Paper
19 March 2013 Risk degree evaluation on water and soil loss in central Hunan province of red soil hilly region, China
Yuenan Zhang, Zhongwu Li, Zhiliang Chen, Xiaoyan Wang, Xiaochun Peng, Min Yuan, Jinquan Huang
Author Affiliations +
Proceedings Volume 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering; 87620N (2013) https://doi.org/10.1117/12.2019729
Event: Third International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2013), 2013, Sanya, China
Abstract
By taking the red soil hilly region of Central Hunan Province in China as an example, this paper evaluated the risk degree of water and soil loss using analytic hierarchy process (AHP) methods. Firstly, the synthetic index system of water and soil loss risk degree (WSLRD) evaluation was established based on the current situation, natural and human factors. Secondly, the weights of fifteen indices were determined using AHP methods. Finally, a comprehensive evaluation model was used to evaluate the risk degree of water and soil loss at the research locations. The results showed that five cities (Changsha, Zhuzhou, Xiangtan, Loudi, and Yiyang) had a slight degree of risk, while Hengyang and Shaoyang had a middle degree of risk. The WSLRD in this region can provide scientific basis for developing effective plan of soil and water conversation, especially it is of importance to consider human activity factors when evaluating the risk.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuenan Zhang, Zhongwu Li, Zhiliang Chen, Xiaoyan Wang, Xiaochun Peng, Min Yuan, and Jinquan Huang "Risk degree evaluation on water and soil loss in central Hunan province of red soil hilly region, China", Proc. SPIE 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 87620N (19 March 2013); https://doi.org/10.1117/12.2019729
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KEYWORDS
Soil science

Chromium

Vegetation

Matrices

Analytical research

Environmental management

Feature extraction

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