: BigEarthNet Extended with Geographical and Environmental Data/Elevation 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 digital elevation model (DEM) data of ben-ge, which were extracted from the Copernicus Digital Elevation Model (GLO-30). 

Data

Topographic maps are generated based on the global Copernicus Digital Elevation Model (GLO-30) (https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model). Relevant GLO-30 map tiles from the 2021 data release were downloaded through AWS (https://registry.opendata.aws/copernicus-dem/), reprojected into the coordinate frame of the corresponding Sentinel-1/2 patches and interpolated with bilinear resampling to 10 m resolution on the ground. 

Elevation 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 _dem.tif. Each file contains a single band with 16-bit integer values that refer to the elevation of that pixel over sea level.

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)
|---  dem/                         (digital elevation model data)
   |---  S2A_MSIL2A_20171208T093351_3_82_dem.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/DEM requires 17.2 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.