Landslide hidden danger assessment method and system
By processing and weighting reference landslide hazard data, and combining the data processing results of multiple landslide hazard elements, the problems of low assessment accuracy and poor adaptability in landslide hazard assessment were solved, achieving a more efficient and accurate landslide risk assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-27
- Publication Date
- 2026-04-10
AI Technical Summary
Existing technologies lack effective verification processes in landslide hazard assessment, are difficult to adapt to dynamically changing risk data, are prone to declining assessment accuracy, rely on human experience, are inefficient and highly subjective, and are difficult to cope with the characteristics of high-dimensional and nonlinear data.
By obtaining reference landslide hazard data with similarity information and multiple landslide hazard elements, data processing and weight assessment are performed. Multiple landslide hazard elements are used to assess the hazard weight of the reference landslide hazard data, and the processing results are determined. This includes comparison and updating of simplified values of data collection points, combined with weight coefficient verification, to improve the accuracy of the assessment results.
This approach achieves more refined and model-adaptable landslide hazard assessments, improves the accuracy and adaptability of assessment results, overcomes the limitations of traditional methods, and enhances data utilization and assessment precision.
Smart Images
Figure CN121836347A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the technical field of landslide hazard assessment, and in particular to a landslide hazard assessment method and system. Background Technology
[0002] The verification and optimization mechanisms for assessment results are inadequate. After obtaining the assessment results of hazard weights, existing technologies lack an effective validity verification process, making it difficult to determine the reliability of the assessment results for each data unit. Furthermore, after the model is trained, there is a lack of fine-tuning mechanisms for specific application scenarios. When faced with new risk data or complex working conditions, the assessment accuracy is prone to significant decline, making it difficult to adapt to the dynamically changing needs of landslide risk prevention and control.
[0003] Furthermore, traditional assessment methods largely rely on data analysis and model debugging dominated by human experience, resulting in low efficiency and strong subjectivity, making it difficult to cope with the high-dimensional, non-linear, and dynamically changing characteristics of landslide risk data. Therefore, how to overcome the limitations of data coverage, lack of refined assessment, and insufficient model adaptability, and construct a landslide risk and hazard assessment method that combines data utilization, assessment refinement, and model generalization ability, has become a core technical challenge that urgently needs to be solved in the field of landslide disaster prevention and control. It is also the key to promoting the transformation of assessment technology from "experience-driven" to "data-intelligent-driven." Summary of the Invention
[0004] To address the technical problems existing in related technologies, this disclosure provides a method and system for assessing landslide hazards.
[0005] A method for assessing landslide hazards, the method comprising: Obtain reference landslide hazard data and corresponding multiple landslide hazard elements; The reference landslide hazard data is processed to determine the processing result of the reference landslide hazard data; Based on the processing results of the reference landslide hazard data using the multiple landslide hazard elements, a hazard weight assessment is performed to obtain the hazard weight assessment result of the reference landslide hazard data, specifically including: For each character in the reference landslide hazard data, the hazard weight is evaluated using the hazard weight evaluation results of each data collection point in the partial landslide hazard data block corresponding to the implemented character in the processing result. This yields a simplified hazard weight evaluation result for the implemented character in the reference landslide hazard data. The data collection points are determined as follows: several sampling ranges are divided in the partial landslide hazard data block corresponding to the implemented character; the simplified values of the several data collection points and the implemented character between the reference landslide hazard data and the source landslide hazard data are compared; within each sampling range, at least one character with the largest simplified value is extracted and determined as the data collection point. The simple hazard weight assessment result of the implementation character in the reference landslide hazard data is updated to obtain the target hazard weight assessment result of the implementation character in the reference landslide hazard data. Based on the target hazard weight evaluation results of each character in the reference landslide hazard data, the hazard weight evaluation results of the reference landslide hazard data are obtained.
[0006] In one standalone embodiment, obtaining reference landslide hazard data and corresponding multiple landslide hazard elements includes: Obtain multiple matching landslide hazard data that have similarity information to the reference landslide hazard data; Obtain the similarity and difference of landslide hazard data between each of the matched landslide hazard data and the reference landslide hazard data; A preset number of matching landslide hazard data that meet preset conditions in terms of similarity and difference are identified as the multiple landslide hazard elements.
[0007] In one standalone embodiment, processing the reference landslide hazard data and determining the processing result of the reference landslide hazard data includes: The processing result of the reference landslide hazard data is formed by assigning all character attribute descriptions to the reference landslide hazard data whose hazard weight assessment results are unknown.
[0008] In one independent embodiment, the step of using the hazard weight assessment results of each data collection point in a portion of the landslide hazard data block corresponding to the implementation character in the reference landslide hazard data to perform hazard weight assessment, and obtaining a simple hazard weight assessment result of the implementation character in the reference landslide hazard data, includes: The hazard weight assessment result of the data collection point with the largest corresponding simplified value in the processing result is determined as the simplified hazard weight assessment result of the implementation character in the reference landslide hazard data.
[0009] In one standalone embodiment, updating the simple hazard weight assessment result of the implementing character in the reference landslide hazard data to obtain the target hazard weight assessment result of the implementing character in the reference landslide hazard data includes: The attribute description content of the implementation character in the reference landslide hazard data is cleaned; Compare the simplified values before and after cleaning; In response to the fact that the simplified value after cleaning is better than the simplified value before cleaning, the attribute description content of the implementation character in the reference landslide hazard data is replaced with the attribute description content after cleaning, so as to obtain the target hazard weight evaluation result of the implementation character in the reference landslide hazard data.
[0010] In one standalone embodiment, after performing a hazard weight assessment on the processing results of the reference landslide hazard data based on the plurality of landslide hazard elements to obtain the hazard weight assessment result of the reference landslide hazard data, the method further includes: Based on the reference landslide hazard data and the multiple landslide hazard elements, the hazard weight assessment results of the reference landslide hazard data are processed to obtain the processing results of the reference landslide hazard data.
[0011] In one standalone embodiment, the step of processing the hazard weight assessment results of the reference landslide hazard data based on the reference landslide hazard data and the plurality of landslide hazard elements to obtain the processing result of the reference landslide hazard data includes: Based on the hazard weight assessment results of the reference landslide hazard data and the hazard weight assessment results of the multiple landslide hazard elements, the corresponding weight coefficients are obtained; For each character, determine whether the corresponding weight coefficient meets the preset conditions; If the weight coefficient corresponding to the implemented character meets the preset conditions, the risk assessment result of the implemented character is determined to be valid; If the weight coefficient corresponding to the implemented character does not meet the preset conditions, the risk assessment result of the implemented character is determined to be invalid.
[0012] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects.
[0013] A method and system for assessing landslide hazards involves obtaining reference landslide hazard data with similarity information and corresponding multiple landslide hazard elements. After processing the reference landslide hazard data, the processing result can be determined. Then, the processing result of the reference landslide hazard data is evaluated using multiple landslide hazard elements to obtain the hazard weight evaluation result of the reference landslide hazard data. By evaluating the hazard weight of the reference landslide hazard data through the processing result, the obtained hazard weight evaluation result of the reference landslide hazard data can better handle detailed structures, which is conducive to improving the accuracy of hazard identification.
[0014] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Attached Figure Description
[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the principles of this application.
[0016] Figure 1 A flowchart illustrating a landslide hazard assessment method provided in this application embodiment; Detailed Implementation
[0017] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0018] Based on the above, please refer to the following: Figure 1 This is a flowchart illustrating a landslide hazard assessment method provided in this application embodiment. Further, a landslide hazard assessment method may specifically include the content described in the following steps S11-S13.
[0019] Step S11: Obtain reference landslide hazard data and corresponding multiple landslide hazard elements. The source landslide hazard data and the reference landslide hazard data have similarity information.
[0020] Step S12: Process the reference landslide hazard data and determine the processing result of the reference landslide hazard data.
[0021] In one embodiment, step S12 may specifically include: assigning character attribute descriptions to all characters in the reference landslide hazard data whose hazard weight assessment results are unknown, thereby forming the processing result of the reference landslide hazard data.
[0022] Step S13: Based on the processing results of the reference landslide hazard data using the multiple landslide hazard elements, perform a hazard weight assessment to obtain the hazard weight assessment result of the reference landslide hazard data.
[0023] The above scheme obtains reference landslide hazard data with similarity information and corresponding multiple landslide hazard elements. After processing the reference landslide hazard data, the processing result can be determined. Then, multiple landslide hazard elements are used to evaluate the hazard weight of the processed reference landslide hazard data, obtaining the hazard weight evaluation result of the reference landslide hazard data. By evaluating the hazard weight of the processed reference landslide hazard data, the obtained hazard weight evaluation result of the reference landslide hazard data can better handle the detailed structure, which is conducive to improving the accuracy of hazard identification.
[0024] In one embodiment, after step S13 above, the landslide hazard data depth estimation method may further include: Step S14: Based on the reference landslide hazard data and the multiple landslide hazard elements, process the hazard weight evaluation results of the reference landslide hazard data to obtain the processing results of the reference landslide hazard data.
[0025] The above scheme, after evaluating the hazard weights of the reference landslide hazard data using multiple landslide hazard elements and obtaining the hazard weight evaluation results of the reference landslide hazard data, processes the hazard weight evaluation results of the reference landslide hazard data based on the reference landslide hazard data and multiple landslide hazard elements to obtain the processed results of the reference landslide hazard data. Furthermore, by using multiple landslide hazard elements to determine the processed results of the reference landslide hazard data and evaluating the hazard weights of the processed results, the obtained hazard weight evaluation results of the reference landslide hazard data can better handle the detailed structure, which is conducive to improving the accuracy of hazard identification.
[0026] A flowchart illustrating an embodiment of step S11. In this embodiment, step S11 may specifically include the following steps: Step S111: Obtain multiple matching landslide hazard data that have similarity information to the reference landslide hazard data.
[0027] Step S112: Obtain the similarity and difference of landslide hazard data between each of the matched landslide hazard data and the reference landslide hazard data.
[0028] Step S113: Extract a preset number of matching landslide hazard data that meet preset conditions for similarity and difference between the landslide hazard data and the landslide hazard data, and determine them as the multiple landslide hazard elements.
[0029] Therefore, among all matching landslide hazard data with similarity information to the reference landslide hazard data, multiple matching landslide hazard data whose similarity and difference meet the preset conditions are selected as multiple landslide hazard elements. This allows the processing results of the reference landslide hazard data to be determined using multiple landslide hazard elements. When evaluating the hazard weight of the processing results of the reference landslide hazard data, a wider range of hazard weight evaluation results for the reference landslide hazard data can be obtained, which is beneficial for estimating the accurate hazard weight evaluation results of the reference landslide hazard data.
[0030] A flowchart illustrating an embodiment of step S13. In this embodiment, step S13 may specifically include the following steps: Step S131: For each character in the reference landslide hazard data, the hazard weight is evaluated using the hazard weight evaluation results of each data collection point in the partial landslide hazard data block corresponding to the implementation character in the reference landslide hazard data, so as to obtain the simple hazard weight evaluation result of the implementation character in the reference landslide hazard data.
[0031] Step S132: Update the simple hazard weight assessment result of the implementation character in the reference landslide hazard data to obtain the target hazard weight assessment result of the implementation character in the reference landslide hazard data.
[0032] Step S133: Based on the target hazard weight evaluation results of each character in the reference landslide hazard data, obtain the hazard weight evaluation results of the reference landslide hazard data.
[0033] For each character in the reference landslide hazard data, determine the data collection points in the corresponding landslide hazard data block of the implementation character. Then, using the hazard weight evaluation results of each data collection point in the corresponding landslide hazard data block of the implementation character in the processing results of the reference landslide hazard data, propagate the hazard weight evaluation results of each data collection point in the processing results of the reference landslide hazard data to the implementation character to obtain a simple hazard weight evaluation result of the implementation character in the reference landslide hazard data.
[0034] A flowchart illustrating an embodiment of step S131. In this embodiment, step S131 may specifically include the following steps: Step S1311: Obtain several data collection points from the partial landslide hazard data block corresponding to the implementation character.
[0035] Step S1312: Compare the simplified values of the plurality of data collection points and the implementation character between the reference landslide hazard data and the source landslide hazard data, and determine the hazard weight evaluation result of the data collection point with the largest simplified value in the processing result as the simplified hazard weight evaluation result of the implementation character in the reference landslide hazard data.
[0036] In a single iteration, each character, in addition to considering the simplified value corresponding to its own attribute description, also needs to consider the simplified value corresponding to the attribute description of the data collection point. By obtaining several data collection points in the partial landslide hazard data block corresponding to the implementation character, and then comparing the simplified values of several data collection points and the implementation character between the reference landslide hazard data and the source landslide hazard data, the hazard weight evaluation result of the data collection point with the largest simplified value in the processing result is propagated to the implementation character, thereby realizing the rapid propagation of the hazard weight evaluation result of the data collection point to the implementation character, which can improve the convergence speed of the propagation process.
[0037] A flowchart illustrating an embodiment of step S1311. In this embodiment, step S1311 may specifically include the following steps: Step S13111: Divide the partial landslide hazard data block corresponding to the implementation character into several sampling ranges.
[0038] Step S13112: Within each sampling range, extract at least one character with the largest simplified value and determine it as the data acquisition point.
[0039] A flowchart illustrating an embodiment of step S132. In this embodiment, step S132 may specifically include the following steps: Step S1321: Clean the attribute description content of the implementation character in the reference landslide hazard data.
[0040] Step S1322: Compare the simplified values before and after cleaning.
[0041] Step S1323: In response to the simplified value after cleaning being better than the simplified value before cleaning, the attribute description content of the implementation character in the reference landslide hazard data is replaced with the attribute description content after cleaning, so as to obtain the target hazard weight evaluation result of the implementation character in the reference landslide hazard data.
[0042] A flowchart illustrating an embodiment of step S14. In this embodiment, step S14 may specifically include the following steps: Step S141: Based on the hazard weight assessment results of the reference landslide hazard data and the hazard weight assessment results of the multiple landslide hazard elements, obtain the corresponding weight coefficients.
[0043] Step S142: For each character, determine whether the corresponding weight coefficient meets the preset conditions.
[0044] Step S143: In response to the weight coefficient corresponding to the implemented character meeting the preset conditions, the potential risk weight assessment result of the implemented character is determined to be valid.
[0045] Step S144: In response to the fact that the weight coefficient corresponding to the implemented character does not meet the preset conditions, the risk assessment result of the implemented character is determined to be invalid.
[0046] It should be understood that this application is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.
Claims
1. A method for assessing landslide hazard, characterized in that, The method includes: Obtain reference landslide hazard data and corresponding multiple landslide hazard elements; The reference landslide hazard data is processed to determine the processing result of the reference landslide hazard data; Based on the processing results of the reference landslide hazard data using the multiple landslide hazard elements, a hazard weight assessment is performed to obtain the hazard weight assessment result of the reference landslide hazard data, specifically including: For each character in the reference landslide hazard data, the hazard weight is evaluated using the hazard weight evaluation results of each data collection point in the partial landslide hazard data block corresponding to the implemented character in the processing result. This yields a simplified hazard weight evaluation result for the implemented character in the reference landslide hazard data. The data collection points are determined as follows: several sampling ranges are divided in the partial landslide hazard data block corresponding to the implemented character; the simplified values of the several data collection points and the implemented character between the reference landslide hazard data and the source landslide hazard data are compared; within each sampling range, at least one character with the largest simplified value is extracted and determined as the data collection point. The simple hazard weight assessment result of the implementation character in the reference landslide hazard data is updated to obtain the target hazard weight assessment result of the implementation character in the reference landslide hazard data. Based on the target hazard weight evaluation results of each character in the reference landslide hazard data, the hazard weight evaluation results of the reference landslide hazard data are obtained.
2. The method for estimating the depth of landslide hazard data according to claim 1, characterized in that, The acquisition of reference landslide hazard data and corresponding multiple landslide hazard elements includes: Obtain multiple matching landslide hazard data that have similarity information to the reference landslide hazard data; Obtain the similarity and difference of landslide hazard data between each of the matched landslide hazard data and the reference landslide hazard data; A preset number of matching landslide hazard data that meet preset conditions in terms of similarity and difference are identified as the multiple landslide hazard elements.
3. The method for estimating the depth of landslide hazard data according to claim 1, characterized in that, The process of processing the reference landslide hazard data and determining the processing result of the reference landslide hazard data includes: The processing result of the reference landslide hazard data is formed by assigning all character attribute descriptions to the reference landslide hazard data whose hazard weight assessment results are unknown.
4. The method for estimating the depth of landslide hazard data according to claim 1, characterized in that, The method involves using the hazard weight assessment results of each data collection point in the partial landslide hazard data block corresponding to the implementation character in the reference landslide hazard data to perform hazard weight assessment, thereby obtaining a simple hazard weight assessment result for the implementation character in the reference landslide hazard data, including: The hazard weight assessment result of the data collection point with the largest corresponding simplified value in the processing result is determined as the simplified hazard weight assessment result of the implementation character in the reference landslide hazard data.
5. The method for estimating the depth of landslide hazard data according to claim 1, characterized in that, The step of updating the simple hazard weight assessment result of the implementing character in the reference landslide hazard data to obtain the target hazard weight assessment result of the implementing character in the reference landslide hazard data includes: The attribute description content of the implementation character in the reference landslide hazard data is cleaned; Compare the simplified values before and after cleaning; In response to the fact that the simplified value after cleaning is better than the simplified value before cleaning, the attribute description content of the implementation character in the reference landslide hazard data is replaced with the attribute description content after cleaning, so as to obtain the target hazard weight evaluation result of the implementation character in the reference landslide hazard data.
6. The method for estimating the depth of landslide hazard data according to claim 1, characterized in that, After performing a hazard weight assessment on the processing results of the reference landslide hazard data based on the multiple landslide hazard elements to obtain the hazard weight assessment results of the reference landslide hazard data, the method further includes: Based on the reference landslide hazard data and the multiple landslide hazard elements, the hazard weight assessment results of the reference landslide hazard data are processed to obtain the processing results of the reference landslide hazard data.
7. The method for estimating the depth of landslide hazard data according to claim 6, characterized in that, The process of processing the hazard weight assessment results of the reference landslide hazard data based on the reference landslide hazard data and the multiple landslide hazard elements to obtain the processing result of the reference landslide hazard data includes: Based on the hazard weight assessment results of the reference landslide hazard data and the hazard weight assessment results of the multiple landslide hazard elements, the corresponding weight coefficients are obtained; For each character, determine whether the corresponding weight coefficient meets the preset conditions; If the weight coefficient corresponding to the implemented character meets the preset conditions, the risk assessment result of the implemented character is determined to be valid; If the weight coefficient corresponding to the implemented character does not meet the preset conditions, the risk assessment result of the implemented character is determined to be invalid.
8. A landslide hazard assessment system, characterized in that, It includes a processor and a memory that communicate with each other, the processor being used to read a computer program from the memory and execute it to implement the method of any one of claims 1-7.