@article{fdi:010082763,
  title = {{S}entinel-1 and 2 multitemporal water surface detection accuracies, evaluated at regional and reservoirs level},
  author = {{P}ena-{L}uque, {S}. and {F}errant, {S}ylvain and {C}ordeiro, {M}. {C}. {R}. and {L}edauphin, {T}. and {M}axant, {J}. and {M}artinez, {J}ean-{M}ichel},
  editor = {},
  language = {{ENG}},
  abstract = {{W}ater stock monitoring is a major issue for society on a local and global scale. {S}entinel-1&2 satellites provide frequent acquisitions to track water surface dynamics, proxy variables to enable water surface volume monitoring. {H}ow do we combine such observations along time for each sensor? {W}hat advantages and disadvantages of single-date, monthly or time-windowed estimations? {I}n this context, we analysed the impact of merging information through different types and lengths of time-windows. {S}atellite observations were processed separately on optical ({S}entinel-2) and radar ({S}entinel-1) water detectors at 10 m resolution. {T}he analysis has been applied at two scales. {F}irst, validating with 26 large scenes (110 x 110 km) in different climatic zones in {F}rance, time-windows yielded an improvement on radar detection ({F}1-score improved from 0.72 to 0.8 for 30 days on average logic) while optical performances remained stable ({F}1-score 0.89). {S}econd, validating reservoir area estimations with 29 instrumented reservoirs (20-1250 ha), time-windows presented in all cases an improvement on both optical and radar error for any window length (5-30 days). {T}he 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). {R}egarding reservoir filling rates, we identified an increased negative bias for both sensors when the reservoir is nearly full. {T}his 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. {F}urthermore, we propose a geomorphological indicator of reservoirs to predict the quality of radar area monitoring ({R}-2 = 0.58). {I}n conclusion, we suggest the use of time-windows on operational water mapping or reservoir monitoring systems, using 10-20 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.},
  keywords = {water cycle ; water surfaces ; reservoirs ; multi-temporal ; water detection ; radar imaging ; optical imaging ; area monitoring},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {13},
  numero = {16},
  pages = {3279 [25 p.]},
  year = {2021},
  DOI = {10.3390/rs13163279},
  URL = {https://www.documentation.ird.fr/hor/fdi:010082763},
}