📆 Project Period | February, 2022 |
📍 GitHub | gitlab.esa.int |
Project Summary
This is an aggregation of different crop types in several regions of the world. The variance in the data should drive the development of new methods and different experiments. The merging of data represents only one part of the project. For each field polygon, a time series of mean values and other statistical properties was created. For example, a field (polygon) is represented by a Sentinel-2 time series of means per field. The labels for the crop types come from different sources and have been summarised.
Notebook
Example for crop type data
Crop type labels and id:
Bavaria: Potatos: 600, 601, 602 Winter barley: 476, 131 Winter rapeseed: 311, 489 Winter wheat: 115 Corn: 400, 177, 171, 411, 410 Sugar beet: 603
The labels for the following data are documented in:
- Kenya: https://mlhub.earth/data/ref_african_crops_kenya_01
- Central Asia: https://www.nature.com/articles/s41597-020-00591-2?proof=t
- France: https://breizhcrops.org/
#plot shapefile for durnast in bavaria
durnast_shp.plot()


Crop type labels
durnast_ts[durnast_ts.id == '58cb970d59ab4e618787ff1aadd85599'].crop_type.unique()References
[1] Breizhcrops, https://breizhcrops.org
[2] Radiant Earth Foundation, https://www.radiant.earth/
[3] Remelgado, R., Zaitov, S., Kenjabaev, S. et al. A crop type dataset for consistent land cover classification in Central Asia. Sci Data 7, 250 (2020). https://doi.org/10.1038/s41597-020-00591-2
[4] Chair of Plant Nutrition, TUM, https://www.pe.wzw.tum.de/