Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4349-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-4349-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Surface water monitoring in small water bodies: potential and limits of multi-sensor Landsat time series
G-EAU, AgroParisTech, Cirad, IRD, IRSTEA, Montpellier SupAgro, Univ Montpellier, Montpellier, France
Department of Geography, King's College London, WC2R 2LS London, UK
Gilles Belaud
G-EAU, AgroParisTech, Cirad, IRD, IRSTEA, Montpellier SupAgro, Univ Montpellier, Montpellier, France
Sylvain Massuel
G-EAU, AgroParisTech, Cirad, IRD, IRSTEA, Montpellier SupAgro, Univ Montpellier, Montpellier, France
Mark Mulligan
Department of Geography, King's College London, WC2R 2LS London, UK
Patrick Le Goulven
G-EAU, AgroParisTech, Cirad, IRD, IRSTEA, Montpellier SupAgro, Univ Montpellier, Montpellier, France
Roger Calvez
G-EAU, AgroParisTech, Cirad, IRD, IRSTEA, Montpellier SupAgro, Univ Montpellier, Montpellier, France
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Discussed (preprint)
Latest update: 26 Dec 2024
Short summary
Accurate monitoring of surface water extent is essential for hydrological investigation of small lakes (1–10 ha), which supports millions of smallholder farmers. Landsat monitoring of long-term surface water dynamics is shown to be suited to lakes over 3 ha based on extensive hydrometric data from seven field sites over 15 years. MNDWI water classification optimized here for the specificities of small water bodies reduced mean surface area errors by 57 % compared to published global datasets.
Accurate monitoring of surface water extent is essential for hydrological investigation of small...