Mapping rice areas with Sentinel-1 time series and superpixel segmentation

ABSTRACT

Rice is the single most important crop for food security in Asia. Knowledge about the distribution of rice fields is also relevant in the context of greenhouse-relevant methane emissions, disease transmission, and water resource management. Copernicus Sentinel-1 provides the first openly available archive of C-band SAR (synthetic aperture radar) data at high spatial and temporal resolution. We developed one of the first methods that shows the potential of this data for accurate and timely mapping of rice-growing areas. We used superpixel segmentation to create spatially averaged backscatter time series, which is robust to speckle and reduces the amount of data to process. This method has been applied to six study sites in different rice-growing regions of the world and achieved an average overall accuracy of 0.83.

Acknowledgements

We would like to thank Dr Xiaoping Du and Dr Tuan Quoc Vo for their valuable input and discussions on the remote sensing of rice areas in China and Vietnam. We would also like to thank our anonymous reviewers for their constructive comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

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Additional information

Funding

This work was partially funded by the German Ministry of Education and Research (BMBF) through the DeltAdapt and Catch-Mekong projects.