The objective of this challenge was to use time-series of Sentinel-2 multispectral and Sentinel-1 SAR data to classify crops in the Western Cape of South Africa. Participants were asked to build a machine learning model to predict crop type classes for the test dataset. The training dataset was generated by the Radiant Earth Foundation team, using the ground reference data collected and provided by the Western Cape Department of Agriculture.
This repository contains the winning models from the XL track of the competition in which participants used time series of Sentinel-1 SAR data in addition to Sentinel-2 multispectral data as input for crop type classification.
The competition was run on Zindi platform.
The evaluation metric for the competition was Cross Entropy with binary outcome for each crop:
The following table shows the competition scores of the awarded winners.
| Team | Competition Score |
|---|---|
| SkaMo | 0.634814703680626 |
| Ensemble | 0.680127144327633 |
| ASSAZZIN | 0.690294803999381 |
