Spectral characteristics and feature selection of hyperspectral remote sensing data
Abstract:Hyperspectral remote sensing data with bandwidth of nanometre (nm) level have tens or even several hundreds of channels and contain abundant spectral information. Different channels have their own properties and show the spectral characteristics of various objects in image. Rational feature selection from the varieties of channels is very important for effective analysis and information extraction of hyperspectral data. This paper, taking Shunyi region of Beijing as a study area, comprehensively analysed the spectral characteristics of hyperspectral data. On the basis of analysing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from hyperspectral remote sensing data was proposed.
Document Type: Research Article
Affiliations: 1: China Remote Sensing Satellite Ground Station Chinese Academy of Sciences Beijing, 100086 People's Republic of China 2: LARSIS, Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing, 100101 People's Republic of China 3: Institute of Geography Science Nanjing Normal University Nanjing, 210097 People's Republic of China
Publication date: January 1, 2004