Recently, methods based on convolutional neural networks (CNNs) achieve superior
performance in polarimetric synthetic aperture radar (PolSAR) image classification …

Unsupervised methods play an essential role in polarimetric synthetic aperture radar
(PolSAR) image classification, where labeled data are difficult to obtain. However, there is …

The analysis of hybrid-polarimetric synthetic aperture radar (hybrid-pol SAR) data can be
carried out using two different types of analytical approaches. The first approach is by …

合成孔径雷达(Synthetic Aperture Radar, SAR) 应用性能主要受限于同时获取高分辨与宽测绘
幅宽的雷达图像的能力. 而对于极化SAR (Polarimetric SAR, PolSAR) 系统而言 …

Convolutional Neural Network (CNN) models are widely used in supervised Polarimetric
Synthetic Aperture Radar (PolSAR) image classification. They are powerful tools to capture …

Polarimetric SAR (PolSAR) image classification is a critical application of remote sensing
image interpretation. Most of the early algorithms that use hand-crafted features to divide the …

Abstract The microwave Synthetic Aperture Radar (SAR) is an active type of remote sensing.
The classification analysis has become one of the very important task, after the availability of …

Operational sea ice maps are usually generated manually using dual-polarization (DP)
synthetic aperture radar (SAR) satellite imagery, but there is strong interest in automating …

Globally, the rapid loss of mangrove forests often creates long-lasting environmental
damage alongside coastlines, mudflats, and river banks. All-weather, physical monitoring of …

This paper displays a case study which accomplishes crop classification of simulated
compact polarimetric (CP) SAR and fully polarimetric (FP) SAR images with Random Forest …