Version 1
: Received: 29 May 2023 / Approved: 30 May 2023 / Online: 30 May 2023 (11:24:44 CEST)
How to cite:
Tesfaye, M.; Breuer, L. Performance of Water Indices for Water Resources Monitoring Using Large-Scale Sentinel-2 Data. Preprints2023, 2023052125. https://doi.org/10.20944/preprints202305.2125.v1
Tesfaye, M.; Breuer, L. Performance of Water Indices for Water Resources Monitoring Using Large-Scale Sentinel-2 Data. Preprints 2023, 2023052125. https://doi.org/10.20944/preprints202305.2125.v1
Tesfaye, M.; Breuer, L. Performance of Water Indices for Water Resources Monitoring Using Large-Scale Sentinel-2 Data. Preprints2023, 2023052125. https://doi.org/10.20944/preprints202305.2125.v1
APA Style
Tesfaye, M., & Breuer, L. (2023). Performance of Water Indices for Water Resources Monitoring Using Large-Scale Sentinel-2 Data. Preprints. https://doi.org/10.20944/preprints202305.2125.v1
Chicago/Turabian Style
Tesfaye, M. and Lutz Breuer. 2023 "Performance of Water Indices for Water Resources Monitoring Using Large-Scale Sentinel-2 Data" Preprints. https://doi.org/10.20944/preprints202305.2125.v1
Abstract
Evaluating the performance of water indices and mapping the spatial distribution of water-related ecosystems are important for monitoring surface water resources. This is particularly the case for Ethiopia since there is limited information available on water resources development over time despite its relevance for the people and ecosystems. To address this problem, this paper evaluates the performance of seven water indices for country-scale surface water detection based on high spatial and multi-temporal resolution Sentinel-2 data, processed using the Google Earth Engine cloud computing system. Results show that the water index (WI) and automatic water extraction index with shadow (AWEIsh) are the most accurate ones to extract surface water. Comparisons are based on qualitative visual inspections and quantitative accuracy indicators. For the latter, WI and AWEIsh obtained kappa coefficients of 0.96 and 0.95, respectively, and an overall accuracy of 0.98 each. Both indices accounted for similar spatial coverages of surface waters with 82,650 km2 (WI) and 86,530 km2 (AWEIsh) for the whole of Ethiopia.
Keywords
Sentinel-2; remote sensing; Google Earth Engine; large-scale; water resource
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
