Mapping of Vegetation Biophysical Variables Using Radiative Transfer Models - Coping with the ill-posed Inverse Problem

Remote sensing plays a fundament role in attempts to map the status of the Earth system. To avoid site-specific calibration of statistical models, physically based radiative transfer models (RTM) have been developed. The inverse problem of these RTM, however, is ill-posed. This means that the inverse solution is not always unique, leading to large uncertainties in the estimated fields. To cope with the ill-posed inverse problem, various strategies have been proposed such as the use of prior info within the cost function or the use of information provided by the continuous temporal evolution of key vegetation characteristics. The present contribution aims to further develop an approach that takes the signature of adjacent pixels into account [RSE (2004), 93: 53-67]. The idea builds on the geographical principle that near-by locations are probably more alike than locations at a larger distance. The proposed object-based inversion allows to effectively constrain the inverse problem. The developed approach will be presented and discussed in the context of vegetation related studies dealing with agricultural fields and/or managed forest stands.

ATZBERGER Clement; 

2009-09-11

Remote Sensing and Photogrammetry Society (RSPSOC)

JRC54161

https://publications.jrc.ec.europa.eu/repository/handle/JRC54161,