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REMOTE SENSING FOR LAND & RESOURCES    2014, Vol. 26 Issue (2) : 48-53     DOI: 10.6046/gtzyyg.2014.02.09
Technology and Methodology |
Estimation of impervious surface based on semi-constrained spectral mixture analysis
ZHU Honglei1,2, LI Ying1, LIU Zhaoli1, FU Bolin1,2
1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China
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Abstract  

Impervious surface plays an important role in monitoring urban sprawl and understanding human activities. Linear spectral mixture analysis (LSMA) is commonly used to estimate impervious surface due to its simple structure and clear physical meaning. However, previous researches found that LSMA seemed to overestimate slightly impervious surface fraction in less developed areas (0-20%) but underestimate it in the central business district (CBD) (over 80%). To tackle this problem, the authors developed impervious surface of Fujin Town in Heilongjiang Province from the Landsat Thematic Mapper (TM) image by using LSMA model under different constrained conditions and end-members. The results indicated that three end-members (high albedo, soil, and vegetation) semi-constrained LSMA provided a fine performance with a RMSE of 16.71%. Moreover, the paddy field in impervious surface fraction image was removed by using land surface temperature and vegetation coverage data.

Keywords HJ-1B      IRS4      error analysis      single window algorithm      sea water temperature retrieval model      Daya Bay nuclear power plant     
:  TP79  
Issue Date: 28 March 2014
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XIONG Pan
ZHU Li
GU Xingfa
ZHAO Limin
YU Tao
MENG Qingyan
LI Jiaguo
ZHANG Feng
Cite this article:   
XIONG Pan,ZHU Li,GU Xingfa, et al. Estimation of impervious surface based on semi-constrained spectral mixture analysis[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(2): 48-53.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2014.02.09     OR     https://www.gtzyyg.com/EN/Y2014/V26/I2/48

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