Toward consistent regional-to-global-scale vegetation characterization using orbital SAR systems

A study was conducted to assess the potential of combined imagery from the existing European and Japanese orbitar synthetic aperture radar (SAR) systems, ERS-1 (C-hand, VV-polarization) and JERS-1 (L-band, HH-palarization), for regional-to-global-scale vegetation classification. For seven test sites from various ecoregions in North and South America, ERS-1/JERS-1 composites were generated using high-resolution digital elevation model (DEM) data for terrain correction of geometric and radiometric distortions. An edge-preserving speckle reduction process was applied to reduce the fading variance and prepare the data for an unsupervised clustering of the two-dimensional (2D) SAR feature space. Signature-based classification of the clusters was performed for all test sites with the same set of radar backscatter signatures, which were measured from well-defined polygons throughout all test sites. While trained on one-half of the polygons, the classification result was tested against the other half of the total sample population. The multisite study was followed by a multitemporal study in one test site, clearly showing the necessity of including multitemporal data beyond a level 1 (woody, herbaceous, mixed) vegetation characterization. Finally, classifications with simulation of backscatter variations shows the dependence of the classification results on calibration accuracy and on naturally occurring backscatter changes of natural surfaces. Overall, it is demonstrated that the combination of existing orbital L- and C-band SAR data is quite powerful for structural vegetation characterization.