Snow cover mapping is a very important parameter for snowmelt runoff modeling and forecasting. Snow cover information is also useful for managing transportation and avalanche forecasting. This study will discuss the capability of full polarimetric L-band ALOS PALSAR data for snow classification. Therefore, Polarimetric decomposition and the complex Wishart classifier will be applied on ALOSPALS...

Echoes in clear air from two types of biological scatteres mixed within the resolution volumes over a large region, observed with S-band dual polarization radar, are presented. This case occurred in the evening of September 7, 2004, at the beginning of the Fall migrating season of song birds (passerines). Polarimetric spectral analyses are used for distinguishing birds and insects in multimodal...

Tidal wetlands including intertidal flats are highly productive and have dynamic and diverse ecosystems. Despite the importance of the tidal flats and associated coastal habitats, theses areas are at risk due to high development pressure, such as reclamation and marine pollution. Because of their poor accessibility, remote sensing techniques are the most effective tool for tidal flat observatio...

In this paper, two polarimetric segmentation techniques for polarimetric SAR images are compared. They are both based on the maximum generalised likelihood approach and on a Wishart distribution model. The first technique, named POLSEGANN, is based on a global likelihood approach and on the simulated annealing maximization technique, while the second one (POL MUM) is based on a Maximum Likeliho...

Overhead multiand hyperspectral imaging has enabled a variety of quantitative remote sensing techniques, such as the determination of the abundance and health of vegetation through the Normalized Difference Vegetation Index (NDVI). In addition, anomaly and target detection have been made possible by advanced matched filter algorithms. However, the derived surface reflectance from which all thes...

We address the issue of adapting optical images-based edge detection techniques for use in Polarimetric Synthetic Aperture Radar (PolSAR) imagery. We modify the gravitational edge detection technique (inspired by the Law of Universal Gravity) proposed by Lopez-Molina et al, using the non-standard neighbourhood configuration proposed by Fu et al, to reduce the speckle noise in polarimetric SAR i...

Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach. As classical descriptors of polarimetric SAR, covariance and coherency matrices are Hermitian semidefinite and form a Riemannian manifold. Conventional Euclidean metrics are not suitable for a Riemannia...

The GaoFen-3 (GF-3) satellite is the first fully polarimetric synthetic aperture radar (SAR) satellite designed for civil use in China. The satellite operates in the C-band and has 12 imaging modes for various applications. Three fully polarimetric SAR (PolSAR) imaging modes are provided with a resolution of up to 8 m. Although polarimetric calibration (PolCAL) of the SAR system is periodically...

There is currently widespread interest in the development of radar sensors for the detection of surface and buried targets and the remote sensing of land, sea and ice surfaces. An important feature of electromagnetic radiation is its state of polarisation and a wide range of classification algorithms and inversion techniques have recently been developed based on the transformation of polarisati...

This paper presents a robust radial basis function (RBF) network based classifier for polarimetric synthetic aperture radar (SAR) images. The proposed feature extraction process utilizes the covariance matrix, the gray level co-occurrence matrix (GLCM) based texture features, and the backscattering power (Span) combined with the H/α/A decomposition, which are projected onto a lower dimensional ...