Abstract
Using remote sensing to provide reliable information over extensive areas of dense and heterogeneous tropical forests is a challenging task. Not 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. The AMAP laboratory in Montpellier, France, is contributing to this challenge at the interface between signal processing and plant and vegetation modelling which is its central domain of expertise. Models of forest structure are an important tool to fill the scale gap between field observations and remotely sensed information. They help also to understand the complex interactions between signal and forest vegetation. As remotely-sensed data are diversifying, coupling forest structure and radiative transfer models helps to translate signal information into biophysical parameters. Refining 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.