Urban geological disaster toughness level evaluation method, system and equipment and storage medium

Abstract

The invention discloses an urban geological disaster toughness level assessment method, system and device, and a storage medium. The method comprises the steps of determining a plurality of geological disaster assessment indexes corresponding to each district and county according to urban geological disaster information; based on an analytic hierarchy process and an entropy weight method, respectively calculating an index weight corresponding to each geological disaster evaluation index; according to the plurality of geological disaster evaluation indexes corresponding to each district and county and the index weight corresponding to each geological disaster evaluation index, calculating the index close degree of each district and county through a TOPSIS method; and evaluating the geological disaster toughness level of the city according to the index closeness degree of each district and county. Compared with insufficient comprehensiveness and strong subjectivity caused by multi-focus single disaster or static indexes in the prior art, the urban geological disaster toughness level is quantitatively evaluated by constructing a scientific and reasonable evaluation index system, so that a scientific basis and decision support are provided for urban geological disaster prevention and control.

Description

Technical Field

[0001] The present invention relates to the technical field of urban resilience assessment, and in particular to a method, system, device and storage medium for assessing the resilience level of urban geological disasters. Background Art

[0002] With the acceleration of urbanization, cities face an increasing risk of geological disasters. Traditional geological hazard assessment methods often focus on a single hazard type or static indicators. By ignoring the synergistic effects of multiple factors, such as social, economic, and infrastructure factors, they lack comprehensiveness and are highly subjective, making it impossible to effectively assess a city's overall resilience.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention The main purpose of the present invention is to provide a method, system, equipment and storage medium for evaluating the level of urban geological disaster resilience, aiming to solve the technical problem of how to effectively evaluate the overall resilience of a city.

[0004] To achieve the above objectives, the present invention provides a method for evaluating the resilience level of urban geological hazards, the method comprising: Determine multiple geological disaster assessment indicators corresponding to each district and county based on the city's geological disaster information; Based on the analytic hierarchy process and entropy weight method, the weights of the indicators corresponding to each geological disaster assessment indicator are calculated respectively; According to the multiple geological hazard assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological hazard assessment indicator, the indicator closeness of each district and county is calculated by the TOPSIS method; The geological disaster resilience level of the city is assessed based on the closeness of the indicators of each district and county.

[0005] Optionally, the step of determining a plurality of geological hazard assessment indicators corresponding to each district and county based on the geological hazard information of the city includes: Determine the geological disaster threat information, urban disaster bearing capacity information and disaster management capacity information corresponding to each district and county based on the city's geological disaster information; Extracting a plurality of geological disaster characteristic data corresponding to each district and county from the geological disaster threat information, the urban disaster bearing capacity information, and the disaster management capacity information; Based on the multiple geological disaster characteristic data corresponding to each district and county, multiple geological disaster assessment indicators corresponding to each district and county are determined.

[0006] Optionally, the step of determining a plurality of geological hazard assessment indicators corresponding to each district and county based on a plurality of geological hazard characteristic data corresponding to each district and county includes: Constructing an evaluation index system corresponding to each district and county based on multiple geological disaster characteristic data corresponding to each district and county, wherein the evaluation index system is constructed by a pressure layer, a state layer, and a response layer; Based on the pressure layer, the state layer and the response layer, a plurality of geological disaster assessment indicators corresponding to each district and county are determined.

[0007] Optionally, the step of respectively calculating the indicator weights corresponding to each geological hazard assessment indicator based on the analytic hierarchy process and the entropy weight method includes: Based on the hierarchical analysis method, the range standardization processing of multiple geological disaster assessment indicators in each district and county was carried out respectively, and the standardized index values ​​corresponding to each geological disaster assessment indicator were obtained; According to the standardized index values ​​corresponding to the geological disaster assessment indicators of each place, the information entropy of the geological disaster assessment indicators of each place is calculated by the entropy weight method; Based on the information entropy of each geological disaster assessment indicator, the indicator weights corresponding to each geological disaster assessment indicator are calculated respectively.

[0008] Optionally, the step of respectively calculating the indicator weights corresponding to each geological disaster assessment indicator based on the information entropy of each geological disaster assessment indicator includes: According to the information entropy of the geological disaster assessment indicators of each region, the index difference coefficient of each region's geological disaster assessment indicators is determined; The indicator weights corresponding to the geological disaster assessment indicators of each place are calculated according to the indicator difference coefficient of each place.

[0009] Optionally, the step of calculating the indicator closeness of each district and county respectively by using the TOPSIS method according to the multiple geological hazard assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological hazard assessment indicator includes: Determine the maximum and minimum values ​​of multiple geological hazard assessment indicators corresponding to each district and county; Based on the TOPSIS method, the ideal solution and negative ideal solution of the indicators are constructed according to the maximum and minimum values ​​of the geological disaster assessment indicators. The indicator closeness of each district and county is calculated based on the ideal solution of the indicator, the negative ideal solution of the indicator and the indicator weights corresponding to each geological disaster assessment indicator.

[0010] Optionally, the step of calculating the indicator closeness of each district and county based on the indicator ideal solution, the indicator negative ideal solution, and the indicator weights corresponding to each geological disaster assessment indicator includes: Based on the indicator weights corresponding to each geological disaster assessment indicator, the ideal weighted Euclidean distance and the negative ideal weighted Euclidean distance of each district and county are calculated according to the standardization indicator values ​​corresponding to each geological disaster assessment indicator, respectively, according to the ideal solution of the indicator and the negative ideal solution of the indicator; The indicator closeness of each district and county is calculated based on the ideal weighted Euclidean distance and negative ideal weighted Euclidean distance of each district and county.

[0011] In addition, to achieve the above-mentioned purpose, the present invention also proposes an urban geological disaster resilience level assessment system, which includes: A determination module is used to determine multiple geological disaster assessment indicators corresponding to each district and county based on the geological disaster information of the city; The calculation module is used to calculate the indicator weights corresponding to each geological disaster assessment indicator based on the hierarchical analysis method and the entropy weight method; The calculation module is further used to calculate the indicator closeness of each district and county respectively through the TOPSIS method according to the multiple geological disaster assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological disaster assessment indicator; The evaluation module is used to evaluate the geological disaster resilience level of the city based on the closeness of the indicators of each district and county.

[0012] In addition, to achieve the above-mentioned purpose, the present invention also proposes a device for evaluating the level of resilience of urban geological hazards, which includes: a memory, a processor, and a program for evaluating the level of resilience of urban geological hazards stored in the memory and executable on the processor, wherein the program for evaluating the level of resilience of urban geological hazards is configured to implement the steps of the method for evaluating the level of resilience of urban geological hazards as described above.

[0013] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a city geological hazard resilience level assessment program is stored. When the city geological hazard resilience level assessment program is executed by a processor, the steps of the city geological hazard resilience level assessment method described above are implemented.

[0014] The present invention first determines the multiple geological disaster assessment indicators corresponding to each district and county based on the geological disaster information of the city, and then calculates the indicator weights corresponding to each geological disaster assessment indicator based on the hierarchical analysis method and the entropy weight method. After that, the indicator closeness of each district and county is calculated by the TOPSIS method according to the multiple geological disaster assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological disaster assessment indicator. Finally, the city's geological disaster resilience level is evaluated based on the indicator closeness of each district and county. Compared with the existing technology that focuses on a single disaster type or static indicators, resulting in insufficient comprehensiveness and strong subjectivity, the present invention quantitatively evaluates the city's geological disaster resilience level by constructing a scientific and reasonable evaluation index system, thereby providing a scientific basis and decision-making support for urban geological disaster prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1Schematic diagram of the structure of the urban geological disaster resilience level assessment device in the hardware operating environment involved in the embodiment of the present invention; Figure 2 This is a flow chart of the first embodiment of the urban geological hazard resilience assessment method of the present invention; Figure 3 This is a structural block diagram of the first embodiment of the urban geological hazard resilience level assessment system of the present invention.

[0016] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0017] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of the urban geological disaster resilience level assessment equipment in the hardware operating environment involved in the embodiment of the present invention.

[0019] like Figure 1 As shown, the urban geological hazard resilience assessment device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display and an input unit, such as a keyboard. Optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a wireless fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. Optionally, the memory 1005 may be a storage system independent of the processor 1001.

[0020] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the urban geological hazard resilience level assessment equipment, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0021] like Figure 1As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an urban geological hazard resilience level assessment program.

[0022] exist Figure 1 In the urban geological hazard resilience level assessment device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the urban geological hazard resilience level assessment device of the present invention can be set in the urban geological hazard resilience level assessment device, and the urban geological hazard resilience level assessment device calls the urban geological hazard resilience level assessment program stored in the memory 1005 through the processor 1001, and executes the urban geological hazard resilience level assessment method provided by the embodiment of the present invention.

[0023] The embodiment of the present invention provides a method for evaluating the resilience level of urban geological hazards, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the urban geological hazard resilience level assessment method of the present invention.

[0024] In this embodiment, the urban geological disaster resilience level assessment method includes the following steps: Step S10: Determine a plurality of geological disaster assessment indicators corresponding to each district and county based on the geological disaster information of the city.

[0025] It is easy to understand that the execution entity of this embodiment can be an urban geological hazard resilience level assessment system with functions such as data processing, network communication and program running, or other computer equipment with similar functions, etc. This embodiment is not limited.

[0026] Furthermore, the processing method for determining multiple geological disaster assessment indicators corresponding to each district and county based on the city's geological disaster information is as follows: determining the geological disaster threat information, urban disaster bearing capacity information and disaster management capacity information corresponding to each district and county based on the city's geological disaster information; extracting multiple geological disaster characteristic data corresponding to each district and county from the geological disaster threat information, urban disaster bearing capacity information and disaster management capacity information; and determining multiple geological disaster assessment indicators corresponding to each district and county based on the multiple geological disaster characteristic data corresponding to each district and county.

[0027] It should be noted that geological disaster threat information includes disaster susceptibility information and meteorological conditions. Disaster susceptibility information includes the density of potential collapse, landslide, and debris flow risk points, and meteorological conditions include the number of days with heavy rain and rainfall.

[0028] The city's disaster bearing capacity information includes economic level information, infrastructure information and social security information. The economic level information can be per capita GDP, the infrastructure information can be the coverage rate of shelters, and the social security information can be the density of medical resources.

[0029] Disaster management capacity information includes the completeness of the early warning system, emergency team construction, and public education investment.

[0030] Furthermore, the processing method for determining multiple geological disaster assessment indicators corresponding to each district and county based on multiple geological disaster characteristic data corresponding to each district and county is to construct an assessment indicator system corresponding to each district and county based on multiple geological disaster characteristic data corresponding to each district and county, and the assessment indicator system is constructed by a pressure layer, a state layer and a response layer; based on the pressure layer, the state layer and the response layer, the multiple geological disaster assessment indicators corresponding to each district and county are determined.

[0031] In its implementation, an assessment indicator system was constructed based on the pressure-state-response framework. Each district and county has multiple geological hazard assessment indicators, including those for the pressure layer, the state layer, and the response layer. The pressure layer includes indicators for disaster susceptibility and meteorological conditions; the state layer includes indicators for economic development, infrastructure, and social security; and the response layer includes indicators for the completeness of the early warning system, emergency response team development, and public education investment.

[0032] The disaster susceptibility index can be expressed as:

[0033] Meteorological condition indicators can be expressed as: P 2 = Average number of rainy days per year P 3 = average annual rainfall The economic level indicator can be expressed as:

[0034] Infrastructure indicators can be expressed as: Social security indicators can be expressed as: The early warning system perfection index can be expressed as: R 1 = Early warning system coverage The emergency team construction indicators can be expressed as:

[0035] The public education investment index can be expressed as:

[0036] Step S20: Calculate the indicator weights corresponding to each geological disaster assessment indicator based on the analytic hierarchy process and the entropy weight method.

[0037] Furthermore, the processing method for calculating the indicator weights corresponding to each geological hazard assessment indicator based on the hierarchical analysis method and the entropy weight method is to perform range standardization processing on multiple geological hazard assessment indicators of each district and county based on the hierarchical analysis method to obtain the standardized indicator values ​​corresponding to each geological hazard assessment indicator; according to the standardized indicator values ​​corresponding to each geological hazard assessment indicator, the information entropy of each geological hazard assessment indicator is calculated by the entropy weight method; based on the information entropy of each geological hazard assessment indicator, the indicator weights corresponding to each geological hazard assessment indicator are calculated.

[0038] In this embodiment, the range method is used to normalize the positive and negative indicators, and the weight of each indicator is determined based on the entropy weight method combined with the Analytic Hierarchy Process (AHP) to ensure the objectivity and scientific nature of the indicator weight and eliminate subjective bias.

[0039] It should also be noted that the positive and negative indicators can be set by the user according to actual conditions. In this embodiment, the indicator corresponding to the pressure layer can be used as a negative indicator, and the indicators corresponding to the state layer and the response layer can be used as positive indicators.

[0040] Range method standardization processing: For positive indicators: For negative indicators:

[0041] in, is the jth original index value of a certain layer in the i-th district or county, is the normalized index value (range 0, 1).

[0042]

[0043] Normalized matrix:

[0044] Calculate the proportion of each district and county in each indicator:

[0045] Calculate information entropy: ,

[0046] Where n is the number of districts and counties.

[0047] Furthermore, the weights of the indicators corresponding to the geological disaster assessment indicators are calculated based on the information entropy of the geological disaster assessment indicators. The index difference coefficients of the geological disaster assessment indicators (i.e., 1-H j ); Calculate the indicator weights corresponding to the geological disaster assessment indicators of each place according to the indicator difference coefficient of each place.

[0048] Calculate the weight of each indicator:

[0049] Where m is the number of indicators.

[0050] Step S30: Calculate the index closeness of each district and county respectively by using the TOPSIS method according to the multiple geological hazard assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological hazard assessment indicator.

[0051] Furthermore, the indicator closeness of each district and county is calculated respectively according to the multiple geological hazard assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological hazard assessment indicator through the approximate ideal solution ranking method or the superior and inferior solution distance method (Technique for Order Preference by Similarity to Ideal Solution TOPSIS). The processing method is to determine the maximum and minimum values ​​of the multiple geological hazard assessment indicators corresponding to each district and county respectively; based on the TOPSIS method, the indicator ideal solution and the indicator negative ideal solution are constructed according to the maximum and minimum values ​​of each geological hazard assessment indicator; and the indicator closeness of each district and county is calculated according to the indicator ideal solution, the indicator negative ideal solution and the indicator weights corresponding to each geological hazard assessment indicator.

[0052] In the specific implementation, the entropy weight-TOPSIS method is used to quantitatively evaluate the level of urban geological disaster resilience, calculate the closeness of each district and county to the ideal solution (T value), and divide the resilience levels (high, relatively high, medium, relatively low, and low).

[0053] Calculate closeness: The ideal solution is a hypothetical solution where each evaluation metric takes the most favorable and ideal value. As the optimal benchmark for evaluation, the closer the evaluation object is to the ideal solution, the better its performance or status.

[0054] A negative ideal solution is a virtual solution where each of the evaluation indicators takes the most unfavorable and undesirable value. As the worst benchmark for evaluation, the further the evaluation object moves from the negative ideal solution, the better its performance or status.

[0055] By calculating the distance between each indicator and the ideal solution and the negative ideal solution, the comprehensive resilience level of the city's geological disaster resilience level is obtained.

[0056] Determine the ideal solution (i.e., the index ideal solution) and the negative ideal solution (i.e., the index negative ideal solution): Ideal solution:

[0057] For each indicator x j : If it is a benefit indicator (the bigger the better), then .

[0058] If it is a cost-type indicator (the smaller the better), then .

[0059] Negative ideal solution:

[0060] For each indicator x j : If it is a benefit indicator (the smaller the better), then .

[0061] If it is a cost-type indicator (the larger the better), then .

[0062] Furthermore, the index closeness of each district and county is calculated based on the index ideal solution, the index negative ideal solution and the index weight corresponding to each geological disaster assessment index. The ideal weighted Euclidean distance and negative ideal weighted Euclidean distance of each district and county are calculated based on the index weight corresponding to each geological disaster assessment index according to the index ideal solution and the index negative ideal solution and the standardized index value corresponding to each geological disaster assessment index. The indicator closeness of each district and county is calculated based on the ideal weighted Euclidean distance and negative ideal weighted Euclidean distance of each district and county.

[0063] Calculate the weighted Euclidean distance between each evaluation object (i.e. each district and county) and the ideal solution and the negative ideal solution: The distance to the ideal solution (i.e., the ideal weighted Euclidean distance):

[0064] The distance to the negative ideal solution (i.e., the negative ideal weighted Euclidean distance):

[0065] Calculate the indicator closeness:

[0066] Where C i is the indicator closeness of the i-th district or county.

[0067] Step S40: Evaluate the geological disaster resilience level of the city based on the indicator proximity of each district and county.

[0068] In the specific implementation, according to the indicator closeness C i Determine the toughness level.

[0069]

[0070] In this embodiment, first, multiple geological disaster assessment indicators corresponding to each district and county are determined based on the geological disaster information of the city. Then, the indicator weights corresponding to each geological disaster assessment indicator are calculated based on the hierarchical analysis method and the entropy weight method. Then, the indicator closeness of each district and county is calculated based on the multiple geological disaster assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological disaster assessment indicator using the TOPSIS method. Finally, the city's geological disaster resilience level is evaluated based on the indicator closeness of each district and county. Compared with the existing technology that focuses on a single type of disaster or static indicators, resulting in insufficient comprehensiveness and strong subjectivity, this embodiment quantitatively evaluates the city's geological disaster resilience level by constructing a scientific and reasonable evaluation index system, thereby providing a scientific basis and decision-making support for urban geological disaster prevention and control.

[0071] Reference Figure 3 , Figure 3 This is a structural block diagram of the first embodiment of the urban geological hazard resilience level assessment system of the present invention.

[0072] like Figure 3 As shown, the urban geological disaster resilience level assessment system proposed in the embodiment of the present invention includes: Determination module 3001, for determining multiple geological disaster assessment indicators corresponding to each district and county based on the geological disaster information of the city; Calculation module 3002, for calculating the indicator weights corresponding to each geological disaster assessment indicator based on the analytic hierarchy process and the entropy weight method; The calculation module 3002 is further configured to calculate the index closeness of each district and county using the TOPSIS method based on the multiple geological hazard assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological hazard assessment indicator; The evaluation module 3003 is used to evaluate the geological disaster resilience level of the city based on the indicator proximity of each district and county.

[0073] Other embodiments or specific implementation methods of the urban geological hazard resilience level assessment system of the present invention can refer to the above-mentioned method embodiments and will not be repeated here.

[0074] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0075] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0076] Through the description of the above embodiments, those skilled in the art will clearly understand that the above-mentioned embodiments and methods can be implemented by means of software plus the necessary general-purpose hardware platform. Of course, hardware can also be used, but in many cases the former is a more preferred embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, or optical disk) and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0077] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for assessing urban geological hazard resilience, characterized in that: The urban geological disaster resilience level assessment method comprises the following steps: Determine multiple geological disaster assessment indicators corresponding to each district and county based on the city's geological disaster information; Based on the analytic hierarchy process and entropy weight method, the weights of the indicators corresponding to each geological disaster assessment indicator are calculated respectively; According to the multiple geological hazard assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological hazard assessment indicator, the indicator closeness of each district and county is calculated by the TOPSIS method; The geological disaster resilience level of the city is assessed based on the closeness of the indicators of each district and county.

2. The method according to claim 1, wherein The step of determining a plurality of geological disaster assessment indicators corresponding to each district and county based on the geological disaster information of the city includes: Determine the geological disaster threat information, urban disaster bearing capacity information and disaster management capacity information corresponding to each district and county based on the city's geological disaster information; Extracting a plurality of geological disaster characteristic data corresponding to each district and county from the geological disaster threat information, the urban disaster bearing capacity information, and the disaster management capacity information; Based on the multiple geological disaster characteristic data corresponding to each district and county, multiple geological disaster assessment indicators corresponding to each district and county are determined.

3. The method according to claim 2, wherein The step of determining a plurality of geological hazard assessment indicators corresponding to each district and county based on a plurality of geological hazard characteristic data corresponding to each district and county includes: Constructing an evaluation index system corresponding to each district and county based on multiple geological disaster characteristic data corresponding to each district and county, wherein the evaluation index system is constructed by a pressure layer, a state layer, and a response layer; Based on the pressure layer, the state layer and the response layer, a plurality of geological disaster assessment indicators corresponding to each district and county are determined.

4. The method according to claim 1, wherein The step of respectively calculating the indicator weights corresponding to each geological disaster assessment indicator based on the analytic hierarchy process and the entropy weight method includes: Based on the hierarchical analysis method, the range standardization processing of multiple geological disaster assessment indicators in each district and county was carried out respectively, and the standardized index values ​​corresponding to each geological disaster assessment indicator were obtained; According to the standardized index values ​​corresponding to the geological disaster assessment indicators of each place, the information entropy of the geological disaster assessment indicators of each place is calculated by the entropy weight method; Based on the information entropy of each geological disaster assessment indicator, the indicator weights corresponding to each geological disaster assessment indicator are calculated respectively.

5. The method according to claim 4, wherein The step of respectively calculating the indicator weights corresponding to each geological disaster assessment indicator based on the information entropy of each geological disaster assessment indicator includes: According to the information entropy of the geological disaster assessment indicators of each region, the index difference coefficient of each region's geological disaster assessment indicators is determined; The indicator weights corresponding to the geological disaster assessment indicators of each place are calculated according to the indicator difference coefficient of each place.

6. The method according to any one of claims 1 to 5, wherein: The step of calculating the index closeness of each district and county respectively by using the TOPSIS method according to the multiple geological hazard assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological hazard assessment indicator includes: Determine the maximum and minimum values ​​of multiple geological hazard assessment indicators corresponding to each district and county; Based on the TOPSIS method, the ideal solution and negative ideal solution of the indicators are constructed according to the maximum and minimum values ​​of the geological disaster assessment indicators. The indicator closeness of each district and county is calculated based on the ideal solution of the indicator, the negative ideal solution of the indicator and the indicator weights corresponding to each geological disaster assessment indicator.

7. The method according to claim 6, wherein The step of calculating the indicator closeness of each district and county based on the indicator ideal solution, the indicator negative ideal solution and the indicator weight corresponding to each geological disaster assessment indicator includes: Based on the indicator weights corresponding to each geological disaster assessment indicator, the ideal weighted Euclidean distance and the negative ideal weighted Euclidean distance of each district and county are calculated according to the standardization indicator values ​​corresponding to each geological disaster assessment indicator, respectively, according to the ideal solution of the indicator and the negative ideal solution of the indicator; The indicator closeness of each district and county is calculated based on the ideal weighted Euclidean distance and negative ideal weighted Euclidean distance of each district and county.

8. An urban geological disaster resilience level assessment system, characterized by: The urban geological disaster resilience level assessment system includes: A determination module is used to determine multiple geological disaster assessment indicators corresponding to each district and county based on the geological disaster information of the city; The calculation module is used to calculate the indicator weights corresponding to each geological disaster assessment indicator based on the hierarchical analysis method and the entropy weight method; The calculation module is further used to calculate the indicator closeness of each district and county respectively through the TOPSIS method according to the multiple geological disaster assessment indicators corresponding to each district and county and the indicator weights corresponding to each geological disaster assessment indicator; The evaluation module is used to evaluate the geological disaster resilience level of the city based on the closeness of the indicators of each district and county.

9. An urban geological disaster resilience level assessment device, characterized in that: The device includes: a memory, a processor, and an urban geological hazard resilience level assessment program stored in the memory and executable on the processor, wherein the urban geological hazard resilience level assessment program is configured to implement the steps of the urban geological hazard resilience level assessment method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a program for evaluating the level of resilience of urban geological hazards. When the program is executed by the processor, the steps of the method for evaluating the level of resilience of urban geological hazards as described in any one of claims 1 to 7 are implemented.

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