CN-122023724-A - Urban ground collapse risk assessment method and device

CN122023724ACN 122023724 ACN122023724 ACN 122023724ACN-122023724-A

Abstract

The application relates to the field of geological risk analysis, in particular to a method and a device for evaluating urban ground collapse risk. According to the application, the attribute grid table of the associated risk factors is formed by acquiring and preprocessing the multi-source urban geological environment data, so that the geological, environmental and other information of different sources are integrated, and the problems of single detection means and data fragmentation are solved. And secondly, calculating the information magnitude of each risk factor based on the attribute grid table, determining a weight set, and quantifying the risk influence degree in a data driving mode to replace subjective experience judgment. And then, the comprehensive risk value is obtained by summing the information values of the grid risk factors, so that the risk evolution caused by urban dynamic change can be reflected in time, and the timeliness of evaluation is improved. Finally, dividing risk grades according to the frequency distribution inflection points and generating a visual risk partition map, realizing visual presentation and unified management of risk results, effectively integrating data and treatment actions, and further realizing dynamic and accurate prevention and control of underground space risks.

Inventors

QIN GAN
LI LI
Rao Yangan
LING JUN
CHANG HAOSONG
YU LILING
BAI YUYING

Assignees

深圳市城市公共安全技术研究院有限公司
城市安全发展科技研究院(深圳)

Dates

Publication Date: 20260512
Application Date: 20260211

Claims (10)

1. A method for evaluating urban ground collapse risk, the method comprising: Acquiring multi-source urban geological environment data, and preprocessing the urban geological environment data to obtain an attribute grid table of associated risk factors, wherein the attribute grid table comprises a plurality of grids, and the risk factors are used for representing the influence degree of the spatial characteristics of the corresponding grids on the occurrence probability of ground collapse events; calculating information magnitude of each risk factor based on the key evaluation data in the attribute grid table to obtain a factor weight set reflecting a risk rule; Algebraic summation is carried out on the information magnitude of all risk factors in each grid to obtain a comprehensive risk value of each grid; And carrying out statistical analysis on the comprehensive risk values of all grids, dividing risk grades according to inflection points of the frequency distribution curve, and generating a visualized risk partition map.
2. The method of claim 1, wherein preprocessing the urban geological environment data to obtain a grid table of attributes associated with risk factors, comprises: Carrying out spatial registration on the urban geological environment data corresponding to each data source to obtain a spatially aligned multi-source data set; Dividing a research area into regular grids based on the multi-source data set, and associating data in the multi-source data set to corresponding grids to obtain an initial grid data set associated with original attributes; Performing numerical coding on qualitative data in each grid in the initial grid data set, and performing grading interval division on quantitative data to obtain a target grid data set, wherein each grid comprises qualitative data and quantitative data corresponding to spatial characteristics of the grid, the qualitative data are used for representing category type geological environment and engineering characteristics of the grid, and the quantitative data are used for representing numerical type surface deformation, pipe network and engineering parameters of the grid; and integrating corresponding risk factors and collapse label information aiming at each grid in the target grid data set to obtain an attribute grid table of the associated risk factors.
3. The method of claim 2, wherein for each grid in the target grid dataset, integrating the corresponding risk factor with collapse tag information to obtain an attribute grid table of associated risk factors, comprising: based on the target grid data set, extracting qualitative data and quantitative data of each grid to obtain feature data corresponding to each grid; mapping the characteristic data into corresponding ground collapse risk factors to obtain a mapping data set; based on the mapping data set, associating historical collapse label information corresponding to each grid to obtain a fusion data set; and based on the fusion data set, the structured data is arranged to obtain an attribute grid table of the associated risk factors.
4. The method of claim 1, wherein calculating information magnitudes for each risk factor based on key assessment data in the attribute grid table, resulting in a set of factor weights reflecting a law of risk, comprises: Screening risk factors and collapse labels of each grid in the current time period from the attribute grid table to obtain key evaluation data; Counting the number of collapse-containing grids, the total grid area and the total area of the whole collapse grid of the region corresponding to each risk factor based on the key evaluation data to obtain factor probability statistics data; Calculating information magnitude of each risk factor based on the factor probability statistical data; and determining the corresponding weight of each grid based on the information magnitude corresponding to each risk factor, and constructing a factor weight set reflecting the risk rule based on the weight of each grid.
5. The method of claim 1, wherein statistically analyzing the integrated risk values of all grids, classifying risk levels according to inflection points of a frequency distribution curve, and generating a visualized risk partition map, comprises: Acquiring comprehensive risk values of all grids for statistics to obtain frequency distribution data of the comprehensive risk values; Drawing a frequency distribution curve and identifying curve inflection points based on the frequency distribution data of the comprehensive risk values to obtain boundary points of risk levels; classifying the comprehensive risk value of each grid according to the demarcation points of the risk levels to obtain a grid-risk level mapping table; and performing space visualization rendering according to the grid-risk level mapping table and the research area space information to obtain the risk partition map.
6. The method according to claim 1, wherein the method further comprises: monitoring whether a data updating or timing triggering condition is met currently; If the data updating or timing triggering condition is met, acquiring various newly added data and finishing preprocessing to obtain an updated attribute grid table; based on the updated attribute grid table, calculating comprehensive risk values of all grids, generating a most recent risk partition map, and comparing the most recent risk partition map with the risk partition map to obtain a risk assessment result; And determining a target area with increased risk level according to the risk assessment result, obtaining a risk trend early warning report, and pushing corresponding early warning information based on the risk trend early warning report.
7. The method according to claim 1, wherein the method further comprises: matching control strategy entries corresponding to the risk levels in a knowledge base based on the risk partition map; based on the control strategy entries, corresponding monitoring, engineering and management measures are matched in batches according to the risk levels of the grids, and a differential control strategy list of each grid is obtained; And integrating the differential control strategy lists of all grids to generate a differential control strategy suggestion report.
8. An urban floor collapse risk assessment device, the device comprising: The acquisition module is used for acquiring multi-source urban geological environment data, preprocessing the urban geological environment data, and obtaining an attribute grid table associated with risk factors, wherein the attribute grid table is provided with a plurality of grids, and the risk factors are used for representing the influence degree of the space characteristics of the corresponding grids on the occurrence probability of the ground collapse event; The calculation module is used for calculating the information magnitude of each risk factor based on the key evaluation data in the attribute grid table to obtain a factor weight set reflecting a risk rule; The processing module is used for algebraically summing the information magnitude of all risk factors in each grid to obtain a comprehensive risk value of each grid; And the statistical module is used for carrying out statistical analysis on the comprehensive risk values of all grids, dividing the risk level according to the inflection points of the frequency distribution curve and generating a visualized risk partition map.
9. A computer device, comprising: a memory and a processor in communication with each other, the memory having stored therein computer instructions which, upon execution, cause the processor to perform the method of any of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1 to 7.

Description

Urban ground collapse risk assessment method and device Technical Field The invention relates to the field of geological risk analysis, in particular to a method and a device for evaluating urban ground collapse risk. Background The urban ground collapse is used as a typical urban disease, the cause is complex, the concealment is strong, the burst is high, the existing control work is in a fragmentation state, the departments data such as water affairs, living construction and planning, knowledge and actions are lack of unified platform integration, the risk assessment is dependent on history case statistics or expert experience, the subjectivity is strong, and the dynamic change caused by urban construction activities is difficult to reflect in time. In the prior art, a single geophysical prospecting detection method can only acquire a snapshot result, cannot reflect the dynamic development of a cavity, is high in cost and low in efficiency, a pipeline endoscopic detection method can only evaluate the state of a pipeline and cannot quantify the integral risk of coupling the pipeline with an external environment, and a historical data statistical method ignores urban dynamic change, so that the evaluation result is easy to be outdated. Disclosure of Invention In view of the above, the embodiment of the invention provides a method and a device for evaluating urban ground collapse risk, which are used for solving the problems that the detection means is single and lacks dynamic monitoring capability, the risk evaluation is strong in subjectivity and insufficient in timeliness, the data and treatment actions of each department are fragmented, and the dynamic prevention and control of underground space risk are difficult to realize. In a first aspect, an embodiment of the present invention provides a method for evaluating risk of urban ground collapse, where the method includes: Acquiring multi-source urban geological environment data, and preprocessing the urban geological environment data to obtain an attribute grid table of associated risk factors, wherein the attribute grid table comprises a plurality of grids, and the risk factors are used for representing the influence degree of the spatial characteristics of the corresponding grids on the occurrence probability of ground collapse events; calculating information magnitude of each risk factor based on the key evaluation data in the attribute grid table to obtain a factor weight set reflecting a risk rule; Algebraic summation is carried out on the information magnitude of all risk factors in each grid to obtain a comprehensive risk value of each grid; And carrying out statistical analysis on the comprehensive risk values of all grids, dividing risk grades according to inflection points of the frequency distribution curve, and generating a visualized risk partition map. Further, preprocessing the urban geological environment data to obtain an attribute grid table of associated risk factors, including: Carrying out spatial registration on the urban geological environment data corresponding to each data source to obtain a spatially aligned multi-source data set; Dividing a research area into regular grids based on the multi-source data set, and associating data in the multi-source data set to corresponding grids to obtain an initial grid data set associated with original attributes; Performing numerical coding on qualitative data in each grid in the initial grid data set, and performing grading interval division on quantitative data to obtain a target grid data set, wherein each grid comprises qualitative data and quantitative data corresponding to spatial characteristics of the grid, the qualitative data are used for representing category type geological environment and engineering characteristics of the grid, and the quantitative data are used for representing numerical type surface deformation, pipe network and engineering parameters of the grid; and integrating corresponding risk factors and collapse label information aiming at each grid in the target grid data set to obtain an attribute grid table of the associated risk factors. Further, for each grid in the target grid dataset, integrating corresponding risk factors and collapse tag information to obtain an attribute grid table associated with the risk factors, including: based on the target grid data set, extracting qualitative data and quantitative data of each grid to obtain feature data corresponding to each grid; mapping the characteristic data into corresponding ground collapse risk factors to obtain a mapping data set; based on the mapping data set, associating historical collapse label information corresponding to each grid to obtain a fusion data set; and based on the fusion data set, the structured data is arranged to obtain an attribute grid table of the associated risk factors. Further, calculating information magnitude of each risk factor based on the key evaluation data in the attribute gri