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Terrain classification is one of the most important applications of the polarimetric SAR (PolSAR) data. Although many effective methods have been proposed, it is still a hot issue. This paper proposes a novel algorithm using deep convolutional networks (ConvNets) for PolSAR data classification. This algorithm is validated by AirSAR data over San Francisco and ALOS-PALSAR2 data over Shanghai Hengsha...
JERS-1/SAR images taken in 1990's and ALOS/PALSAR images taken in 2000's are used and examined the deforestation status during ~14 years. Many trees had been fallen by a typhoon hit in 2004 in a test site, Tomakomai. There is also a plantation area and the site show active change during the term. The forest stands could be roughly classified for four types, forest stands, vacant, where almost all...
The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest...
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