A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements
Abstract Spatiotemporal mapping of surface water extent constitutes a valuable dataset for the management of water resources, the monitoring of flood- and drought-affected areas, and the conservation of wetlands and freshwater ecosystems. Surface water indices, derived from optical satellite data, s...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05562-z |
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| author | Yohei Miura Mohammad Shamsudduha Anawat Suppasri Daisuke Sano |
| author_facet | Yohei Miura Mohammad Shamsudduha Anawat Suppasri Daisuke Sano |
| author_sort | Yohei Miura |
| collection | DOAJ |
| description | Abstract Spatiotemporal mapping of surface water extent constitutes a valuable dataset for the management of water resources, the monitoring of flood- and drought-affected areas, and the conservation of wetlands and freshwater ecosystems. Surface water indices, derived from optical satellite data, serve as effective indicators for estimating surface water coverage. However, global-scale datasets featuring high-resolution surface water mapping using multiple water indices remain scarce and constrained in temporal and spatial scope. Here, we present monthly surface-water maps derived from three water indices, Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and Water Index 2015 (WI2015), utilizing high-resolution earth observation satellite data from Landsat-8 and Sentinel-2 for the period January 2019 to December 2021. These maps will be regularly updated as new satellite data become available. These water index mappings provide a baseline for projecting the distribution of surface-water resources and deliver critical information for the sustainable management of surface water resources under the challenges posed by the global climate change. |
| format | Article |
| id | doaj-art-e827facb6d4d448ea92e178df3893664 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-e827facb6d4d448ea92e178df38936642025-08-20T03:42:44ZengNature PortfolioScientific Data2052-44632025-07-0112111310.1038/s41597-025-05562-zA Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite MeasurementsYohei Miura0Mohammad Shamsudduha1Anawat Suppasri2Daisuke Sano3Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku UniversityDepartment of Risk and Disaster Reduction, University College LondonInternational Research Institute of Disaster Science, Tohoku UniversityDepartment of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku UniversityAbstract Spatiotemporal mapping of surface water extent constitutes a valuable dataset for the management of water resources, the monitoring of flood- and drought-affected areas, and the conservation of wetlands and freshwater ecosystems. Surface water indices, derived from optical satellite data, serve as effective indicators for estimating surface water coverage. However, global-scale datasets featuring high-resolution surface water mapping using multiple water indices remain scarce and constrained in temporal and spatial scope. Here, we present monthly surface-water maps derived from three water indices, Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and Water Index 2015 (WI2015), utilizing high-resolution earth observation satellite data from Landsat-8 and Sentinel-2 for the period January 2019 to December 2021. These maps will be regularly updated as new satellite data become available. These water index mappings provide a baseline for projecting the distribution of surface-water resources and deliver critical information for the sustainable management of surface water resources under the challenges posed by the global climate change.https://doi.org/10.1038/s41597-025-05562-z |
| spellingShingle | Yohei Miura Mohammad Shamsudduha Anawat Suppasri Daisuke Sano A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements Scientific Data |
| title | A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements |
| title_full | A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements |
| title_fullStr | A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements |
| title_full_unstemmed | A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements |
| title_short | A Global Multi-Sensor Dataset of Surface Water Indices from Landsat-8 and Sentinel-2 Satellite Measurements |
| title_sort | global multi sensor dataset of surface water indices from landsat 8 and sentinel 2 satellite measurements |
| url | https://doi.org/10.1038/s41597-025-05562-z |
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