This paper addresses the local incidence angle dependence of several polarimetric indices corresponding to landslides in forested areas. Landslide is deeply related to the loss of human lives and their property. Various kinds of remote sensing techniques, including aerial photography, high-resolution optical satellite imagery, LiDAR and SAR interferometry (InSAR), have been available for landsl...

We propose a new approach at the rectangle feature level to extract buildings from high-resolution polarimetric synthetic aperture radar (PolSAR) data, using both region-based and edge-based information. The first step employs low-level detectors to provide raw region and edge information of the scene. In the second step, the rectangle features are initially extracted from the edge detection re...

This paper reflects the polarimetric synthetic aperture radar (POLSAR) data utilization for near-real time earthquake and/or tsunami damage assessment in urban areas. In order to show the potential of the fully polarimetric high resolution polarimetric SAR (POLSAR) image data sets, a fourcomponent scattering power decomposition scheme has been developed and applied to monitor near-real time ear...

Deep learning and convolutional neural networks (CNNs) have made progress in polarimetric synthetic aperture radar (PolSAR) image classification over the past few years. However, a crucial issue has not been addressed, i.e., requirement of CNNs for abundant labeled samples versus insufficient human annotations PolSAR images. It is well known that following supervised paradigm may lead to overfi...

In this paper, the three-component power decomposition for polarimetric SAR (PolSAR) data with an adaptive volume scattering model is proposed. The volume scattering model is assumed to be reflection-symmetric but parameterized. For each image pixel, the decomposition first starts with determining the adaptive parameter based on matrix similarity metric. Then, a respective scattering power comp...

Built-up area extraction from polarimetric SAR (PolSAR) imagery has a close relationship with urban planning, disaster management, etc. Since the buildings have complex geometries and may be misclassified as forests due to the significant cross-polarized scattering, built-up area extraction from PolSAR data is still a challenging problem. This paper proposes a new urban extraction method for Po...

Synthetic Aperture Radar (SAR) data can be difficult to interpret over glacierized terrain, especially in areas of high relief where most of the smaller glaciers of the world are found. The two primary objectives of this paper are to correct the topographically induce distortions inherent in SAR image of rugged terrain and to map glacier facies in the corrected polarimetric (PolSAR) image. Meth...

The presence of speckle complicates the tasks of interpreting and analysing polarimetric synthetic aperture radar (PolSAR) images. The nonlinear anisotropic diffusion (AD) method has been found to perform well in removing image noise. In this article, we propose a new ADmethod for PolSAR speckle reduction. An iterative refinement method is employed to measure the similarity between pixels and c...

This paper presents some applications of the Maximum Likelihood (ML) texture tracking on displacement estimation of some alpine and antarctic glaciers surfaces. This method is adapted to the statistical characteristic of the new High Resolution (HR) Polarimetric SAR (PolSAR) data. The ML texture tracking method is firstly reminded and a statistical model of HR PolSAR data is explained. The main...

This study intends to investigate the use of NASA/JPL POLSAR data (multilook Cand L-bands) for classifying land cover features, such as vegetation (i.e. grass, rice paddy, rubber), natural feature (i.e. river), and man-made features (i.e. canal, highway, runway, built-up area). Covering the area of Jitra, the 10 meters resolution air-borne POLSAR data acquired on 3 December 1996 was used in thi...