Landslide disaster susceptibility spatial prediction method based on clustering-information quantity coupling model

A technology of spatial prediction and information content, which is applied in the fields of prediction, geographic information database, character and pattern recognition, etc. It can solve the problems such as the influence of the accuracy of the information content model, the lack of reliable basis for dividing the breakpoints, and the neglect, and achieve high objectivity. and systematic, high precision, and improved accuracy

Active Publication Date: 2020-03-27
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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The applicant found that this grading method will ignore the similarity between non-adjacent categories, and there is no reliable basis for dividing breakpoints. Elements near so

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  • Landslide disaster susceptibility spatial prediction method based on clustering-information quantity coupling model
  • Landslide disaster susceptibility spatial prediction method based on clustering-information quantity coupling model
  • Landslide disaster susceptibility spatial prediction method based on clustering-information quantity coupling model

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[0021] Sichuan Province is located in the Southwest of my country, and its complex terrain has led to frequent occurrence of geological disasters in the Southwest Mountains in recent years. This poses a serious threat to the life and life safety of local residents. The susceptibility evaluation of landslides can understand the possibility of landslides in a region at a macro level, and provide scientific reference for disaster prevention and mitigation. The present invention selects and analyzes eight evaluation factors such as DEM, slope, slope aspect, curvature, road, water system, vegetation index and stratum lithology, etc., and first uses the K-Means clustering algorithm to analyze topography such as DEM, slope, slope aspect and curvature Evaluation factors are classified into grades; for distance evaluation factors with strong regional continuity such as roads, water systems, vegetation coverage indexes, and stratum lithology, the natural breakpoint method is used to clas...

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Abstract

The invention provides a landslide disaster susceptibility space prediction method based on a clustering-information quantity coupling model. Clustering grading is carried out on evaluation indexes ofthe terrain evaluation factors by adopting a K-means algorithm, the internal relation of each terrain evaluation factor in a single evaluation unit is fully considered, and grading is carried out onthe distance type evaluation factors from the aspect of numerical value by adopting a natural breakpoint method; the information amount of each evaluation factor under different levels is calculatedaccording to the information amount model; and according to the sum of the information amounts of the grades of the evaluation factors of each evaluation unit, the landslide information amount of theevaluation unit is obtained so as to obtain the landslide information amounts of all the evaluation units in the map, and information amount grading is carried out in combination with a frequency ratio model so as to finally obtain a landslide susceptibility grade division map. The method has high spatial prediction precision of landslide disaster susceptibility, and can be used as a basis for disaster prevention and control and disaster treatment.

Description

technical field [0001] The invention relates to geological disaster assessment and prediction technology. [0002] technical background [0003] Geological hazards are formed under the interaction of multiple evaluation factors. Systematic analysis of the contribution of each evaluation factor to the susceptibility of landslide disasters based on information entropy can accurately reflect the development characteristics of geological hazards. The evaluation factor can be some kind of terrain or landform feature. As an effective regional geological disaster prediction method, the traditional information model converts the measured data of the evaluation factors affecting regional stability into information reflecting regional stability. The greater the amount of information, the more prone to geological disasters. high. [0004] The establishment of the information amount model is to classify each evaluation factor, and then calculate the information amount of each evaluatio...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/26G06F16/29G06K9/62
CPCG06Q10/04G06Q10/06393G06Q50/265G06F16/29G06F18/23213Y02A90/10
Inventor 何静刘强许丁友刘乾坤毛宇坤王超
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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