Red Layer Of Central Yunnan Landslide Hazard Multivariate Linear Regression Model

Landslide, as one of the major geological disasters around the world, makes huge threaten to people's lives, property and economic construction. China is a country prone to landslide disaster. With the development of construction projects on a large scale, landslide becomes increasingly prominent in process of road, railway, water conservancy and hydropower and other infrastructure construction.It adopts geological survey in field, indoor data processing, fractal, fractal dimensions, model calculation and multi-subjects theory and methods, studying the following problems by the numbers:First, analyze the form conditions and mechanism of various types of representative landslide disasters; discuss the spatial distributing rule of the landslide disasters development.Second, expound the development distributing and diversification rule of the landslide disaster under each influencing factors. In particular, mainly discuss the development distribution rule of the landslide in different aspects, slope gradient, stratum, water fractal dimension and fracture fractal dimension. Analyze diversification rule of the landslide disaster in developing extent and depth in different scope and stratum. Discuss the developing rule direction of the landslide disasters under different slope. Reveal with the change of the slope the mutual-transformation trend diversification rule between landslide disasters in different scope, and the motile diversification rule of the slope under different transformation trend process.Third, By analyzing the diversification of water system fractal value and landslide density, suggest an curve form between ideal water system fractal value and landslide development density.Last, based on above research, choose main index which control the landslide disaster development, and build regression model by SPSS software, establish multiple linear regression equation.In a word, this article discusses the development distributing rule of regional landslide disaster under respective influenced factors and the relationship between landslide density and development influenced factors by multiple linear regression theory. Provide a new idea for judging the effect of each factor in the landslide development process.