Estimating boreal forest species type with airborne polarimetric synthetic aperture radar

Abstract

We have applied a non-parametric classifier (k nearest neighbour) to two calibrated orthogonal passes of airborne polarimetric synthetic aperture radar (POLSAR) image data over boreal forest for the purpose of discriminating canopy tree species of predefined stands. We found that a single classifier based on a single feature space (i.e. one set of POLSAR variables for all species) was less accurate than a hierarchical two-stage classifier that used different POLSAR variables for each species. We designed a two-stage classifier that first grouped stands into broad classes: pine, spruce and deciduous, and then classified each sample within the broad classes into individual species. We found that the most effective feature spaces had two or three dimensions. The two-stage classifier attained overall accuracies of between 60% and 75%.

We provide a first use of an equivalency test applied to remote-sensing classification. We use Lloyd's test of equivalency to find equivalent classifiers and thus infer informative POLSAR variables. The POLSAR variables that were most informative varied between the two passes and between the various elements of the hierarchical classifier. For the initial three-class classifier the most informative POLSAR variables were the two circular polarization ratios, several of Touzi's Stokes vector variables, HHVV coherence, several texture measures such as the variance of several scattering coefficients and the order parameter of the K-distribution and characteristics of the polarization signature pedestal. These results demonstrate that C-band POLSAR has great potential for mapping boreal forest cover either on its own or in concert with other geospatial data.

Acknowledgements

This research has been financed by the Natural Sciences and Engineering Research Council, the Alberta Ingenuity Fund, Informatics Circle of Research Excellence, the Canadian Forest Service, Natural Resources Canada, the Canada Space Agency and the University of Calgary. We thank Dave Hill, and Hao Chen of the Pacific Forestry Center for their invaluable contributions and support of this research. During the course of this work we have also received a great deal of assistance from Ridha Touzi, Joost van der Sanden, Karim Mattar and Joe Buckley, who have shared their knowledge and have generously given their input to help define the scope of this research. In particular, Touzi's PWS POLSAR analysis software was invaluable. We also acknowledge the help of Giles Foody with equivalency testing issues and particularly to Chris Lloyd for his help implementing and interpreting his equivalency test.