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Journal of Applied Remote Sensing

Estimating surface water area changes using time-series Landsat data in the Qingjiang River Basin, China
Author(s): Zhiqiang Du; Linghu Bin; Feng Ling; Wenbo Li; Weidong Tian; Hailei Wang; Yuanmiao Gui; Bingyu Sun; Xiaoming Zhang
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Paper Abstract

The Qingjiang River Basin, which is 423 km long in the Hubei province, China, is the first large tributary of the Yangtze River below the Three Gorges. The Qingjiang River Basin surface water area monitoring plays an important role in the water resource management strategy and regular monitoring management of the Yangtze River watershed. Hydropower cascade exploitation, which started in 1987, has formed three reservoirs including the Geheyan reservoir, the Gaobazhou reservoir, and the Shuibuya reservoir in the midstream and downstream of the Qingjiang River Basin. They have made a great impact on surface water area changes of the Qingjiang River Basin and need to be taken into account. We monitor the Qingjiang River Basin surface water area changes from 1973 to 2010. Ten scenes from the Multispectral Scanner System (MSS), seven scenes from the Thematic Mapper (TM), and two scenes from the Enhanced Thematic Mapper Plus (ETM+) remote sensing data of Landsat satellites, the normalized different water index (NDWI), the modified NDWI (MNDWI), and Otsu image segmentation method were employed to quantitatively estimate the Qingjiang River Basin surface water area in the 1970s, 1980s, 1990s, and 2000s, respectively. The results indicate that the surface water area of the Qingjiang River Basin shows a growing trend with the hydropower cascade development from the 1980s to the first decade of the 21st century. The study concluded the significance of human activities impact on surface water spatiotemporal distribution. Surface water accretion is significant in most parts of the Qingjiang River Basin and might be related to the constructed cascade hydropower dams.

Paper Details

Date Published: 28 November 2012
PDF: 16 pages
J. Appl. Rem. Sens. 6(1) 063609 doi: 10.1117/1.JRS.6.063609
Published in: Journal of Applied Remote Sensing Volume 6, Issue 1
Show Author Affiliations
Zhiqiang Du, Wuhan Univ. (China)
Linghu Bin, Institute of Intelligent Machines (China)
Feng Ling, Institute of Geodesy and Geophysics (China)
Wenbo Li, Institute of Intelligent Machines (China)
Weidong Tian, Hefei Univ. of Technology (China)
Hailei Wang, Institute of Intelligent Machines (China)
Yuanmiao Gui, Institute of Intelligent Machines (China)
Bingyu Sun, Institute of Intelligent Machines (China)
Xiaoming Zhang, Institute of Intelligent Machines (China)

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