Multi-otsu

Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh

We developed a novel framework to map boro rice at peak season using Sentinel images. These Boro rice maps in Bangladesh showed high classification accuracy (mean of 87.90%). There was no requirement of sample data collection for training the classification model. Multi-Otsu effectively maps rice in low-data areas, outperforming other ML methods and provides stakeholders rice area statistics to support food security management.