Polarimetric synthetic aperture radar (PolSAR) image classification, an important technique
in the remote sensing area, has been deeply studied for a couple of decades. In order to …

In multidimensional observations, many classification algorithms (supervised or
unsupervised) require the selection of optimum bands in which the classes are most distinct …

摘要为抑制相干斑噪声对极化SAR 图像分类结果的干扰, 本文提出一种综合多特征的极化SAR
图像随机森林分类方法. 该方法首先利用简单线性迭代聚类(SLIC) 算法生成超像素作为分类单元 …

Impervious surface data has become an indicator of the degree of urbanization and the
environmental quality, which inspires the widely use of remote sensing technology in …

This paper aims to develop a new methodology for monitoring forest disturbances and
regrowth using ALOS PALSAR data in tropical regions. In the study, forest disturbances and …

Classification techniques play an important role in the analysis of polarimetric synthetic
aperture radar (PolSAR) images. PolSAR image classification is widely used in the fields of …

Detection of surface water from satellite images is important for water management
purposes like for mapping flood extents, inundation dynamics, and water resources …

This paper proposes a novel unsupervised, non-Gaussian, and contextual segmentation
method that combines an advanced statistical distribution with spatial contextual information …

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the
classification of land cover, such as forest canopies, vegetation, sea ice types, and urban …

Speckle filtering is an indispensable operation in synthetic aperture radar (SAR) image
processing but one which inevitably reduces image resolution. In order to preserve the …