Remote Sensing Applications and Decision Support

Monitoring urban impervious surface area change using China-Brazil Earth Resources Satellites and HJ-1 remote sensing images

[+] Author Affiliations
Peijun Du

Nanjing University, Key Laboratory for Satellite Mapping Technology and Applications of State Administration of Surveying, Mapping and Geoinformation of China, Nanjing City, No. 163 Xianlin Avenue, Qixia District, Nanjing, Jiangsu Province 210023, China

Nanjing University, Jiangsu Provincial Key Laboratory for Geographic Information Sciences and Technology, No. 163 Xianlin Avenue, Qixia District, Nanjing, Jiangsu Province 210023, China

Junshi Xia

Nanjing University, Key Laboratory for Satellite Mapping Technology and Applications of State Administration of Surveying, Mapping and Geoinformation of China, Nanjing City, No. 163 Xianlin Avenue, Qixia District, Nanjing, Jiangsu Province 210023, China

Nanjing University, Jiangsu Provincial Key Laboratory for Geographic Information Sciences and Technology, No. 163 Xianlin Avenue, Qixia District, Nanjing, Jiangsu Province 210023, China

Li Feng

Nanjing University, Key Laboratory for Satellite Mapping Technology and Applications of State Administration of Surveying, Mapping and Geoinformation of China, Nanjing City, No. 163 Xianlin Avenue, Qixia District, Nanjing, Jiangsu Province 210023, China

Nanjing University, Jiangsu Provincial Key Laboratory for Geographic Information Sciences and Technology, No. 163 Xianlin Avenue, Qixia District, Nanjing, Jiangsu Province 210023, China

J. Appl. Remote Sens. 9(1), 096094 (Jan 21, 2015). doi:10.1117/1.JRS.9.096094
History: Received October 1, 2014; Accepted December 23, 2014
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Abstract.  Impervious surface area (ISA) plays an important role in monitoring urbanization and related environmental changes, and has become a hotspot in urban and environmental studies. Xuzhou City, located in northwest Jiangsu Province, China, is chosen as the study area, and two scenes of China-Brazil Earth Resources Satellites images and one scene of HJ-1 image are employed to estimate ISA percentage and analyze the change trend from 2001 to 2009. Using a linear spectral mixture model (LSMM) and nonlinear backpropagation neural network (BPNN) method, all pixels are decomposed to derive four fraction images representing the abundance of four endmembers: vegetation, high-albedo objects, low-albedo objects, and soil. The ISA percentage is then derived by the combination of high- and low-albedo fraction images after removing the influence of water. Some high spatial resolution images are selected to validate the ISA estimation results, and the experimental results indicate that the accuracy of BPNN is higher than LSMM. By comparing the urban ISA abundances derived by BPNN from three dates, it is found that the ISA of Xuzhou City has increased rapidly from 2001 to 2009, especially in the northeast and southeast regions, corresponding to the urban planning scheme and fast urbanization. Compared to other medium remote sensing images, the revisit cycle of HJ-1 multispectral image is only two days, demonstrating the potential of such data for ISA extraction in urbanization, disaster, and other related applications.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Peijun Du ; Junshi Xia and Li Feng
"Monitoring urban impervious surface area change using China-Brazil Earth Resources Satellites and HJ-1 remote sensing images", J. Appl. Remote Sens. 9(1), 096094 (Jan 21, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096094


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