@article{fdi:010094204,
  title = {{M}ultitemporal monitoring of {E}cuadorian {A}ndean high wetlands using radar and multispectral remote sensing},
  author = {{H}uaraca, {L}. and {B}ourrel, {L}uc and {Z}apata-{R}íos, {X}. and {P}áez-{B}imos, {S}. and {L}ahuatte, {B}. and {G}aleas, {R}. and {F}uentes, {P}. and {F}rappart, {F}.},
  editor = {},
  language = {{ENG}},
  abstract = {{H}igh-altitude wetlands in the {E}cuadorian {A}ndes are key ecosystems for water regulation and biodiversity conservation but remain poorly monitored due to persistent cloud cover and complex terrain. {T}his study aims to develop a multitemporal approach to map and monitor these wetlands under challenging environmental conditions. {W}e integrated {S}entinel-1 ({SAR}) and {S}entinel-2 (multispectral) satellite imagery within the {G}oogle {E}arth {E}ngine platform, applying a {R}andom {F}orest classifier and soil moisture estimation through the {W}ater {C}loud {M}odel. {R}esults show that using only multispectral data underestimated wetland extent (18,919 ha in 2022; 4.7% of the area). {I}n 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 {A}pril (6.7%). {S}oil moisture estimates showed stable monthly wetland extents (15.3-15.9%), with a maximum of 3065 ha in {J}anuary-{F}ebruary, and demonstrated a strong link with cumulative rainfall patterns. {T}his 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.},
  keywords = {high wetlands ; bofedal ; mapping ; {S}entinel ; water cloud model ; surface ; soil moisture ; {EQUATEUR} ; {ANDES}},
  booktitle = {},
  journal = {{W}ater},
  volume = {17},
  numero = {11},
  pages = {1637 [30 p.]},
  year = {2025},
  DOI = {10.3390/w17111637},
  URL = {https://www.documentation.ird.fr/hor/fdi:010094204},
}