STUDY ON THE DISTRIBUTION OF GEOLOGICAL HAZARDS BASED ON FRACTAL CHARACTERISTICS – A CASE STUDY OF DACHUAN DISTRICT

• Main Authors: X. Wang, H. Liu, K. Yao, Y. Wei
• Format: Article
• Language: English
• Published: Copernicus Publications 2018-04-01
• Series: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
• Online Access: https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3/1781/2018/isprs-archives-XLII-3-1781-2018.pdf

It is a complicated process to analyze the cause of geological hazard. Through the analysis function of GIS software, 250 landslides were randomly selected from 395 landslide hazards in the study area, superimposed with the types of landforms, annual rainfall and vegetation coverage respectively. It used box dimension method of fractal dimension theory to study the fractal characteristics of spatial distribution of landslide disasters in Dachuan district, and analyse the statistical results. Research findings showed that the The fractal dimension of the landslides in the Dachuan area is 0.9114, the correlation coefficient is 0.9627, and it has high autocorrelation. Zoning statistics according to various natural factors, the fractal dimension between landslide hazard points and deep hill, middle hill area is strong as well as the area whose average annual rainfall is 1050 mm–1250 mm and vegetation coverage is 30 %–60 %. Superposition of the potential hazard distribution map of single influence factors to get the potential hazard zoning of landslides in the area. Verifying the potential hazard zoning map of the potential landslides with 145 remaining disaster points, among them, there are 74 landslide hazard points in high risk area, accounting for 51.03 % of the total. There are 59 landslides in the middle risk area, accounting for 40.69 % of the total, and 12 in the low risk area, accounting for 8.28 % of the total. The matching degree of the verifying result and the potential hazard zoning is high. Therefore, the fractal dimension value divided the degree of geological disaster susceptibility can be described the influence degree of each influence factor to geological disaster point more intuitively, it also can divide potential disaster risk areas and provide visual data support for effective management of geological disasters.