Forest Mapping and Classification at L band using POL-inSAR Optimal Coherence Set Statistics

Konferenz: EUSAR 2006 - 6th European Conference on Synthetic Aperture Radar
16.05.2006 - 18.05.2006 in Dresden, Germany

Tagungsband: EUSAR 2006

Seiten: 4Sprache: EnglischTyp: PDF

Persönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt

Ferro-Famil, Laurent; Pottier, Eric (University of Rennes 1, IETR, Remote Sensing group, Rennes, France)
Kugler, Florian (DLR, Microwave and Radar Institute, SAR technology department, Pol-inSAR group, Oberpfaffenhofen, Germany)
Lee, Jong-Sen (Remote Sensing Division, Naval Research Laboratory, Washington, DC, USA)

This paper presents a new approach to classify forested areas from POL-inSAR data. The statistics of an optimal coherence set are derived to define a log-likelihood distance that can be used in iterative classification processes. This novel method is compared to an existing technique based on a POL-inSAR coherency matrix Wishart statistics. The invariance properties of optimal coherences may be used to overcome some limitations encountered with theWishart approach. It is then shown that such an approach may be used to relyably classify forest stand biomass into broad categories.