Improving Selection of Spectral Variables for Vegetation Classification of East Dongting Lake, China, Using a Gaofen-1 Image

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成果类型：

期刊论文

作者：

Song, Renfei;Lin, Hui*;Wang, Guangxing*;Yan, Enping;Ye, Zilin

通讯作者：

Lin, Hui;Wang, Guangxing

作者机构：

[Ye, Zilin; Wang, Guangxing; Lin, Hui; Wang, GX; Song, Renfei; Yan, Enping] Cent South Univ Forestry & Technol, Res Ctr Forest Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China.

[Ye, Zilin; Wang, Guangxing; Lin, Hui; Wang, GX; Song, Renfei; Yan, Enping] Key Lab Forestry Remote Sensing Based Big Data &, Changsha 410004, Hunan, Peoples R China.

[Wang, Guangxing] Southern Illinois Univ, Dept Geog & Environm Resources, Carbondale, IL 62901 USA.

通讯机构：

[Lin, H; Wang, GX] C

[Lin, H; Wang, GX] K

[Wang, Guangxing] S

Cent South Univ Forestry & Technol, Res Ctr Forest Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China.

Key Lab Forestry Remote Sensing Based Big Data &, Changsha 410004, Hunan, Peoples R China.

语种：

英文

关键词：

Class separability measure;Correlation-weighted measure;East Dongting Lake;Gaofen-1 image;Spectral variable selection;Wetland classification

期刊：

Remote Sensing

ISSN：

2072-4292

年：

2018

卷：

期：

页码：

DOI：

10.3390/rs10010050

基金类别：

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [31370639]; Central South University of Forestry and Technology

机构署名：

本校为第一且通讯机构

院系归属：

林学院

摘要：

There is a large amount of remote sensing data available for land use and land cover (LULC) classification and thus optimizing selection of remote sensing variables is a great challenge. Although many methods such as Jeffreys-Matusita (JM) distance and random forests (RF) have been developed for this purpose, the existing methods ignore correlation and information duplication among remote sensing variables. In this study, a novel approach was proposed to improve the measures of potential class separability for the selection of remote sensing variables by taking into account correlations among ...

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Improving Selection of Spectral Variables for Vegetation Classification of East Dongting Lake, China, Using a Gaofen-1 Image

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