Emergency shelter site selection method and device based on mountain torrent disasters

Abstract

The invention relates to the technical field of mountain torrent disaster emergency management, in particular to an emergency shelter site selection method and device based on mountain torrent disasters, and the method comprises the steps: collecting the flood element time-space change data of the mountain torrent in a target region along with the time-space evolution process when the mountain torrent breaks out; calculating a casualty rate of transfer of a transfer subject in the target area based on the flood element spatio-temporal change data; and determining a final shelter position of the transfer main body according to the initial shelter position and the casualty rate. Therefore, the problems that in the related technology, only roads existing in a map are considered, and special terrains such as slow hillsides are ignored, so that judgment of the casualty rate is too simple, in addition, a machine learning method is adopted in an emergency shelter site selection method, attributes of shelters are not classified, the method has a black box characteristic, a physical mechanism is lacked, and the emergency shelter site selection efficiency is poor are solved. And a site selection result is not accurate and reliable enough.

Description

Technical Field

[0001] The present application relates to the technical field of emergency management of flash flood disasters, and in particular to a method and device for selecting a site for an emergency shelter based on flash flood disasters. Background Art

[0002] Flash floods are characterized by suddenness, rapidity, steep rise and fall, and a wide range of occurrence, which can easily lead to casualties and damage to infrastructure and the ecological environment. In the face of severe flash flood disasters, scientific disaster prevention and mitigation planning is particularly important, among which the site selection planning of emergency shelters is a key link. Emergency shelters provide refuge services, living supplies and medical assistance to disaster-stricken residents, and play an important role in maintaining social public security. Reasonable emergency shelter site selection is of great significance to reducing losses caused by flash floods.

[0003] In the related technology, disaster data can be collected in real time based on the received signals of the disaster occurrence, and the disaster data can be input into the escape path node evaluation model based on the neural network to obtain the generated path node score value, and then generate several optional paths; various hydrological information can also be monitored in real time, and then remotely controlled and transmitted through the Internet of Things system, and automatic alarm can be issued when the water level or flow is high.

[0004] However, related technologies only consider the roads on the map and ignore special terrain such as gentle slopes, which results in an overly simplistic determination of the casualty rate. In addition, the emergency shelter site selection method uses a machine learning approach and does not classify the attributes of the shelter. It has a black box nature and lacks a physical mechanism, making the site selection results inaccurate and unreliable, which urgently needs to be improved. Summary of the invention

[0005] The present application provides a method and device for selecting an emergency shelter site based on flash flood disasters, in order to solve the problem in the related art that only the roads existing in the map are considered, and special terrains such as gentle slopes are ignored, resulting in an overly simple determination of the casualty rate. In addition, the method for selecting an emergency shelter site adopts a machine learning method, and does not classify the attributes of the shelter. It has a black box characteristic and lacks a physical mechanism, which makes the site selection results inaccurate and unreliable.

[0006] The first aspect of the present application provides an emergency shelter site selection method based on flash flood disasters, which includes the following steps: collecting spatiotemporal variation data of flood elements in a target area during the temporal and spatial evolution of flash floods when flash floods occur; calculating the casualty rate of the transfer subject in the target area based on the spatiotemporal variation data of flood elements; and determining the final shelter location of the transfer subject based on the initial shelter location and the casualty rate.

[0007] Optionally, in one embodiment of the present application, the casualty rate of the transfer subjects in the target area is calculated based on the spatiotemporal change data of the flood elements, including: obtaining the emergency evacuation behavior data of each transfer subject in the target area; based on the emergency evacuation behavior data, obtaining the spatiotemporal position data and energy consumption data of each transfer subject during the transfer process; and calculating the casualty rate based on the spatiotemporal change data of the flood elements, the spatiotemporal position data and the energy consumption data.

[0008] Optionally, in one embodiment of the present application, the collecting of spatiotemporal variation data of flood elements in the target area during the temporal and spatial evolution of flash floods when flash floods occur includes: acquiring the watershed range, meteorological data and terrain data of the target area; calculating the flash flood inundation depth and flow velocity of the target area based on the watershed range, the meteorological data and the terrain data; collecting the rainfall intensity, river interface strength and roughness of the target area; and generating the spatiotemporal variation data of the flood elements according to the flash flood inundation depth, the flow velocity, the rainfall intensity, the river interface strength and the roughness.

[0009] Optionally, in one embodiment of the present application, determining the final shelter position of the transfer entity based on the initial shelter position and the casualty rate includes: generating the initial shelter position of the transfer entity based on an objective function; and screening the initial shelter position by the casualty rate to obtain the final shelter position.

[0010] Optionally, in one embodiment of the present application, the initial shelter positions are screened by the casualty rate to obtain the final shelter position, including: obtaining initial shelter casualty rates corresponding to different initial shelter positions; comparing the initial shelter casualty rates to obtain a final shelter casualty rate that meets a preset casualty rate condition; and generating the final shelter position based on the final shelter casualty rate.

[0011] The second aspect of the present application provides an emergency shelter site selection device based on flash flood disasters, including: a collection module for collecting spatiotemporal variation data of flood elements in a target area during the flash flood's spatial and temporal evolution process; a calculation module for calculating the casualty rate of a transfer subject in the target area based on the spatiotemporal variation data of the flood elements; and a generation module for determining a final shelter location of the transfer subject based on an initial shelter location and the casualty rate.

[0012] Optionally, in one embodiment of the present application, the calculation module includes: a first acquisition unit, used to obtain the emergency evacuation behavior data of each transfer subject in the target area; a second acquisition unit, used to obtain the position spatiotemporal data and energy consumption data of each transfer subject during the transfer process based on the emergency evacuation behavior data; a first calculation unit, used to calculate the casualty rate based on the spatiotemporal change data of the flood elements, the position spatiotemporal data and the energy consumption data.

[0013] Optionally, in one embodiment of the present application, the acquisition module includes: a third acquisition unit, used to acquire the watershed range, meteorological data and terrain data of the target area; a second calculation unit, used to calculate the flash flood inundation depth and flow velocity of the target area based on the watershed range, the meteorological data and the terrain data; a collection unit, used to collect the rainfall intensity, river interface strength and roughness of the target area; a first generation unit, used to generate the spatiotemporal change data of the flood elements according to the flash flood inundation depth, the flow velocity, the rainfall intensity, the river interface strength and the roughness.

[0014] Optionally, in one embodiment of the present application, the generation module includes: a second generation unit, used to generate the initial shelter position of the transfer entity according to the objective function; and a screening unit, used to screen the initial shelter position by the casualty rate to obtain the final shelter position.

[0015] Optionally, in one embodiment of the present application, the screening unit includes: an acquisition subunit, used to acquire initial shelter casualty rates corresponding to different initial shelter locations; a comparison subunit, used to compare the initial shelter casualty rates to obtain a final shelter casualty rate that meets a preset casualty rate condition; and a generation subunit, used to generate the final shelter location based on the final shelter casualty rate.

[0016] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for selecting an emergency shelter site based on flash flood disasters as described in the above embodiment.

[0017] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned method for emergency shelter site selection based on flash flood disasters.

[0018] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, implements the above-mentioned method for emergency shelter site selection based on flash flood disasters.

[0019] The embodiment of the present application can collect the spatiotemporal variation data of flood elements in the target area during the flash flood outbreak with the temporal and spatial evolution process in real time, can quickly understand the evolution trend of the flash flood and the potential impact area, improve the efficiency of emergency response, calculate the casualty rate of the transfer subject in the target area, can quickly evaluate the risk level of the transfer subject, improve the pertinence of the emergency response, use the casualty rate to screen the initial shelter location, determine the final shelter location of the transfer subject, and ensure that the transfer subject can reach the shelter quickly and safely in an emergency through scientific site selection, reducing casualties and property losses. Thus, the problem that only the roads existing in the map are considered in the related technology, and special terrains such as gentler slopes are ignored, resulting in an overly simple determination of the casualty rate, in addition, the method of selecting the site for the emergency shelter adopts a machine learning method, does not classify the attributes of the shelter, has a black box characteristic, lacks a physical mechanism, and makes the site selection result inaccurate and unreliable.

[0020] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 A flowchart of a method for selecting an emergency shelter site based on a flash flood disaster provided according to an embodiment of the present application;

[0023] Figure 2 A block diagram of an emergency shelter site selection system based on flash flood disasters provided according to an embodiment of the present application;

[0024] Figure 3 A schematic block diagram of an emergency shelter site selection device based on flash flood disasters provided according to an embodiment of the present application;

[0025] Figure 4 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0027] The following is a description of the method and device for selecting a site for an emergency shelter based on a flash flood disaster in accordance with an embodiment of the present application with reference to the accompanying drawings. In view of the fact that only roads existing in the map are considered in the above background technology, special terrains such as gentler slopes are ignored, resulting in an overly simple determination of the casualty rate. In addition, the method for selecting a site for an emergency shelter adopts a machine learning method, and does not classify the attributes of the shelter, has a black box characteristic, lacks a physical mechanism, and makes the site selection result inaccurate and unreliable. The present application provides a method for selecting a site for an emergency shelter based on a flash flood disaster, in which the temporal and spatial variation data of flood elements in the flash flood in the target area during the flash flood can be collected in real time, and the evolution trend and potential impact area of ​​the flash flood can be quickly understood, and the emergency response efficiency can be improved. The casualty rate of the transfer subject in the target area can be calculated, and the risk level of the transfer subject can be quickly evaluated, and the pertinence of the emergency response can be improved. The initial shelter location is screened using the casualty rate, and the final shelter location of the transfer subject is determined. Through scientific site selection, it is ensured that the transfer subject can quickly and safely reach the shelter in an emergency, reducing casualties and property losses. This solves the problem in the related technology that only the roads existing in the map are considered, and special terrains such as gentle slopes are ignored, resulting in an overly simple judgment of the casualty rate. In addition, the method for selecting emergency shelters uses a machine learning method, and does not classify the attributes of the shelters. It has a black box characteristic and lacks a physical mechanism, which makes the site selection results inaccurate and unreliable.

[0028] Specifically, Figure 1 The present invention is a flowchart of a method for selecting an emergency shelter site based on flash flood disasters provided according to an embodiment of the present application.

[0029] like Figure 1 As shown, the method for selecting an emergency shelter site based on flash flood disasters includes the following steps:

[0030] In step S101, the spatiotemporal variation data of flood elements in the target area during the flash floods are collected.

[0031] It is understandable that in order to collect the spatiotemporal variation data of flood elements in the target area when flash floods occur, the embodiment of the present application can first model the environment of the target area, such as modeling roads and terrain, etc., and this application does not make specific limitations.

[0032] In addition, it should be noted that the spatiotemporal variation data of flood elements in the embodiment of the present application can be understood as the variation of flood characteristic values ​​in time and space. Among them, flood characteristic values ​​can include but are not limited to flood level, flood peak flow, flood peak propagation time, flood rise and fall rate, flood peak flow modulus, flood duration, flood total volume and flood process line, etc., and this application does not make specific restrictions.

[0033] In some embodiments, the embodiments of the present application can simulate flash floods in the target area according to the rainfall, and issue flash flood disaster warnings, and then simulate the evolution of flash floods over time and space to obtain corresponding spatiotemporal change data of flood elements.

[0034] For example, Figure 2 As shown, the embodiment of the present application can utilize the flash flood simulation module to download the remote sensing image of the target area in XX software (such as Google Earth, etc., which is not specifically limited in the present application), and respectively vectorize the roads and terrain in the remote sensing image on a geographic information system platform (such as ArcGIS platform, etc., which is not specifically limited in the present application), and then process them into a topological structure that can be used for path analysis, and simulate the rainfall in the target area, and then simulate the scene of flash floods in the target area, thereby obtaining the corresponding spatiotemporal change data of flood elements.

[0035] Optionally, in one embodiment of the present application, data on the spatiotemporal variation of flood elements in a target area during the temporal and spatial evolution of flash floods when flash floods occur are collected, including: obtaining the watershed range, meteorological data and terrain data of the target area; calculating the flash flood inundation depth and flow velocity in the target area based on the watershed range, meteorological data and terrain data; collecting rainfall intensity, river interface strength and roughness in the target area; and generating data on the spatiotemporal variation of flood elements according to the flash flood inundation depth, flow velocity, rainfall intensity, river interface strength and roughness.

[0036] It can be understood that in the embodiment of the present application, the data source of the watershed range can be a water system data set (such as rivers, lakes, etc.) or a watershed boundary data set, etc., which is not specifically limited in the present application, and can be obtained with the help of ArcSWAT (Agricultural Non-Point Source Pollution Watershed Assessment Tool) tool; the data source of meteorological data can be meteorological station observation data or meteorological model output data, etc., which is not specifically limited in the present application, and can be rainfall process data within a certain time range of the target area, wherein the certain time can be set by technicians in this field according to actual conditions, and is not specifically limited in the present application; the data source of terrain data can be DEM (Digital Elevation Model) data, which can be DEM data obtained with a resolution of 12.5 meters from ALOS PALSAR (Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar) terrain observer.

[0037] In the actual implementation process, the embodiment of the present application can use the ArcSWAT tool to obtain the watershed range, obtain meteorological data through the rainfall process data within a certain time range of the target area, and use the ALOS PALSAR terrain observer with a 12.5-meter resolution to obtain terrain data, and then calculate the flash flood inundation depth and flow rate of the target area based on the obtained watershed range, meteorological data and terrain data.

[0038] For example, Figure 2 As shown, the embodiment of the present application utilizes a series of processes such as flash flood inundation units, two-dimensional grids, calculation of hydraulic attribute tables, setting of boundaries and initial conditions, and execution of operations to construct a two-dimensional hydrodynamic model, and inputs the watershed range, meteorological data, and terrain data into the pre-constructed two-dimensional hydrodynamic model to output the flash flood inundation depth and flow rate with a time resolution of 1 minute.

[0039] Furthermore, the embodiment of the present application simulates different rainfall intensities, river interface strengths and roughnesses in the target area through the scenario comparison unit, thereby simulating different intensities of mountain torrents. Among them, in the embodiment of the present application, the derivation of different rainfall intensities can adopt the "Hubei Province Heavy Rain Runoff Calculation Chart" method. Specifically, the embodiment of the present application first checks the "Hubei Province Heavy Rain Runoff Calculation Chart" based on the center position of the basin to obtain the mean value, CV, and Cs / CV of the heavy rain at the centroid point of the basin, wherein Cs / CV is uniformly taken as 3.5 according to the requirements of the "Hubei Province Heavy Rain Runoff Calculation Chart", CV represents the coefficient of variation, and Cs represents the skewness coefficient of the heavy rain. Further, the embodiment of the present application calculates the rainfall at the design points of different frequencies of different durations according to different duration parameters. By selecting the rainfall at the same duration and different frequencies, the impact of different mountain torrent intensities on the transfer of the transfer subject can be compared.

[0040] Furthermore, the embodiment of the present application obtains the spatiotemporal variation data of flood elements when flash floods occur in the target area based on the flash flood inundation depth, flow velocity, rainfall intensity, river interface strength and roughness.

[0041] In step S102, based on the spatiotemporal variation data of flood elements, the casualty rate of the transfer subjects in the target area is calculated.

[0042] As a possible implementation method, the embodiment of the present application can simulate the transfer process of the transfer subject when a flash flood occurs, and then calculate the casualty rate of the transfer subject through the spatiotemporal variation data of flood elements.

[0043] For example, Figure 2As shown, the embodiment of the present application can simulate the most unfavorable situation that occurs when a flash flood breaks out through the main body evacuation module, and randomly assign the initial position of the transfer subject to any position in the target area. After the transfer subject receives the early warning information of the flash flood, it can first go through a period of transfer preparation before starting the transfer. During the transfer preparation time, the transfer subject will choose to climb the hillside to a temporary climbing point to avoid the flood or to the initial shelter to escape, and simulate the transfer process of the transfer subject starting to transfer, and then obtain the casualty rate of the transfer subject based on the spatiotemporal change data of flood elements.

[0044] Optionally, in one embodiment of the present application, the casualty rate of the transfer subjects in the target area is calculated based on the spatiotemporal change data of flood elements, including: obtaining the emergency evacuation behavior data of each transfer subject in the target area; based on the emergency evacuation behavior data, obtaining the spatiotemporal position data and energy consumption data of each transfer subject during the transfer process; and calculating the casualty rate based on the spatiotemporal change data of flood elements, the spatiotemporal position data and the energy consumption data.

[0045] In some embodiments, after receiving the warning information of flash floods, the transfer subject of the embodiment of the present application can first undergo a period of transfer preparation before starting the transfer. During the transfer preparation time, the transfer subject will generate a series of emergency evacuation behavior data, such as choosing to climb along the hillside to a temporary climbing point to avoid the flood, or to escape to the initial shelter, etc. This application does not make specific restrictions.

[0046] Specifically, after receiving the warning information of flash floods, the transfer subject of the behavior selection unit in the embodiment of the present application still needs a period of time to prepare for transfer. The transfer preparation time of the transfer subject is a complex process, involving psychological preparation for emergency transfer, including a series of stages, such as confirming whether the flood will pose a direct threat to people, whether to transfer, whether to go to the initial shelter, whether to stay at home, etc. This application does not make specific restrictions, and then generates a series of emergency evacuation behavior data.

[0047] In the embodiment of the present application, the delay time (τ) and the action probability using Rayleigh distribution can be specified to simplify the process. The probability of the transfer subject starting to transfer can be, but is not limited to:

[0048]

[0049] Among them, τ is the delay time of the transfer subject; σ is the scale parameter of the Rayleigh distribution, which controls the shape of the probability density function of the random variable; t is the time after the warning is issued, in minutes, and both σ and τ can be changed according to the social vulnerability of the simulation area. When the transfer subject does not transfer during the delay time, when t is greater than τ, P(t) represents the probability of the transfer subject starting to transfer, which is used to estimate the number of people transferred by the transfer subject within a certain period of time.

[0050] Furthermore, the transfer behavior simulation unit of the embodiment of the present application can simulate the transfer route and transfer speed of each transfer subject based on the emergency evacuation behavior data, and then obtain the position and spatiotemporal data of each transfer subject during the transfer process.

[0051] Among them, in the embodiment of the present application, the transfer route is determined based on the principle of minimizing the distance between the current position of the transfer subject and the destination, taking into account the distance between the current position of the transfer subject and the destination and the surrounding conditions that may appear at the next moment (such as crowd density, water depth, flow rate, etc., which are not specifically limited in this application).

[0052] For example, the transfer route of the embodiment of the present application can be determined based on the principle of minimizing the distance between the current position of the transfer subject and the destination. Taking into account that the disaster occurs in a short time and the target area is small in size in flash flood disasters, and the transfer method is generally walking, the transfer process of the transfer subject can be displayed in the interface, and then the transfer route of each transfer subject can be observed and recorded.

[0053] In addition, it should be noted that each transfer subject in the embodiment of the present application will also generate a certain amount of energy consumption during the transfer process. When the energy consumption reaches the critical value of the transfer subject, the transfer subject will no longer be able to move. At this time, energy consumption data of each transfer subject during the transfer process can be generated.

[0054] Exemplarily, when the transfer subject chooses to temporarily climb a slope to avoid the risk of flooding, the climbing energy consumption unit of the embodiment of the present application is generally a rural or township area, and the proportion of the elderly and children is high, the social vulnerability is high, and the slope and length of the slope are different. The transfer subject cannot climb any slope. Therefore, the energy consumption of the transfer subject when climbing the slope can be considered in combination with the slope of the slope. Among them, the embodiment of the present application can combine the climbing speed and net oxygen consumption of the transfer subject to obtain the climbing energy consumption function of the transfer subject, which can be but not limited to expressed as:

[0055] Cr i =155.4i 5 -30.4i 4 -43.3i 3 +46.3i 2 +19.5i+3.6, (2)

[0056] E maxi =v max,i ×Cr i , (3)

[0057] Among them, Cr i is the metabolic energy consumption of running, i is the slope of the hill, E maxi is the net oxygen consumption, v max,iis the maximum climbing speed.

[0058] It can be understood that the embodiment of the present application can calculate the metabolic energy consumption of the transfer subject at the slope according to the slope of the hill, and multiply the metabolic energy consumption by the speed of the transfer subject to obtain the net oxygen consumption, and then judge whether the transfer subject can continue to transfer based on the net oxygen consumption. When the net oxygen consumption exceeds 80% of the maximum oxygen uptake of the human body, the transfer subject will find it difficult to continue exercising.

[0059] Furthermore, the embodiment of the present application calculates the casualty rate of the transfer subject based on the spatiotemporal variation data of flood elements, the spatiotemporal data of location and the energy consumption data.

[0060] Specifically, the casualty rate calculation unit of the embodiment of the present application can calculate the casualty rate based on the location spatiotemporal data, energy consumption data and spatiotemporal change data of flood elements (such as mountain torrent inundation depth and flow rate), and combines the human body instability model. When the transfer subject is impacted by mountain torrents, two situations of slippage and fall may occur. Therefore, in the embodiment of the present application, the calculation of the casualty rate can be based on the two situations of slippage and fall, and its calculation formula can be but not limited to:

[0061] Slip:

[0062]

[0063] fall:

[0064]

[0065] Among them, h p is height, m p is body weight, h f is the water depth, U c is the flow rate, ρ f is the density of water, a1, a2, b1, b2 are human body parameters.

[0066] It can be understood that in the embodiment of the present application, when the transfer subject slips or falls in the water during the transfer process, a certain proportion of the transfer subjects will be marked as casualties. The set proportion is determined according to the social sensitivity of the target area. The proportion is higher in rural areas where there are many vulnerable groups such as the elderly and children. The specific setting can be made by technical personnel in this field according to actual conditions, and this application does not impose any specific restrictions.

[0067] In step S103, the final shelter location of the transfer subject is determined according to the initial shelter location and the casualty rate.

[0068] It can be understood that after a flash flood occurs, the shelter site selection module of the embodiment of the present application can initially plan the target area according to the shelter constraints, set the initial shelter location and temporary climbing points in the target area, and after satisfying the objective function, if an extreme rainfall event occurs, the casualty rate is used to re-screen the initial shelter location to obtain the final shelter location of the transferred entity.

[0069] Optionally, in one embodiment of the present application, the final shelter position of the transfer subject is determined based on the initial shelter position and the casualty rate, including: generating the initial shelter position of the transfer subject according to the objective function; and screening the initial shelter position by the casualty rate to obtain the final shelter position.

[0070] As a possible implementation method, the embodiment of the present application can initially screen the shelter locations according to the shelter constraints and the objective function to obtain the initial shelter location of the transfer subject, and re-screen the initial shelter location using the casualty rate to obtain the final shelter location of the transfer subject.

[0071] Exemplarily, the machine learning unit of the embodiment of the present application can extract the elevation, slope, aspect and other terrain data of the target area based on the DEM data of the target area, and model the target function based on the shelter constraints, such as the maximum number of people reaching the shelter, the lowest shelter construction cost and the shortest time for the transfer subject to transfer to the shelter, and screen the positions that meet the target function in the target area to obtain the initial shelter position of the transfer subject. Among them, in the embodiment of the present application, the selection and verification of the initial shelter position is based on the official shelter position in the government report, and then the initial shelter is used to simulate the flash flood transfer of the transfer subject, and the shelter evaluation unit is used to re-screen the initial shelter position according to the casualty rate to obtain the final shelter position.

[0072] Optionally, in one embodiment of the present application, the initial shelter locations are screened by casualty rate to obtain the final shelter location, including: obtaining the initial shelter casualty rates corresponding to different initial shelter locations; comparing the initial shelter casualty rates to obtain the final shelter casualty rates that meet preset casualty rate conditions; and generating the final shelter location based on the final shelter casualty rates.

[0073] It can be understood by those skilled in the art that different initial shelter locations in the embodiments of the present application correspond to different casualty rates. Therefore, the initial shelter casualty rates can be compared to select a shelter location that meets certain casualty rate conditions (such as the lowest casualty rate, etc., which is not specifically limited in the present application), that is, the initial shelter location is re-screened to generate the final shelter location. Among them, the certain casualty rate condition can be set by those skilled in the art according to actual conditions, which is not specifically limited in the present application.

[0074] Illustratively, the shelter evaluation unit of the embodiment of the present application inputs the initial shelter casualty rate corresponding to the initial shelter location into a pre-constructed shelter evaluation model to select the shelter location with the lowest corresponding casualty rate as the final shelter location to which the transfer subject will transfer when facing a flash flood.

[0075] Combine the following Figure 2 As shown, the working principle of the method for selecting an emergency shelter site based on flash flood disasters proposed in the embodiment of the present application is introduced with a specific embodiment.

[0076] in, Figure 2 The present invention is a block diagram of a system for selecting an emergency shelter site based on flash flood disasters according to an embodiment of the present application.

[0077] like Figure 2 As shown, the emergency shelter site selection system 20 based on flash flood disasters includes: a main evacuation module 201, a flash flood simulation module 202 and a shelter site selection module 203.

[0078] The subject evacuation module 201 is used to simulate the transfer process of the transfer subject during flash floods and obtain the casualty rate of the transfer subject.

[0079] Furthermore, in the embodiment of the present application, the main evacuation module 201 includes: a behavior selection unit 2011, a transfer behavior simulation unit 2012, a climbing energy consumption unit 2013 and a casualty rate calculation unit 2014.

[0080] The behavior selection unit 2011 is used to simulate the emergency evacuation behavior data generated by each transfer subject after receiving the warning information of flash floods, such as going to the initial shelter and climbing the hillside to the temporary shelter.

[0081] The transfer behavior simulation unit 2012 is used to simulate the transfer route and transfer speed of each transfer subject to obtain the positional spatiotemporal data of each transfer subject during the transfer process.

[0082] The climbing energy consumption unit 2013 is used to simulate the energy consumption of each transfer subject during the transfer process. When the energy consumption reaches the critical value of the transfer subject, the transfer subject will no longer be able to move, thereby generating energy consumption data.

[0083] The casualty rate calculation unit 2014 is used to calculate the casualty rate of the transfer subject according to the spatiotemporal variation data of flood elements, the spatiotemporal data of location and the energy consumption data.

[0084] The flash flood simulation module 202 is used to simulate the temporal and spatial evolution process of flash flood disasters in the target area and obtain the temporal and spatial variation data of flood elements in the target area.

[0085] Furthermore, in the embodiment of the present application, the flash flood simulation module 202 includes: a flash flood inundation unit 2021 and a scenario comparison unit 2022 .

[0086] Among them, the flash flood inundation unit 2021 is used to obtain the flash flood inundation depth and flow rate of the target area.

[0087] The scenario comparison unit 2022 is used to obtain the rainfall intensity, river interface strength and roughness of the target area to simulate different flash flood intensities.

[0088] The shelter site selection module 203 is used to select the location of the shelter for the transfer subject.

[0089] Furthermore, in the embodiment of the present application, the shelter site selection module 203 includes: a machine learning unit 2031 and a shelter evaluation unit 2032 .

[0090] The machine learning unit 2031 is used to preliminarily screen the shelter locations according to the shelter constraints and the objective function to obtain the initial shelter locations of the transfer subjects.

[0091] The shelter evaluation unit 2032 is used to compare the casualty rates of the initial shelter locations, select shelter locations that meet certain casualty rate conditions, re-screen the initial shelter locations, and generate final shelter locations.

[0092] According to the method for selecting a site for emergency shelters based on flash flood disasters proposed in the embodiment of the present application, the temporal and spatial variation data of flood elements in the flash floods in the target area during the flash floods can be collected in real time, and the evolution trend and potential impact area of ​​the flash floods can be quickly understood, and the efficiency of emergency response can be improved. The casualty rate of the transfer subject in the target area can be calculated, and the risk level of the transfer subject can be quickly evaluated, and the pertinence of the emergency response can be improved. The initial shelter location can be screened using the casualty rate, and the final shelter location of the transfer subject can be determined. Through scientific site selection, it is ensured that the transfer subject can quickly and safely reach the shelter in an emergency, reducing casualties and property losses. Thus, the problem that only the roads existing in the map are considered in the related technology, and special terrains such as gentle slopes are ignored, resulting in an overly simple determination of the casualty rate, in addition, the method for selecting a site for emergency shelters adopts a machine learning method, and does not classify the attributes of the shelter, has a black box characteristic, lacks a physical mechanism, and makes the site selection result inaccurate and unreliable.

[0093] Next, the emergency shelter site selection device based on flash flood disasters proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0094] Figure 3A block diagram of an emergency shelter site selection device based on flash flood disasters provided according to an embodiment of the present application.

[0095] like Figure 3 As shown, the device 30 for selecting an emergency shelter site based on flash flood disasters includes: a collection module 301 , a calculation module 302 and a generation module 303 .

[0096] The collection module 301 is used to collect the temporal and spatial variation data of flood elements in the target area during the flash floods' spatial and temporal evolution process.

[0097] The calculation module 302 is used to calculate the casualty rate of the transfer subjects in the target area based on the spatiotemporal variation data of flood elements.

[0098] The generating module 303 is used to determine the final shelter location of the transfer subject according to the initial shelter location and the casualty rate.

[0099] Optionally, in one embodiment of the present application, the calculation module 302 includes: a first acquisition unit, a second acquisition unit and a first calculation unit.

[0100] The first acquisition unit is used to acquire the emergency evacuation behavior data of each transfer subject in the target area.

[0101] The second acquisition unit is used to acquire the position spatiotemporal data and energy consumption data of each transfer subject during the transfer process based on the emergency evacuation behavior data.

[0102] The first calculation unit is used to calculate the casualty rate according to the spatiotemporal variation data of flood elements, the spatiotemporal location data and the energy consumption data.

[0103] Optionally, in one embodiment of the present application, the acquisition module 301 includes: a third acquisition unit, a second calculation unit, a acquisition unit and a first generation unit.

[0104] The third acquisition unit is used to acquire the watershed range, meteorological data and terrain data of the target area.

[0105] The second calculation unit is used to calculate the flooding depth and flow rate of the mountain torrents in the target area based on the watershed range, meteorological data and terrain data.

[0106] The collection unit is used to collect rainfall intensity, river interface strength and roughness in the target area.

[0107] The first generation unit is used to generate the spatiotemporal variation data of flood elements according to the flooding depth, flow velocity, rainfall intensity, river channel interface strength and roughness of the mountain torrents.

[0108] Optionally, in one embodiment of the present application, the generating module 303 includes: a second generating unit and a screening unit.

[0109] The second generating unit is used to generate the initial shelter position of the transfer subject according to the objective function.

[0110] The screening unit is used to screen the initial shelter locations according to the casualty rate to obtain the final shelter locations.

[0111] Optionally, in one embodiment of the present application, the screening unit includes: an acquisition subunit, a comparison subunit and a generation subunit.

[0112] The acquisition subunit is used to obtain the initial shelter casualty rates corresponding to different initial shelter locations.

[0113] The comparison subunit is used to compare the initial shelter casualty rates to obtain the final shelter casualty rates that meet the preset casualty rate conditions.

[0114] A generating subunit is used to generate a final shelter location based on the final shelter casualty rate.

[0115] It should be noted that the aforementioned explanation of the embodiment of the method for selecting a site for an emergency shelter based on a flash flood disaster is also applicable to the device for selecting a site for an emergency shelter based on a flash flood disaster of this embodiment, and will not be repeated here.

[0116] According to the emergency shelter site selection device based on flash flood disasters proposed in the embodiment of the present application, the temporal and spatial variation data of flood elements in the flash flood in the target area during the flash flood outbreak can be collected in real time, and the evolution trend and potential impact area of ​​the flash flood can be quickly understood, and the efficiency of emergency response can be improved. The casualty rate of the transfer subject in the target area can be calculated, and the risk level of the transfer subject can be quickly evaluated to improve the pertinence of the emergency response. The initial shelter location is screened by the casualty rate, and the final shelter location of the transfer subject is determined. Through scientific site selection, it is ensured that the transfer subject can quickly and safely reach the shelter in an emergency, reducing casualties and property losses. Thus, the problem that only the roads existing in the map are considered in the related technology, and special terrains such as gentle slopes are ignored, resulting in an overly simple determination of the casualty rate, in addition, the method of emergency shelter site selection adopts a machine learning method, and does not classify the attributes of the shelter, has a black box characteristic, lacks a physical mechanism, and makes the site selection result inaccurate and unreliable.

[0117] Figure 4 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. The electronic device may include:

[0118] Memory 401 , processor 402 , and a computer program stored in the memory 401 and executable on the processor 402 .

[0119] When the processor 402 executes the program, the method for selecting an emergency shelter site based on a flash flood disaster provided in the above embodiment is implemented.

[0120] Furthermore, the electronic device further comprises:

[0121] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0122] The memory 401 is used to store computer programs that can be executed on the processor 402 .

[0123] The memory 401 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0124] If the memory 401, the processor 402 and the communication interface 403 are implemented independently, the communication interface 403, the memory 401 and the processor 402 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0125] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0126] The processor 402 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0127] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for selecting an emergency shelter site based on flash flood disasters.

[0128] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements the above-mentioned method for selecting an emergency shelter site based on flash flood disasters.

[0129] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0130] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0131] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0132] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0133] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0134] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0135] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0136] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for selecting an emergency shelter site based on flash flood disasters, characterized in that: The following steps are involved: Collect the spatiotemporal variation data of flood elements in the target area during flash floods; Based on the spatiotemporal variation data of the flood elements, calculating the casualty rate of the transfer of the transfer subjects in the target area; The final shelter location of the transfer subject is determined according to the initial shelter location and the casualty rate.

2. The method according to claim 1, characterized in that The calculating the casualty rate of the transfer of the transfer subjects in the target area based on the spatiotemporal variation data of the flood elements comprises: Acquire emergency evacuation behavior data of each transfer subject in the target area; Based on the emergency evacuation behavior data, obtaining the positional spatiotemporal data and energy consumption data of each transfer subject during the transfer process; The casualty rate is calculated based on the spatiotemporal variation data of flood elements, the spatiotemporal location data and the energy consumption data.

3. The method according to claim 1, characterized in that The data on the spatiotemporal variation of flood elements in the target area during the flash floods over time and space are collected, including: Obtaining the watershed range, meteorological data and topographic data of the target area; Calculate the flooding depth and flow rate of the target area based on the watershed range, the meteorological data and the terrain data; Collecting rainfall intensity, river channel interface strength and roughness of the target area; The spatiotemporal variation data of the flood elements are generated according to the flood inundation depth, the flow velocity, the rainfall intensity, the river channel interface intensity and the roughness.

4. The method according to claim 1, characterized in that: Determining the final shelter position of the transfer subject according to the initial shelter position and the casualty rate includes: generating an initial shelter position of the transfer subject according to an objective function; The initial shelter positions are screened according to the casualty rate to obtain the final shelter positions.

5. The method according to claim 4, characterized in that The screening of the initial shelter positions by the casualty rate to obtain the final shelter positions includes: Obtain the initial shelter casualty rates corresponding to different initial shelter locations; Comparing the initial casualty rates of the shelters to obtain final casualty rates of the shelters that meet a preset casualty rate condition; The final shelter position is generated based on the final shelter casualty rate.

6. An emergency shelter site selection device based on mountain torrent disasters, characterized in that: include: The collection module is used to collect the spatiotemporal variation data of flood elements in the target area during the flash floods’ temporal and spatial evolution process; A calculation module, for calculating the casualty rate of the transfer subject in the target area based on the spatiotemporal variation data of the flood elements; A generating module is used to determine the final shelter location of the transfer subject according to the initial shelter location and the casualty rate.

7. The device according to claim 6, characterized in that The computing module comprises: A first acquisition unit is used to acquire the emergency evacuation behavior data of each transfer subject in the target area; A second acquisition unit is used to acquire the position spatiotemporal data and energy consumption data of each transfer subject during the transfer process based on the emergency evacuation behavior data; The first calculation unit is used to calculate the casualty rate according to the spatiotemporal variation data of the flood elements, the spatiotemporal location data and the energy consumption data.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for selecting an emergency shelter site based on flash flood disasters as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for selecting an emergency shelter site based on a flash flood disaster as described in any one of claims 1 to 5.

10. A computer program product, characterized in that It comprises a computer program, which, when executed, is used to implement the method for selecting an emergency shelter site based on a flash flood disaster as described in any one of claims 1 to 5.

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