[1]JIA Xichun,ZHANG Yu,CONG Peitong.Risk Assessment and Early Warning of Mountain Flood Geological Disaster in Zhongshan County[J].Research of Soil and Water Conservation,2018,25(01):208-214.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
25
Number of periods:
2018 01
Page number:
208-214
Column:
Public date:
2018-02-28
- Title:
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Risk Assessment and Early Warning of Mountain Flood Geological Disaster in Zhongshan County
- Author(s):
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JIA Xichun1, ZHANG Yu2, CONG Peitong1
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1. College of Water Conservancy and Civil Engineering, South China Agriculture University, Guangzhou 510642, China;
2. School of Geographical Science and Tourism, Meizhou Jiaying University, Meizhou, Guangdong 514015, China
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- Keywords:
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mountain flood geological disaster; disaster early warning; geographic information system; generalized regression neural network
- CLC:
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X43
- DOI:
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- Abstract:
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To study the intelligent assessment and early warning of mountain flood geological disaster, Zhongshan County of Guangxi Zhuang Autonomous Region was taken as the research sample. Remote sensing images and actual surveys were used as data sources. Remote sensing images, spectral data and DEM data were processed on ENVI and ArcGIS platforms. The data of the study area were obtained, such as slope, NDVI, soil looseness coefficient, valley and ridge classification and rainfall. These data were taken as the input factors, the risk degree of the mountain flood geological disaster was taken as the output factor. A generalized regression neural network model for risk assessment of mountain flood geological disaster in Zhongshan County was established. After the training of historical data, the model has a strong self-learning function. By case checking, the risk degree calculated by the model is in good agreement with the actual risk degree. The model can be applied to the assessment of the risk degree of the mountain flood geological disaster in Zhongshan County. Through the wireless transmission technology to enter GPS positioning latitude and longitude to the model, the model platform can receive and automatically match the neural network input data, and output the disaster risk degree by the model operation, and output the warning on the user’s terminal, so as to realize the real-time intelligent early warning of the mountain flood geological disaster, which has a good application effect in Zhongshan County.