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CropClimateX

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satellite-imagery
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ajstewart drnhhl commited on
Commit
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·
1 Parent(s): bb182de

Drought Indices (#5)

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- Update README.md (615bfd4e1ed98cca05ec226b860282ad939373e9)
- Upload data_table.png (55ba6efc9237e441995969837e29074a35713adf)
- Upload folder using huggingface_hub (731554a715f8792192651e01349434186c6f6b57)


Co-authored-by: A <drnhhl@users.noreply.huggingface.co>

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  2. drought_indices/drought_indices_01003_0-9.zarr.tar +3 -0
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README.md CHANGED
@@ -33,6 +33,7 @@ Adrian Höhl, Stella Ofori-Ampofo, Miguel-Ángel Fernández-Torres, Rıdvan Sali
33
  The database includes 15,500 small data cubes (i.e., minicubes), each with a spatial coverage of 12x12km, spanning 1527 counties in the US. The minicubes comprise data from multiple sensors (Sentinel-1/2, Landsat-8, MODIS), weather and extreme events (Daymet, heat/cold waves, and U.S. drought monitor maps), as well as soil and terrain features, making it suitable for various agricultural monitoring tasks. It integrates crop- and climate-related tasks within a single, cohesive dataset.
34
  In detail, the following data sources are provided:
35
  ![Data Table](images/data_table.png)
 
36
 
37
  ## Uses
38
  The dataset allows various tasks, including yield prediction, phenology mapping, crop condition forecasting, extreme weather event detection/prediction, sensor fusion, pretraining on crop areas, and multi-task learning.
 
33
  The database includes 15,500 small data cubes (i.e., minicubes), each with a spatial coverage of 12x12km, spanning 1527 counties in the US. The minicubes comprise data from multiple sensors (Sentinel-1/2, Landsat-8, MODIS), weather and extreme events (Daymet, heat/cold waves, and U.S. drought monitor maps), as well as soil and terrain features, making it suitable for various agricultural monitoring tasks. It integrates crop- and climate-related tasks within a single, cohesive dataset.
34
  In detail, the following data sources are provided:
35
  ![Data Table](images/data_table.png)
36
+ †The drought indices have been added to the original dataset from a master's thesis. Additional information can be found in the repository.
37
 
38
  ## Uses
39
  The dataset allows various tasks, including yield prediction, phenology mapping, crop condition forecasting, extreme weather event detection/prediction, sensor fusion, pretraining on crop areas, and multi-task learning.
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