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REMOTE SENSING FOR LAND & RESOURCES    2016, Vol. 28 Issue (2) : 8-13     DOI: 10.6046/gtzyyg.2016.02.02
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Progress in the study of vegetation cover classification of multispectral remote sensing imagery
YAN Li, JIANG Weiwei
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
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Abstract  

Vegetation cover classification using multispectral remote sensing imagery is a hot research area, in which various new methods emerge endlessly. On the basis of reading a large number of references, the authors summarized in this paper the status and progress of vegetation cover classification with multispectral remote sensing imagery, analyzed advantages and disadvantages, adaptation and application of each vegetation classification feature and method, pointed out current difficulties and challenge, and predicted future development trend. The analysis suggests that future vegetation cover classification of multispectral remote sensing imagery needs not only innovation of classifier in the aspects of improvement of automation, efficiency, learning rate, adaptation and robustness, but also feature mining of vegetation classification. For the purpose of enhancing such aspects as using feature reparability and fusing multisource data, the adoption of multi-temporal images and the tapping of more new features in vegetation classification seem to be future trends.

Keywords reclamation      remote sensing monitoring      classification system      interpretation criteria      high-resolution remote sensing image     
:  TP79  
Issue Date: 14 April 2016
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WEN Li
WU Haiping
JIANG Fangfang
SU Wei
ZHU Dehai
ZHANG Chao
Cite this article:   
WEN Li,WU Haiping,JIANG Fangfang, et al. Progress in the study of vegetation cover classification of multispectral remote sensing imagery[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 8-13.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.02.02     OR     https://www.gtzyyg.com/EN/Y2016/V28/I2/8

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