Emergency shelter global planning method based on multi-disaster risk coupling

Abstract

The invention relates to the technical field of path optimization, in particular to an emergency shelter global planning method based on multi-disaster risk coupling, which comprises the following steps: acquiring disaster source and DEM grid coordinates and calculating distance, selecting grids according to influence radius, comparing and connecting grid elevation identification peak points, and determining a propagation restriction area by combining the disaster source and a water diversion line. And matching the positions of the shelters and sorting with the road network. According to the method, differential disaster diffusion ranges are identified in a unified space framework by introducing spatial positions of various disaster sources and combining a grid distance relation, terrain peak points are identified by combining grid elevation differences, correlation analysis is performed by combining a spatial adjacency relation, and the disaster diffusion ranges are identified according to a spatial cross relation between the disaster source positions and water diversion line nodes. A potential disaster diffusion channel is avoided in the shelter screening process, space matching is carried out by combining the shelter boundary position and the road network, and the shelter space layout stability under the terrain and the multi-disaster scene is enhanced according to the road access direction.

Description

Technical Field

[0001] This invention relates to the field of path optimization technology, and in particular to a method for comprehensive planning of emergency shelters based on the coupling of multiple disaster risks. Background Technology

[0002] The field of route optimization technology mainly studies methods for planning facility locations and travel routes under given spatial environment and constraints. This field involves core matters such as spatial node determination, establishing road connection relationships between nodes, road length calculation, travel route selection, and delineation of facility service areas. Typically, by collecting regional road distribution maps, residential location data, and public facility location data, the urban area is divided into several nodes and road connection relationships are established. Then, based on road length, road intersection location, and travel direction, the travel routes between nodes are calculated. At the same time, the service area is determined by combining population distribution and facility location, thereby forming an overall plan for regional facility layout and travel routes. The traditional method of comprehensive planning for emergency shelters refers to the method of arranging shelter layouts and evacuation routes in response to the needs of evacuation and centralized resettlement of people in urban disaster situations. It usually selects school playgrounds, open spaces in parks or squares as candidate shelters based on urban administrative divisions, determines the shelter capacity by counting the population of each residential area, determines the road connection between residential areas and shelters based on urban road maps, determines the route from residential areas to shelters by calculating road lengths, and delineates unusable areas based on historical flood records or earthquake-affected areas. Within the usable areas, the location of shelters and evacuation routes of residents are laid out as a whole.

[0003] Existing shelter planning mainly relies on the established public space and population size for capacity allocation. The planning basis focuses on site availability and road connectivity. In the spatial analysis process, there is a lack of detailed identification of the relationship between topographic structure and disaster spread boundary. In areas with significant topographic relief or multiple disasters, it is difficult to identify potential disaster spread channels. For example, when landslides and floods spread along slopes and low-lying channels in mountainous cities, existing plans tend to form shelter layouts near topographic confluence channels. At the same time, evacuation route planning focuses on road length and connectivity, ignoring the spatial impact of topographic barriers and disaster spread direction. During the disaster development stage, there may be situations where the personnel transfer path and the disaster spread direction intersect, thereby weakening the stability of the safety boundary of the shelter space and affecting the efficiency of evacuation organization in disaster situations. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a method for comprehensive planning of emergency shelters based on multi-hazard risk coupling; To achieve the above objectives, the present invention adopts the following technical solution: a comprehensive planning method for emergency shelters based on multi-hazard risk coupling, comprising the following steps: S1: Obtain the location of the earthquake epicenter, flood overflow point and landslide source, read the city DEM grid coordinates, calculate the distance between the disaster source and the grid center, select the grid area according to the disaster type's influence radius, and obtain the set of multi-hazard influence coverage areas; S2: Based on the set of multi-hazard impact coverage areas, read grid elevation data, compare the elevation values ​​of adjacent grids, identify elevation peaks and connect them along the spatial adjacency direction, divide the terrain boundary structure, and obtain the spatial node sequence of the surface watershed. S3: Based on the spatial node sequence of the surface watershed, read the coordinates of the disaster source and the center of the grid, and compare the cross relationship with the spatial node sequence of the surface watershed to obtain the set of disaster propagation restriction areas; S4: Based on the set of disaster propagation restriction areas, obtain the boundary locations of emergency shelter squares and community shelter parks, read the spatial comparison between the center coordinates of the site and the propagation restriction areas, and obtain the set of shelter locations; S5: Based on the set of locations of the emergency shelters, read the site boundary coordinates and perform spatial matching with the urban road network, sort the site locations along the road access directions, arrange the spatial distribution relationship, and obtain the overall deployment plan of emergency shelters.

[0005] As a further aspect of the present invention, the set of multi-hazard impact coverage areas includes earthquake impact coverage areas, flood impact coverage areas, landslide impact coverage areas, and disaster superposition impact areas; the spatial node sequence of the surface watershed includes watershed node coordinates, topographic boundary line nodes, slope aspect separation nodes, and peak-ridge connection nodes; the set of disaster propagation restriction areas includes watershed blocking areas, topographic shielding areas, propagation interception areas, and risk isolation areas; the set of refuge site locations includes square refuge sites, park refuge sites, community emergency site locations, and centralized refuge node locations; and the overall deployment scheme of emergency refuge sites includes the spatial layout structure of refuge sites, road access and connection structure, site service coverage structure, and urban refuge network structure.

[0006] As a further aspect of the present invention, the landslide source location refers to the starting point of the initial occurrence of the landslide disaster, that is, the spatial source point coordinates of the landslide body that begins to generate and spread outward. The terrain boundary structure refers to the terrain boundary line and watershed structure identified and connected based on DEM elevation data, which is used to divide the spatial boundaries of differentiated terrain units and disaster propagation directions.

[0007] As a further aspect of the present invention, the intersection relationship refers to the spatial intersection or crossing relationship between the disaster source location and the sequence of surface watershed nodes, in order to determine the limitation of terrain on disaster propagation; The spatial distribution relationship refers to the overall distribution structure formed by spatially sorting and arranging multiple refuge sites according to the road access direction and site location.

[0008] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Obtain the location of the city's earthquake epicenter, river flood overflow location, and landslide source location; collect the grid coordinates of the city's digital elevation model; extract the spatial coordinates of the center point of each grid; perform coordinate difference calculations by calling the coordinates of the epicenter, overflow, and landslide source locations with the coordinates of the grid center point; calculate the point-to-point spatial distance based on the plane coordinate difference values; measure the distance between the disaster source and the grid center point; and obtain the disaster source grid spatial distance table. S102: Based on the disaster source grid spatial distance table, obtain the preset earthquake influence radius, flood inundation radius, and landslide influence radius, call the distance value and the corresponding disaster source radius comparison value, select the grid number within the radius range and associate it with the disaster source type to obtain the disaster effect grid set; S103: Based on the disaster impact grid set, read the spatial adjacency relationship of the grid numbers, perform up, down, left and right adjacency determination according to the row and column index of the grid numbers, perform connectivity identification and range merging on continuous adjacent grid numbers, associate the grid numbers of the same connected region, and obtain the set of multi-hazard impact coverage areas.

[0009] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Based on the set of multi-hazard impact coverage areas, collect elevation data of the corresponding grid area, extract the elevation value of the center point of each grid, call the center point elevation value and compare the spatial values ​​with the center point elevation values ​​of the four neighboring grids, identify the coordinates of the grid center point where the adjacent directions are all lower than the center point elevation value, extract the coordinates of the corresponding grid center point and associate them with the grid number to obtain the set of elevation peak point coordinates; S202: Based on the set of elevation peak coordinates, detect the spatial adjacency relationship of elevation peak coordinates, call the grid row and column index to identify the position direction of adjacent peaks, connect the consecutive peak coordinates in adjacent directions and associate the direction sequence to obtain the elevation peak connection sequence. S203: Based on the elevation peak connection sequence, monitor the spatial distribution direction of the connection segment, identify the segment partition according to the change in the connection segment direction, extract the node sequence of the continuous direction consistent line segment and associate it with the spatial coordinate sequence to obtain the spatial node sequence of the surface watershed.

[0010] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Based on the spatial node sequence of the surface watershed, obtain the location coordinates of the disaster source, collect the center coordinates of the grid area, connect the location coordinates of the disaster source with the center coordinates of the grid area with a straight line, and determine the direction and spatial position of the connecting line according to the starting coordinates and the ending coordinates to obtain the disaster source grid connection sequence. S302: Based on the disaster source grid connection sequence, compare the coordinate trajectory of each connection with the spatial position of the adjacent node line segment of the node sequence, detect the intersection position of the connection trajectory and the node line segment, associate the connection number of the intersection position with the corresponding node line segment number, and obtain the connection intersection relationship sequence. S303: Based on the connection and intersection sequence, retrieve the center coordinates of the corresponding grid area and the location coordinates of the disaster source, retrieve the corresponding grid number according to the connection number of the intersection position, divide the area according to the spatial distribution range of the intersection position, and aggregate and associate the grid numbers of the same distribution range to obtain the set of disaster propagation restriction areas.

[0011] As a further aspect of the present invention, in the process of connecting the disaster source location coordinates and the grid area center coordinates with a straight line: points are continuously sampled along the line connecting the disaster source location coordinates and the grid area center coordinates at fixed intervals to obtain a sequence of line sampling point coordinates distributed along the line direction; In the process of comparing the coordinate trajectory of each connecting line with the spatial position of the adjacent node line segment of the node sequence: the coordinate sequence of the connecting line sampling points is matched point by point with the spatial position of the adjacent node line segment of the node sequence, and the spatial position status of the connecting line sampling point coordinates on both sides of the adjacent node line segment of the node sequence is identified, so as to locate the intersection position between the connecting line trajectory and the node line segment by the connecting line sampling point coordinates that have changed position.

[0012] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: Based on the set of disaster propagation restriction areas, obtain the boundary locations of the emergency shelter square and the community emergency shelter park, collect the center coordinates of the site, call the site center coordinates and compare the spatial location with the center coordinates of the grid of the disaster propagation restriction area set, identify the site number where the center coordinates are located within the area and associate the site type information to obtain a set of candidate coordinates for shelter sites. S402: Based on the candidate coordinate set of the refuge sites, detect the spatial orientation distribution of the candidate coordinates, call the row and column index of the city grid to identify the spatial direction sequence of the candidate coordinates, associate the coordinate orientations with the same direction sequence and aggregate the coordinate numbers to obtain the direction distribution sequence of the refuge sites. S403: Based on the distribution sequence of the refuge sites, retrieve the spatial relationship between the site boundary position and the center coordinates corresponding to the coordinate number, classify the positions according to the spatial distribution direction of the city, associate the site numbers in the same spatial direction, and obtain the set of refuge site locations.

[0013] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: Based on the set of locations of the refuge sites, obtain the boundary coordinates of the refuge sites, collect the spatial distribution coordinates of the urban road network, compare the spatial location of the site boundary coordinates with the coordinates of the road network line segments, identify the relationship between the access directions of the adjacent roads of the boundary coordinates, associate the road direction information corresponding to the site number, and obtain the sequence of the access directions of the site roads. S502: Based on the site road access direction sequence, detect the road direction extension path corresponding to the site number, call the spatial direction of the road network line segment to identify the road extension direction, divide the site number along the road extension direction and associate the site number order to obtain the site road access sequence sequence. S503: Based on the road access sequence of the site, retrieve the boundary coordinates and spatial orientation information corresponding to the site number, uniformly arrange the site numbers according to the road extension direction, associate the spatial position relationship of the site numbers in the direction, and obtain the overall layout plan of emergency shelters.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by introducing the spatial locations of multiple types of disaster sources and combining them with grid distance relationships, the differentiated disaster spread ranges are identified within a unified spatial framework. Topographic peaks are identified by combining grid elevation differences and correlation analysis is performed by combining spatial adjacency relationships. By using the spatial intersection relationship between disaster source locations and watershed nodes, the selection process of refuge sites avoids potential disaster spread channels. Spatial matching is performed by combining the boundary locations of refuge sites with road networks and based on road access directions, thereby enhancing the stability of refuge space layout under terrain and multi-disaster scenarios. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6This is a detailed schematic diagram of S5 of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] Please see Figure 1 This invention provides a method for comprehensive planning of emergency shelters based on multi-hazard risk coupling, comprising the following steps: S1: Obtain the location of the urban earthquake epicenter, the location of river flood overflow, and the location of landslide source. Collect the grid coordinates of the urban terrain digital elevation model. Compare the spatial distance between the earthquake epicenter, the location of river flood overflow, the location of landslide source and the grid center coordinates. Combine the earthquake influence radius, the flood inundation radius, and the landslide influence radius to spatially select the grid area. Merge the range along the spatial adjacency direction to obtain the set of multi-hazard impact coverage areas. S2: Based on the set of multi-hazard impact coverage areas, read the elevation data of the corresponding grid area, spatially compare the elevation values ​​of the grid area with those of adjacent grid areas, select the elevation peak coordinates, continuously connect the elevation peak coordinates along the spatial adjacency direction, and divide the terrain boundary line structure according to the spatial distribution direction to obtain the spatial node sequence of the surface watershed. S3: Based on the spatial node sequence of the surface watershed, read the location of the disaster source and the coordinates of the center of the grid area, identify the spatial relationship between the location of the disaster source and the coordinates of the center of the grid area, and compare the cross relationship with the spatial node sequence of the surface watershed to divide the propagation range of the area where the cross relationship occurs, and obtain the set of disaster propagation restriction areas; S4: Based on the set of disaster propagation restriction areas, obtain the boundary locations of emergency shelter plazas and community emergency shelter parks, read the center coordinates of the sites and compare them with the set of disaster propagation restriction areas, filter the spatial locations of sites within the disaster propagation restriction areas, and classify the locations along the urban spatial distribution direction to obtain the set of shelter locations. S5: Based on the set of locations of emergency shelters, read the site boundary coordinates, compare the site boundary coordinates with the spatial distribution of the urban road network, divide the site location order along the road access direction, and uniformly arrange the spatial distribution relationship of the sites to obtain the overall deployment plan of emergency shelters.

[0020] The set of multi-hazard impact areas includes earthquake-affected areas, flood-affected areas, landslide-affected areas, and areas with overlapping disaster impacts. The spatial node sequence of the surface watershed includes watershed node coordinates, topographic boundary nodes, slope aspect separation nodes, and peak-ridge connection nodes. The set of disaster propagation restriction areas includes watershed barrier areas, topographic shielding areas, propagation interception areas, and risk isolation areas. The set of shelter locations includes plaza shelter locations, park shelter locations, community emergency site locations, and centralized shelter node locations. The overall deployment plan for emergency shelters includes the spatial layout structure of shelters, road access and connection structure, site service coverage structure, and urban shelter network structure.

[0021] Please see Figure 2 The specific steps of S1 are as follows: S101: Obtain the location of the city's earthquake epicenter, river flood overflow location, and landslide source location; collect the grid coordinates of the city's digital elevation model; extract the spatial coordinates of the center point of each grid; perform coordinate difference calculations by calling the coordinates of the epicenter, overflow, and landslide source locations with the coordinates of the grid center point; calculate the point-to-point spatial distance based on the plane coordinate difference values; measure the distance between the disaster source and the grid center point; and obtain the disaster source grid spatial distance table. First, the coordinates of the epicenter in the disaster-stricken area of ​​the target city were retrieved. These coordinates were obtained based on latitude and longitude data from the Global Positioning System (GPS) and converted to the Gauss-Kruger projection coordinate system. For example, the abscissa of the epicenter was measured as 345,678.25 meters, and the ordinate as 3,123,456.72 meters. Simultaneously, the location of flood overflow was identified using hydrological remote sensing monitoring stations deployed around major rivers, and the abscissa of the flood overflow point was extracted as 346,120.50 meters, and the ordinate as 3,124,100.15 meters. Furthermore, the location of the landslide source was collected using BeiDou high-precision displacement sensors deployed at landslide hazard points, yielding the abscissa of the landslide source point as 344,980.12 meters, and the ordinate as 3,122,850.40 meters. During the spatial gridding process, the coordinates of the topographic digital elevation model grid in the urban basic mapping database were retrieved. The grid side length was set to 20 meters, and grid data containing 250,000 cells was collected. When extracting the spatial coordinates of the center point of each grid, this is achieved by obtaining the coordinates of the lower left corner of the grid and adding an offset of 10 meters to each. For example, for grid number 101, the x-coordinate of its center point is 345000 meters and the y-coordinate is 3123000 meters. Then, the coordinates of the epicenter, overflow, and landslide source are used to perform a planar coordinate difference calculation with the coordinates of the grid center point. Taking the epicenter as an example, the horizontal difference of 678.25 meters is obtained by subtracting the horizontal coordinate of the grid center of 345000 meters from the horizontal coordinate of the epicenter of 345678.25 meters, and the vertical difference of 456.72 meters is obtained by subtracting 3123000 meters from the vertical coordinate of the epicenter of 3123456.72 meters. The spatial distance between points is calculated based on the difference in planar coordinates. The difference in both directions is squared and then summed: 678.25 squared plus 456.72 squared, resulting in 668616.22. This result is then square-rooted, yielding a spatial distance of 817.69 meters between the center point of grid 101 and the epicenter. This process is repeated to measure the spatial mapping distance between all disaster source points and grid center points across the entire region. The distance values ​​from all grids to different disaster sources are then compiled into a table, resulting in a disaster source grid spatial distance table.

[0022] S102: Based on the disaster source grid spatial distance table, obtain the preset earthquake influence radius, flood inundation radius, and landslide influence radius, call the distance value and compare it with the corresponding disaster source radius value, select the grid number within the radius range and associate it with the disaster source type to obtain the disaster effect grid set; First, the pre-set disaster diffusion characteristic parameters in the urban disaster emergency plan are retrieved, obtaining the pre-set earthquake influence radius of 5000 meters, flood inundation radius of 1200 meters, and landslide influence radius of 600 meters. These values ​​are set based on the intensity attenuation model of similar historical disasters and the failure envelope of fluid dynamics simulation. Based on the spatial distance table of disaster source grids, spatial threshold filtering logic is executed, comparing the distance values ​​with the corresponding disaster source radii, and performing Boolean judgments row by row for all grids. For example, for grid number 205, its distance to the epicenter is retrieved as 4200 meters. This is compared with the earthquake influence radius of 5000 meters. Since 4200 is less than 5000, this grid is marked as being affected by an earthquake. Similarly, if the distance of a grid to the flood overflow point is 1300 meters, it is compared with the inundation radius of 1200 meters. Since 1300 is greater than 1200, this grid is determined not to be within the flood influence range. During the full traversal, grid numbers within the radius are selected and associated with the corresponding disaster type identifier. If a grid is within the influence radius of multiple disasters, multiple attribute annotations are performed. By completing the radius comparison and attribute association of all 250,000 grids, all grid records identified as affected are extracted to obtain the disaster-affected grid set.

[0023] S103: Based on the disaster impact grid set, read the spatial adjacency relationship of grid numbers, perform up, down, left and right adjacency determination according to the row and column index of grid numbers, perform connectivity identification and range merging on consecutive adjacent grid numbers, associate grid numbers of the same connected area, and obtain a set of multi-hazard impact coverage areas. First, based on the data in the disaster impact grid set, spatial topological relationships are established and analyzed, and the spatial adjacency relationships of grid numbers are read. Moore's neighborhood determination is performed based on the row and column indices of the grid numbers, extracting the row and column numbers of each grid, calculating the index position of the current grid in the horizontal and vertical directions adjacent to one unit, and determining whether grids in the eight surrounding directions exist in the disaster set. The determination logic is set so that if adjacent grids are in the disaster set, they are considered to have spatial connectivity. Connectivity identification and range merging are performed on consecutively adjacent grid numbers. A depth-first search algorithm is used, starting with any disaster-affected grid in the set as a seed point, to traverse and divide all spatially adjacent grids into the same connected cluster, assigning a unique region identification ID code to this cluster. Grid numbers of the same connected region are associated, aggregating discrete grid units into polygonal areas with continuous geometric boundaries. By performing connectivity traversal on the entire disaster-affected grid, all independent or superimposed disaster impact ranges are identified, resulting in a set of multi-hazard impact coverage areas.

[0024] Please see Figure 3 The specific steps of S2 are as follows: S201: Based on the set of areas covered by multiple disasters, collect elevation data of the corresponding grid area, extract the elevation value of the center point of each grid, call the center point elevation value and compare the spatial values ​​with the center point elevation values ​​of the four neighboring grids, identify the coordinates of the grid center point where the adjacent directions are all lower than the center point elevation value, extract the coordinates of the corresponding grid center point and associate them with the grid number to obtain the set of elevation peak point coordinates. First, based on the set of areas affected by multiple disasters, the terrain database interface is invoked to collect elevation data for the corresponding grid areas. The terrain digital elevation model file is parsed to extract the elevation value of the center point of each grid. For example, grid number 8001 is retrieved, and its vertical elevation value is read as 125.5 meters. The elevation value of the center point is spatially compared with the elevation values ​​of the center points of the four adjacent grids (above, below, to the left, and to the right). The elevation values ​​of the four adjacent grids above, below, to the left, and to the right of grid 8001 are obtained through the grid index: 124.2 meters, 123.8 meters, 124.5 meters, and 125.1 meters, respectively. Local maximum detection is performed to identify the coordinates of the center points of grids whose adjacent directions are all lower than the center point's elevation value. During this process, since the elevation of grid 8001 (125.5 meters) is strictly greater than the maximum elevation of all its surrounding points (125.1 meters), the logic output is true, and the coordinates of the grid's center point are recorded. By iterating through each grid cell in the disaster-stricken area, the coordinates of the corresponding elevation maximum center point are extracted and associated with the grid cell number. Grid cells on slopes or in depressions are filtered out to obtain the set of elevation peak coordinates.

[0025] S202: Based on the set of elevation peak coordinates, detect the spatial adjacency relationship of elevation peak coordinates, call the grid row and column index to identify the position direction of adjacent peaks, connect the coordinate order of consecutive peaks in adjacent directions and associate the direction sequence to obtain the elevation peak connection sequence. First, based on the set of elevation peak coordinates, a preliminary connection of terrain ridge lines is constructed to detect the spatial adjacency of elevation peak coordinates. The grid row and column indices are used to identify the position and direction of adjacent peaks. A distance search threshold for peak connection is set; if the absolute difference in the row number and column number of two peaks is no greater than 2, they are considered to have topological connection potential. The coordinate sequence of consecutive peaks in adjacent directions is connected and associated with the direction sequence. A greedy algorithm is used to establish directed connection vectors from the highest elevation peak in the region to the second highest elevation peak in its neighborhood that meets the distance threshold. For example, if peak P1 is located at row 100, column 150, and peak P2 is found at row 101, column 151, a broken line segment is established from P1 to P2. The azimuth angle of this connection relative to true north is recorded, and each directed segment is chained together according to spatial topological order, thus transforming isolated peaks into continuous line segments reflecting the ridge trend, resulting in the elevation peak connection sequence.

[0026] S203: Based on the elevation peak connection sequence, monitor the spatial distribution direction of the connection segment, identify the segment partition according to the change of the connection segment direction, extract the node sequence of the continuous direction consistent line segment and associate it with the spatial coordinate sequence to obtain the spatial node sequence of the surface watershed. First, based on the elevation peak connection sequence, geometric simplification and feature extraction of terrain barriers are performed to monitor the spatial distribution direction of the connection segments. Consistency identification is performed by calculating the directional angle between adjacent vectors in the connection sequence, with a directional change threshold set at 20 degrees, determined based on the average variability of the terrain slope. Line segment partitioning is identified based on the directional changes of the connection segments. If the directional deviation of multiple consecutive connection segments consistently meets the requirement of less than 20 degrees, they are classified as surface watersheds with the same stable trend; if the directional change exceeds 20 degrees, path segmentation is performed at that node. The sequence of line segment nodes with consistent directions is extracted and associated with a spatial coordinate sequence. The Douglas-Puk algorithm is used to simplify the segmented polylines, retaining the coordinate sequence of key control points with physical significance of terrain barriers. By performing logical partitioning and simplification on the entire connection sequence, the spatial node sequence of surface watersheds is obtained.

[0027] Please see Figure 4 The specific steps of S3 are as follows: S301: Based on the spatial node sequence of the surface watershed, obtain the location coordinates of the disaster source, collect the center coordinates of the grid area, connect the location coordinates of the disaster source with the center coordinates of the grid area with a straight line, and determine the direction and spatial position of the connecting line according to the starting coordinates and the ending coordinates to obtain the disaster source grid connection sequence. First, based on the spatial node sequence of the watershed, the planar projection coordinates of the disaster source are obtained. For example, the horizontal and vertical coordinates of the earthquake epicenter are 345,678 meters and 3,123,456 meters, respectively. The center coordinates of the grid area are collected, and the center point positions of all grids to be evaluated within the disaster area are extracted. Straight lines are connected to the disaster source location coordinates and the center coordinates of each grid area to establish a spatial radiation vector line simulating the straight-line propagation path of disaster energy. The direction of the connecting line is determined based on the relative positions of the starting and ending points. By calculating the azimuth angle of the grid center point relative to the disaster source, the geometric equation of the propagation path is determined. For example, for grid number 2001, a ray is established from the epicenter to its center point, and its planar straight-line propagation distance is calculated. By repeatedly performing the connecting operation on each grid unit within the area, the point units in geographic space are transformed into a path sequence with propagation direction attributes, resulting in the disaster source grid connection sequence.

[0028] S302: Based on the disaster source grid connection sequence, compare the coordinate trajectory of each connection with the spatial position of the adjacent node line segment in the node sequence, detect the intersection position of the connection trajectory and the node line segment, associate the connection number of the intersection position with the corresponding node line segment number, and obtain the connection intersection relationship sequence. First, based on the disaster source grid connection sequence, spatial interference collision detection is performed to compare the coordinate trajectory of each propagation line with the spatial positional relationship of the line segments in the surface watershed node sequence. Each pair of adjacent nodes in the surface watershed is treated as a rigid physical barrier boundary, and the geometric intersection of the propagation line trajectory and the watershed segment is detected. The decision logic uses a vector cross product algorithm, which determines whether the two endpoints of the propagation line are located on opposite sides of the watershed segment, and whether the endpoints of the watershed segment are also located on opposite sides of the propagation line, to confirm whether they intersect in the two-dimensional plane. For example, when the propagation line numbered 5005 geometrically intersects the watershed segment numbered FS-05, the line number at the intersection position and the corresponding watershed segment number are recorded, thereby identifying all grids whose propagation paths are intercepted by terrain ridges, and obtaining the connection intersection relationship sequence.

[0029] S303: Based on the sequence of line intersection relationships, retrieve the center coordinates of the corresponding grid area and the location coordinates of the disaster source, retrieve the corresponding grid number according to the line number of the intersection, divide the area according to the spatial distribution range of the intersection, and aggregate and associate the grid numbers of the same distribution range to obtain the set of disaster propagation restriction areas; First, based on the sequence of intersecting lines, the coordinates of the center of the corresponding grid area and the coordinates of the disaster source are retrieved to identify grid cells located in the disaster propagation shadow zone due to terrain obstruction. The corresponding grid number is retrieved based on the line number at the intersection, and the area is divided according to the spatial distribution range of the intersection. A density-based spatial clustering algorithm is used to merge grids that are blocked by the same waterline and are geographically adjacent. Grid numbers with the same distribution range are clustered together, and these terrain-protected grid cells are encapsulated as independent safe zones, with the geometric boundary of their enclosing polygons calculated. Through this process, the shielding effect of terrain on disaster kinetic energy is transformed into a quantitative disaster avoidance spatial range, resulting in a set of disaster propagation restriction areas.

[0030] Please see Figure 5 The specific steps of S4 are as follows: S401: Based on the set of disaster propagation restriction areas, obtain the boundary locations of emergency shelter squares and community emergency shelter parks, collect the center coordinates of the sites, compare the spatial location of the site center coordinates with the center coordinates of the grid of the disaster propagation restriction area set, identify the site number where the center coordinates are located within the area and associate the site type information to obtain a set of candidate coordinates for shelter sites. First, based on the disaster propagation restriction zone set, the boundary locations of emergency shelter plazas and community emergency shelter parks registered by the urban emergency management department are obtained. Vector redline polygons for each candidate shelter are extracted from the urban public facility geographic information layer, and the center coordinates of the sites are collected. The planar coordinates of the geometric center of each candidate shelter are calculated. The inclusion relationship between the site center coordinates and the polygon boundaries in the disaster propagation restriction zone set is determined, using the ray casting method to determine whether the center point falls within the restricted area. For example, if the center coordinates of Shelter Plaza No. 1 are confirmed to be within the restricted area after comparison, it indicates that the site is effectively protected by natural terrain barriers. Site numbers whose center coordinates are within the area are identified and their functional attribute information is associated. Points located in the direct impact zone of the disaster or high-risk exposure zone are eliminated, resulting in a candidate set of shelter coordinates.

[0031] S402: Based on the candidate coordinate set of refuge sites, detect the spatial orientation distribution of candidate coordinates, call the row and column index of the city grid to identify the spatial orientation sequence of candidate coordinates, associate the coordinate orientations with the same orientation sequence and aggregate the coordinate numbers to obtain the orientation distribution sequence of refuge sites. First, based on the candidate coordinate set of refuge sites, a spatial distribution balance test of refuge resources is performed to detect the spatial orientation distribution characteristics of the candidate coordinates. By determining the coordinates of the city's geographic center, the azimuth angle of each candidate refuge site relative to the city center is calculated. The city grid row and column index is used to identify the spatial orientation sequence of the candidate coordinates, dividing the 360-degree radius into eight main orientation sectors, each covering a 45-degree range. Coordinates with consistent orientation sequences are associated and their coordinate numbers are grouped together. Refuge sites located within the same orientation sector are statistically classified, and the supply capacity of refuge resources in different geographic directions is quantitatively analyzed. Through this orientation mapping logic, the orientation distribution sequence of refuge sites is obtained.

[0032] S403: Based on the distribution sequence of refuge sites by direction, retrieve the spatial relationship between the site boundary position and the center coordinate of the corresponding coordinate number, classify the location according to the spatial distribution direction of the city, associate the site number of the same spatial direction, and obtain the set of refuge site locations. First, based on the directional distribution sequence of refuge sites, the spatial relationship between the site boundary locations and center coordinates corresponding to the coordinate numbers is retrieved. Sites are categorized according to their urban spatial distribution direction, and within each specific directional sector, the carrying capacity and service level of the sites are screened. Site numbers in the same spatial direction are associated, and the effective refuge area, per capita allocation index, and spatial distance from surrounding densely populated areas are comprehensively considered. For example, in the eastward sequence, the boundary coordinates of each site are compared, retaining sites with sufficient area and evacuation center characteristics, while eliminating resource redundancy caused by overlapping service radii. Through refined location optimization and scale classification of candidate sites, a set of refuge site locations is obtained.

[0033] Please see Figure 6 The specific steps of S5 are as follows: S501: Based on the set of locations of refuge sites, obtain the boundary coordinates of refuge sites, collect the spatial distribution coordinates of the urban road network, compare the spatial location of the site boundary coordinates with the coordinates of the road network line segments, identify the relationship between the access directions of adjacent roads of the boundary coordinates, associate the road direction information corresponding to the site number, and obtain the sequence of road access directions of the site. First, based on the set of refuge site locations, the boundary coordinates of the refuge sites are obtained, and the key entrance and exit node information of each selected site is extracted. The spatial distribution coordinates of the urban road network are collected, and vector map data including the centerlines of main roads, secondary roads, and branch roads is retrieved. Spatial buffer comparison is performed between the site boundary coordinates and road network segments, with an accessibility search radius set to 100 meters. The accessibility direction relationships of roads adjacent to the boundary coordinates are identified, and the perpendicular distance from the entrance / exit node to the nearest road segment is calculated. If the distance is within 100 meters, a virtual connection is established, and the road's accessibility level is recorded. By summarizing the road network interface characteristics of each site, the sequence of road accessibility directions for each site is obtained.

[0034] S502: Based on the site road access direction sequence, detect the road extension path corresponding to the site number, call the spatial orientation of road network line segments to identify the road extension direction, divide the site number along the road extension direction and associate the site number order to obtain the site road access sequence. First, based on the road accessibility sequence of each site, the extension paths of the roads corresponding to the site numbers in the overall transportation network are detected, and the topological connectivity depth and traffic redundancy of the roads are analyzed. The road network topology map is used to identify the extension trends of the roads, and the shortest path algorithm is used to calculate the path time from the refuge site to the high-density community. The order of site numbers along the road extension direction is divided and associated with the site number priority order, and efficiency is classified according to the effective width of the road, the number of lanes, and the population size covered. For example, sites connecting to main roads and whose extension paths cover large communities are set as high priority. By dynamically ranking the traffic evacuation potential of sites across the entire region, the road accessibility sequence of the sites is obtained.

[0035] S503: Based on the sequence of accessibility of site roads, retrieve the boundary coordinates and spatial orientation information corresponding to the site number, uniformly arrange the site numbers according to the road extension direction, associate the spatial position relationship of the site numbers in the direction, and obtain the overall layout plan of emergency shelters. First, based on the sequence of road accessibility to the site, the boundary coordinates and spatial orientation information corresponding to the site numbers are retrieved to perform logical integration and layout arrangement of the entire area's evacuation system. Site numbers are spatially uniformly coded according to road extension directions. The spatial positional relationship of site numbers in related directions is used to generate the final layout scheme of evacuation sites on a digital urban disaster prevention base map. This process integrates the logic of terrain blocking physical paths of disasters with the accessibility logic of the road network, marking candidate evacuation points protected by terrain and their corresponding evacuation routes, completing the spatial positioning and sequential division of disaster prevention and evacuation spaces across the entire area, and obtaining a comprehensive layout scheme for emergency evacuation sites.

[0036] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for comprehensive planning of emergency shelters based on multi-hazard risk coupling, characterized in that, Includes the following steps: S1: Obtain the location of the earthquake epicenter, flood overflow point and landslide source, read the city DEM grid coordinates, calculate the distance between the disaster source and the grid center, select the grid area according to the disaster type's influence radius, and obtain the set of multi-hazard influence coverage areas; S2: Based on the set of multi-hazard impact coverage areas, read grid elevation data, compare the elevation values ​​of adjacent grids, identify elevation peaks and connect them along the spatial adjacency direction, divide the terrain boundary structure, and obtain the spatial node sequence of the surface watershed. S3: Based on the spatial node sequence of the surface watershed, read the coordinates of the disaster source and the center of the grid, and compare the cross relationship with the spatial node sequence of the surface watershed to obtain the set of disaster propagation restriction areas; S4: Based on the set of disaster propagation restriction areas, obtain the boundary locations of emergency shelter squares and community shelter parks, read the spatial comparison between the center coordinates of the site and the propagation restriction areas, and obtain the set of shelter locations; S5: Based on the set of locations of the emergency shelters, read the site boundary coordinates and perform spatial matching with the urban road network, sort the site locations along the road access directions, arrange the spatial distribution relationship, and obtain the overall deployment plan of emergency shelters.

2. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The set of multi-hazard impact coverage areas includes earthquake impact coverage areas, flood impact coverage areas, landslide impact coverage areas, and disaster superposition impact areas. The spatial node sequence of the surface watershed includes watershed node coordinates, topographic boundary line nodes, slope aspect separation nodes, and peak-ridge connection nodes. The set of disaster propagation restriction areas includes watershed barrier areas, topographic shielding areas, propagation interception areas, and risk isolation areas. The set of refuge site locations includes square refuge sites, park refuge sites, community emergency site locations, and centralized refuge node locations. The overall deployment plan for emergency refuge sites includes the spatial layout structure of refuge sites, road access and connection structure, site service coverage structure, and urban refuge network structure.

3. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The landslide source location refers to the initial location where the landslide disaster first occurred, that is, the spatial coordinates of the source point where the landslide body begins to form and spread outward; The terrain boundary structure refers to the terrain boundary line and watershed structure identified and connected based on DEM elevation data, which is used to divide the spatial boundaries of differentiated terrain units and disaster propagation directions.

4. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The intersection relationship refers to the spatial intersection or crossing relationship between the disaster source location and the sequence of surface watershed nodes, which determines the limitation of the terrain on the spread of the disaster; The spatial distribution relationship refers to the overall distribution structure formed by spatially sorting and arranging multiple refuge sites according to the road access direction and site location.

5. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain the location of the city's earthquake epicenter, river flood overflow location, and landslide source location; collect the grid coordinates of the city's digital elevation model; extract the spatial coordinates of the center point of each grid; perform coordinate difference calculations by calling the coordinates of the epicenter, overflow, and landslide source locations with the coordinates of the grid center point; calculate the point-to-point spatial distance based on the plane coordinate difference values; measure the distance between the disaster source and the grid center point; and obtain the disaster source grid spatial distance table. S102: Based on the disaster source grid spatial distance table, obtain the preset earthquake influence radius, flood inundation radius, and landslide influence radius, call the distance value and the corresponding disaster source radius comparison value, select the grid number within the radius range and associate it with the disaster source type to obtain the disaster effect grid set; S103: Based on the disaster impact grid set, read the spatial adjacency relationship of the grid numbers, perform up, down, left and right adjacency determination according to the row and column index of the grid numbers, perform connectivity identification and range merging on continuous adjacent grid numbers, associate the grid numbers of the same connected region, and obtain the set of multi-hazard impact coverage areas.

6. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The specific steps of S2 are as follows: S201: Based on the set of multi-hazard impact coverage areas, collect elevation data of the corresponding grid area, extract the elevation value of the center point of each grid, call the center point elevation value and compare the spatial values ​​with the center point elevation values ​​of the four neighboring grids, identify the coordinates of the grid center point where the adjacent directions are all lower than the center point elevation value, extract the coordinates of the corresponding grid center point and associate them with the grid number to obtain the set of elevation peak point coordinates. S202: Based on the set of elevation peak coordinates, detect the spatial adjacency relationship of elevation peak coordinates, call the grid row and column index to identify the position direction of adjacent peaks, connect the consecutive peak coordinates in adjacent directions and associate the direction sequence to obtain the elevation peak connection sequence. S203: Based on the elevation peak connection sequence, monitor the spatial distribution direction of the connection segment, identify the segment partition according to the change in the connection segment direction, extract the node sequence of the continuous direction consistent line segment and associate it with the spatial coordinate sequence to obtain the spatial node sequence of the surface watershed.

7. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The specific steps for S3 are as follows: S301: Based on the spatial node sequence of the surface watershed, obtain the location coordinates of the disaster source, collect the center coordinates of the grid area, connect the location coordinates of the disaster source with the center coordinates of the grid area with a straight line, and determine the direction and spatial position of the connecting line according to the starting coordinates and the ending coordinates to obtain the disaster source grid connection sequence. S302: Based on the disaster source grid connection sequence, compare the coordinate trajectory of each connection with the spatial position of the adjacent node line segment of the node sequence, detect the intersection position of the connection trajectory and the node line segment, associate the connection number of the intersection position with the corresponding node line segment number, and obtain the connection intersection relationship sequence. S303: Based on the connection and intersection sequence, retrieve the center coordinates of the corresponding grid area and the location coordinates of the disaster source, retrieve the corresponding grid number according to the connection number of the intersection position, divide the area according to the spatial distribution range of the intersection position, and aggregate and associate the grid numbers of the same distribution range to obtain the set of disaster propagation restriction areas.

8. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 7, characterized in that: In the process of connecting the disaster source location coordinates with the grid area center coordinates by a straight line: points are continuously taken along the line connecting the disaster source location coordinates with the grid area center coordinates at a fixed interval to obtain a sequence of line sampling point coordinates distributed along the line direction; In the process of comparing the coordinate trajectory of each connecting line with the spatial position of the adjacent node line segment of the node sequence: the coordinate sequence of the connecting line sampling points is matched point by point with the spatial position of the adjacent node line segment of the node sequence, and the spatial position status of the connecting line sampling point coordinates on both sides of the adjacent node line segment of the node sequence is identified, so as to locate the intersection position between the connecting line trajectory and the node line segment by the connecting line sampling point coordinates that have changed position.

9. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The specific steps of S4 are as follows: S401: Based on the set of disaster propagation restriction areas, obtain the boundary locations of the emergency shelter square and the community emergency shelter park, collect the center coordinates of the site, call the site center coordinates and compare the spatial location with the center coordinates of the grid of the disaster propagation restriction area set, identify the site number where the center coordinates are located within the area and associate the site type information to obtain a set of candidate coordinates for shelter sites. S402: Based on the candidate coordinate set of the refuge sites, detect the spatial orientation distribution of the candidate coordinates, call the row and column index of the city grid to identify the spatial direction sequence of the candidate coordinates, associate the coordinate orientations with the same direction sequence and aggregate the coordinate numbers to obtain the direction distribution sequence of the refuge sites. S403: Based on the distribution sequence of the refuge sites, retrieve the spatial relationship between the site boundary position and the center coordinates corresponding to the coordinate number, classify the positions according to the spatial distribution direction of the city, associate the site numbers in the same spatial direction, and obtain the set of refuge site locations.

10. The method for comprehensive planning of emergency shelters based on multi-hazard risk coupling according to claim 1, characterized in that, The specific steps of S5 are as follows: S501: Based on the set of locations of the refuge sites, obtain the boundary coordinates of the refuge sites, collect the spatial distribution coordinates of the urban road network, compare the spatial location of the site boundary coordinates with the coordinates of the road network line segments, identify the relationship between the access directions of the adjacent roads of the boundary coordinates, associate the road direction information corresponding to the site number, and obtain the sequence of the access directions of the site roads. S502: Based on the site road access direction sequence, detect the road direction extension path corresponding to the site number, call the spatial orientation of road network line segments to identify the road extension direction, divide the site number along the road extension direction and associate the site number order to obtain the site road access sequence sequence. S503: Based on the road access sequence of the site, retrieve the boundary coordinates and spatial orientation information corresponding to the site number, uniformly arrange the site numbers according to the road extension direction, associate the spatial position relationship of the site numbers in the direction, and obtain the overall layout plan of emergency shelters.

Images