Combined Land-Cover Classification and Stem Volume Estimation Using Multitemporal ERS Tandem INSAR Data

A radar-based method for producing both land-cover classification and stem volume estimates for the forested areas is demonstrated. The method utilizes multi-temporal INSAR data that is segmented into quasi-homogenous segments, and a semiempirical backscattering-coherence model that is inverted to produce stem volume estimates for the forest segments. Forest stands with known stem volumes are required as training areas for determining the values of the model parameters. The performance of the method was studied by estimating the stemvolumes of 4000+ forest segments and comparing the results with stem volume estimates produced by ground-based estimates and the National Forest Inventory (NFI) of Finland. The method is suitable for operational use and the performance in stem volume estimation is comparable with optical methods. Keywords; SAR Interferometry, coherence, stem volume estimation, land-cover classification