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Proceedings Paper

Mapping impervious surfaces in the Xiangjiang River basin based on remote sensing spectral indices: a case study in Chang-Zhu-Tan region
Author(s): Xiaoping Zhang; Ying Lyu; Huaguo Zhang; Fang Gong; Yongxin Zhang; Chaokui Li
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Paper Abstract

Increased impervious surfaces pose significant threats to the hydrologic cycle of the Xiangjiang River basin as a consequence of urbanization. Quantifying the percentage of imperviousness within the Xiangjiang River basin is important to pollution control and watershed management. Per-pixel and sub-pixel methods have been widely used for analyzing impervious surface changes, but these methods are considered as complicated, computationally intensive, and sometimes subjective, especially when applied to a large geographic area. In this paper, normalized difference built-up index (NDBI), normalized difference impervious surface index (NDISI), normalized difference vegetation index (NDVI) and enhanced built-up and bareness index (EBBI) were respectively used to estimate impervious surfaces in Chang-ZhuTan region (CZT) of the Xiangjiang River basin, and a comparative analyses was conducted. Then the optimum spectral index was chosen to map the percentage of impervious surfaces for the study area. The results show that the spectral index of NDBI has the optimum estimation of large-scale impervious surfaces, and the percentage of imperviousness in CZT was 13.87%. The water quality in CZT was characterized as “protected”, indicating that water quality protection in the plain areas of CZT is imperative.

Paper Details

Date Published: 5 October 2017
PDF: 8 pages
Proc. SPIE 10428, Earth Resources and Environmental Remote Sensing/GIS Applications VIII, 104281I (5 October 2017); doi: 10.1117/12.2277984
Show Author Affiliations
Xiaoping Zhang, Luoyang Normal Univ. (China)
Hunan Univ. of Science and Technology (China)
The Second Institute of Oceanography, SOA (China)
Ying Lyu, Luoyang Normal Univ. (China)
Huaguo Zhang, The Second Institute of Oceanography, SOA (China)
Fang Gong, The Second Institute of Oceanography, SOA (China)
Yongxin Zhang, Luoyang Normal Univ. (China)
Chaokui Li, Hunan Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10428:
Earth Resources and Environmental Remote Sensing/GIS Applications VIII
Ulrich Michel; Karsten Schulz, Editor(s)

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