@article{fdi:010090020,
  title = {{C}ontribution of automatically generated radar altimetry water levels from unsupervised classification to study hydrological connectivity within {A}mazon floodplains},
  author = {{E}nguehard, {P}auline and {F}rappart, {F}. and {Z}eiger, {P}. and {B}larel, {F}. and {S}atg{\'e}, {F}r{\'e}d{\'e}ric and {B}onnet, {M}arie-{P}aule},
  editor = {},
  language = {{ENG}},
  abstract = {{S}tudy region. {T}he {C}uruaí floodplain in the low {A}mazon river in the {P}ará state of {B}razil and {J}uruá basin, a major {S}olimões tributary. {S}tudy focus. {C}haracterizing the hydrological dynamics of {A}mazon floodplains is essential to better understand and preserve these environments providing important resources to local populations. {R}adar altimetry is an effective remote sensing tool for monitoring water levels of continental hydrosystems, including floodplains. {A}n unsupervised classification approach on radar echoes to determine hydrological regimes has recently been tested and showed a strong potential on the {C}ongo {R}iver basin. {T}his method is adapted to {E}nvisat and {S}aral satellite radar altimetry data on two study areas in the {A}mazon {B}asin. {T}he aim is to improve inland water detection along altimeter tracks to automatically generate water level time series ({WLTS}) over rivers, lakes, and poorly monitored floodplains and wetlands. {N}ew hydrological insights. {R}esults show a good agreement with land cover maps obtained with optical imagery over selected {A}mazonian wetlands (70-80% accuracies with {E}nvisat data and 50-60% with {S}aral data). {A}utomatically generated {WLTS} are strongly correlated to the manually generated {WLTS} ({R}²},
  keywords = {{R}adar altimetry ; {A}mazon ; {F}loodplains ; {U}nsupervised classification ; {A}utomatic generation of water level gauges ; {H}ydrological connectivity ; {BRESIL} ; {PEROU} ; {AMAZONIE} ; {AMAZONE} {BASSIN}},
  booktitle = {},
  journal = {{J}ournal of {H}ydrology : {R}egional {S}tudies},
  volume = {47},
  numero = {},
  pages = {101397 [17 p.]},
  year = {2023},
  DOI = {10.1016/j.ejrh.2023.101397},
  URL = {https://www.documentation.ird.fr/hor/fdi:010090020},
}