Community flood toughness and external relation analysis method based on facility accessibility

Abstract

The invention provides a community flood toughness and external relationship analysis method based on facility accessibility, and relates to the technical field of community disaster toughness evaluation. According to the invention, the complex relation and interaction among elements such as urban roads, facilities, crowds and the like are considered based on the constructed composite spatial network. In a rainstorm situation, service flows between community residents and facilities may be interfered, roads serve as bridges to connect the community residents and the service facilities, road interruption caused by rainstorm may cause isolation between part of communities and the service facilities, reachability heterogeneity changes are affected, and community toughness presents complex spatial distribution. According to the method, the support degree of the community internal and external service facilities to the community recovery capability can be determined by analyzing the contribution of the road-community-community internal service facilities-community external service facilities to the community comprehensive toughness. Based on community disaster toughness evaluation and external association relationship analysis, the embodiment of the invention provides a reliable scientific basis for community disaster prevention and reduction construction.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of community disaster resilience assessment, and in particular to a method for analyzing community flood resilience and external relations based on facility accessibility. Background Art

[0002] In areas where floods and waterlogging disasters occur frequently, whether community residents can obtain basic services in disaster situations is one of the keys to maintaining their normal lives and safety. The provision of a large number of services or prepared facilities in normal situations cannot ensure that residents can obtain services without hindrance during disaster disturbances. In the absence of basic services, it will not only aggravate the difficulties faced by community residents, but also hinder the community recovery process. Disaster disturbances will affect the flow relationship and efficiency between residents and basic service facilities, redistribute factors such as road capacity and infrastructure services, and produce quantitative and spatial impacts. Assessing community flood resilience can provide a reference for community service management in disaster situations. Summary of the invention

[0003] The embodiment of the present invention provides a method for analyzing community flood resilience and external relationships based on facility accessibility, which is oriented to rainstorm and flood disaster scenarios and implements community resilience and external correlation relationship assessment based on service facility accessibility.

[0004] A first aspect of an embodiment of the present invention provides a method for analyzing community flood resilience and external relations based on facility accessibility, the method comprising:

[0005] Simulate flooding and inundation conditions based on hydrological and hydrodynamic models to determine the road capacity of each road during each rainstorm period;

[0006] Determine the population density of each community and the supply of community service facilities and the supply of extra-community service facilities;

[0007] According to the road traffic capacity of each rainstorm period, the population density of each community, and the supply of service facilities in each community and the supply of service facilities outside each community, a composite spatial network corresponding to each rainstorm period is constructed, wherein in the composite spatial network, road intersections are road nodes, roads connecting road nodes are road edges, the road traffic speed of each road is the weight of the road edge, the centroid of each community is the community node, the population density of each community is the weight of the community node, the centroid of the community service facilities in the community is the community service node, the supply of service facilities in the community is the weight of the community service node, the centroid of the community service facilities outside the community is the community service node, the supply of service facilities outside the community is the weight of the service node, the community node and the nearest road node are connected as the community-road edge, the community service node and the nearest road node are connected as the community service-road edge, and the community service node and the nearest road node are connected as the community service-road edge.

[0008] Based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold, the comprehensive community service accessibility, the internal community service accessibility and the external community service accessibility of each community in each rainstorm period are calculated respectively;

[0009] The comprehensive community resilience, internal community resilience and external community resilience of each community are calculated based on the comprehensive community service accessibility, internal community service accessibility and external community service accessibility of each community during each rainstorm period.

[0010] Optionally, flood and inundation conditions are simulated based on hydrological and hydrodynamic models to determine the road capacity during each rainstorm period, including:

[0011] Simulate flooding and inundation conditions based on hydrological and hydrodynamic models, determine the inundation depth of each road, and remove roads whose inundation depth exceeds a preset threshold;

[0012] The vehicle speed of each road in the normal situation of the corresponding period of each rainstorm period is obtained, and the vehicle speed in the normal situation is processed with deviation to obtain the traffic speed of each road in each rainstorm period.

[0013] Optionally, the vehicle speed of each road in a normal situation in a corresponding period of each rainstorm period is obtained, and the vehicle speed in the normal situation is subjected to deviation processing to obtain the traffic speed of each road in each rainstorm period, including:

[0014] For a period of heavy rain:

[0015] Determine the correction coefficient λ corresponding to the jth road based on the road grade and road length of the jth road j ;

[0016] The traffic speed of the jth road is determined based on the following formula:

[0017] V'=λ j V j ;

[0018] Where V' represents the corrected road speed, λ j represents the correction coefficient of the jth road, V j It represents the vehicle speed on the j-th road during the normal period of the rainstorm.

[0019] Optionally, a composite spatial network corresponding to each rainstorm period is constructed according to the road capacity, the population density of each community, the supply of service facilities in each community, and the supply of service facilities outside each community during each rainstorm period, including:

[0020] For a period of heavy rain:

[0021] Abstract road intersections as road node sets Abstract the road segments connecting road intersections into road edge sets

[0022] The road intersection v i ,v j The required travel time of the connecting section during the current rainstorm period t As the weight of the road edge, construct the adjacency matrix for time period t Form a dynamic weighted undirected graph that changes with the rainstorm period

[0023] Extract the centroid of each community and use the population density of the community as the weight to form a community node set

[0024]

[0025] The centroids of the community's internal and external service facilities are extracted, and the supply of service facilities is used as weight to form a set of internal and external service nodes that change with the rainstorm period:

[0026]

[0027] Determine the road intersections closest to the community node and the service nodes within the community and the service nodes outside the community, and connect them to create community-road edge sets, community service-road edge sets, and community service-road edge sets respectively:

[0028] The dynamic weighted composite spatial network G(V P ∪VD ∪V S_in ∪V S_ex ,L P ∪L D ∪L S_in ∪L S_ex ).

[0029] Optionally, based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold, the community comprehensive service accessibility, the community internal service accessibility and the community external service accessibility in each rainstorm period are calculated respectively, including:

[0030] For a service facility during a rainstorm period: the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold d0 are used to determine the service range of the service facility, and the Gaussian equation is used to weight each community within the service range, and the weighted sum is performed to calculate the number of residents within the service range; the supply of the service facility is then divided by the number of residents within the service range to calculate the supply-demand ratio:

[0031]

[0032] in, represents the comprehensive supply-demand ratio of community i; represents the supply-demand ratio of service facilities within community i; P represents the supply-demand ratio of extra-community service facilities in community i; i It is within the scope of the service facility space (d kj ≤d0) the number of residents in community i; d ij represents the distance from the service facility center to the center of community i; It indicates the supply of service facilities in the community; represents the supply of service facilities outside the community; G(d ij ,d0) is the Gaussian equation that considers the impact of distance on service efficiency. The calculation formula is as follows:

[0033]

[0034] For a community i in a certain rainstorm period, a time threshold d0 is given to form another spatial scope. The supply-demand ratio of service facilities in the spatial scope is weighted and summed using the Gaussian equation to obtain the accessibility A of the service facilities in the community i. i :

[0035]

[0036] in, It indicates the accessibility of comprehensive community services; It indicates the accessibility of services within the community; Represents the accessibility of external services in the community.

[0037] Optionally, the community comprehensive resilience, community internal resilience and community external resilience are calculated based on the community comprehensive service accessibility, community internal service accessibility and community external service accessibility during each rainstorm period, including:

[0038] The comprehensive service resilience of community i in each rainstorm period is determined based on the comprehensive service accessibility of community i under normal circumstances and the comprehensive service accessibility of community i in each rainstorm period. The comprehensive internal community service resilience of community i in each rainstorm period is determined based on the internal community service accessibility of community i under normal circumstances and the internal community service accessibility of community i in each rainstorm period. The external community service resilience of community i in each rainstorm period is determined based on the external community service accessibility of community i under normal circumstances and the external community service accessibility of community i in each rainstorm period.

[0039] The community comprehensive service accessibility, community internal service accessibility and community external service accessibility at different periods of heavy rain are fitted into community resilience curves to obtain community comprehensive resilience, community internal resilience and community external resilience:

[0040]

[0041] in, represents the comprehensive service accessibility of the community during the rainstorm period t, the internal service accessibility of the community during the rainstorm period t, or the external service accessibility of the community during the rainstorm period t. It represents the comprehensive service accessibility of the community under normal circumstances, the internal service accessibility of the community under normal circumstances, or the external service accessibility of the community under normal circumstances. R represents the comprehensive resilience of the community, the internal resilience of the community, or the external resilience of the community.

[0042] A second aspect of an embodiment of the present invention provides a community flood resilience and external relationship analysis device based on facility accessibility, the device comprising:

[0043] The first determination module is used to simulate flooding and inundation conditions based on a hydrological and hydrodynamic model to determine the road capacity of each road during each rainstorm period;

[0044] The second determination module is used to determine the population density of each community and the supply of service facilities within each community and the supply of service facilities outside each community;

[0045] A construction module is used to construct a composite spatial network corresponding to each rainstorm period according to the road capacity of each rainstorm period, the population density of each community, and the supply of service facilities in each community and the supply of service facilities outside each community, wherein in the composite spatial network, road intersections are road nodes, roads connecting road nodes are road edges, the road capacity of each road is the weight of the road edge, the centroid of each community is the community node, the population density of each community is the weight of the community node, the centroid of the service facilities in each community is the service node in the community, the supply of service facilities in each community is the weight of the service node in the community, the centroid of the service facilities outside the community is the service node outside the community, the supply of service facilities outside the community is the weight of the service node, the community node and the nearest road node are connected as a community-road edge, the service node in the community and the nearest road node are connected as a service-road edge in the community, and the service node outside the community and the nearest road node are connected as an edge set of service-road outside the community;

[0046] The first calculation module is used to calculate the community comprehensive service accessibility, community internal service accessibility and community external service accessibility of each community in each rainstorm period based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold;

[0047] The second calculation module is used to calculate the comprehensive community resilience, internal community resilience and external community resilience of each community based on the comprehensive community service accessibility, internal community service accessibility and external community service accessibility of each community during each rainstorm period.

[0048] A third aspect of an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executed, implements the community flood resilience and external relationship analysis method based on facility accessibility as described in the first aspect of the present invention.

[0049] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the community flood resilience and external relationship analysis method based on facility accessibility as described in the first aspect of the present invention.

[0050] A fifth aspect of an embodiment of the present invention provides a computer program product, including a computer program / instruction, which is used by a processor to implement the steps in the community flood resilience and external relationship analysis method based on facility accessibility as described in the first aspect of the present invention.

[0051] In the embodiment of the present invention, the complex connections and interactions between urban roads, facilities, people and other elements are considered based on the constructed composite spatial network. Specifically, in the case of heavy rain, the service flow between community residents and facilities may be disturbed. Roads act as "bridges" to connect community residents and service facilities. Road interruptions caused by heavy rain may cause isolation between some communities and service facilities, affecting heterogeneous changes in accessibility. Community resilience analysis based on composite spatial networks can make the community resilience analysis conform to actual conditions. In the embodiment of the present invention, by analyzing the contribution of roads-communities-internal service facilities in the community-external service facilities in the community to the comprehensive resilience of the community, the degree of support of internal and external service facilities in the community for the community's resilience can be determined. Based on the community disaster resilience assessment and external correlation analysis, the embodiment of the present invention provides a reliable scientific basis for community disaster prevention and mitigation construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0053] Figure 1 is a flowchart of the steps of a method for analyzing community flood resilience and external relations based on facility accessibility provided by an embodiment of the present invention;

[0054] Figure 2 It is a schematic diagram of community resilience analysis results of an exemplary embodiment of the community flood resilience and external relationship analysis method based on facility accessibility provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] Traditional community resilience assessment research rarely considers the interactions and complex influences between urban spatial elements. In addition, most existing studies focus on the community, ignoring the impact of the community and its external related facilities on the community resilience assessment, and are unable to accurately complete the community flood resilience assessment. Based on this, the embodiment of the present invention proposes a community resilience and external relationship analysis method based on service facility accessibility, which provides a systematic community disaster resilience assessment method for urban managers through urban rainstorm disaster scenario construction-demand and supply capacity assessment-composite spatial network construction-service facility accessibility calculation-community disaster resilience calculation.

[0057] like Figure 1As shown, it shows a flowchart of a method for analyzing community flood resilience and external relations based on facility accessibility provided by an embodiment of the present invention. Specifically, the method includes the following steps:

[0058] S101, simulating flooding and inundation conditions based on a hydrological and hydrodynamic model to determine the road capacity of each road during each rainstorm period.

[0059] S102, determining the population density of each community and the supply of service facilities within the community and the supply of service facilities outside the community.

[0060] S103, constructing a composite spatial network corresponding to each rainstorm period according to the road capacity, the population density of each community, the supply of service facilities in each community, and the supply of service facilities outside each community during each rainstorm period.

[0061] In the embodiment of the present invention, in the composite spatial network, road intersections are road nodes, roads connecting road nodes are road edges, the road speed of each road is the weight of the road edge, the centroid of each community is a community node, the population density of each community is the weight of the community node, the centroid of the community's intra-community service facilities is the intra-community service node, the supply of the community's intra-community service facilities is the weight of the intra-community service node, the centroid of the community's extra-community service facilities is the extra-community service node, the supply of the extra-community service facilities is the weight of the service node, the community node and the nearest road node are connected as a community-road edge, the intra-community service node and the nearest road node are connected as an intra-community service-road edge, and the extra-community service node and the nearest road node are connected as an extra-community service-road edge set.

[0062] S104, based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold, respectively calculate the community comprehensive service accessibility, community internal service accessibility and community external service accessibility of each community in each rainstorm period.

[0063] S105, calculating the comprehensive community resilience, internal community resilience and external community resilience of each community based on the comprehensive community service accessibility, internal community service accessibility and external community service accessibility of each community during each rainstorm period.

[0064] In the embodiment of the present invention, in step S101, based on the rainfall in each rainstorm period, the hydrological and hydrodynamic model is used to simulate the flooding situation, determine the flooding depth of each road under the corresponding rainfall, and determine the impact of flooding in each rainstorm period on the travel speed and road connectivity of each road. Then, in the flood scenario, the travel capacity of each road in each rainstorm period is determined.

[0065] In the embodiment of the present invention, for the convenience of calculation, the entire rainfall process can be divided into multiple rainstorm periods, and the corresponding community resilience can be calculated based on each rainstorm period. Specifically, the division granularity can be determined according to actual needs and historical experience, for example, every two hours can be regarded as a rainstorm period.

[0066] In the embodiment of the present invention, the road capacity may be reflected in whether the road is passable and the passing speed of the road. Specifically, step S101 may include the following sub-steps:

[0067] S1011, simulating flood inundation conditions based on a hydrological and hydrodynamic model, determining the inundation depth of each road, and removing roads whose inundation depth exceeds a preset threshold.

[0068] S1012, obtaining the vehicle speed of each road in a normal situation during each rainstorm period, performing deviation processing on the vehicle speed under the normal situation, and obtaining the traffic speed of each road in each rainstorm period.

[0069] In the embodiment of the present invention, in step S1011, the preset threshold can be determined based on vehicle driving requirements. Specifically, when the height of the vehicle exhaust pipe is exceeded, the vehicle driving becomes unsafe. Therefore, 30 cm water depth can be defined as the preset threshold for prohibiting the passage of the road, and the roads with a flood depth exceeding 30 cm are eliminated.

[0070] In the embodiment of the present invention, in step S1012, the vehicle speed of each road in the normal situation of each rainstorm period can be determined based on historical traffic data. For example, the rainstorm periods currently analyzed are 14:00-16:00, 16:00-18:00, and 18:00-20:00. For a certain road, the road speed at four times of 14:00, 16:00, 18:00, and 20:00 on five working days can be obtained, and the average of the speeds of the five working days is used as the road speed at the corresponding time, based on which the traffic speed of the road in each rainstorm period is determined.

[0071] Specifically, in step S1012, for a certain rainstorm period, the following steps may be used to determine the speed of vehicles on each road:

[0072] Determine the correction coefficient λ corresponding to the jth road based on the road grade and road length of the jth road j ; Determine the speed of the jth road based on the following formula:

[0073] V'=λ j V j ; Where V' represents the corrected road speed, λ j represents the correction coefficient of the jth road, V jIt represents the vehicle speed on the j-th road during the normal period of the rainstorm.

[0074] In the embodiment of the present invention, it is considered that when a rainstorm occurs, the lower the road grade, the narrower the available road width, and the more likely it is to cause congestion. At the same time, the longer the road, the lower the road driving efficiency. Therefore, in the embodiment of the present invention, the road speed can be corrected according to the correction coefficient of the road grade and the road length. As shown in the following Table 1:

[0075] Table 1 Road grade and road length correction coefficient table

[0076] Road Class Expressway Main Road Secondary trunk road Branch Road Correction factor 1.0 0.9 0.7 0.5 Road length S(m) S<600 600≤S<1200 1200≤S<1800 S≥1800 Correction factor 1.0 0.9 0.8 0.7

[0077] Specifically, a comprehensive correction coefficient of a certain road can be obtained based on the correction coefficient of the road grade and the correction coefficient of the road length, and then the road speed in a rainstorm scenario can be obtained based on the comprehensive correction coefficient and the vehicle speed in a normal situation.

[0078] In the embodiment of the present invention, in step S102, the corresponding population density can be determined according to the number of residents in each community, and the supply of service facilities can be determined according to the scale of service facilities such as hospitals, convenience stores, and large supermarkets. Among them, the service facilities in the community and the service facilities outside the community are equivalent to a certain community. Specifically, the service facilities in the community and the service facilities outside the community corresponding to a community can be predetermined according to the shortest path between each service facility and the community, and each community can be associated with the corresponding service facilities in the community and the service facilities outside the community. When calculating accessibility later, the community can be used as the source point, and the service facilities in the community and the service facilities outside the community can be used as the destination point for analysis. For example, assuming that there are communities A, B, and C, the number of residents in each community corresponds to the population density, and each service facility also has its own value (supply). Taking community A as an example, in order to meet basic needs, residents go to convenience stores to purchase. They may choose to go to the convenience store in community A (service facilities in the community), or they may choose to go to the convenience store in community B (service facilities outside the community). In this case, the resilience analysis of community A needs to consider the supply provided by the convenience store in community A, and also consider the supply provided by the convenience store in community B.

[0079] In the embodiment of the present invention, the population density of the community can be used to calculate the demand capacity of service facilities. Specifically, the population density of each community can be calculated based on the population heat map. Considering that the demand for service facilities of some groups of people varies, the demand for service facilities of the community can also be calculated based on the density of vulnerable areas such as nursing homes, kindergartens, and primary schools coupled with the population density.

[0080] In the embodiment of the present invention, in step S103, a composite spatial network of multiple elements of the city may be constructed based on complex network and flow space theory.

[0081] In the embodiment of the present invention, the constructed composite spatial network of urban multi-elements changes with the change of the rainstorm period. For example, as the rainstorm develops, a certain road section will be impassable and needs to be removed from the composite spatial network.

[0082] Specifically, for a certain rainstorm period, step S103 may include the following sub-steps:

[0083] S1031, abstracting the road intersection into a road node set Abstract the road segments connecting road intersections into road edge sets

[0084] S1032, the road intersection v i ,v j The required travel time of the connecting section during the current rainstorm period t As the weight of the road edge, construct the adjacency matrix for time period t Form a dynamic weighted undirected graph that changes with the rainstorm period

[0085] S1033, extract the centroid of each community, use the population density of the community as the weight, and form a community node set

[0086] S1034, extracting the centroids of the community's internal service facilities and the community's external service facilities, using the supply of the service facilities as weights, to form a set of community service nodes and a set of community external service nodes that change with the rainstorm period:

[0087] S1035, determine the road intersections closest to the community node and the service nodes within the community and the service nodes outside the community, and connect them to create a community-road edge set, a community service-road edge set, and a community service-road edge set respectively:

[0088] S1036, obtain a dynamic weighted composite spatial network G(V) considering roads-communities-internal service facilities of the community-external service facilities of the community P ∪V D ∪V S_in ∪V S_ex ,L P ∪L D ∪L S_in ∪L S_ex ).

[0089] In the embodiment of the present invention, considering that the flooding conditions of roads caused by floods in different rainstorm periods are different, the road node set and the road edge set change dynamically with the different rainstorm periods.

[0090] In the embodiment of the present invention, due to the changes in the road node set and the road edge set, the community-road edge set, the community service-road edge set and the community service-road edge set also change dynamically. Finally, a composite spatial network that changes dynamically with the rainstorm period is constructed.

[0091] In the embodiment of the present invention, each community node corresponds to a set of in-community service nodes and a set of out-community service nodes, so that the shortest path from each community node to the corresponding in-community service nodes and out-community service nodes can be calculated in a rainstorm scenario.

[0092] In an embodiment of the present invention, in step S104, based on road capacity, service facility supply and demand, an improved two-step mobile search method can be used to calculate community comprehensive service accessibility, community internal service accessibility, and community external service accessibility.

[0093] Specifically, in step S104, for a certain service facility in a certain rainstorm period, the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold d0 can be used to determine the service range of the service facility.

[0094] Specifically, the shortest path can be calculated using the Dijkstra algorithm based on the actual road nodes and road edges during each rainstorm period. The specific calculation steps can be as follows:

[0095] S1, construct a graph set G = (N, E), where N represents the node set of the network graph and E represents the road travel time.

[0096] S2, the nodes in the network graph are grouped, one group is the shortest path set M from the known source point (community) s to other nodes, and the other group is the undetermined shortest path set R. The initial distance of the source point s is assigned to d[s] = 0, and the initial distance from the source point to other nodes is set to ∞.

[0097] S3, place the source point s in set M and other nodes in set R.

[0098] S4, traverse the set R to find the node m closest to the source point s i , m i Put it into the set M as the known shortest path node. Check whether the distance from other nodes in the set R to the source point s is greater than m i .

[0099] S4, repeat step S4 until the set R is empty, and then end the algorithm. The shortest path from the source point s to the target node (service facility) can be obtained.

[0100] In the embodiment of the present invention, in order to reduce the amount of calculation, for each community, only the shortest path between the community and predetermined service facilities within the community and service facilities outside the community may be calculated.

[0101] In the embodiment of the present invention, the service scope of each service facility can be determined based on the shortest path from the community to each service facility and the service response threshold d0. Specifically, based on the travel speed of each road section included in the shortest path during the corresponding rainstorm period, the shortest time required for the shortest path from the community to each service facility is determined. When the shortest time is less than the service response threshold, it is determined that the service facility can provide services to the community. Further, for a service facility, the community that it can serve can be determined.

[0102] In the embodiment of the present invention, after the shortest path is determined, the road capacity may also be calculated based on the following formula:

[0103]

[0104] Among them, B t (a) is the road capacity of road node a at time t; p t is the total number of shortest paths between road nodes b and c at time t; p t (a) The number of shortest paths between b and c passing through road node a at time t. In the embodiment of the present invention, considering that the lower the road capacity, the lower the accessibility of service facilities, which in turn affects the resilience assessment, the road capacity of each road node can be used as an influencing factor for the subsequent resilience assessment.

[0105] In the embodiment of the present invention, the two-step moving search method can be used to weight each community within the service range of the service facility using the Gaussian equation, and perform weighted summation to calculate the number of residents within the service range; then the supply of the service facility is divided by the number of residents within the service range to calculate the supply-demand ratio:

[0106]

[0107] in, represents the comprehensive supply-demand ratio of community i; represents the supply-demand ratio of service facilities within community i; P represents the supply-demand ratio of extra-community service facilities in community i; i It is within the scope of the service facility space (d kj ≤d0) of residents; d ij represents the distance from the service facility center to the center of community i; It indicates the supply of service facilities in the community; represents the supply of service facilities outside the community; G(dij ,d0) is the Gaussian equation that considers the impact of distance on service efficiency. The calculation formula is as follows:

[0108]

[0109] In an embodiment of the present invention, for community i, the corresponding service facilities within the community and service facilities outside the community are determined based on the service facilities determined to be able to provide services to the community. The service facilities within the community and service facilities outside the community are actual service facilities within the community and service facilities outside the community determined based on the road traffic conditions during the corresponding rainstorm period.

[0110] In the embodiment of the present invention, the supply-demand ratio of each service facility can be determined based on the supply volume of the service facility and the number of residents within its service area.

[0111] For a certain community, the supply-demand ratio of its within-community service facilities can be used as the corresponding supply-demand ratio of within-community service facilities for the community, the supply-demand ratio of its outside-community service facilities can be used as the corresponding supply-demand ratio of outside-community service facilities for the community, and the sum of the supply-demand ratio of within-community service facilities and the supply-demand ratio of outside-community service facilities can be used as the comprehensive supply-demand ratio of the community.

[0112] Furthermore, for a community i in a certain rainstorm period, a time threshold d0 is given to form another spatial scope. The supply-demand ratio of service facilities falling in the spatial scope is weighted and weighted summed using the Gaussian equation to obtain the service facility accessibility A of the community i. i :

[0113]

[0114] in, It indicates the accessibility of comprehensive community services; It indicates the accessibility of services within the community; Represents the accessibility of external services in the community.

[0115] In an embodiment of the present invention, the internal service accessibility of a community can be obtained based on the supply-demand ratio of all service facilities within the community, and the external service accessibility of the community can be obtained based on the supply-demand ratio of all service facilities outside the community. The sum of the internal service accessibility and the external service accessibility can be used as the comprehensive service accessibility of the community.

[0116] In an embodiment of the present invention, in step S105, the comprehensive resilience of the community, the internal resilience of the community and the external resilience of the community can be calculated respectively based on the comprehensive service accessibility of the community, the internal service accessibility of the community and the external service accessibility of the community that dynamically change with the rainstorm period.

[0117] Specifically, step S105 includes the following sub-steps:

[0118] S1051, determine the comprehensive service resilience of community i in each rainstorm period based on the comprehensive service accessibility of community i under normal circumstances and the comprehensive service accessibility of community i in each rainstorm period; determine the comprehensive community internal service resilience of community i in each rainstorm period based on the internal service accessibility of community i under normal circumstances and the internal service accessibility of community i in each rainstorm period; determine the community external service resilience of community i in each rainstorm period based on the external service accessibility of community i under normal circumstances and the external service accessibility of community i in each rainstorm period.

[0119] S1052, based on the comprehensive service accessibility of the community, the internal service accessibility of the community, and the external service accessibility of the community at different periods of the rainstorm, the community comprehensive resilience, the internal resilience of the community, and the external resilience of the community are obtained by fitting the community resilience curve:

[0120]

[0121] in, represents the comprehensive service accessibility of the community during the rainstorm period t, the internal service accessibility of the community during the rainstorm period t, or the external service accessibility of the community during the rainstorm period t. It represents the comprehensive service accessibility of the community under normal circumstances, the internal service accessibility of the community under normal circumstances, or the external service accessibility of the community under normal circumstances. R represents the comprehensive resilience of the community, the internal resilience of the community, or the external resilience of the community.

[0122] In the embodiment of the present invention, after determining the comprehensive resilience of the community, the internal resilience of the community, and the external resilience of the community, the community can also be classified into balanced development type, external dependence type, self-dominant type, and comprehensive weak type community. According to the characteristics of community resilience, corresponding improvement strategies are adopted according to local conditions.

[0123] The study found that most communities not only rely on their own service facilities when facing natural disasters, but also rely on external service support. In addition, taking life service facilities and medical service facilities as examples, the spatial distribution of service facilities has also brought significant changes to community resilience. Based on the community disaster resilience assessment and external correlation analysis, a reliable scientific basis can be provided for community disaster prevention and mitigation construction. For example, for externally dependent communities, it is necessary to balance the community's own development and external support, strengthen the construction and improvement of community internal service facilities, and improve the community's service capabilities for residents by improving the service facility network; for self-dominant communities, it is possible to try to establish a cross-community disaster material inventory system, including food, water, medical supplies, clothing and other urgently needed materials, and establish a sharing platform so that different communities can share these materials to improve resource sharing and response capabilities within the entire living circle. By quantitatively analyzing the resilience of internal service facilities and external service facilities in different communities, a scientific decision-making basis tailored to local conditions is provided for urban planning and management departments.

[0124] For ease of understanding, an exemplary embodiment is also provided in the embodiments of the present invention. Specifically, the exemplary embodiment is applied to a certain district in a certain city. Taking a rainstorm and flood event with a recurrence period of 100 years as an example, the community resilience based on the accessibility of service facilities and its external correlation relationship evaluation method proposed by the present invention is used as an implementation case. The data used in this implementation plan include population heat maps, POI data of service facilities such as large hospitals, community hospitals, convenience stores, vegetable markets, supermarkets, community attributes, real-time road speeds and flood disaster inundation data. The implementation plan conducts road risk analysis based on the inundation situation under a once-in-a-century rainfall scenario simulated by the SWMM and LISFLOOD-FP models provided by a certain geographic virtual laboratory. First, according to the inundation situation, the prohibited roads are processed, and then the roads are topologically processed using the spatial analysis function of ArcGIS, and the road nodes and road edges are connected using the spatial connection function, and exported as an EXCEL table. Finally, the road capacity is calculated using the GEPHI software, and the results are imported into ArcGIS for visualization.

[0125] In this embodiment, constructing a composite spatial network specifically includes:

[0126] The first step is to construct a road network. First, the road intersections and ramps at different rainstorm periods are abstracted as point sets, and the road sections connecting the intersections are abstracted as edge sets. Secondly, the travel time required for the road sections connecting the road intersections at the time of flooding t is calculated, and the adjacency matrix at time t is constructed to form a dynamic weighted undirected graph that changes over time.

[0127] The second step is to construct a composite spatial network. First, extract the centroids of community internal service facilities and community external service facilities, and use the capacity of the service facilities as weights to form a dynamic node set. Secondly, extract the centroids of community blocks and use crowd density as weights to form a dynamic node set. Then, determine the road intersections closest to these nodes and connect them to create edge sets. Finally, create a dynamic weighted urban composite spatial network that considers roads-communities-internal community service facilities-external community service facilities.

[0128] In this embodiment, calculating the community comprehensive service accessibility, the community internal service accessibility, and the community external service accessibility includes:

[0129] First, this embodiment selects the evening peak period to conduct resilience assessment under the rainfall scenario. Therefore, the historical road speeds at four time periods of 14:00, 16:00, 18:00, and 20:00 on five working days are obtained from the Amap network service API using the data acquisition interface, and the average of the speeds on the five working days is used as the real-time road speed for road connectivity analysis, where 14:00 is the real-time speed before the rain starts, 16:00 represents the speed when the rain lasts for 2 hours, 18:00 represents the speed when the rain lasts for 4 hours, and 20:00 represents the speed when the rain lasts for 6 hours.

[0130] Secondly, the supply capacity of service facilities is determined based on the scale of service facilities such as hospitals, convenience stores, and large supermarkets. The population density of each community is calculated based on the population heat map. Considering that some people have different needs for service facilities, the demand for service facilities in the community is calculated based on the density of vulnerable areas such as nursing homes, kindergartens, and primary schools coupled with the population density.

[0131] Finally, calculate the accessibility of service facilities. The implementation steps are as follows:

[0132] Step 1: Use ArcGIS's spatial analysis function to create a network dataset and change "Traffic Flow Attribute-Cost" to "Travel Time".

[0133] Step 2: First connect the service facilities with the community data, and then connect the block data with the data data.

[0134] Step 3: Calculate accessibility using ArcGIS OD cost matrix. First, calculate the accessibility of community services within the 15-minute living circle. Then, divide the service facilities within the living circle into internal community service facilities and external community service facilities, and calculate the accessibility of service facilities within the community and the accessibility of service facilities outside the community respectively.

[0135] The calculation of community comprehensive resilience, community internal resilience and community external resilience includes:

[0136] First, the resilience curve is fitted according to the accessibility of service facilities obtained in different periods, and the area of ​​the resilience curve is solved using the Python program to obtain the community's comprehensive resilience, community internal resilience, and community external resilience. Figure 2 The figure shows a schematic diagram of the resilience curve of service facilities in some communities, where the left figure is a schematic diagram of the distribution of communities and service facilities, and the right figure is the calculated resilience of each community. The line represents the comprehensive resilience curve of the community, the dotted line represents the external resilience curve of the community, and the dotted line represents the internal resilience curve of the community. Part A represents the community resilience analysis corresponding to living service facilities, and Part B represents the community resilience analysis corresponding to medical service facilities.

[0137] Based on the same inventive concept, an embodiment of the present invention further provides a community flood resilience and external relationship analysis device based on facility accessibility, the device comprising:

[0138] The first determination module is used to simulate flooding and inundation conditions based on a hydrological and hydrodynamic model to determine the road capacity of each road during each rainstorm period;

[0139] The second determination module is used to determine the population density of each community and the supply of service facilities within the community and the supply of service facilities outside the community;

[0140] A construction module is used to construct a composite spatial network corresponding to each rainstorm period according to the road traffic capacity of each rainstorm period, the population density of each community, and the supply of service facilities in each community and the supply of service facilities outside each community, wherein in the composite spatial network, road intersections are road nodes, roads connecting road nodes are road edges, the road traffic speed of each road is the weight of the road edge, the centroid of each community is the community node, the population density of each community is the weight of the community node, the centroid of the service facilities within the community is the service node within the community, the supply of service facilities within the community is the weight of the service node within the community, the centroid of the service facilities outside the community is the service node outside the community, the supply of service facilities outside the community is the weight of the service node, the community node and the nearest road node are connected as a community-road edge, the service node within the community and the nearest road node are connected as a community service-road edge, and the service node outside the community and the nearest road node are connected as an edge set of the service-road outside the community;

[0141] The first calculation module is used to calculate the community comprehensive service accessibility, community internal service accessibility and community external service accessibility of each community in each rainstorm period based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold;

[0142] The second calculation module is used to calculate the comprehensive community resilience, internal community resilience and external community resilience of each community based on the comprehensive community service accessibility, internal community service accessibility and external community service accessibility of each community during each rainstorm period.

[0143] Based on the same inventive concept, an embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes, the steps in the method for analyzing community flood resilience and external relations based on facility accessibility as described in any of the above embodiments are implemented.

[0144] Based on the same inventive concept, an embodiment of the present invention also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps in the community flood resilience and external relationship analysis method based on facility accessibility described in any of the above embodiments are implemented.

[0145] Based on the same inventive concept, an embodiment of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps in the community flood resilience and external relationship analysis method based on facility accessibility described in any of the above embodiments.

[0146] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0147] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0148] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (apparatus), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0149] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0150] These computer program instructions can also be loaded onto a computer or other programmable terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0151] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0152] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0153] The above is a detailed introduction to a community flood resilience and external relationship analysis method based on facility accessibility provided by the present invention. This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for analyzing community flood resilience and external relations based on facility accessibility, characterized in that: The method comprises: Simulate flooding and inundation conditions based on hydrological and hydrodynamic models to determine the road capacity of each road during each rainstorm period; Determine the population density of each community and the supply of community service facilities and the supply of extra-community service facilities; According to the road traffic capacity of each rainstorm period, the population density of each community, and the supply of service facilities in each community and the supply of service facilities outside each community, a composite spatial network corresponding to each rainstorm period is constructed, wherein in the composite spatial network, road intersections are road nodes, roads connecting road nodes are road edges, the road traffic speed of each road is the weight of the road edge, the centroid of each community is the community node, the population density of each community is the weight of the community node, the centroid of the community service facilities in the community is the community service node, the supply of service facilities in the community is the weight of the community service node, the centroid of the community service facilities outside the community is the community service node, the supply of service facilities outside the community is the weight of the service node, the community node and the nearest road node are connected as the community-road edge, the community service node and the nearest road node are connected as the community service-road edge, and the community service node and the nearest road node are connected as the community service-road edge. Based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold, the comprehensive community service accessibility, the internal community service accessibility and the external community service accessibility of each community in each rainstorm period are calculated respectively; The comprehensive community resilience, internal community resilience and external community resilience of each community are calculated based on the comprehensive community service accessibility, internal community service accessibility and external community service accessibility of each community during each rainstorm period.

2. The community flood resilience and external relationship analysis method based on facility accessibility according to claim 1 is characterized in that: Based on the hydrological and hydrodynamic model, the flood and inundation conditions are simulated to determine the road capacity during each rainstorm period, including: Simulate flooding and inundation conditions based on hydrological and hydrodynamic models, determine the inundation depth of each road, and remove roads whose inundation depth exceeds a preset threshold; The vehicle speed of each road in the normal situation of the corresponding period of each rainstorm period is obtained, and the vehicle speed in the normal situation is processed with deviation to obtain the traffic speed of each road in each rainstorm period.

3. The community flood resilience and external relationship analysis method based on facility accessibility according to claim 2 is characterized in that: The vehicle speed of each road in the normal situation of each rainstorm period is obtained, and the vehicle speed in the normal situation is processed with deviation to obtain the traffic speed of each road in each rainstorm period, including: For a period of heavy rain: Determine the correction coefficient λ corresponding to the jth road based on the road grade and road length of the jth road j ; The traffic speed of the jth road is determined based on the following formula: V'=λ j V j ; Where V' represents the corrected road speed, λ j represents the correction coefficient of the jth road, V j It represents the vehicle speed on the j-th road during the normal period of the rainstorm.

4. The community flood resilience and external relationship analysis method based on facility accessibility according to claim 1 is characterized in that: According to the road capacity of each rainstorm period, the population density of each community, the supply of service facilities in each community, and the supply of service facilities outside each community, a composite spatial network corresponding to each rainstorm period is constructed, including: For a period of heavy rain: Abstract road intersections as road node sets Abstract the road segments connecting road intersections into road edge sets The road intersection v i ,v j The required travel time of the connecting section during the current rainstorm period t As the weight of the road edge, construct the adjacency matrix for time period t Form a dynamic weighted undirected graph that changes with the rainstorm period Extract the centroid of each community and use the population density of the community as the weight to form a community node set The centroids of the community's internal and external service facilities are extracted, and the supply of service facilities is used as weight to form a set of internal and external service nodes that change with the rainstorm period: Determine the road intersections closest to the community node and the service nodes within the community and the service nodes outside the community, and connect them to create community-road edge sets, community service-road edge sets, and community service-road edge sets respectively: The dynamic weighted composite spatial network G(V P ∪V D ∪V S_in ∪V S_ex ,L P ∪L D ∪L S_in ∪L S_ex ).

5. The community flood resilience and external relationship analysis method based on facility accessibility according to claim 4 is characterized in that: Based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold, the comprehensive service accessibility of the community, the internal service accessibility of the community and the external service accessibility of the community during each rainstorm period are calculated respectively, including: For a service facility during a rainstorm period: the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold d0 are used to determine the service range of the service facility, and the Gaussian equation is used to weight each community within the service range, and the weighted sum is performed to calculate the number of residents within the service range; the supply of the service facility is then divided by the number of residents within the service range to calculate the supply-demand ratio: in, represents the comprehensive supply-demand ratio of community i; represents the supply-demand ratio of service facilities within community i; P represents the supply-demand ratio of extra-community service facilities in community i; i It is within the scope of the service facility space (d kj ≤d0) the number of residents in community i; d ij represents the distance from the service facility center to the center of community i; It indicates the supply of service facilities in the community; represents the supply of service facilities outside the community; G(d ij ,d0) is the Gaussian equation that considers the impact of distance on service efficiency. The calculation formula is as follows: For a community i in a certain rainstorm period, a time threshold d0 is given to form another spatial scope. The supply-demand ratio of service facilities in the spatial scope is weighted and summed using the Gaussian equation to obtain the accessibility A of the service facilities in the community i. i : in, It indicates the accessibility of comprehensive community services; It indicates the accessibility of services within the community; Represents the accessibility of external services in the community.

6. The community flood resilience and external relationship analysis method based on facility accessibility according to claim 5 is characterized in that: The comprehensive resilience of the community, internal resilience of the community, and external resilience of the community are calculated based on the comprehensive service accessibility of the community, internal service accessibility of the community, and external service accessibility of the community during each rainstorm period, including: The comprehensive service resilience of community i in each rainstorm period is determined based on the comprehensive service accessibility of community i under normal circumstances and the comprehensive service accessibility of community i in each rainstorm period. The comprehensive internal community service resilience of community i in each rainstorm period is determined based on the internal community service accessibility of community i under normal circumstances and the internal community service accessibility of community i in each rainstorm period. The external community service resilience of community i in each rainstorm period is determined based on the external community service accessibility of community i under normal circumstances and the external community service accessibility of community i in each rainstorm period. The community comprehensive service accessibility, community internal service accessibility and community external service accessibility at different periods of heavy rain are fitted into community resilience curves to obtain community comprehensive resilience, community internal resilience and community external resilience: in, represents the comprehensive service accessibility of the community during the rainstorm period t, the internal service accessibility of the community during the rainstorm period t, or the external service accessibility of the community during the rainstorm period t. It represents the comprehensive service accessibility of the community under normal circumstances, the internal service accessibility of the community under normal circumstances, or the external service accessibility of the community under normal circumstances. R represents the comprehensive resilience of the community, the internal resilience of the community, or the external resilience of the community.

7. A community flood resilience and external relationship analysis device based on facility accessibility, characterized in that: The device comprises: The first determination module is used to simulate flooding and inundation conditions based on a hydrological and hydrodynamic model to determine the road capacity of each road during each rainstorm period; The second determination module is used to determine the population density of each community and the supply of service facilities within the community and the supply of service facilities outside the community; A construction module is used to construct a composite spatial network corresponding to each rainstorm period according to the road traffic capacity of each rainstorm period, the population density of each community, and the supply of service facilities in each community and the supply of service facilities outside each community, wherein in the composite spatial network, road intersections are road nodes, roads connecting road nodes are road edges, the road traffic speed of each road is the weight of the road edge, the centroid of each community is the community node, the population density of each community is the weight of the community node, the centroid of the service facilities within the community is the service node within the community, the supply of service facilities within the community is the weight of the service node within the community, the centroid of the service facilities outside the community is the service node outside the community, the supply of service facilities outside the community is the weight of the service node, the community node and the nearest road node are connected as a community-road edge, the service node within the community and the nearest road node are connected as a community service-road edge, and the service node outside the community and the nearest road node are connected as an edge set of the service-road outside the community; The first calculation module is used to calculate the community comprehensive service accessibility, community internal service accessibility and community external service accessibility of each community in each rainstorm period based on the shortest path calculation algorithm, the two-step mobile search method, the composite spatial network and the service response threshold; The second calculation module is used to calculate the comprehensive community resilience, internal community resilience and external community resilience of each community based on the comprehensive community service accessibility, internal community service accessibility and external community service accessibility of each community during each rainstorm period.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the community flood resilience and external relationship analysis method based on facility accessibility described in any one of claims 1-6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the community flood resilience and external relationship analysis method based on facility accessibility as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps in the community flood resilience and external relationship analysis method based on facility accessibility described in any one of claims 1-6 are implemented.

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