Estimation of comprehensive forest variable sets from multiparameter SAR data over a large area with diverse species

Abstract

Polarimetric and multifrequency data from the NASA/JPL airborne synthetic aperture radar (AIRSAR) have been used in a multitier estimation algorithm to calculate a comprehensive set of forest canopy properties including branch layer moisture and thickness, trunk density, trunk water content and diameter, trunk height, and subcanopy soil moisture. The estimation algorithm takes advantage of species-specific allometric relations, and is applied to a 100 km /spl times/100 km area in the Canadian boreal region containing many different vegetation species types. The results show very good agreement with ground measurements taken at several focused and auxiliary study sites. This paper expands on the results reported in Moghaddam and Saatchi (2000) and applies the algorithm on the regional scale.