Analysis of Spatial Statistics in PALSAR Data by Wavelet Frames for Forest Structural Characterization
Gianfranco De Grandi(1), Richard Lucas(2), Jan Kropacek(1), Paolo Pasquali(3) and Francesco Holecz(3)
(1) European Commission - DG Joint Research Centre, via Fermi - TP 440, 21027 Ispra (VA), Italy
(2) University of Wales at Aberystwyth, King Street, SY23 2AX , Ceredigion, United Kingdom
(3) SARMAP s.a., Cascine di Barico, 6989 Purasca, Switzerland
Spatial variations of SAR backscatter bear information on structural and geometric properties of natural targets, and therefore can be potentially useful for deriving biophysical parameters, or for classification problems. These variations and their relationships are visually perceived as image texture, and can be measured by the statistics of some underlying random process. A method for retrieving local texture measures in SAR imagery using wavelet frames was proposed in  from the theoretical point of view. In particular the concept of polarimetric texture was revisited, by investigating the dependences of these measures on the antenna polarization states. The method provides estimates of a two-point statistics (a proxy of the structure function) in the combined space-scale-polarization domain. To analyze from the observational standpoint these dependences, suitable analytical tools are introduced to represent these dependences through signatures that condense information in graphical form. In particular, the Wavelet Scaling Signature (WASS) for single polarization detected data, and the Wavelet Polarization Signature (WASP) for fully polarimetric data are used to characterize the textural properties of extended homogeneous areas of interest. Moreover, textural separability of two regions is studied by means of a criterion function of the Fischer discriminant analysis. Based on this theoretical background, experiments are reported where wavelet frame texture measures and signature analysis are applied to PALSAR observations of natural targets. The experiments are thematically oriented towards the characterization of woodlands and open forests in Australia. The objective is to assess whether texture measures could capture the rich natural variability in forest structure (including re-growth) and variability related to human intervention (clearings), thus augmenting the capability of forest mapping by PALSAR observations beyond the use of backscatter only.
 De Grandi G., Lee J.S., Schuler D.L., "Target Detection and Texture Segmentation in Polarimetric SAR Images Using a Wavelet Frame: Theoretical Aspects", IEEE Transactions on Geoscience and Remote Sensing, 2007, in press.