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Shallow landslide susceptibility evaluation method based on data model

A data model and susceptibility technology, applied in the direction of electrical digital data processing, complex mathematical operations, instruments, etc., can solve problems such as structural and infrastructure damage

Pending Publication Date: 2022-07-29
CHONGQING INST OF GEOLOGY & MINERAL RESOURCES +1
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Problems solved by technology

Shallow landslides tend to cause significant damage to structures and infrastructure when they occur in densely populated urban areas despite the small size of the slide

Method used

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  • Shallow landslide susceptibility evaluation method based on data model
  • Shallow landslide susceptibility evaluation method based on data model
  • Shallow landslide susceptibility evaluation method based on data model

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Embodiment Construction

[0052] The following is further described in detail by specific embodiments:

[0053] In the present invention, S1 represents step 1, S101 represents step 01 in S1, S102 represents step 02 in S1, and so on.

[0054] The specific implementation process is as follows:

[0055] Let the study area be N area.

[0056] S1: Landslide data collection: Divide the collected landslide data into modeling group and verification group;

[0057] There are 81 shallow landslides in this study area. Time standard is used to model and verify the sensitivity of landslide failure. 64 of the shallow landslides are used as the modeling group for modeling, and the other 17 are used as the verification group. The model results were compared with 17 shallow landslides for verification.

[0058] Landslide data in the study area were obtained by collecting existing literature, field investigation, and identifying digital terrain feature maps with a scale of 1:10,000. The collected landslide data were d...

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Abstract

The invention relates to the field of landslide disaster prediction, and discloses a shallow landslide susceptibility evaluation method based on a data model. According to the method, shallow landslide susceptibility evaluation is carried out by respectively simulating a damage area and a sliding area, shallow sliding damage is evaluated by using logistic regression (LR), and the LR also has the advantage of allowing integration of variables with abnormal distribution. Furthermore, the LR is insensitive to conditional dependencies of the evoked factors, which may result in an overestimated spatial probability value. For sliding evaluation, a simple CA model is provided. The main purpose of the invention is to construct a final shallow landslide sensitivity map including a failure area and a jumping area. Finally, the invention aims to realize the combination of a low-cost method and limited input data, so that the sensitivity evaluation has good performance and can be easily applied to other research fields.

Description

technical field [0001] The invention relates to the field of landslide disaster prediction, in particular to a shallow landslide susceptibility assessment method based on a data model. Background technique [0002] The potential damage caused by shallow sliding and flow occurs mostly in the sliding path and deposition area. It is a good method to integrate the landslide initiation area and the sliding area for landslide susceptibility evaluation. Therefore, the landslide susceptibility map should include the landslide initiation area as well as the downstream area that may be affected by the moving material; in this framework, the landslide susceptibility analysis is divided into two distinct phases: first, the susceptibility assessment of damage must be determined, then , using information about the starting area as input to the landslide slip modeling. Susceptibility maps of potential failures can be implemented using qualitative or quantitative (statistical and determini...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/28G06F17/16G06F113/08G06F119/14
CPCG06F30/28G06F17/16G06F2113/08G06F2119/14
Inventor 梁丹杨海清陈立川李卓航康燕飞陈念邓兴波魏来
Owner CHONGQING INST OF GEOLOGY & MINERAL RESOURCES
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