@article{fdi:010040617,
  title = {{M}apping of flood dynamics and spatial distribution of vegetation in the {A}mazon floodplain using multitemporal {SAR} data},
  author = {{M}artinez, {J}ean-{M}ichel and {L}e {T}oan, {T}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his paper presents the use of time series of {SAR} images to map the flood temporal dynamics and the spatial distribution of vegetation over a large {A}mazonian floodplain. {T}he region under study (3500 km(2)) presents a diversity of landscape units with open lakes, bogs, large meadows, savannahs, alluvial forests and terra firma forest, covered by 21 images acquired by {J}-{ERS} between 1993 and 1997. {G}round data include in situ observations of vegetation structure and flood extent as well as water level records. {I}mage analysis demonstrates that temporal variations of the radar backscatter can be used to monitor efficiently the flood extent regardless of the landscape units. {A}lso, analysis of the backscatter temporal variation greatly reduces the confusion between smooth surfaces (e.g. open water bodies, bare soils) inherent to {L}-band backscatter. {T}he mapping method is based on decision rules over two decision variables: 1) the mean backscatter coefficient computed over the whole time series; 2) the total change computed using an "{A}bsolute {C}hange" estimator. {T}he first variable provides classification into rough vegetation types while the second variable yields a direct estimate of the intensity of change that is related to flood dynamics. {T}he classifier is first applied to the whole time series to map the maximum and minimum flood extent by defining 3 flood conditions: never flooded ({NF}); occasionally flooded ({OF}); permanently flooded ({PF}). {I}t also furnishes the broad land cover type: open water/bare soils/low vegetation/forest. {T}he accuracy of the flood extent mapping shows a kappa value of 0.82. {T}hen, the classifier is run iteratively on the {OF} pixels to monitor flood stages during which the occasionally flooded areas get submerged. {T}he mapping accuracy is assessed on one intermediate flood stage, showing a precision in excess of 90%. {T}he importance of the time sampling for flood mapping is discussed along with the influence of {SAR} backscatter accuracy and the number of images. {T}hen general guidelines for floodplain mapping are presented. {B}y combining water level reports with maps of different flood stages the flooding pattern can be retrieved along with the vegetation succession processes. {I}t is shown that the spatial distribution of vegetation communities is governed by flood stress and can be modelled as a function of the mean annual exposure to floods.},
  keywords = {wetland ; floodplain ; vegetation ; flood ; temporal dynamic ; radar ; classification},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {108},
  numero = {3},
  pages = {209--223},
  ISSN = {0034-4257},
  year = {2007},
  DOI = {10.1016/j.rse.2006.11.012},
  URL = {https://www.documentation.ird.fr/hor/fdi:010040617},
}