{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T17:32:37Z","timestamp":1792949557852,"version":"4.5.0"},"reference-count":84,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T00:00:00Z","timestamp":1629331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water stock monitoring is a major issue for society on a local and global scale. Sentinel-1&amp;2 satellites provide frequent acquisitions to track water surface dynamics, proxy variables to enable water surface volume monitoring. How do we combine such observations along time for each sensor? What advantages and disadvantages of single-date, monthly or time-windowed estimations? In this context, we analysed the impact of merging information through different types and lengths of time-windows. Satellite observations were processed separately on optical (Sentinel-2) and radar (Sentinel-1) water detectors at 10 m resolution. The analysis has been applied at two scales. First, validating with 26 large scenes (110 \u00d7 110 km) in different climatic zones in France, time-windows yielded an improvement on radar detection (F1-score improved from 0.72 to 0.8 for 30 days on average logic) while optical performances remained stable (F1-score 0.89). Second, validating reservoir area estimations with 29 instrumented reservoirs (20\u20131250 ha), time-windows presented in all cases an improvement on both optical and radar error for any window length (5\u201330 days). The mean relative absolute error in optical area detection improved from 16.9% on single measurements to 12.9% using 15 days time-windows, and from 22.15% to 15.1% in radar detection). Regarding reservoir filling rates, we identified an increased negative bias for both sensors when the reservoir is nearly full. This work helped to compare accuracies of separate optical and radar capabilities, where optical statistically outperforms radar at both local and large scale to the detriment of less frequent measurements. Furthermore, we propose a geomorphological indicator of reservoirs to predict the quality of radar area monitoring (R2 = 0.58). In conclusion, we suggest the use of time-windows on operational water mapping or reservoir monitoring systems, using 10\u201320 days time-windows with average logic, providing more frequent and faster information to water managers in periods of crisis (e.g., water shortage) compared to monthly estimations.<\/jats:p>","DOI":"10.3390\/rs13163279","type":"journal-article","created":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T09:58:06Z","timestamp":1629367086000},"page":"3279","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Sentinel-1&amp;2 Multitemporal Water Surface Detection Accuracies, Evaluated at Regional and Reservoirs Level"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7729-1198","authenticated-orcid":false,"given":"Santiago","family":"Pe\u00f1a-Luque","sequence":"first","affiliation":[{"name":"Centre National d\u2019Etudes Spatiales (CNES), 18 Avenue Edouard Belin, 31400 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3478-2624","authenticated-orcid":false,"given":"Sylvain","family":"Ferrant","sequence":"additional","affiliation":[{"name":"Centre d\u2019Etude Spatiale de la BIOsph\u00e8re (CESBIO), UPS-Universit\u00e9 de Toulouse, CNRS, CNES, IRD, INRAE, 18 Av. Edouard Belin, bpi 2801, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mauricio C. R.","family":"Cordeiro","sequence":"additional","affiliation":[{"name":"Ag\u00eancia Nacional de \u00c1guas (ANA), Setor Policial Sul, \u00c1rea 5, Quadra 3, Bras\u00edlia 70610-200, Brazil"},{"name":"G\u00e9osciences Environnement Toulouse (GET), Unit\u00e9 Mixte de Recherche 5563, IRD\/CNRS\/Universit\u00e9, 31400 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5299-6039","authenticated-orcid":false,"given":"Thomas","family":"Ledauphin","sequence":"additional","affiliation":[{"name":"ICUBE-SERTIT, Universit\u00e9 de Strasbourg, 67412 Illkirch Graffenstaden, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5447-6421","authenticated-orcid":false,"given":"Jerome","family":"Maxant","sequence":"additional","affiliation":[{"name":"ICUBE-SERTIT, Universit\u00e9 de Strasbourg, 67412 Illkirch Graffenstaden, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3281-8512","authenticated-orcid":false,"given":"Jean-Michel","family":"Martinez","sequence":"additional","affiliation":[{"name":"G\u00e9osciences Environnement Toulouse (GET), Unit\u00e9 Mixte de Recherche 5563, IRD\/CNRS\/Universit\u00e9, 31400 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Biemans, H., Haddeland, I., Kabat, P., Ludwig, F., Hutjes, R.W.A., Heinke, J., Von Bloh, W., and Gerten, D. 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