Chunle Wang

Comparison of Nonnegative Eigenvalue Decompositions With and Without Reflection Symmetry Assumptions

Nonnegative eigenvalue decomposition (NNED), which insists and guarantees that each decomposed scattering component corresponds to a physically realizable scatterer, is powerful for polarimetric synthetic aperture radar (SAR) images analysis. Previous NNED is mainly illustrated under the reflection symmetric condition. In this paper, the coherency matrix approach is derived to implement the NNED for the nonreflection symmetry scattering case. We explicitly show the diversifications of the decomposition results between NNED with and without reflection symmetry assumptions, and quantitatively analyze the differences between them using the E-SAR polarimetric data acquired over the Oberpfaffenhofen area in Germany.

Polarimetric Response of Landslides at X-Band Following the Wenchuan Earthquake

A fully polarimetric response of landslide areas at X-band was studied by a Chinese high-resolution airborne synthetic aperture radar system. Polarimetric decompositions, including the Yamaguchi four-component decomposition and the Cloude decomposition, are used to analyze the scattering mechanisms of several typical landslides caused by the 2008 Wenchuan Earthquake in southwestern China. The experimental results indicate that areas affected by large-scale landslides show complicated scattering mechanisms at X-band, which are a mixture of surface, double bounce, and volume scattering. Simple classification results based on supervised Wishart classifier and polarimetric scattering similarity parameters are also presented, which can distinguish landslide areas from others, such as forest and water, very well. However, it does not perform well for urban areas. Additional information, such as prelandslide imagery, is needed to distinguish landslide areas from urban areas or bare soil. From these results, we can conclude that landslide mapping using fully polarimetric data has great potential for rapid response and management of landslide disasters.

Unsupervised polarimetric synthetic aperture radar classification of large-scale landslides caused by Wenchuan earthquake in hue-saturation-intensity color space

Abstract A simple and effective approach for unsupervised classification of large-scale landslides caused by the Wenchuan earthquake is developed. The data sets used were obtained by a high-resolution fully polarimetric airborne synthetic aperture radar system working at X-band. In the proposed approach, Pauli decomposition false-color RGB imagery is first transformed to the hue-saturation-intensity (HSI) color space. Then, a good combination of k-means clustering and HSI imagery in different channels is used stage-by-stage for automatic landslides extraction. Two typical case studies are presented to evaluate the feasibility of the proposed scheme. Our approach is an important contribution to the rapid assessment of landslide hazards.