Abstract
SDGSAT-1, the first scientific satellite dedicated to advancing the United Nations 2030 Agenda for Sustainable Development, brings renewed vigor and opportunities to water resource monitoring and research. This study evaluates the effectiveness of SDGSAT-1 in extracting water bodies in comparison to Sentinel-2 multi-spectral imager (MSI) data. We applied a confidence thresholding method to delineate river water from land, utilizing the Normalized Differential Water Body Index (NDWI), Normalized Difference Water Index (MNDWI), and Shaded Water Body Index (SWI). It was found that the SWI works best for SDGSAT-1 while the NDWI works best for Sentinel-2. Specifically, the NDWI demonstrates proficiency in delineating a broader spectrum of water bodies and the MNDWI effectively mitigates the impact of shadows, while SDGSAT-1’s SWI extraction of rivers offers high precision, clear outlines, and shadow exclusion. SDGSAT-1’s SWI overall outperforms Sentinel-2’s NDWI in water extraction accuracy (overall accuracy: 90% vs. 91%, Kappa coefficient: 0.771 vs. 0.416, and F1 value: 0.844 vs. 0.651), likely due to its deep blue bands. This study highlights the comprehensive advantages of SDGSAT-1 data in extracting river water bodies, providing a theoretical basis for future research.
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