Human settlement space toughness detection method

Abstract

The invention discloses a human settlement space toughness detection method, and relates to the technical field of toughness detection, and the method comprises the steps: obtaining a plurality of different spatial data of a target human settlement city; processing a plurality of different spatial data, and constructing an urban spatial database for the processed data; determining index values of a plurality of toughness indexes of the target living city based on the city spatial database; and based on the index values of the plurality of toughness indexes, determining the spatial toughness of the target living city. Through combined calculation of different toughness indexes, the finally obtained spatial toughness can reflect toughness evaluation results of different targets and different perspectives of a target human settlement city, so that the evaluation of the spatial toughness is more comprehensive.

Description

Technical Field

[0001] The present invention relates to the technical field of urban resilience detection, and in particular to a method for detecting the resilience of a residential space. Background Art

[0002] Resilience is the process of a system's actions and state changes in a series of events, including pre-disaster preparation activities, emergency response when a disaster occurs, and the implementation of emergency plans after a disaster. In recent years, the concept of resilience has gradually been combined with the development of human settlement cities, forming the concept of human settlement space resilience. Spatial resilience will affect the regional system at multiple spatial and temporal scales, and is a branch system of resilience that changes in space. Summary of the invention

[0003] In view of this, an object of the present invention is to provide a method for detecting the resilience of a human settlement space.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] A method for detecting the toughness of a human settlement space, the method comprising the following steps:

[0006] Obtain various spatial data of the target residential city;

[0007] Process a variety of spatial data and build an urban spatial database based on the processed data;

[0008] Determining index values ​​of a plurality of resilience indicators of the target residential city based on the urban spatial database;

[0009] Based on the index values ​​of the multiple resilience indicators, the spatial resilience of the target residential city is determined.

[0010] In some embodiments of the present invention, the obtaining of a variety of different spatial data of the target residential city includes:

[0011] Acquire location point of interest data of the target residential city, wherein the location point of interest data includes name information, type information and location information of the location point of interest;

[0012] The processing of a variety of different spatial data includes:

[0013] Acquire the location point of interest data whose type information is first type of information from the location point of interest data as firefighting facility point data, wherein the first type of information is firefighting related information;

[0014] Acquire the location point of interest data whose type information is second type of information from the location point of interest data as emergency shelter facility point data, wherein the location represented by the second type of information is suitable for emergency sheltering from an earthquake;

[0015] The acquisition of various spatial data of the target residential city includes:

[0016] Acquire medical facility data of the target residential city, wherein the medical facility data includes location information, name information, nature information, and grade information of the medical facilities;

[0017] The processing of a variety of different spatial data includes:

[0018] Based on the medical facility data, determining the medical facility point data;

[0019] The step of constructing an urban space database based on the processed data includes:

[0020] The urban space database is constructed based on the fire protection facility point data, medical facility point data and emergency shelter facility point data.

[0021] In some embodiments of the present invention, determining the index values ​​of multiple resilience indicators of the target residential city based on the urban space database includes:

[0022] Determine each block unit of the target residential city;

[0023] Determine the fire facility robustness, fire facility redundancy, fire facility diversity and fire facility rapidity of each of the block units according to the fire facility point data, wherein the fire facility diversity includes fire facility selection diversity and fire facility transfer diversity;

[0024] Determine the robustness, redundancy, diversity and rapidity of medical facilities of each of the block units according to the medical facility point data, wherein the diversity of medical facilities includes the diversity of medical facility selection and the diversity of medical facility transfer;

[0025] Based on the emergency shelter facility point data, the emergency shelter facility robustness, emergency shelter facility redundancy, emergency shelter facility diversity and emergency shelter facility rapidity of each of the block units are determined, and the emergency shelter facility diversity includes emergency shelter facility selection diversity and emergency shelter facility transfer diversity.

[0026] In some embodiments of the present invention, determining the firefighting facility robustness, firefighting facility redundancy, firefighting facility diversity and firefighting facility rapidity of each of the block units according to the firefighting facility point data includes:

[0027] Determine the centrality of each fire protection facility point within each block unit;

[0028] Determine the robustness of the firefighting facilities of each block unit based on the centrality of each firefighting facility point in each block unit;

[0029] Determine the service area of ​​each fire protection facility;

[0030] Determine the redundancy of firefighting facilities in each block unit based on the number of firefighting facilities points with overlapping service areas in each block unit;

[0031] Determine the number of selectable facilities for each fire demand point in each block unit, and determine the diversity of fire facility options for each of the block units;

[0032] Determine the number of facilities that can be transferred within a preset range for each fire demand point in each block unit, and determine the diversity of fire facility transfers in each of the block units;

[0033] Determine the rapidity of firefighting facilities at each firefighting facility point based on the shortest travel time between each firefighting facility point and other firefighting facility points other than the firefighting facility point;

[0034] Based on the firefighting facility rapidity of each firefighting facility point within each block unit, the firefighting facility rapidity of each block unit is determined.

[0035] In some embodiments of the present invention, determining the robustness, redundancy, diversity and rapidity of medical facilities of each of the block units according to the medical facility point data includes:

[0036] Determine the centrality of each of the medical facilities within each block unit;

[0037] Determine the robustness of the medical facilities in each block unit based on the centrality of each of the medical facilities in each block unit;

[0038] Determine the service area of ​​each of the medical facilities;

[0039] Determine the redundancy of medical facilities in each block unit based on the number of medical facilities with overlapping service areas in each block unit;

[0040] Determine the number of selectable facilities for each medical demand point in each block unit, and determine the diversity of medical facility options for each block unit;

[0041] Determine the number of facility points that can be transferred within a preset range for each medical demand point in each block unit, and determine the diversity of medical facility transfers in each of the block units;

[0042] Determine the medical facility rapidity of each medical facility point based on the shortest travel time between each medical facility point and other medical facility points except the medical facility point;

[0043] Based on the medical facility rapidity of each of the medical facility points within each block unit, the medical facility rapidity of each block unit is determined.

[0044] In some embodiments of the present invention, determining the robustness of emergency shelter facilities, the redundancy of emergency shelter facilities, the diversity of emergency shelter facilities, and the rapidity of emergency shelter facilities of each of the block units based on the emergency shelter facility point data includes:

[0045] Determine the centrality of each of the emergency shelter facilities within each block unit;

[0046] Determining the robustness of the emergency shelter facilities in each block unit based on the centrality of each of the emergency shelter facility points in each block unit;

[0047] Determine the service area of ​​each of the emergency shelter facilities;

[0048] Determining the redundancy of emergency shelter facilities in each block unit based on the number of emergency shelter facilities in which the service areas of each block unit overlap;

[0049] Determine the number of facility points available for each emergency shelter demand point within each block unit, and determine the diversity of emergency shelter facility options for each of the block units;

[0050] Determine the number of facilities that can be transferred within a preset range for each emergency shelter demand point in each block unit, and determine the diversity of emergency shelter facility transfers in each of the block units;

[0051] Determine the facility rapidity of each emergency shelter facility point based on the shortest travel time between each emergency shelter facility point and other emergency shelter facility points other than the emergency shelter facility point;

[0052] Based on the emergency shelter facility rapidity of each of the emergency shelter facility points within each block unit, the emergency shelter facility rapidity of each block unit is determined.

[0053] In some embodiments of the present invention, determining the spatial resilience of the target residential city based on the index values ​​of the multiple resilience indicators includes:

[0054] Normalizing the robustness, redundancy, diversity and rapidity of fire-fighting facilities of each of the block units, the robustness, redundancy, diversity and rapidity of medical facilities of each of the block units, and the robustness, redundancy, diversity and rapidity of emergency shelter facilities of each of the block units;

[0055] Determine the spatial resilience of firefighting facilities in each of the block units based on the normalized robustness, redundancy, diversity and rapidity of firefighting facilities in each of the block units;

[0056] Determine the medical facility spatial resilience of each of the block units based on the normalized medical facility robustness, medical facility redundancy, medical facility diversity and medical facility rapidity of each of the block units;

[0057] Determine the spatial resilience of the emergency shelter facilities of each of the block units based on the normalized robustness of the emergency shelter facilities, the redundancy of the emergency shelter facilities, the diversity of the emergency shelter facilities, and the rapidity of the emergency shelter facilities of each of the block units;

[0058] The spatial resilience of the target residential city is determined based on the spatial resilience of the fire-fighting facilities of each block unit, the spatial resilience of the medical facilities of each block unit, and the spatial resilience of the emergency shelter facilities of each block unit.

[0059] In some embodiments of the present invention, the method further comprises the following steps:

[0060] Acquire urban road traffic data of the target inhabited city, wherein the urban road traffic data includes location information, length information, type information and road name of the road;

[0061] Acquire building data of the target residential city, wherein the building data includes location and size information of the building, and the size information includes length, width and height;

[0062] Constructing a post-disaster scenario based on the urban road traffic data and the building data;

[0063] Determine the post-disaster spatial resilience of the target human settlement city in post-disaster scenarios.

[0064] In some embodiments of the present invention, constructing a post-disaster scene based on the urban road traffic data and the building data includes:

[0065] Based on the building data and a preset earthquake level, determining a building in the building data that is predicted to collapse;

[0066] Determine the impact area after the collapse of each building predicted to collapse;

[0067] Based on each of the impact areas, determining the interrupted roads in the urban road traffic data and the interruption points in the interrupted roads, so as to update the urban road traffic data;

[0068] Based on the updated urban road traffic data, updating the urban space database;

[0069] Determining index values ​​of multiple post-disaster resilience indicators of the target residential city based on the updated urban spatial database;

[0070] Based on the index values ​​of the multiple post-disaster resilience indicators, the post-disaster spatial resilience of the target residential city is determined.

[0071] In some embodiments of the present invention, the method further includes: determining a fire facility point adjustment strategy, a medical facility point adjustment strategy, an emergency shelter facility point adjustment strategy, and / or a road planning adjustment strategy based on the post-disaster spatial resilience of the target residential city.

[0072] The beneficial effects of the human settlement space toughness detection method provided by the present invention are:

[0073] An urban spatial database is constructed based on various spatial data of the target residential city, and the index values ​​of multiple resilience indicators of the target residential city are determined based on the urban spatial database, and finally the spatial resilience of the target residential city is determined. In this way, through the combined calculation of different resilience indicators, the final spatial resilience can reflect the resilience assessment results of the target residential city with different goals and different perspectives, making the assessment of spatial resilience more comprehensive. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings.

[0075] Figure 1 A schematic diagram showing a flow chart of a method for detecting the toughness of a living space provided by a specific embodiment of the present invention;

[0076] Figure 2 A schematic diagram showing a flow chart of determining the index values ​​of multiple resilience indicators in a method for detecting resilience of a human settlement space provided in a specific embodiment of the present invention;

[0077] Figure 3 A schematic diagram showing a flow chart of determining the robustness, redundancy, diversity and rapidity of various facilities in a human settlement space resilience detection method provided by a specific embodiment of the present invention;

[0078] Figure 4A schematic diagram showing a process of determining the spatial resilience of a target residential city in a method for detecting residential space resilience provided in a specific embodiment of the present invention;

[0079] Figure 5 Another schematic flow chart of a method for detecting the toughness of a living space provided by a specific embodiment of the present invention is shown;

[0080] Figure 6 A schematic diagram of the process of constructing a post-disaster scenario in a method for detecting resilience of a living space provided in a specific embodiment of the present invention is shown. DETAILED DESCRIPTION

[0081] The present invention is described below based on embodiments. Those skilled in the art should understand that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0082] Unless the context clearly requires otherwise, throughout the specification and claims, the words "include", "comprising" and similar words should be interpreted in an inclusive sense rather than an exclusive or exhaustive sense; that is, in the sense of "including but not limited to".

[0083] Resilience is the process of a system's actions and state changes in a series of events, including pre-disaster preparation activities, emergency response when a disaster occurs, and the implementation of emergency plans after a disaster. In recent years, the concept of resilience has gradually been combined with the development of human settlement cities, forming the concept of human settlement space resilience. Spatial resilience will affect the regional system at multiple spatial and temporal scales, and is a branch system of resilience that changes in space.

[0084] An exemplary embodiment of the present disclosure provides a method for detecting the resilience of a human settlement space, such as Figure 1 As shown, the method comprises the following steps:

[0085] S100: Acquire various spatial data of the target residential city.

[0086] Spatial data may include, for example, building data, road data, medical and other facility data related to spatial resilience of the target residential city, etc., which can be obtained from statistical data, survey data, remote sensing image data, urban planning data, map data and other data.

[0087] S200, processing a variety of different spatial data, and constructing an urban spatial database based on the processed data.

[0088] The processing of various spatial data may include, for example, target data extraction, noise data removal, invalid data removal, duplicate data merging, etc. After the processing of various spatial data is completed, the processed data may be used to construct an urban spatial database, so that the spatial resilience of the target residential city may be determined based on the data in the urban spatial database.

[0089] S300. Determine the index values ​​of multiple resilience indicators of the target residential city based on the urban space database.

[0090] In this step, the index values ​​of multiple different resilience indicators are determined based on the urban space database. The resilience indicators may include, for example, robustness, redundancy, diversity, rapidity, adaptability, resilience, flexibility, innovation capability, etc. Different resilience indicators respectively characterize the resilience of urban space in different aspects.

[0091] S400. Determine the spatial resilience of the target residential city based on the index values ​​of multiple resilience indicators.

[0092] The spatial resilience of the target residential city is determined based on the index values ​​of multiple resilience indicators, so that the final result can reflect the spatial resilience of the target residential city from multiple different angles.

[0093] In the method for detecting the resilience of residential space provided in this embodiment, an urban space database is constructed based on a variety of different spatial data of the target residential city, the index values ​​of multiple resilience indicators of the target residential city are determined based on the urban space database, and finally the spatial resilience of the target residential city is determined. In this way, through the combined calculation of different resilience indicators, the spatial resilience finally obtained can reflect the resilience assessment results of the target residential city with different goals and different perspectives, making the assessment of spatial resilience more comprehensive.

[0094] In one embodiment, step S100 specifically includes:

[0095] The location point of interest data of the target residential city is obtained, and the location point of interest data includes name information, type information and location information of the location point of interest.

[0096] Among them, the location point of interest (POI) can be selected according to the needs, for example, it can include fire stations, emergency shelters, emergency shelters, for example, schools, parks, squares, parking lots. The location point of interest data can be obtained by crawling the navigation map data through the crawler tool.

[0097] Step S200 specifically includes:

[0098] The location point of interest data whose type information is the first type of information is obtained from the location point of interest data as firefighting facility point data, and the first type of information is firefighting related information.

[0099] For example, the location point of interest data whose type information includes the word "firefighting" can be extracted from the location point of interest data as firefighting facility point data. In order to improve the accuracy of the extracted information, after the extraction is completed, useless data such as micro fire rooms and fire offices can be eliminated. In order to avoid the omission of firefighting facilities, the planning data of the target residential city can also be obtained to supplement the plots whose urban land use codes represent firefighting land.

[0100] Step S200 specifically also includes:

[0101] The location point of interest data whose type information is the second type of information is obtained from the location point of interest data as the emergency shelter facility point data, and the place represented by the second type of information is suitable for emergency sheltering during earthquakes.

[0102] The second type of information can, for example, represent places such as schools, parks, squares, and parking lots that can be used for earthquake emergency avoidance. In order to improve the accuracy of the extracted information, after the extraction is completed, useless data such as underground parking lots and training schools can also be removed. Similar to fire-fighting facilities, emergency shelter facilities can also be supplemented based on the planning data of the target residential city.

[0103] Step S100 specifically also includes:

[0104] Obtain the medical facility data of the target residential city, which includes the location information, name information, nature information and level information of the medical facilities.

[0105] This data can also be obtained from the navigation map data and supplemented with data based on the planning data.

[0106] Step S200 specifically also includes:

[0107] Based on the medical facility data, determine the medical facility point data.

[0108] In this embodiment, the medical facility data may be directly used as the medical facility point data, or the qualifications, scale, etc. of the medical institutions in the medical facility data may be evaluated to determine suitable medical institutions as medical facility points.

[0109] As mentioned above, firefighting facility point data, medical facility point data, and emergency shelter facility point data are determined based on a variety of different spatial data. These three types of facility point data constitute an urban spatial database, which can comprehensively reflect the earthquake resistance of the target residential city. Of course, other required data can also be added to the urban spatial database, such as urban road traffic data, building data, etc. The following uses firefighting facility point data, medical facility point data, and emergency shelter facility point data as examples to specifically explain the process of determining spatial resilience. Of course, it is understandable that different facility points and combinations of facility points can be selected according to specific needs to determine different spatial resilience. The determination process is similar and will not be repeated here.

[0110] like Figure 2 As shown, in one embodiment, step S300 specifically includes the following steps:

[0111] S310. Determine each block unit of the target residential city.

[0112] In this step, the block units of the target residential city can be determined according to the division of administrative regions. For example, each block unit belongs to a street. This facilitates the final statistics of various resilience indicators of each block unit and subsequent policy control.

[0113] S320. Determine the robustness, redundancy, diversity and rapidity of various types of facilities in each block unit based on the urban space database, wherein diversity includes selection diversity and transfer diversity.

[0114] The above-mentioned toughness indicators are described in detail below.

[0115] robustness

[0116] Robustness reflects the system's ability to resist risks and maintain its own functions and status. The spatial robustness of the urban disaster prevention facility system is not only affected by the scale and density of the facility system network itself, but also by the interaction between different nodes in the network. In the actual operation of the city, there are many connections between the individual nodes of the disaster prevention system (fire stations, hospitals or emergency shelters), and the degree of their connection is affected by the spatial network, such as mutual dispatch and joint rescue between fire stations, cooperation and communication between hospitals and patient referral, and resource allocation and transfer of emergency shelters.

[0117] In urban resilience, the robustness index is more important than other resilience indicators. It is the primary guarantee for cities when facing disaster impacts. For urban systems, urban systems with poor robustness often show their vulnerability to disasters when they are hit by disasters. According to the network characteristics of the three types of urban disaster prevention facility subsystems, the degree centrality of the nodes is used to characterize the capacity of the disaster prevention facility system to reflect its robustness.

[0118] For the degree centrality of the three types of urban disaster prevention facility subsystems (firefighting, medical care, and emergency shelter), the location of the facility point in space is different, and the status of the facility point in its subsystem network is also different. The degree centrality of the facility point reflects the importance of the facility point in its system network. The facility point that is closer to other facility points and can serve more demand points plays a more important role in space.

[0119] The calculation formula of degree centrality is:

[0120] C D (n i )=d(n i )

[0121] Among them, C D (n i ) is the degree centrality, d(n i ) is the number of facilities that a facility point is directly connected to other facilities points.

[0122] Among them, directly connected with other facility points, for example, the distance between the two facility points can be less than the preset distance, or there is a cooperative relationship between the two facility points. For example, among medical facility points, two medical facility points that can conduct consultation, referral and medical cooperation with each other are determined as directly connected medical facility points; among firefighting facility points, two firefighting facility points that can cooperate with each other are determined as directly connected firefighting facility points; among emergency shelter facility points, two emergency shelter facility points that can transfer refugees with each other are determined as directly connected emergency shelter facility points.

[0123] The robustness of each facility point can be determined based on the degree centrality of each facility point within the block unit.

[0124] Redundancy

[0125] In order to avoid the vulnerability caused by the number of facilities just meeting the demand, cities must reserve redundancy that can be replaced, used in parallel and self-repaired in infrastructure construction, and the greater the redundancy, the stronger the resilience, that is, the overlapping of some facilities in the system can also make up for some vulnerabilities of the city. For urban fire protection facility systems, urban medical facility systems, and urban emergency shelter facility systems, the spatial redundancy of the disaster prevention facility system is reflected in the multiple choices of facilities for demand points within a certain range around them. The present invention reflects the spatial redundancy by calculating the overlap of the range formed by the service radius of each facility point in the unit.

[0126] The redundancy calculation formula is:

[0127] Red i,j =N b(r)

[0128] Among them, Red i,j is the spatial redundancy of a certain type of service facility system i in block unit j, N b(r) is the number of overlapping service ranges of service facility system i within block unit j, that is, the number of facility points with overlapping service ranges in service facility system i within block unit j. The service facility system may be, for example, a medical facility system, in which the corresponding facility point is a medical facility point; it may also be a firefighting facility system or an emergency shelter facility system, in which the corresponding facility point is a firefighting facility point or an emergency shelter facility point. The service range of a facility point may be a circular range with the facility point as the center and the service radius corresponding to the facility point as the radius. The size of the service radius of a facility point is related to the specification of the facility point. The larger the specification, the larger the corresponding service radius. The facility point may also be used as the destination, and the area range where the time to reach the destination is less than the corresponding preset time is determined as the service range of the facility point. The preset time of the facility point is related to the specification of the facility point. The larger the specification, the longer the corresponding preset time.

[0129] Diversity

[0130] The concept of diversity originates from the field of ecology. In an ecosystem, the greater the diversity of species and habitat types, the stronger the ecosystem's resistance to interference. The construction of urban disaster prevention facilities in a distributed, decentralized or miniaturized parallel manner enables urban disaster prevention facilities to have stronger disaster response capabilities and truly strong resilience. At the same time, diversity also has a positive impact on the rapid response of urban disaster prevention systems when disasters occur. In this application, diversity includes selection diversity and transfer diversity.

[0131] Choose Diversity

[0132] The diversity of the urban disaster prevention facility subsystem is expressed by measuring the number of optional facilities at demand points (urban buildings). The selection diversity reflects the diverse selectivity of demand points for facility points within a certain range.

[0133] The formula for calculating selection diversity is:

[0134]

[0135] Among them, C ij is the selection diversity of a certain type of service facility system i in block unit j, n is the number of demand points (urban buildings) contained in block unit j, c ij The number of facility points of a certain type that can be selected for the nth demand point (urban building). The service facility system can be, for example, a medical facility system, and the corresponding facility point is a medical facility point. It can also be a firefighting facility system or an emergency shelter facility system, and the corresponding facility point is a firefighting facility point or an emergency shelter facility point.

[0136] Transfer Diversity

[0137] In various emergency rescue operations in cities, in addition to the situation where those in need are directly sent to the nearest facility, there are also situations where the nearest facility is damaged or its rescue capacity has reached its limit. In this case, secondary transfer is required to other facilities.

[0138] The calculation formula for transfer diversity is:

[0139]

[0140] Among them, T ij is the transfer diversity of a service facility system i in block unit j, n is the number of demand points (urban buildings) contained in block unit j, t ij The number of facility points that the nth demander (urban building) can transfer within a certain range through a certain type of facility point that can be selected. The service facility system can be, for example, a medical facility system, and the corresponding facility point is a medical facility point. It can also be a firefighting facility system or an emergency shelter facility system, and the corresponding facility point is a firefighting facility point or an emergency shelter facility point.

[0141] Fast

[0142] Rapidity refers to the restoration of urban service levels before the disaster through command and rescue actions after the urban disaster prevention facilities are affected by the impact of the disaster. In general, the recovery speed of the city after a disaster is affected by the adequacy of the city's preparations before the disaster, and is also affected by the spatial convenience of various rescue operations after the disaster. The rapidity of actions involved in the post-disaster recovery process, such as the arrival of rescue forces, medical transfer of the injured, and refuge transfer of survivors, can be quantified by time. After a disaster, urban roads are damaged, and the rapidity index of spatial resilience will be affected. The shorter the time taken for accessibility, the stronger the rapidity.

[0143] The specific calculation method of accessibility is not limited. In one embodiment, a weighted average travel time model based on a traffic network is used as follows:

[0144]

[0145]

[0146] Where H is the average accessibility of a facility, n is the number of facility ODs (origin-destination), i is the number of the starting point, j is the number of the destination, d is the ij The time taken for the shortest path from the i-th facility point to the j-th destination point. The accessibility in this embodiment is the time taken to calculate the demand point to the facility point. The shorter the accessibility time, the stronger the rapidity, and the greater the loss recovered by the rescue.

[0147] The calculation methods of robustness, redundancy, selection diversity, transfer diversity and rapidity have been introduced above. The following is a further explanation of the calculation process of the resilience indicators of various types of facilities.

[0148] like Figure 3 As shown, in one embodiment, step S320 specifically includes:

[0149] S321. Based on the fire facility point data, determine the fire facility robustness, fire facility redundancy, fire facility diversity and fire facility rapidity of each block unit. The fire facility diversity includes the fire facility selection diversity and fire facility transfer diversity.

[0150] Among them, the robustness of fire protection facilities in each block unit is determined by the following method:

[0151] Determine the centrality of each fire protection facility point within each block unit;

[0152] Based on the centrality of each fire facility point in each block unit, the robustness of the fire facilities in each block unit is determined.

[0153] The redundancy of fire protection facilities in each block unit is determined as follows:

[0154] Determine the service area of ​​each fire protection facility;

[0155] Based on the number of overlapping fire-fighting facility points in the service area of ​​each block unit, the redundancy of fire-fighting facilities in each block unit is determined.

[0156] The diversity of fire protection facilities in each block unit is determined as follows:

[0157] Determine the number of optional facilities for each fire demand point in each block unit, and determine the diversity of fire facility options in each block unit;

[0158] Determine the number of facility points that can be transferred within a preset range for each fire demand point in each block unit, and determine the diversity of fire facility transfer in each block unit.

[0159] The rapidity of fire fighting facilities in each block unit is determined as follows:

[0160] Determine the rapidity of firefighting facilities at each firefighting facility point based on the shortest travel time between each firefighting facility point and other firefighting facilities points except the firefighting facility point itself;

[0161] Based on the rapidity of fire-fighting facilities at each fire-fighting facility point within each block unit, the rapidity of fire-fighting facilities in each block unit is determined.

[0162] Step S320 also includes:

[0163] S322. Based on the medical facility point data, determine the robustness, redundancy, diversity and rapidity of medical facilities in each block unit. The diversity of medical facilities includes the diversity of medical facility selection and the diversity of medical facility transfer.

[0164] The robustness of medical facilities in each block unit is determined as follows:

[0165] Determine the centrality of each medical facility within each block unit;

[0166] Based on the centrality of each medical facility point in each block unit, the robustness of the medical facilities in each block unit is determined.

[0167] The redundancy of medical facilities in each block unit is determined as follows:

[0168] Determine the service area of ​​each medical facility;

[0169] Based on the number of overlapping medical facilities in the service area of ​​each block unit, the redundancy of medical facilities in each block unit is determined.

[0170] The diversity of medical facilities in each block unit is determined as follows:

[0171] Determine the number of available facilities for each medical demand point in each block unit, and determine the diversity of medical facility options in each block unit;

[0172] Determine the number of facility points that can be transferred within a preset range for each medical demand point in each block unit, and determine the diversity of medical facility transfer in each block unit.

[0173] The accessibility of medical facilities in each block unit is determined as follows:

[0174] Determine the rapidity of each medical facility based on the shortest travel time between each medical facility and other medical facilities except this medical facility.

[0175] Based on the medical facility rapidity of each medical facility point within each block unit, the medical facility rapidity of each block unit is determined.

[0176] Step S320 also includes:

[0177] S323. Based on the emergency shelter facility point data, determine the emergency shelter facility robustness, emergency shelter facility redundancy, emergency shelter facility diversity and emergency shelter facility rapidity of each block unit. The emergency shelter facility diversity includes the emergency shelter facility selection diversity and the emergency shelter facility transfer diversity.

[0178] The robustness of the emergency shelter facilities in each block unit is determined by the following method:

[0179] Determine the centrality of each emergency shelter facility within each block unit;

[0180] Based on the centrality of each emergency shelter facility point in each block unit, the robustness of the emergency shelter facilities in each block unit is determined.

[0181] The redundancy of emergency shelter facilities in each block unit is determined as follows:

[0182] Determine the service area of ​​each emergency shelter facility;

[0183] Based on the number of overlapping emergency shelter facilities in the service area of ​​each block unit, the redundancy of emergency shelter facilities in each block unit is determined.

[0184] The diversity of emergency shelter facilities in each block unit is determined by:

[0185] Determine the number of facilities available for each emergency shelter demand point in each block unit, and determine the diversity of emergency shelter facility options in each block unit;

[0186] Determine the number of facility points that can be transferred within a preset range for each emergency shelter demand point in each block unit, and determine the diversity of emergency shelter facility transfers in each block unit.

[0187] The rapidity of emergency shelter facilities in each block unit is determined as follows:

[0188] Determine the facility rapidity of each emergency shelter facility point based on the shortest travel time between each emergency shelter facility point and other emergency shelter facility points except the emergency shelter facility point;

[0189] Based on the rapidity of the emergency shelter facilities at each emergency shelter facility point within each block unit, the rapidity of the emergency shelter facilities in each block unit is determined.

[0190] After determining the robustness, redundancy, diversity and rapidity of various types of facilities in each block unit, the robustness, redundancy, diversity and rapidity of various types of facilities in each block unit can be used as the indicator values ​​of multiple resilience indicators, and the spatial resilience of the target residential city can be determined based on the indicator values ​​of multiple resilience indicators.

[0191] Since the indicators of the above three types of disaster prevention facilities are measured in different dimensions and dimensions, the values ​​of the calculation results vary greatly. In order to eliminate the influence of different dimensions between indicators and avoid the influence of a few indicators on the results being too great and thus covering the influence of other indicators, it is necessary to normalize the data. The "Min-Max normalization" method is used to map the results to the range of [0, 1]. The indicators are in the same order of magnitude and analyzed under the same dimension, making the data comparable and suitable for comprehensive comparative evaluation.

[0192] The normalized conversion formula is:

[0193]

[0194] In the formula, x max is the maximum value of the sample data, x min is the minimum value of the sample data.

[0195] After normalizing all the index values, the spatial resilience of each type of facility in each block unit can be determined based on the normalized data. The spatial resilience of a certain type of facility in each block unit is determined by the following formula:

[0196]

[0197] Among them, R j is the spatial resilience of the jth block unit, x ij is the standardized score of the i-th indicator of the j-th block unit, w i is the weight of the ith indicator.

[0198] The above formula can be used to determine the spatial resilience of each type of facility in each block unit. The weight of each indicator can be set according to the actual situation, or the entropy weight method can be used to determine the weight of each indicator, so that the value after multiplying each indicator with the corresponding weight is more balanced, avoiding that some indicator values ​​differ too much from other values, resulting in the final spatial resilience result being difficult to comprehensively reflect various indicators.

[0199] Furthermore, the weights of various indicators can be adjusted according to the city's own attributes. In one embodiment, the weight of the indicator with the highest correlation with the preferred attribute of the target residential city is increased, while the weights corresponding to other indicators are reduced. For example, when the city attribute includes the attribute of convenient transportation, the weight corresponding to the rapidity indicator with the highest correlation with the convenient transportation attribute can be increased, while the weights corresponding to other indicators are reduced to ensure that the sum of the weights is 1, thereby further improving the accuracy of the spatial resilience value finally obtained. When reducing the weights corresponding to other indicators, in one embodiment, the weight value added to a certain indicator can be evenly divided to reduce other indicators. In another embodiment, the weight of the indicator with medium correlation with the preferred attribute of the target residential city can be reduced less, and the weight of the indicator with poor correlation with the preferred attribute of the target residential city can be reduced more, so that the spatial resilience value is more in line with the city's own attributes. When adjusting the weights of various indicators according to the city's own attributes, the amount of weight to be increased can be determined according to the attribute level. For example, the higher the attribute level, the higher the weight to be increased, and the lower the attribute level, the lower the weight to be increased.

[0200] After determining the spatial resilience of each type of facility in each block unit, the spatial resilience of the target residential city can be calculated using the following formula:

[0201]

[0202] Among them, S i is the comprehensive score of resilience index, W i is the weight of index i, x ij ' is the index value after data standardization, for example, it can be the mean value of the index of all block units i.

[0203] like Figure 4 As shown, step S400 specifically includes:

[0204] S410. Normalize the robustness, redundancy, diversity and rapidity of fire-fighting facilities of each block unit, the robustness, redundancy, diversity and rapidity of medical facilities of each block unit, and the robustness, redundancy, diversity and rapidity of emergency shelter facilities of each block unit.

[0205] S421. Determine the spatial resilience of fire-fighting facilities in each block unit based on the normalized robustness, redundancy, diversity and rapidity of fire-fighting facilities in each block unit.

[0206] S422. Determine the spatial resilience of medical facilities in each block unit based on the normalized robustness, redundancy, diversity and rapidity of medical facilities in each block unit.

[0207] S423. Determine the spatial resilience of the emergency shelter facilities in each block unit based on the normalized robustness of the emergency shelter facilities, redundancy of the emergency shelter facilities, diversity of the emergency shelter facilities and rapidity of the emergency shelter facilities in each block unit.

[0208] S430. Determine the spatial resilience of the target residential city based on the spatial resilience of fire-fighting facilities in each block unit, the spatial resilience of medical facilities in each block unit, and the spatial resilience of emergency shelter facilities in each block unit.

[0209] The above embodiments introduce methods for determining the resilience of residential space before a disaster (e.g., before an earthquake). The resilience of residential space after a disaster is also an important indicator for evaluating urban resilience. The following specifically introduces the construction of a post-disaster scenario for a target residential city and a method for detecting the spatial resilience of the post-disaster scenario.

[0210] In one embodiment, if Figure 5 As shown, the method for checking the resilience of living space provided in this embodiment also includes the following steps:

[0211] S10. Acquire urban road traffic data of the target residential city, where the urban road traffic data includes road location information, length information, type information, and road name.

[0212] Urban road traffic data can be obtained through data sources such as map data and navigation software data.

[0213] S20. Acquire building data of the target residential city, where the building data includes location and size information of the building, and the size information includes length, width, and height.

[0214] Building data can be obtained through data sources such as navigation software data and satellite image data. After extracting building data from multiple data sources, redundant data and invalid data can be deleted.

[0215] Of course, it is understandable that urban road traffic data and building data can also be pre-stored in the urban space database.

[0216] S30. Construct post-disaster scenarios based on urban road traffic data and building data.

[0217] S40. Determine the post-disaster spatial resilience of the target residential city in post-disaster scenarios.

[0218] In this embodiment, a post-disaster scenario is constructed for the target residential city based on urban road traffic data and building data, so that the post-disaster spatial resilience of the target residential city can be predicted based on the constructed post-disaster scenario. Based on the predicted post-disaster spatial resilience, an effective planning strategy can be proposed for the urban construction planning of the target residential city to improve the post-disaster spatial resilience of the target residential city.

[0219] like Figure 6 As shown, in one embodiment, step S30 specifically includes:

[0220] S31. Based on the building data and the preset earthquake level, determine the buildings predicted to collapse in the building data.

[0221] For example, it is possible to determine whether each building in the target residential city collapses under a preset earthquake level based on preset configuration information. The preset configuration information is used to characterize the correspondence between building data under a preset earthquake level and whether the building collapses. For example, it can be the correspondence between the building height under a preset earthquake level and whether the building collapses. The height of each building in the building data can be queried in the preset configuration information to determine whether the building collapses. The preset configuration information can be in the form of a table, a mapping, etc.

[0222] In addition, a pre-trained prediction model can be used to predict whether buildings in the target residential city will collapse under a preset earthquake level.

[0223] Among them, the preset earthquake registration can be set according to specific needs.

[0224] S32. Determine the impact area after the collapse of each building predicted to collapse.

[0225] In one embodiment, the impact area after the building collapse can be determined based on the length, width and height of the building. For example, the length or equivalent length of the building is length L, the width or equivalent width of the building is width B, and the height of the building is H. Different building height ranges correspond to different impact coefficients k. The corresponding relationship between the height H and the impact coefficient k can be set according to the actual scene. The higher the height, the greater the impact coefficient k. The length of the impact area after the building collapses is (1+2k)L, and the width of the impact area after the building collapses is (1+2k)B, where each end in the length direction increases the kL size on the basis of the original building, and each end in the width direction increases the kB on the basis of the original building.

[0226] In another embodiment, parameters are used to predict the impact area after the building collapses. For example, the parameters of the building may include construction method, materials, spatial structure, topography, geology, collapse direction, etc. These parameters are used as input data of the prediction model, and the prediction model extracts shallow features and / or deep features therein and predicts the impact area after the building collapses.

[0227] As an example, the affected area after the building collapse can be characterized by coordinates, such as GPS coordinates. Alternatively, longitude and latitude can also be used.

[0228] S33. Based on each affected area, determine the interrupted roads in the urban road traffic data and the interruption points in the interrupted roads, so as to update the urban road traffic data.

[0229] For example, the roads in urban road traffic can be characterized by trajectory coordinates, and then the trajectory coordinates of the roads and the impact area after the building collapse are used to determine whether the two intersect. If they intersect, it means that the road is interrupted, and the intersection is the interruption point of the road. Each interrupted road can include one or more interruption points. Afterwards, the interruption status of the road and the interruption points of the interrupted road can be imported into the urban road traffic data to update the urban road traffic data.

[0230] S34. Update the urban space database based on the updated urban road traffic data.

[0231] S35. Based on the updated urban spatial database, determine the index values ​​of multiple post-disaster resilience indicators of the target residential city.

[0232] In this step, the index values ​​of multiple post-disaster resilience indicators of the target residential city can be determined based on the updated urban space database using the calculation method in the above embodiment.

[0233] For example, when calculating the degree centrality, due to the interruption of some roads, two facilities that were originally directly connected may become not directly connected, which will reduce the degree centrality of some facilities and affect the robustness.

[0234] For another example, when calculating redundancy, the interruption of some roads will affect the service range of some facilities, thereby affecting redundancy.

[0235] S36. Determine the post-disaster spatial resilience of the target residential city based on the index values ​​of multiple post-disaster resilience indicators.

[0236] In this embodiment, it is possible to predict whether a building will collapse in an earthquake disaster and the affected area after the collapse, and then predict the interruption status of the road, and use this to update the post-disaster urban road traffic status. This can more accurately predict the post-disaster status of the city, and help to more accurately calculate the accuracy of the post-disaster spatial resilience of the target human settlement city.

[0237] In some embodiments, the method may also include: determining fire facility point adjustment strategies, medical facility point adjustment strategies, emergency shelter facility point adjustment strategies, and / or road planning adjustment strategies based on the post-disaster spatial resilience of the target human settlement city.

[0238] In this embodiment, the post-disaster spatial resilience of the target residential city can be used as reference data to adjust various facilities and plans of the city, which will help improve the resilience of the city and the rationality of the planning.

[0239] For example, when the difference between post-disaster spatial resilience and spatial resilience is greater than the preset threshold, it means that the post-disaster spatial resilience has decreased significantly and the post-disaster spatial resilience of the target residential city is poor. In this case, the spatial resilience of each type of facility in each block unit with the largest difference between post-disaster and pre-disaster is determined, and then branch roads are added to the roads in the block unit with the largest difference to avoid interruption points. The urban road traffic data with the added branch roads are used to update the urban spatial database. If the difference between the post-disaster spatial resilience and the spatial resilience calculated after the update is less than or equal to the preset threshold, the determined added branch roads are used as the road planning adjustment strategy. If the difference between the post-disaster spatial resilience and the spatial resilience calculated after the update is still large, the added branch roads are used as the road planning adjustment strategy. If the difference between the post-disaster spatial resilience and the spatial resilience calculated after the update is less than or equal to the preset threshold, the determined added facility points will be used as the facility point adjustment strategy. If the difference between the post-disaster spatial resilience and the spatial resilience calculated after the update is still greater than the preset threshold, the spatial resilience of each type of facility in each block unit with the largest difference between the post-disaster and pre-disaster is determined again, and the above steps are continued until the difference between the post-disaster spatial resilience and the spatial resilience calculated after the update is less than or equal to the preset threshold.

[0240] In addition, in step S310, the division of block units is usually carried out according to administrative regions, and the subsequent spatial resilience calculations are all carried out in block units. This division method may not be reasonable for the resilience of human settlement space. Therefore, when the difference between post-disaster spatial resilience and spatial resilience is greater than the preset threshold, the target human settlement city can also be divided into regions based on facility points. For example, when the target human settlement city is divided into regions, the target human settlement city can be divided so that the number of each type of facility points in each regional unit is the same, and it is assumed that there is a direct connection relationship between each type of setting in the regional unit. On the basis of the regional division, the post-disaster spatial resilience and spatial resilience are recalculated. If the difference between the recalculated post-disaster spatial resilience and spatial resilience is less than the preset threshold, each block unit located in the same regional unit is regarded as a disaster prevention-related block, and an association suggestion is sent to the disaster prevention-related block, suggesting that each type of facility point in the disaster prevention-related block establishes a direct connection relationship. For another example, when dividing the target residential city into regions, the target residential city can be divided into regions so that the difference in the total function scores of each type of facility points in each regional unit is less than a preset difference. The functional score refers to the score of the functionality of the facility point. For example, for medical facilities, the medical facilities can be scored according to the scale of the medical facilities, internal facilities, hospital grade, etc., for fire protection facilities, the fire protection facilities can be scored according to the scale of the fire protection facilities, internal facilities, etc., for emergency shelter facilities, the emergency shelter facilities can be scored according to the area of ​​the emergency shelter facilities, the number of escape exits, etc. After completing the regional division, the difference in the total score of the fire protection facility points in each regional unit is less than the first preset difference, the difference in the total score of the medical facility points in each regional unit is less than the second preset difference, and the difference in the total score of the emergency shelter facility points in each regional unit is less than the third preset difference. In this way, the regional division can be more reasonable.

[0241] It is easy for those skilled in the art to understand that, under the premise of no conflict, the above-mentioned preferred solutions can be freely combined and superimposed.

[0242] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for detecting the resilience of a human settlement space, characterized in that: The method comprises the following steps: Obtain various spatial data of the target residential city; Process a variety of spatial data and build an urban spatial database based on the processed data; Determining index values ​​of a plurality of resilience indicators of the target residential city based on the urban spatial database; Based on the index values ​​of the multiple resilience indicators, the spatial resilience of the target residential city is determined.

2. The method for detecting the resilience of living space according to claim 1, characterized in that: The acquiring of a plurality of different spatial data of the target residential city includes: acquiring location interest point data of the target residential city, wherein the location interest point data includes name information, type information and location information of the location interest point; the processing of a plurality of different spatial data includes: acquiring the location interest point data with type information of the first type information in the location interest point data as firefighting facility point data, wherein the first type information is firefighting related information; acquiring the location interest point data with type information of the second type information in the location interest point data as emergency shelter facility point data, wherein the second type information represents a place suitable for emergency sheltering during an earthquake; The acquiring of various spatial data of the target residential city includes: acquiring medical facility data of the target residential city, wherein the medical facility data includes location information, name information, property information and grade information of the medical facilities; The processing of the plurality of different spatial data includes: determining the medical facility point data based on the medical facility data; The constructing of the urban space database based on the processed data includes: constructing the urban space database based on the fire protection facility point data, medical facility point data and emergency shelter facility point data.

3. The method for detecting the resilience of living space according to claim 2, characterized in that: Based on the urban spatial database, determining the index values ​​of multiple resilience indicators of the target residential city, including: Determine each block unit of the target residential city; Determine the fire facility robustness, fire facility redundancy, fire facility diversity and fire facility rapidity of each of the block units according to the fire facility point data, wherein the fire facility diversity includes fire facility selection diversity and fire facility transfer diversity; Determine the robustness, redundancy, diversity and rapidity of medical facilities of each of the block units according to the medical facility point data, wherein the diversity of medical facilities includes the diversity of medical facility selection and the diversity of medical facility transfer; Based on the emergency shelter facility point data, the emergency shelter facility robustness, emergency shelter facility redundancy, emergency shelter facility diversity and emergency shelter facility rapidity of each of the block units are determined, and the emergency shelter facility diversity includes emergency shelter facility selection diversity and emergency shelter facility transfer diversity.

4. The method for detecting the resilience of living space according to claim 3, characterized in that: Determining the firefighting facility robustness, firefighting facility redundancy, firefighting facility diversity and firefighting facility rapidity of each of the block units according to the firefighting facility point data includes: Determine the centrality of each fire protection facility point within each block unit; Determine the robustness of the firefighting facilities of each block unit based on the centrality of each firefighting facility point in each block unit; Determine the service area of ​​each fire protection facility; Determine the redundancy of firefighting facilities in each block unit based on the number of firefighting facilities points with overlapping service areas in each block unit; Determine the number of selectable facilities for each fire demand point in each block unit, and determine the diversity of fire facility options for each of the block units; Determine the number of facilities that can be transferred within a preset range for each fire demand point in each block unit, and determine the diversity of fire facility transfers in each of the block units; Determine the rapidity of firefighting facilities at each firefighting facility point based on the shortest travel time between each firefighting facility point and other firefighting facility points other than the firefighting facility point; Based on the rapidity of fire-fighting facilities at each of the fire-fighting facility points within each block unit, the rapidity of fire-fighting facilities in each block unit is determined.

5. The method for detecting the resilience of living space according to claim 3, characterized in that: Determining the robustness, redundancy, diversity and rapidity of medical facilities of each of the block units according to the medical facility point data includes: Determine the centrality of each of the medical facilities within each block unit; Determine the robustness of the medical facilities in each block unit based on the centrality of each of the medical facilities in each block unit; Determine the service area of ​​each of the medical facilities; Determine the redundancy of medical facilities in each block unit based on the number of medical facilities with overlapping service areas in each block unit; Determine the number of selectable facilities for each medical demand point in each block unit, and determine the diversity of medical facility options for each of the block units; Determine the number of facility points that can be transferred within a preset range for each medical demand point in each block unit, and determine the diversity of medical facility transfers in each of the block units; Determine the medical facility rapidity of each medical facility point based on the shortest travel time between each medical facility point and other medical facility points except the medical facility point; Based on the medical facility rapidity of each of the medical facility points within each block unit, the medical facility rapidity of each block unit is determined.

6. The method for detecting the resilience of living space according to claim 3, characterized in that: Determining the robustness, redundancy, diversity and rapidity of emergency shelter facilities of each of the block units based on the emergency shelter facility point data includes: Determine the centrality of each of the emergency shelter facilities within each block unit; Determining the robustness of the emergency shelter facilities in each block unit based on the centrality of each of the emergency shelter facility points in each block unit; Determine the service area of ​​each of the emergency shelter facilities; Determining the redundancy of emergency shelter facilities in each block unit based on the number of emergency shelter facilities in which the service areas of each block unit overlap; Determine the number of facility points available for each emergency shelter demand point within each block unit, and determine the diversity of emergency shelter facility options for each of the block units; Determine the number of facilities that can be transferred within a preset range for each emergency shelter demand point in each block unit, and determine the diversity of emergency shelter facility transfers in each of the block units; Determine the facility rapidity of each emergency shelter facility point based on the shortest travel time between each emergency shelter facility point and other emergency shelter facility points other than the emergency shelter facility point; Based on the emergency shelter facility rapidity of each of the emergency shelter facility points within each block unit, the emergency shelter facility rapidity of each block unit is determined.

7. The method for detecting the resilience of living space according to claim 3, characterized in that: Determining the spatial resilience of the target residential city based on the index values ​​of the multiple resilience indicators includes: Normalizing the robustness, redundancy, diversity and rapidity of fire-fighting facilities of each of the block units, the robustness, redundancy, diversity and rapidity of medical facilities of each of the block units, and the robustness, redundancy, diversity and rapidity of emergency shelter facilities of each of the block units; Determine the spatial resilience of firefighting facilities in each of the block units based on the normalized robustness, redundancy, diversity and rapidity of firefighting facilities in each of the block units; Determine the medical facility spatial resilience of each of the block units based on the normalized medical facility robustness, medical facility redundancy, medical facility diversity and medical facility rapidity of each of the block units; Determine the spatial resilience of the emergency shelter facilities of each of the block units based on the normalized robustness of the emergency shelter facilities, the redundancy of the emergency shelter facilities, the diversity of the emergency shelter facilities, and the rapidity of the emergency shelter facilities of each of the block units; The spatial resilience of the target residential city is determined based on the spatial resilience of the fire-fighting facilities of each block unit, the spatial resilience of the medical facilities of each block unit, and the spatial resilience of the emergency shelter facilities of each block unit.

8. The method for detecting the resilience of a living space according to any one of claims 1 to 7, characterized in that: The method further comprises the steps of: Acquire urban road traffic data of the target inhabited city, wherein the urban road traffic data includes road location information, length information, type information and road name; Acquire building data of the target residential city, wherein the building data includes location and size information of the building, and the size information includes length, width and height; Constructing a post-disaster scenario based on the urban road traffic data and the building data; Determine the post-disaster spatial resilience of the target human settlement city in post-disaster scenarios.

9. The method for detecting the resilience of living space according to claim 8, characterized in that: The constructing of a post-disaster scenario based on the urban road traffic data and the building data includes: Based on the building data and a preset earthquake level, determining a building in the building data that is predicted to collapse; Determine the impact area after the collapse of each building predicted to collapse; Based on each of the impact areas, determining the interrupted roads in the urban road traffic data and the interruption points in the interrupted roads, so as to update the urban road traffic data; Based on the updated urban road traffic data, updating the urban space database; Determining index values ​​of multiple post-disaster resilience indicators of the target residential city based on the updated urban spatial database; Based on the index values ​​of the multiple post-disaster resilience indicators, the post-disaster spatial resilience of the target residential city is determined.

10. The method for detecting the resilience of living space according to claim 9, characterized in that: The method also includes: determining a fire facility point adjustment strategy, a medical facility point adjustment strategy, an emergency shelter facility point adjustment strategy, and / or a road planning adjustment strategy based on the post-disaster spatial resilience of the target human settlement city.

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