Potential of texture measurements of two-date dual polarization PALSAR data for the improvement of forest biomass estimation

Abstract

The recently available space-borne SAR sensor, PALSAR, is more promising than its predecessor JERS-1 for biomass estimation because of its long wavelength (L-band), and its ability to provide data with different polarizations, varying incidence angles and higher spatial resolutions. This research investigates the potential of two-date dual polarization (HH and HV) SAR imagery for biomass estimation using different kinds of texture processing and different combinations of single and dual polarization ratios. The investigation is conducted in a mountainous, sub-tropical study area where biomass levels are far beyond the previously recognized saturation levels for L-band SAR images, and forest is a mixture of native and non-native species and plantations.We analyzed two-date SAR data with four steps of image processing, including raw data processing in various combinations, texture measurement parameters of HH and HV polarizations, texture measurement parameters of HH and HV together (both jointly and as a ratio), and a ratio of two-date texture parameters along with a single and two-date ratio. When the processed images were compared with ground data from 50 plots, the performance from raw data processing was low, with adjusted r 2=0.22, but after all four processing steps, promising model accuracy (adjusted r 2=0.90 and RMSE=28.58t/ha) and validation accuracy (using the Leave-One-Out-Cross-Validation) with adjusted r 2=0.88 and RMSE=35.69t/ha, were achieved from the combination of single- and two-date polarization ratios of texture parameters.The strong performance achieved indicates that L-band dual-polarization (HH and HV) SAR data from PALSAR has great potential for biomass estimation, far beyond the previously reported L-band saturation point for biomass. This result is attributed to the synergy among texture processing and dual polarization on the one hand, which were able to average out random speckle noise, and the use of ratio instead of absolute quantities, due to its well known ability to reduce forest structural and terrain effects. The additional use of two-date SAR data with these processing techniques was able to add complementary information derived from biomass response in both wet and dry seasons. Thus overall, undesirable image noise and terrain effects were reduced.