A system for evaluating the function loss of urban refuge places under strong wind and waterlogging disasters

Abstract

The present application relates to a kind of strong wind-flood multi-disaster under urban refuge place function loss evaluation system, belong to urban resilience and disaster prevention and mitigation technical field, wherein basic data processing module includes network open source data, topology and data processing system, for building city road network-shelter function network topology structure model and the basic data for disaster physical loss analysis;Monitoring module includes meteorological observation data, for obtaining real-time disaster intensity parameter, such as wind speed, wind direction and rain intensity parameter etc.;Calculation module includes the disaster damage analysis system for calculating the physical damage of city road network, building group and shelter component caused by strong wind and flood disaster and the function loss analysis system for calculating the function loss of city shelter caused by corresponding physical damage, the system established more accurately quantifies the function loss of city shelter under the joint action of strong wind-flood multi-disaster, considering the influence of traffic network.

Description

Technical Field

[0001] This invention belongs to the field of urban resilience and disaster prevention and mitigation technology, and relates to a system for assessing the functional loss of urban refuge sites under multiple disasters such as strong winds and urban flooding. In particular, it relates to a system for assessing the functional loss of urban refuge sites under the combined effects of strong winds and urban flooding, taking into account the impact of transportation networks. Background Technology

[0002] Typhoons and severe convective weather often bring strong winds and heavy rainfall. Strong winds can cause serious damage to building envelope systems and large-scale uprooting of roadside trees, leading to traffic disruptions or interruptions. Heavy rainfall can easily induce urban flooding, causing low-lying communities to be submerged and road networks to be paralyzed due to water accumulation. The impacts of both strong winds and flooding are important and need to be considered simultaneously.

[0003] Some communities have become uninhabitable due to severe wind damage to their protective structures or flooding, resulting in a large number of people needing to be relocated. Meanwhile, the city's road network has been disrupted by fallen trees or deep water, causing a sharp drop in road network efficiency and severely impacting the evacuation of refugees and residents' daily travel. There is a coupling effect between the transportation system and the evacuation efforts.

[0004] Regarding natural disasters, the following loss assessment methods have been studied:

[0005] (1) Methods for evaluating the function of urban medical systems after earthquakes

[0006] The main process is as follows: a. Establish finite element models of typical hospital buildings and typical residential buildings, and conduct dynamic elastoplastic analysis of seismic loads; b. Based on the finite element analysis response results, determine the damage level of hospital buildings and community buildings, and determine the post-earthquake remaining functional level of each floor of the hospital; c. Determine the number of injured people in different communities based on empirical methods, and analyze the road network congestion status based on the building damage level and the post-earthquake building debris model; d. Analyze the hospital accessibility level and hospital waiting time for injured people, and compare them with the pre-disaster functions to assess the functional loss of the medical system after the earthquake.

[0007] (2) Methods for assessing the functional loss of urban road network under strong winds or waterlogging

[0008] The main process is as follows: a. Based on meteorological observations of wind speed or rainfall intensity data, conduct physical damage analysis of roadside trees in the urban road network or carry out urban flooding simulation; b. Analyze the physical damage status of roadside trees in the urban road network or the spatial distribution of urban flooding to determine road interruptions caused by fallen roadside trees or water accumulation; c. Analyze the connectivity between nodes in the road network to assess the functional loss of the urban road network after strong winds or flooding.

[0009] (3) Method for assessing physical losses of low-rise buildings (groups) under strong winds and waterlogging

[0010] The main process is as follows: a. Obtain the wind load coefficient and wind-driven rain intensity coefficient of the surface of low-rise buildings (groups) based on wind tunnel tests or numerical simulations; b. Combine measured wind speed and rainfall intensity data to calculate the magnitude of the wind load on the surface of low-rise buildings (groups) and determine whether the surface enclosure system has suffered wind-induced damage; c. If wind-induced damage occurs, further calculate the amount of wind-driven rain intrusion into the interior; d. Calculate the indoor and outdoor economic losses caused by wind-induced damage and rainwater intrusion to assess the level of physical damage to low-rise buildings (groups) under strong winds or heavy rain.

[0011] Unlike the safety assessment of individual engineering structures, the function of urban refuge sites is not only related to the safety of their own structures and enclosure systems, but also affected by the traffic efficiency and capacity of the road network. However, existing technologies mainly focus on the assessment of physical damage to road network components and road network function under single disasters such as strong winds or urban flooding. Some technologies only analyze the transfer process of evacuees within the road network after a disaster. There is a lack of methods to consider the impact of physical damage to community building complexes, road network components, and refuge sites on the function of urban refuge sites under multiple disasters such as strong winds and urban flooding, and there is no quantitative method for assessing the functional loss of refuge sites under the combined effects of multiple disasters such as strong winds and urban flooding, taking into account the impact of the traffic network.

[0012] Currently, emergency management departments primarily formulate evacuation strategies based on disaster warning levels when facing multiple disasters such as strong winds and urban flooding. However, due to the lack of quantitative data on the functional loss of evacuation sites under such conditions, existing decision-making methods are inefficient and inaccurate. To ensure the safety of evacuees, emergency management departments need to constantly monitor whether urban evacuation sites are safe, accessible, and capable of accommodating evacuees in order to formulate reasonable evacuation plans. Therefore, it is necessary to assess the functional loss of urban evacuation sites under multiple disasters such as strong winds and urban flooding. The assessment process must consider the combined effects of both strong winds and urban flooding, as well as the functional coupling effect between the transportation system and evacuation sites.

[0013] Therefore, there is an urgent need to establish a system for assessing the functional loss of urban shelters under the combined effects of strong winds and urban flooding, taking into account the impact of transportation networks. This system can provide decision-making support for urban emergency management departments and is of great significance for reducing the functional loss of urban shelters caused by strong winds and urban flooding, and improving urban disaster resilience. Summary of the Invention

[0014] In view of this, in order to address the problems that existing technologies generally only address single disasters such as strong winds or urban flooding, and lack consideration of the impact of multiple disasters such as strong winds and urban flooding on the physical damage to community building complexes, road network components, and refuge sites on the functional loss of urban refuge sites, and lack a refuge site functional loss assessment system that considers the impact of traffic road networks under the combined effects of multiple disasters such as strong winds and urban flooding, this invention provides a functional loss assessment system for urban refuge sites under multiple disasters such as strong winds and urban flooding, which can analyze the level of functional loss of urban refuge sites under different combinations of disaster parameters in real time based on meteorological observation data.

[0015] To achieve the above objectives, the present invention provides the following technical solution:

[0016] A system for assessing the functional loss of urban refuge sites under multiple disasters such as strong winds and urban flooding includes a basic data processing module, a monitoring module, and a calculation module;

[0017] The basic data processing module includes open-source network data, topology and data processing system, used to construct the urban road network-refuge functional network topology model and basic data for disaster physical loss analysis; the monitoring module includes meteorological observation data, used to obtain real-time disaster intensity parameters, such as wind speed, wind direction and rainfall intensity parameters; the calculation module includes a disaster damage analysis system for calculating physical damage to urban road networks, building complexes and refuge components caused by strong winds and urban flooding disasters, and a function loss analysis system for calculating the functional loss of urban refuges caused by the corresponding physical damage.

[0018] Furthermore, the specific process of this loss assessment system is as follows:

[0019] S1. The open-source network data obtained in the basic data processing module mainly includes map data and functional data. The map data and functional data of the study area are input into the topology and data processing system, and the topology structure model of the urban road network-refuge functional network and the basic data of vulnerable components are output.

[0020] S2. The disaster intensity parameters in the monitoring module, namely the strong wind-waterlogging disaster parameters, mainly include wind speed, wind direction and rainfall intensity data, which can be obtained from the meteorological observation station in the study area.

[0021] S3. Input the strong wind-waterlogging disaster parameters provided by the monitoring module and the basic data of vulnerable components output by the basic data processing module into the disaster damage analysis system in the calculation module. This can analyze the physical damage data of urban components under the current strong wind and waterlogging disasters. Then, input the component physical damage data and the urban road network-refuge functional network output by the basic data processing module into the functional loss analysis system. This can analyze the impact of component physical damage on the loss of urban refuge functions and finally output the refuge function loss value considering the impact of the traffic road network.

[0022] Furthermore, the map data in step S1 includes open-source road network data, satellite map photos, geographic elevation data, and building geometric outline information, which are obtained using the following methods:

[0023] S11. Download urban road network data (including road network coordinates, lane levels, etc.) through the open-source map OpenStreetMap to establish the road network geometric topology;

[0024] S12. Download satellite map photos, geographic elevation information and building outline information through Tianditu to identify the location and geometric parameters of vulnerable components.

[0025] Furthermore, the functional data in step S1 includes real-time road network situation data, names of refuge sites, coordinates, and designed capacity, etc.; the acquisition method is as follows:

[0026] S13. Obtain traffic status data of Gaode Map road network (including road segment name, coordinates, vehicle speed, etc.) through crawler code, and use it to calculate road network topology function parameters;

[0027] S14. Obtain data on refuge sites (site name, coordinates, designed capacity) from government management departments to establish the geometric topology and functional parameters of refuge sites.

[0028] Furthermore, after obtaining the aforementioned open-source network data, it is parsed and processed in the topology and data processing system, specifically as follows:

[0029] S15. Satellite map image analysis and processing:

[0030] Image recognition algorithms were used to determine the roof type and coordinates of low-rise buildings susceptible to wind loads, as well as the geometric dimensions and coordinates of street tree crowns. The roof type was classified into tiled roofs and metal roofs. After obtaining the geometric dimensions of the street tree crowns, the height information of the street trees was further calculated based on the statistical function of the relationship between tree height and crown width.

[0031] S16. Analysis and processing of coordinate data for urban road network and refuge sites:

[0032] S161. Simplify the downloaded urban road network data, filter out urban arterial roads, primary and secondary roads, simplify road network intersections to nodes, and road segments to lines, and construct the geometric topology of the urban road network.

[0033] S162. Simplify the refuge sites into nodes, and further spatially overlay them with the geometric topology of the urban road network based on the coordinates of the refuge sites.

[0034] S163. Construct a geometric topology network of urban road network and refuge sites;

[0035] S17. Data Analysis and Processing of Traffic Situation and Shelter Functions:

[0036] S171. Based on the speed-flow relationship, the average speed of some road sections monitored by traffic situation is converted into traffic flow. The traffic flow back-calculation algorithm is used to obtain the traffic demand between each node of the normally operating road network and the initial road network flow distribution.

[0037] S172. Assign the number of people accommodated in the refuge area to the refuge area node in the geometric topology network, assign the initial road network traffic distribution to the road network edge in the geometric topology network, and assign the traffic demand to the road network node in the geometric topology network.

[0038] S173. Output a functional network topology model of urban road network-refuge area with functional parameters.

[0039] Furthermore, in step S2, wind speed, wind direction, and rainfall intensity data of the study area are obtained through the wind speed and direction observation instrument and the rainfall intensity meter in the meteorological observation station. The wind speed and direction observation instrument can observe wind speed data in the range of 0-70 m / s and wind direction data in the range of 0-360°. The rainfall intensity meter adopts a tipping bucket rain gauge, which can record rainfall intensity of 0-100 mm / day with a resolution of 0.1-0.5 mm. The recorded wind speed, wind direction, and rainfall intensity data will be input into the calculation module to carry out disaster loss analysis.

[0040] Furthermore, the disaster damage analysis system is divided into two parts, one for strong winds and the other for urban flooding.

[0041] Furthermore, the specific damage analysis system for strong winds within the disaster damage analysis system is as follows:

[0042] S311. Input the wind speed and direction data recorded by the monitoring module, combine it with the wind load model of typical roof enclosure structure and roadside tree obtained based on wind tunnel test, and calculate the surface wind load values ​​of roof and roadside tree at different locations using the roof type / coordinate and roadside tree data output by the basic data processing module.

[0043] S312. Based on the established wind-induced damage resistance model of the roof enclosure structure and street trees, and combined with the roof type / coordinates and street tree data output by the basic data processing module, calculate the resistance values ​​of the roof and street trees at different locations.

[0044] S313. Compare the relationship between resistance and wind load. When the resistance is less than the wind load, it is considered that the roof / street tree has been damaged.

[0045] S314. When the roof enclosure structure is damaged, combine the building roof type / coordinates output by the basic data processing module with the geographic elevation information and building outline coordinate information obtained in the basic data processing module to carry out wind-induced flying object damage analysis and determine the damage data of building groups and refuge places that are further impacted by wind-induced flying objects.

[0046] S315. When roadside trees are damaged, combine the basic data of roadside trees output by the basic data processing module to calculate the spatial relationship between the fallen roadside trees and the road, determine whether the roadside trees will cause road blockage, and calculate the width of the blocked road.

[0047] S316 Outputs data on wind-induced damage to the roof and enclosure structures of building complexes, data on wind-induced damage from flying objects to building complexes, and the width of road network blockages caused by fallen trees.

[0048] Furthermore, the specific damage analysis system for urban flooding is as follows:

[0049] S317. The rainfall intensity data recorded by the input monitoring module and the geographic elevation information obtained by the basic data processing module are combined with the drainage capacity designed for the study area. The surface runoff analysis model is used to carry out urban waterlogging simulation and output the spatiotemporal distribution results of urban waterlogging.

[0050] S318. Combining the road network coordinate information and building outline coordinate information output by the basic data processing module, identify communities and road networks where the water depth exceeds the threshold.

[0051] S319 outputs results such as the number of communities unsuitable for habitation due to excessive water accumulation, and the water depth of various road sections in the road network.

[0052] Furthermore, the functional loss analysis system specifically includes:

[0053] S321. Input the severely wind-damaged buildings and communities with excessive water accumulation output by the disaster damage analysis system, combine the building outline coordinate information provided by the basic data processing module to estimate the number of households in each building, estimate the number of people / coordinates required for post-disaster evacuation caused by unsuitable residential buildings, identify potentially damaged evacuation sites, and update the evacuation site capacity.

[0054] S322. Input the road blockage width, interrupted road sections, and road water depth output by the disaster damage analysis system. Combine the urban road network-refuge functional topology network model provided by the basic data processing module to further update the remaining passable width of road sections in the topology network, remove interrupted road sections, and consider the attenuation of the water accumulation effect on the passing speed after removing the interrupted road sections.

[0055] S323. Based on this updated road network-evacuation network, and taking into account both the increased evacuation demand and the traffic demand of the road network in its normal pre-disaster operation state, conduct traffic flow distribution simulation.

[0056] S324. Calculate the post-disaster shelter function index Q1 based on the simulation results. This index comprehensively considers the safety, accessibility, and capacity of the shelter. The ratio of Q1 to the pre-disaster shelter function index Q0 is taken as the final shelter function loss index R. R = 1 indicates that the shelter function has not suffered any loss, R > 1 indicates that the shelter function has suffered a loss, and the larger the value, the greater the loss.

[0057] The beneficial effects of this invention are as follows:

[0058] 1. The present invention discloses a system for assessing the functional loss of urban shelters under multiple disasters of strong winds and urban flooding. The system fully considers the impact of physical damage to urban road networks and building complexes on urban shelter functions under multiple disasters of strong winds and urban flooding. It more accurately quantifies the functional loss of urban shelters under the combined effects of strong winds and urban flooding, taking into account the impact of transportation networks. It can solve the problem of inefficient and inaccurate emergency evacuation decisions caused by the lack of quantitative values ​​for the functional loss of urban shelters affected by transportation networks under the combined effects of strong winds and urban flooding.

[0059] 2. The present invention discloses a functional loss assessment system for urban refuge sites under multiple disasters of strong winds and waterlogging. It establishes a functional network topology model of urban road network-refuge sites based on open-source network data, performs physical damage analysis of urban road network and building complex under strong winds and waterlogging disasters based on monitored wind speed, wind direction and rainfall intensity data, and calculates the functional loss value of urban refuge sites under multiple disasters of strong winds and waterlogging through the functional loss analysis system.

[0060] 3. The functional loss assessment system for urban refuge sites under multiple disasters of strong winds and urban flooding disclosed in this invention can provide decision-making technical support for urban emergency management departments and is of great significance for reducing the loss of urban refuge functions caused by multiple disasters of strong winds and urban flooding and improving urban disaster resilience.

[0061] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0062] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0063] Figure 1 This is a structural block diagram of a system for assessing the functional loss of urban refuge sites under multiple disasters such as strong winds and urban flooding, according to the present invention.

[0064] Figure 2 This is a flowchart of the basic data processing module in a system for assessing the functional loss of urban refuge sites under multiple disasters such as strong winds and urban flooding, according to the present invention.

[0065] Figure 3 This is a structural block diagram of the monitoring module in a system for assessing the functional loss of urban refuge sites under multiple disasters such as strong winds and urban flooding, according to the present invention.

[0066] Figure 4This is a flowchart of the calculation module in an urban refuge area functional loss assessment system under multiple disasters such as strong winds and flooding, according to the present invention. Detailed Implementation

[0067] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0068] like Figure 1 The system shown is a functional loss assessment system for urban refuge sites under multiple disasters such as strong winds and waterlogging, including a basic data processing module (module 1), a monitoring module (module 2), and a calculation module (module 3).

[0069] S1, the basic data processing module includes open-source network data, a topology and data processing system. It inputs the study area map data and functional data into the topology and data processing system, and outputs a functional network topology model of the urban road network-refuge area and basic data on vulnerable components. This is used to construct the functional network topology model of the urban road network-refuge area and as fundamental data for disaster physical loss analysis; the specific process is detailed below. Figure 2 As shown. Open-source network data mainly includes map data and functional data. Map data includes open-source road network data, satellite imagery, geographic elevation data, and building geometric outline information, etc., and is acquired using the following methods:

[0070] S11. Download urban road network data (including road network coordinates, lane levels, etc.) through the open-source map OpenStreetMap to establish the road network geometric topology;

[0071] S12. Download satellite map photos, geographic elevation information and building outline information through Tianditu to identify the location and geometric parameters of vulnerable components.

[0072] Functional data includes real-time road network status data, names, coordinates, and designed capacity of evacuation sites; the acquisition method is as follows:

[0073] S13. Obtain traffic status data of Gaode Map road network (including road segment name, coordinates, vehicle speed, etc.) through crawler code, and use it to calculate road network topology function parameters;

[0074] S14. Obtain data on refuge sites (site name, coordinates, designed capacity) from government management departments to establish the geometric topology and functional parameters of refuge sites.

[0075] After obtaining the aforementioned open-source network data, it is parsed and processed in the topology and data processing system, specifically as follows:

[0076] S15, Satellite map photos:

[0077] Image recognition algorithms were used to determine the roof type and coordinates of low-rise buildings susceptible to wind loads, as well as the geometric dimensions and coordinates of street tree crowns. The roof type was classified into tiled roofs and metal roofs. After obtaining the geometric dimensions of the street tree crowns, the height information of the street trees was further calculated based on the statistical function of the relationship between tree height and crown width.

[0078] S16. Coordinate data of urban road network and refuge sites:

[0079] S161. Simplify the downloaded urban road network data, filter out urban arterial roads, primary and secondary roads, simplify road network intersections to nodes, and road segments to lines, and construct the geometric topology of the urban road network.

[0080] S162. Simplify the refuge sites into nodes, and further spatially overlay them with the geometric topology of the urban road network based on the coordinates of the refuge sites.

[0081] S163. Construct a geometric topology network of urban road network and refuge sites;

[0082] S17. Traffic situation and refuge area function data:

[0083] S171. Based on the speed-flow relationship, the average speed of some road sections monitored by traffic situation is converted into traffic flow. The traffic flow back-calculation algorithm is used to obtain the traffic demand between each node of the normally operating road network and the initial road network flow distribution.

[0084] S172. Assign the number of people accommodated in the refuge area to the refuge area node in the geometric topology network, assign the initial road network traffic distribution to the road network edge in the geometric topology network, and assign the traffic demand to the road network node in the geometric topology network.

[0085] S173. Output a functional network topology model of urban road network-refuge area with functional parameters.

[0086] S2, such as Figure 3The monitoring module shown includes meteorological observation data, which is obtained from meteorological stations in the study area to acquire disaster intensity parameters, such as wind speed, wind direction, and rainfall intensity. Disaster intensity parameters, namely strong wind-waterlogging disaster parameters, mainly include wind speed, wind direction, and rainfall intensity data, which can be obtained from meteorological stations in the study area. Wind speed, wind direction, and rainfall intensity data for the study area are acquired using anemometers and rain gauges at the meteorological stations. The anemometers can observe wind speeds from 0-70 m / s and wind directions from 0-360°, while the rain gauges, specifically tipping bucket rain gauges, can record rainfall intensity from 0-100 mm / day with a resolution of 0.1-0.5 mm. The recorded wind speed, wind direction, and rainfall intensity data are then input into the calculation module for disaster loss analysis.

[0087] S3. Input the strong wind-flood disaster parameters provided by the monitoring module and the basic data of vulnerable components output by the basic data processing module into the disaster damage analysis system in the calculation module. This can analyze the physical damage data of urban components under the current strong wind and flood disasters. Then, input the component physical damage data and the urban road network-refugee site functional network output by the basic data processing module into the function loss analysis system. This can analyze the impact of component physical damage on the loss of urban refuge functions, and finally output the refuge site function loss value considering the impact of the traffic road network. The calculation module includes a disaster damage analysis system for calculating the physical damage to urban road networks, building complexes and refuge site components caused by strong wind and flood disasters, and a function loss analysis system for calculating the functional loss of urban refuge sites caused by the corresponding physical damage. The specific process is as follows: Figure 4 As shown.

[0088] S31 The disaster damage analysis system is divided into two parts, targeting strong winds and urban flooding disasters respectively.

[0089] The damage analysis system specifically for strong winds includes:

[0090] S311. Input the wind speed and direction data recorded by the monitoring module, combine it with the wind load model of typical roof enclosure structure and roadside tree obtained based on wind tunnel test, and calculate the surface wind load values ​​of roof and roadside tree at different locations using the roof type / coordinate and roadside tree data output by the basic data processing module.

[0091] S312. Based on the established wind-induced damage resistance model of the roof enclosure structure and street trees, and combined with the roof type / coordinates and street tree data output by the basic data processing module, calculate the resistance values ​​of the roof and street trees at different locations.

[0092] S313. Compare the relationship between resistance and wind load. When the resistance is less than the wind load, it is considered that the roof / street tree has been damaged.

[0093] S314. When the roof enclosure structure is damaged, combine the building roof type / coordinates output by the basic data processing module with the geographic elevation information and building outline coordinate information obtained in the basic data processing module to carry out wind-induced flying object damage analysis and determine the damage data of building groups and refuge places that are further impacted by wind-induced flying objects.

[0094] S315. When roadside trees are damaged, combine the basic data of roadside trees output by the basic data processing module to calculate the spatial relationship between the fallen roadside trees and the road, determine whether the roadside trees will cause road blockage, and calculate the width of the blocked road.

[0095] S316 Outputs data on wind-induced damage to the roof and enclosure structures of building complexes, data on wind-induced damage from flying objects to building complexes, and the width of road network blockages caused by fallen trees.

[0096] The damage analysis system for urban flooding is as follows:

[0097] S317. The rainfall intensity data recorded by the input monitoring module and the geographic elevation information obtained by the basic data processing module are combined with the drainage capacity designed for the study area. The surface runoff analysis model is used to carry out urban waterlogging simulation and output the spatiotemporal distribution results of urban waterlogging.

[0098] S318. Combining the road network coordinate information and building outline coordinate information output by the basic data processing module, identify communities and road networks where the water depth exceeds the threshold.

[0099] S319 outputs results such as the number of communities unsuitable for habitation due to excessive water accumulation, and the water depth of various road sections in the road network.

[0100] S32, The functional loss analysis system is specifically as follows:

[0101] S321. Input the severely wind-damaged buildings and communities with excessive water accumulation output by the disaster damage analysis system, combine the building outline coordinate information provided by the basic data processing module to estimate the number of households in each building, estimate the number of people / coordinates required for post-disaster evacuation caused by unsuitable residential buildings, identify potentially damaged evacuation sites, and update the evacuation site capacity.

[0102] S322. Input the road blockage width, interrupted road sections, and road water depth output by the disaster damage analysis system. Combine the urban road network-refuge functional topology network model provided by the basic data processing module to further update the remaining passable width of road sections in the topology network, remove interrupted road sections, and consider the attenuation of the water accumulation effect on the passing speed after removing the interrupted road sections.

[0103] S323. Based on this updated road network-evacuation network, and taking into account both the increased evacuation demand and the traffic demand of the road network in its normal pre-disaster operation state, conduct traffic flow distribution simulation.

[0104] S324. Calculate the post-disaster shelter function index Q1 based on the simulation results. This index comprehensively considers the safety, accessibility, and capacity of the shelter. The ratio of Q1 to the pre-disaster shelter function index Q0 is taken as the final shelter function loss index R. R = 1 indicates that the shelter function has not suffered any loss, R > 1 indicates that the shelter function has suffered a loss, and the larger the value, the greater the loss.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A system for evaluating the functional loss of urban refuge places under strong wind-flood multi-disasters, characterized in that, It includes a basic data processing module, a monitoring module, and a computing module; The basic data processing module includes open-source network data, topology and data processing system, used to construct the urban road network-refuge functional network topology model and basic data for disaster physical loss analysis; the monitoring module includes meteorological observation data, used to obtain real-time disaster intensity parameters; the calculation module includes a disaster damage analysis system for calculating physical damage to urban road networks, building complexes and refuge components caused by strong winds and urban flooding, and a function loss analysis system for calculating the functional loss of urban refuges caused by the corresponding physical damage. The disaster damage analysis system specifically targets damage analysis caused by strong winds. S311. Input the wind speed and direction data recorded by the monitoring module, combine it with the wind load model of typical roof enclosure structure and roadside tree obtained based on wind tunnel test, and calculate the surface wind load values ​​of roof and roadside tree at different locations using the roof type / coordinate and roadside tree data output by the basic data processing module. S312. Based on the established wind-induced damage resistance model of the roof enclosure structure and street trees, and combined with the roof type / coordinates and street tree data output by the basic data processing module, calculate the resistance values ​​of the roof and street trees at different locations. S313. Compare the relationship between resistance and wind load. When the resistance is less than the wind load, it is considered that the roof / street tree has been damaged. S314. When the roof enclosure structure is damaged, combine the building roof type / coordinates output by the basic data processing module with the geographic elevation information and building outline coordinate information obtained in the basic data processing module to carry out wind-induced flying object damage analysis and determine the damage data of building groups and refuge places that are further impacted by wind-induced flying objects. S315. When roadside trees are damaged, combine the basic data of roadside trees output by the basic data processing module to calculate the spatial relationship between the fallen roadside trees and the road, determine whether the roadside trees will cause road blockage, and calculate the width of the blocked road. S316, Output data on wind-induced damage to the roof and enclosure structures of the building complex, data on wind-induced damage to the building complex from flying objects, and the width of road network blockage caused by fallen trees. The specific damage analysis system for urban flooding is as follows: S317. The rainfall intensity data recorded by the input monitoring module and the geographic elevation information obtained by the basic data processing module are combined with the drainage capacity designed for the study area. The surface runoff analysis model is used to carry out urban waterlogging simulation and output the spatiotemporal distribution results of urban waterlogging. S318. Combining the road network coordinate information and building outline coordinate information output by the basic data processing module, identify communities and road networks where the water depth exceeds the threshold. S319. Output the results of water depth in communities that are unsuitable for habitation due to excessive water accumulation, as well as the water depth of each road segment in the road network. The functional loss analysis system is as follows: S320. Input the severely wind-damaged buildings and communities with excessive water accumulation output by the disaster damage analysis system, combine the building outline coordinate information provided by the basic data processing module to estimate the number of households in each building, estimate the number of people / coordinates required for post-disaster evacuation caused by unsuitable residential buildings, identify potentially damaged evacuation sites, and update the evacuation site capacity. S321. Input the road blockage width, interrupted road section and road water depth output by the disaster damage analysis system, and combine the urban road network-refuge functional topology network model provided by the basic data processing module to further update the remaining passable width of the road section in the topology network, remove the interrupted road section and consider the attenuation of the water accumulation effect on the passing speed. S322. Based on this updated road network-evacuation network, and taking into account both the increased evacuation demand and the traffic demand of the road network under normal pre-disaster operation, conduct traffic flow distribution simulation. S323. Calculate the post-disaster shelter function index Q1 based on the simulation results. The index comprehensively considers the safety, accessibility and accommodating capacity of the shelter. The ratio of Q1 to the pre-disaster shelter function index Q0 is taken as the final shelter function loss index R. R = 1 indicates that the shelter function has not suffered any loss, R > 1 indicates that the shelter function has suffered a loss, and the larger the value, the greater the loss.

2. The system for functional loss assessment of urban evacuation sites under strong wind-flood multi-disasters according to claim 1, wherein, The specific process of the loss assessment system is as follows: S1. The open-source network data obtained in the basic data processing module includes map data and functional data. The map data and functional data of the study area are input into the topology and data processing system, and the urban road network-refuge functional network topology structure model and basic data of vulnerable components are output. S2. The disaster intensity parameters in the monitoring module, namely the strong wind-waterlogging disaster parameters, include wind speed, wind direction and rainfall intensity data, which are obtained through meteorological observation stations in the study area. S3. Input the strong wind-waterlogging disaster parameters provided by the monitoring module and the basic data of vulnerable components output by the basic data processing module into the disaster damage analysis system in the calculation module to analyze the physical damage data of urban components under the current strong wind and waterlogging disaster; then input the component physical damage data and the urban road network-refuge functional network output by the basic data processing module into the functional loss analysis system to analyze the impact of component physical damage on the loss of urban refuge functions, and finally output the refuge function loss value considering the impact of the traffic road network.

3. The system for functional loss assessment of urban evacuation sites under strong wind-flood multi-disasters according to claim 2, wherein, The map data in step S1 includes open-source road network data, satellite imagery, geographic elevation data, and building geometric outline information, which are acquired using the following methods: S11. Download urban road network data, including road network coordinates and lane levels, from the open-source map OpenStreetMap to establish the road network geometric topology; S12. Download satellite map photos, geographic elevation information and building outline information through Tianditu to identify the location and geometric parameters of vulnerable components.

4. The urban refuge area functional loss assessment system under multiple disasters such as strong winds and urban flooding as described in claim 3, characterized in that, The functional data in step S1 includes real-time road network situation data, names of refuge sites, coordinates, and designed capacity; the data is obtained using the following method: S13. Obtain traffic status data of Gaode Map road network through crawler code, including road segment names, coordinates, and vehicle speeds, to calculate road network topology function parameters. S14. Obtain data on refuge sites, including site name, coordinates, and designed capacity, from government management departments to establish the geometric topology and functional parameters of the refuge sites.

5. The urban refuge area functional loss assessment system under multiple disasters such as strong winds and urban flooding as described in claim 4, characterized in that, After obtaining the open-source network data in step S1, it is parsed and processed in the topology and data processing system, specifically as follows: S15. Satellite map image analysis and processing: Image recognition algorithms were used to determine the roof type and coordinates of low-rise buildings susceptible to wind loads, as well as the geometric dimensions and coordinates of street tree crowns. The roof type was classified into tiled roofs and metal roofs. After obtaining the geometric dimensions of the street tree crowns, the height information of the street trees was further calculated based on the statistical function of the relationship between tree height and crown width. S16. Analysis and processing of coordinate data for urban road network and refuge sites: S161. Simplify the downloaded urban road network data, filter out urban arterial roads, primary and secondary roads, simplify road network intersections to nodes, and road segments to lines, and construct the geometric topology of the urban road network. S162. Simplify the refuge sites into nodes, and further spatially overlay them with the geometric topology of the urban road network based on the coordinates of the refuge sites. S163. Construct a geometric topology network of urban road network and refuge sites; S17. Data Analysis and Processing of Traffic Situation and Shelter Functions: S171. Based on the speed-flow relationship, the average speed of some road sections monitored by traffic situation is converted into traffic flow. The traffic flow back-calculation algorithm is used to obtain the traffic demand between each node of the normally operating road network and the initial road network flow distribution. S172. Assign the number of people accommodated in the refuge area to the refuge area node in the geometric topology network, assign the initial road network traffic distribution to the road network edge in the geometric topology network, and assign the traffic demand to the road network node in the geometric topology network. S173. Output a functional network topology model of urban road network-refuge area with functional parameters.

6. The urban refuge area functional loss assessment system under multiple disasters such as strong winds and urban flooding as described in claim 5, characterized in that, Step S2 involves acquiring wind speed, wind direction, and rainfall intensity data for the study area using an anemometer and a rain gauge at a meteorological observation station. The anemometer can measure wind speeds from 0 to 70 m / s and wind directions from 0 to 360°. The rain gauge is a tipping bucket rain gauge that can record rainfall intensity from 0 to 100 mm / day with a resolution of 0.1 to 0.5 mm. The recorded wind speed, wind direction, and rainfall intensity data will be input into the calculation module to conduct disaster loss analysis.

7. The urban refuge area functional loss assessment system under multiple disasters such as strong winds and urban flooding as described in claim 6, characterized in that, In step S3, the disaster damage analysis system is divided into two parts, targeting strong winds and urban flooding disasters respectively.

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