%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Huaraca, L.
%A Bourrel, Luc
%A Zapata-Ríos, X.
%A Páez-Bimos, S.
%A Lahuatte, B.
%A Galeas, R.
%A Fuentes, P.
%A Frappart, F.
%T Multitemporal monitoring of Ecuadorian Andean high wetlands using radar and multispectral remote sensing
%D 2025
%L fdi:010094204
%G ENG
%J Water
%K high wetlands ; bofedal ; mapping ; Sentinel ; water cloud model ; surface ; soil moisture
%K EQUATEUR ; ANDES
%M ISI:001507516400001
%N 11
%P 1637 [30 ]
%R 10.3390/w17111637
%U https://www.documentation.ird.fr/hor/fdi:010094204
%> https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2025-07/010094204.pdf
%V 17
%W Horizon (IRD)
%X High-altitude wetlands in the Ecuadorian Andes are key ecosystems for water regulation and biodiversity conservation but remain poorly monitored due to persistent cloud cover and complex terrain. This study aims to develop a multitemporal approach to map and monitor these wetlands under challenging environmental conditions. We integrated Sentinel-1 (SAR) and Sentinel-2 (multispectral) satellite imagery within the Google Earth Engine platform, applying a Random Forest classifier and soil moisture estimation through the Water Cloud Model. Results show that using only multispectral data underestimated wetland extent (18,919 ha in 2022; 4.7% of the area). In contrast, integrating radar and multispectral data enabled dynamic analysis, identifying 2023 as the peak year (28,972 ha; 7.2%), with the highest monthly coverage in April (6.7%). Soil moisture estimates showed stable monthly wetland extents (15.3-15.9%), with a maximum of 3065 ha in January-February, and demonstrated a strong link with cumulative rainfall patterns. This integrated approach offers a reliable method for high-resolution, seasonal wetland monitoring in cloud-prone mountain environments, supporting data-driven conservation and land management strategies.
%$ 082 ; 062 ; 126