Ludwig, Antonia; Feilhauer, Hannes (2025): Hyperspectral tundra traits: 20 EnMAP-based plant functional traits of Arctic tundra communities [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.988012
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Published: 2025-12-17 • DOI registered: 2025-12-17
Abstract:
With this dataset, we provide raster data containing 20 predicted plant functional traits based on EnMAP imagery from 2022 to 2024 in the Arctic biome. The traits were predicted based on a convolutional neural network created by Cherif et al. (2023) and adapted specifically to EnMAP data by Mederer et al. (2025). We used all available EnMAP tiles during the vegetation periods from 2022 until 2024 that were obtained in the Arctic region. However, due to the targeted observation scheme of the EnMAP mission, the tiles mainly cover regions on the North American continent and Greenland. Each raster file (in .tif- format) contains 20 layers, one layer per predicted plant trait. A water mask based on NDVI < 0.1 has been applied to all scenes. For further details on model architecture the user is referred to the above mentioned publications. The data was collected in order to assess ecosystem functional diversity and classify land cover types in a trait-based framework across the Arctic biome. It can be further used for mapping purposes, including the distribution of plant functional types. The data can be paired with field spectroscopy for upscaling approaches as well as for fusion with imagery from other sensor types. For now, this dataset can be considered a preliminary version. Meanwhile, the model for trait prediction is being under further development to address the specific requirements of Arctic vegetation for trait predictions from hyperspectral data.
Keyword(s):
References:
Cherif, Eya; Feilhauer, Hannes; Berger, Katja; Dao, Phuong D; Ewald, Michael; Hank, Tobias B; He, Yuhong; Kovach, Kyle R; Lu, Bing; Townsend, Philip A; Kattenborn, Teja (2023): From spectra to plant functional traits: Transferable multi-trait models from heterogeneous and sparse data. Remote Sensing of Environment, 292, 113580, https://doi.org/10.1016/j.rse.2023.113580
Cherif, Eya; Ouaknine, Arthur; Brown, Luke A; Dao, Phuong D; Kovach, Kyle R; Lu, Bing; Mederer, Daniel; Feilhauer, Hannes; Kattenborn, Teja; Rolnick, David (preprint): GreenHyperSpectra: A multi-source hyperspectral dataset for global vegetation trait prediction. arXiv, https://doi.org/10.48550/ARXIV.2507.06806
Mederer, Daniel; Feilhauer, Hannes; Cherif, Eya; Berger, Katja; Hank, Tobias B; Kovach, Kyle R; Dao, Phuong D; Lu, Bing; Townsend, Philip A; Kattenborn, Teja (2025): Plant trait retrieval from hyperspectral data: Collective efforts in scientific data curation outperform simulated data derived from the PROSAIL model. ISPRS Open Journal of Photogrammetry and Remote Sensing, 15, 100080, https://doi.org/10.1016/j.ophoto.2024.100080
Mederer, Daniel; Kattenborn, Teja; Cherif, Eya; Guimaraes-Steinicke, Claudia; Joswig, Julia S; Schneider, Fabian D; Feilhauer, Hannes (2025): Unraveling the seasonality of functional diversity through remote sensing. Communications Earth & Environment, 6(1), 790, https://doi.org/10.1038/s43247-025-02646-x
Project(s):
Coverage:
Median Latitude: 63.930886 * Median Longitude: -114.052974 * South-bound Latitude: 54.590562 * West-bound Longitude: 78.377066 * North-bound Latitude: 74.262241 * East-bound Longitude: -21.023693
Date/Time Start: 2022-06-21T21:10:31 * Date/Time End: 2024-07-02T07:08:06
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Identification | ID | Ludwig, Antonia | |||
| 2 | LATITUDE | Latitude | Ludwig, Antonia | Geocode | ||
| 3 | LONGITUDE | Longitude | Ludwig, Antonia | Geocode | ||
| 4 | DATE/TIME | Date/Time | Ludwig, Antonia | Geocode – utc | ||
| 5 | Metadata file | Metadata | Ludwig, Antonia | |||
| 6 | Metadata file (File Size) | Metadata (Size) | Bytes | Ludwig, Antonia | ||
| 7 | Raster graphic, GeoTIFF format | GeoTIFF | Ludwig, Antonia | |||
| 8 | Raster graphic, GeoTIFF format (File Size) | GeoTIFF (Size) | Bytes | Ludwig, Antonia |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0) (License comes into effect after moratorium ends)
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
150 data points