@article{fdi:010055313,
  title = {{L}inking remote-sensing information to tropical forest structure : the crucial role of modelling},
  author = {{C}outeron, {P}ierre and {B}arbier, {N}icolas and {P}roisy, {C}hristophe and {P}{\'e}lissier, {R}apha{\¨e}l and {V}incent, {G}r{\'e}goire},
  editor = {},
  language = {{ENG}},
  abstract = {{U}sing remote sensing to provide reliable information over extensive areas of dense and heterogeneous tropical forests is a challenging task. {N}ot only is the task challenging, but it also has become closely related to global concerns about reducing greenhouse gas emissions from deforestation and forest degradation, also known as the {REDD} process. {T}he {AMAP} laboratory in {M}ontpellier, {F}rance, is contributing to this challenge at the interface between signal processing and plant and vegetation modelling which is its central domain of expertise. {M}odels of forest structure are an important tool to fill the scale gap between field observations and remotely sensed information. {T}hey help also to understand the complex interactions between signal and forest vegetation. {A}s remotely-sensed data are diversifying, coupling forest structure and radiative transfer models helps to translate signal information into biophysical parameters. {R}efining such an approach is needed to design replicable methods that address the most challenging aspect of monitoring spatiotemporal variations of stand structure in forest types retaining high aboveground biomass},
  keywords = {{FORET} {DENSE} ; {ARCHITECTURE} {DE} {LA} {VEGETATION} ; {STRUCTURE} {DE} {POPULATION} ; {TELEDETECTION} {SPATIALE} ; {IMAGE} {SATELLITE} ; {ALTIMETRIE} ; {CANOPEE} {FORESTIERE} ; {BIOMASSE} ; {PHENOLOGIE} ; {MODELISATION} ; {ZONE} {TROPICALE} ; {GUYANE} {FRANCAISE}},
  booktitle = {},
  journal = {{E}arthzine},
  numero = {},
  pages = {10},
  year = {2012},
  URL = {https://www.documentation.ird.fr/hor/fdi:010055313},
}