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license: cc-by-4.0 |
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This dataset deals with the mapping of forest species using multi-modal Earth Observation data.<br> |
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It is an <b>extension of the existing dataset TreeSatAI by Ahlswede et al.</b><br> |
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While the original dataset only grants access to a single Sentinel-1 & -2 image for each patch, this new dataset compiles all available Sentinel-1 & -2 data spanning a year. |
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This integration of temporal information assists in distinguishing between different tree species. |
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Notably, we aligned the year of the Sentinel Time Series with that of the aerial patch if it was 2017 or later. |
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For preceding years, considering minimal changes in the forest and the need for sufficient temporal context, we specifically chose the year 2017. |
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Ahlswede et al. (https://essd.copernicus.org/articles/15/681/2023/) introduced the TreeSatAI Benchmark Archive, a new dataset for tree species classification in Central Europe based on multi-sensor data from aerial, |
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Sentinel-1 and Sentinel-2 1. The dataset contains labels of 20 European tree species (i.e., 15 tree genera) derived from forest administration data of the federal state of Lower Saxony, Germany. |
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The authors propose models and guidelines for the application of the latest machine learning techniques for the task of tree species classification with multi-label data. |
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Finally, they provide various benchmark experiments showcasing the information which can be derived from the different sensors including artificial neural networks and tree-based machine learning methods. |
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The Sentinel Time Series are provided for each patch in HDF format (.h5) with several datasets : |
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- **`sen-1-asc-data`** : Sentinel-1 ascending orbit backscattering coefficient data (Tx2x6x6) | Channels: VV, VH |
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- **`sen-1-asc-products`** : Sentinel-1 ascending orbit product names (T) |
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- **`sen-1-des-data`** : Sentinel-1 descending orbit backscattering coefficient data (Tx2x6x6) | Channels: VV, VH |
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- **`sen-1-des-data`** : Sentinel-1 ascending orbit product names (T) |
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- **`sen-2-data`** : Sentinel-2 Level-2 BOA reflectances (Tx10x6x6) | Channels: B02,B03,B04,B05,B06,B07,B08,B8A,B11,B12 |
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- **`sen-2-masks`** : Sentinel-2 cloud cover masks (Tx2x6x6) | Channels: snow probability, cloud probability |
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- **`sen-2-products`** : Sentinel-2 product names (T) |
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To access the data in python you can use : |
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``` |
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import h5py |
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with h5py.File(path/to/h5/file, 'r') as h5: |
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sen_1_asc_data = f['sen-1-asc-data'][:] |
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sen_1_asc_products = f['sen-1-asc-products'][:] |
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sen_1_des_data = f['sen-1-des-data'][:] |
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sen_1_des_products = f['sen-1-des-products'][:] |
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sen_2_data = f['sen-2-data'][:] |
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sen_2_products = f['sen-2-products'][:] |
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sen_2_masks = f['sen-2-masks'][:] |
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``` |
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