Flood-affected population assessment method based on three-dimensional building characteristics and spatial indexes

Abstract

The invention belongs to the technical field of natural disaster assessment. A flood-affected population assessment method based on three-dimensional building characteristics and spatial indexes comprises the following steps: establishing a three-dimensional building response model, and calculating an effective base area of a building through height / floor conversion; calculating a population density based on the effective base area and the population data; establishing multi-stage water depth submerging area statistics, and adopting an R-tree spatial index technology to realize rapid spatial analysis of submerging elements and buildings; calculating a submerged area through layer intersection; and generating a submerged population statistical table by taking the administrative division as a unit. The method is used for solving the technical problems that an existing disaster damage assessment method cannot reflect the limitation of three-dimensional characteristics of a building, and an existing flood disaster damage assessment method is low in calculation efficiency and precision.

Description

Technical Field

[0001] This invention belongs to the field of natural disaster assessment technology, specifically involving a method for assessing the population impact of floods by integrating three-dimensional building features and spatial indexes. Background Technology

[0002] China is one of the countries in the world most prone to natural disasters, and floods have always posed a significant threat to the safety of people's lives and property, as well as social stability and development. In recent years, affected by global climate change, extreme weather events have become more frequent. Against this backdrop, establishing an efficient and accurate flood loss assessment system is particularly important. It is not only the core basis for formulating disaster prevention and mitigation strategies, carrying out emergency rescue and post-disaster reconstruction, but also a key support for improving the country's flood control and disaster reduction capabilities.

[0003] Existing flood impact population assessment methods have the following shortcomings in calculating the inundated population: First, according to the "Technical Requirements for the Compilation of Flood Risk Maps and Special Assessments", the three-dimensional features of buildings should be included in the core assessment parameters, but traditional methods still use simple two-dimensional planar calculations (i.e., X and Y axis planes), ignoring the three-dimensional features of buildings in vertical space (on the Z axis) (such as floor height); Second, they use traversal algorithms to process layers and do not use efficient layer space analysis methods, resulting in long calculation times and low efficiency in scenarios with a large amount of layer data.

[0004] However, existing technologies cannot simultaneously meet the above requirements, especially when dealing with complex urban terrain, where the contradiction between assessment accuracy and computational efficiency is particularly prominent. Therefore, it is necessary to propose a method for assessing the population inundated by floods, overcoming the limitation of existing disaster damage assessment methods in failing to reflect the three-dimensional characteristics of buildings, while also improving the efficiency and accuracy of disaster damage calculation. Summary of the Invention

[0005] The purpose of this invention is to provide a flood impact population assessment method based on three-dimensional building features and spatial indexing, in order to solve the limitations of existing disaster damage assessment methods that cannot reflect the three-dimensional features of buildings, and the technical problems of low efficiency and accuracy of disaster damage calculation.

[0006] To address the above technical problems, this invention adopts the following technical solution: a flood impact population assessment method based on three-dimensional building features and spatial indexing, comprising the following steps:

[0007] Step 1: Obtain vector data of buildings within the study area (fields include building height), and calculate the effective base area of ​​the buildings;

[0008] Step 2: Obtain population grid data within the study area and calculate population density using the effective base area of ​​buildings;

[0009] Step 3: Establish a hydrodynamic model for the study area, simulate the flood process based on the model, calculate the flood inundation elements, including inundation depth, inundation duration, inundation range and arrival time, and generate a vector file of flood inundation elements;

[0010] Step 4: Divide the maximum flood depth into several levels, use R-tree spatial indexing technology to realize rapid spatial analysis of flood flood feature layers and buildings, and then calculate the intersection area of ​​the flood range and buildings.

[0011] Step 5: Calculate the effective base area of ​​the inundated building based on the intersection area of ​​the inundation range and the building's floors, and calculate the inundated population under each water depth level;

[0012] Step 6: Group and aggregate the inundated population according to administrative divisions, and output the statistical results of the inundated population at each water depth level and the total inundated population for each division.

[0013] This invention establishes a three-dimensional building response model, quantifies the three-dimensional features of buildings through height / floor conversion and calculation of the effective base area; calculates population density based on the effective base area and population data; establishes statistics on inundation areas for multiple water depths (<0.5m, 0.5m~1.0m, 1.0m~2.0m, 2.0m~3.0m, >3.0m), and uses R-tree spatial indexing technology to achieve rapid spatial analysis of inundation elements and buildings; calculates inundation area through layer intersection; and generates an inundated population statistics table based on administrative divisions. This invention overcomes the limitations of existing disaster damage assessment methods that cannot reflect the three-dimensional features of buildings, and also helps to improve the efficiency and accuracy of flood disaster damage calculation.

[0014] Step 4 employs R-tree spatial indexing technology to reduce computational complexity, enabling rapid spatial analysis of flood-inundated feature layers and buildings. Specifically:

[0015] O ct =N*M

[0016] O Rtree =N*logM

[0017] Among them, O ct 1 represents the computational complexity of the traditional traversal algorithm; N represents the number of geometric features in the flood-inundated feature layer; M represents the number of geometric features in the building layer; O Rtree This represents the computational complexity of the R-tree spatial indexing algorithm.

[0018] To address the technical problem of how to implement step 1, the present invention adopts the following technical solution, wherein step 1 includes:

[0019] Step 11: Collect building vector data, including building height;

[0020] Step 12: Calculate the number of floors in each building based on the average floor height:

[0021]

[0022] Among them, F ji Let F be the number of floors of the i-th building within the study area, and F ji ≥1.0; H ji Let be the height of the i-th building within the study area; h is the average floor height, typically taken as 3.0m.

[0023] Step 13: Calculate the effective footprint area of ​​the i-th building based on its floor area and number of floors.

[0024] S ji =F ji ×A ji

[0025] Among them, S ji Let A be the effective base area of ​​the i-th building within the study area; ji Let be the area occupied by the i-th building within the study area.

[0026] To address the technical problem of how to implement step 2, the present invention adopts the following technical solution, wherein step 2 includes:

[0027] Step 21: Obtain population grid data within the study area, including the population P of the j-th grid. j Step 22: Based on spatial intersection relationships, if two surface layers overlap, and a building vector overlaps with multiple population grids, the population grid containing the centroid of the building vector is used as the intersecting population grid to ensure a one-to-one correspondence between buildings and population grids. Calculate the total effective base area of ​​buildings within the j-th population grid and calculate the building population density.

[0028] S j =ΣS ji

[0029]

[0030] Where, ρ j Let P be the population density of the j-th grid within the study area; j S represents the number of people in the j-th grid within the study area; j Let be the effective base area of ​​the j-th grid in the study area, and let be the sum of the effective base areas of all buildings intersecting with the j-th grid.

[0031] To address the technical problem of how to implement step 3, the present invention adopts the following technical solution, wherein step 3 includes:

[0032] Step 31: Collect basic data for the study area, including hydrological data such as rainfall, water level and flow, as well as river cross-section data, DEM data and underlying surface data;

[0033] Step 32: Construct a hydrodynamic model based on existing data, and first calibrate and verify it to ensure that the model accuracy meets the specifications.

[0034] Step 33: Simulate the regional flood process based on the model and generate a flood inundation element vector file containing inundation elements such as inundation depth, inundation duration, inundation range and arrival time.

[0035] To address the technical problem of how to implement step 4, the present invention adopts the following technical solution, wherein step 4 includes:

[0036] Step 41: According to relevant specifications, establish different water depth classifications as follows: <0.5m, 0.5m~1.0m, 1.0m~2.0m, 2.0m~3.0m, >3.0m;

[0037] Step 42: Build an R-tree spatial index for buildings. For each building element, calculate its minimum bounding rectangle. Group the minimum bounding rectangles of all buildings into different regions and sort the regions. Build a balanced binary tree for each region. Each leaf node of the tree corresponds to a minimum bounding rectangle of a building and the original index. Non-leaf nodes correspond to the minimum bounding rectangle of a large region, which is the minimum bounding rectangle containing all child nodes within that region.

[0038] Step 43: Calculate the minimum bounding rectangle for each geometric feature in the flood-inundated feature layer; starting from the root node of the R-tree spatial index, determine whether the minimum bounding rectangle of each geometric feature intersects with the minimum bounding rectangle of the building of the current node. If they do not intersect, skip all child nodes under that node; if they intersect, continue traversing the child nodes of that node until a leaf node is reached; the building indices corresponding to all leaf nodes that intersect with the minimum bounding rectangles of the geometric features in the flood-inundated feature layer are collected as the initial intersecting building indexes.

[0039] Step 44: The initial screening of intersecting buildings in Step 43 only indicates possible intersection, because the intersection of the smallest bounding rectangle does not mean that the corresponding geometric objects actually intersect. Further geometric intersection verification is required. The indexes that pass the verification are collected as the index of actual intersecting buildings.

[0040] Step 45: For the actual intersecting buildings in Step 44, calculate the intersection area between the buildings and the flooded feature layer, where the flooded area of ​​the i-th building is Aym. ji .

[0041] To address the technical problem of how to implement step 5, the present invention adopts the following technical solution, wherein step 5 includes:

[0042] Step 51: Calculate the effective foundation area of ​​buildings within the inundation range of different water depth levels:

[0043] Sym ji =Aym ji ×F ji

[0044] Among them, Sym ji Let be the effective flooded base area of ​​the i-th building within the study area.

[0045] Step 52: Calculate the inundated population within the inundation range of different water depth levels:

[0046] Pym j =ΣSym ji ×ρ j

[0047] Among them, Pym j Let ∑Sym represent the inundated population within the j-th grid of the study area. ji This represents the sum of the effective flooded base areas of all buildings within the j-th grid in the study area.

[0048] To address the technical problem of how to implement step 6, the present invention adopts the following technical solution, wherein step 6 includes:

[0049] Step 61: Group and aggregate the submerged population according to the regional administrative divisions, and use the administrative division where the center point of the grid is located to represent the administrative region to which the entire grid belongs;

[0050] Step 62: Output the statistical results of the inundated population and total inundated population for each zone and water depth level in .csv format.

[0051] To address the technical problem of how to implement a hydrodynamic model, this invention adopts the following technical solution, wherein the hydrodynamic model includes a continuity equation and a momentum equation:

[0052]

[0053] Where u is the velocity vector; ρ is the fluid density; is the divergence operator; p is the fluid pressure; v is the kinematic viscosity; F is the force per unit mass. Attached Figure Description

[0054] Figure 1 This is a flowchart of the flood impact population assessment based on three-dimensional building features and spatial index in Example 1.

[0055] Figure 2This is a vector diagram of the buildings in the Nantong River embankment flood control protection zone in Example 2;

[0056] Figure 3 This is a grid map showing the population distribution of the Nantong River Embankment Protection Zone in Example 2.

[0057] Figure 4 This is a map showing the distribution of inundation depth in the Nantong River embankment flood control protection area under a 100-year flooding condition.

[0058] Figure 5 This is a flowchart of the R-tree spatial indexing process for buildings in the Nantong River embankment flood control protection area in Example 2.

[0059] Figure 6 This is a schematic diagram of the overlay of submerged water depth distribution, building vectors, and population density grid in Embodiment 2. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0061] Example 1

[0062] like Figure 1 The image shows a flood impact population assessment method based on three-dimensional building features and spatial indexing provided in this embodiment, including:

[0063] Step 1: Within the study area: The total number of buildings is N. B The total number of population grids is N. G The number of people in the j-th grid is P. j ;

[0064] Based on the spatial intersection relationship between buildings and population grids, it can be known that the j-th grid includes N. jB There are 1 building, and the i-th building in the j-th grid is denoted as B. ji N G N B All are natural numbers, 0≤j≤N G , 0≤i≤N jB ≤N B ;

[0065] Based on building vector data, the vector data includes the average floor height h, and the i-th building B in the j-th grid. ji Height H ji With the area A jiCalculate the i-th building B in the j-th grid. ji Effective base area S ji Calculate the value of grid N in the j-th grid. jB The total effective base area Sj of the buildings; specifically:

[0066] Step 11: Collect building vector data, including building height;

[0067] Step 12: Calculate the number of floors in each building based on the average floor height:

[0068]

[0069] Among them, F ji Let F be the number of floors of the i-th building within the study area, and F ji ≥1.0; H ji Let be the height of the i-th building within the study area; h is the average floor height, typically taken as 3.0m.

[0070] Step 13: Calculate the effective footprint area of ​​the i-th building based on its floor area and number of floors.

[0071] S j =F ji ×A ji

[0072] Among them, S ji Let A be the effective base area of ​​the i-th building within the study area; ji Let be the area occupied by the i-th building within the study area.

[0073] Step 2: Based on the number of people P in the j-th grid j , the j-th grid N jB Calculate the total effective base area Sj of all buildings, and the population density ρ of the j-th grid. j Specifically:

[0074] Step 21: Obtain population grid data within the study area, including the population P of the j-th grid. j ;

[0075] Step 22: Based on spatial intersection relationships, if two surface layers overlap, and a building vector overlaps with multiple population grids, use the population grid where the centroid of the building vector is located as the intersecting population grid, ensuring a one-to-one correspondence between buildings and population grids. Calculate the total effective base area of ​​buildings within the j-th population grid and calculate the building population density.

[0076] S j =ΣS ji

[0077]

[0078] Where, ρ j Let P be the population density of the j-th grid within the study area; j S represents the number of people in the j-th grid within the study area; j Let be the effective base area of ​​the j-th grid in the study area, and let be the sum of the effective base areas of all buildings intersecting with the j-th grid.

[0079] Step 3: Establish a hydrodynamic model for the study area, simulate the flood process based on the model, calculate flood inundation elements (inundation depth, inundation duration, inundation range, and arrival time, etc.), and generate a vector file of flood inundation elements. The basic principles of the hydrodynamic model mainly include the continuity equation and the momentum equation.

[0080]

[0081] Where u is the velocity vector; ρ is the fluid density; Here, is the divergence operator; p is the fluid pressure; v is the kinematic viscosity; and F is the force per unit mass. Specifically:

[0082] Step 31: Collect basic data for the study area, including hydrological data such as rainfall, water level and flow, as well as river cross-section data, DEM data and underlying surface data;

[0083] Step 32: Construct a hydrodynamic model based on existing data, and first calibrate and verify it to ensure that the model accuracy meets the specifications.

[0084] Step 33: Simulate the regional flood process based on the model and generate a flood inundation element vector file containing inundation elements such as inundation depth, inundation duration, inundation range and arrival time.

[0085] Step 4: According to relevant specifications, the maximum inundation depth is divided into several levels. Using R-tree spatial indexing technology, rapid spatial analysis of the flood inundation feature layer and buildings is achieved. Then, the intersection area between the inundation area of ​​the inundation feature layer and the buildings is calculated to obtain the i-th building B in the j-th grid. ji The flooded area is Aym ji Specifically:

[0086] Step 41: According to relevant specifications, establish different water depth classifications as follows: <0.5m, 0.5m~1.0m, 1.0m~2.0m, 2.0m~3.0m, >3.0m;

[0087] Step 42: Establish the R-tre of the building eSpatial index: For each building element, calculate its minimum bounding rectangle; group the minimum bounding rectangles of all buildings into different zones and sort the zones; construct a balanced binary tree based on the zones, where each leaf node corresponds to a building's minimum bounding rectangle and the original index, and non-leaf nodes correspond to the minimum bounding rectangle of a large zone, i.e., the minimum bounding rectangle containing all child nodes within that zone.

[0088] Step 43: Calculate the minimum bounding rectangle for each geometric feature in the flood-inundated feature layer; from R-tre e Starting from the root node of the spatial index, it is determined whether the minimum bounding rectangle of each geometric feature intersects with the minimum bounding rectangle of the building of the current node. If they do not intersect, all child nodes under that node are skipped. If they intersect, the child nodes of that node are traversed until a leaf node is reached. The building indexes corresponding to all leaf nodes that intersect with the minimum bounding rectangles of the geometric features of the flooded feature layer are collected into the initial intersecting building index.

[0089] Step 44: The initial screening of intersecting buildings in Step 43 only indicates possible intersection, because the intersection of the smallest bounding rectangle does not mean that the corresponding geometric objects actually intersect. Further geometric intersection verification is required. The indexes that pass the verification are collected as the index of actual intersecting buildings.

[0090] Step 45: For the actual intersecting buildings in Step 44, calculate the intersection area between the buildings and the flooded feature layer, where the flooded area of ​​the i-th building is Aym. ji .

[0091] O ct =N*M

[0092] O Rtree =N*log M

[0093] Among them, O ct 1 represents the computational complexity of the traditional traversal algorithm; N represents the number of geometric features in the flood-inundated feature layer; M represents the number of geometric features in the building layer; O Rtree This represents the computational complexity of the R-tree spatial indexing algorithm.

[0094] Step 5: Calculate the effective base area of ​​the inundated building based on the intersection area of ​​the inundation range and the building's floors, and calculate the inundated population under each water depth level;

[0095] Step 51: Calculate the effective foundation area of ​​buildings within the inundation range of different water depth levels:

[0096] Sym ji =Aym ji ×F ji

[0097] Among them, Sym ji Let be the effective flooded base area of ​​the i-th building within the study area.

[0098] Step 52: Calculate the inundated population within the inundation range of different water depth levels:

[0099] Pym j =∑Sym ji ×ρ j

[0100] Among them, Pym j Let ∑Sym represent the inundated population within the j-th grid of the study area. ji This represents the sum of the effective flooded base areas of all buildings within the j-th grid in the study area.

[0101] Step 6: Group and aggregate the inundated population according to administrative divisions, and output the statistical results of the inundated population at each water depth level and the total inundated population for each division.

[0102] Taking the Nantong River embankment flood control protection area in Jiangsu Province as an example, the implementation steps of the specific technologies are explained in detail, and the implementation of key steps can be referred to the relevant attached figures;

[0103] Step 61: Group and aggregate the submerged population according to the regional administrative divisions, and use the administrative division where the center point of the grid is located to represent the administrative region to which the entire grid belongs;

[0104] Step 62: Output the statistical results of the inundated population and total inundated population for each zone and water depth level in .csv format.

[0105] Example 2

[0106] like Figure 2 The image shown is a vector diagram of the buildings in the Nantong River embankment flood control protection area. The shapefile field includes the building height H. i ; Calculate the floor F of each building based on the average single-floor height h. ji ; Calculate the building's footprint A i And calculate the effective base area S based on the number of floors.

[0107] like Figure 3 The image shows a grid of population distribution within the Nantong River embankment flood control protection area. The shapefile field includes the number of people per grid cell (P). j ; Calculate the total effective base area S of buildings within the grid using spatial intersection relationships. ji And calculate the building population density ρ j Table 1 shows the calculated population density distribution grid of the Nantong River embankment flood protection area.

[0108] Table 1. Population density distribution grid of the Nantong River embankment flood protection area after population density calculation.

[0109]

[0110] Step 3: Collect basic data of the Nantong River embankment flood protection area, including hydrological data such as rainfall, water level and flow, as well as river cross-section data, DEM data and underlying surface data; construct a hydrodynamic model based on existing data, and first calibrate and verify it to ensure that the model accuracy meets the specifications; simulate the regional flood process based on the model and generate a vector file containing inundation elements such as inundation depth, inundation duration, inundation range and arrival time.

[0111] Step 4: According to relevant specifications, establish the following water depth classifications within the area: <0.5m, 0.5m~1.0m, 1.0m~2.0m, 2.0m~3.0m, >3.0m. Figure 5 The image shows the inundation depth distribution map of the Nantong River embankment flood control protection area under a 100-year flooding condition. An R-tree spatial index for buildings was established. For each building feature, its minimum bounding rectangle was calculated. The minimum bounding rectangles of all buildings were grouped according to different regions, and the regions were sorted. A balanced binary tree was constructed for each region. Each leaf node of the tree corresponds to a building's minimum bounding rectangle and the original index, while non-leaf nodes correspond to the minimum bounding rectangle of a large region (i.e., the minimum bounding rectangle containing all child nodes within that region). The minimum bounding rectangle of each geometric feature in the flood inundation feature layer was calculated, starting from the root node of the R-tree spatial index. If the minimum bounding rectangle of a geometric feature intersects with the minimum bounding rectangle of a building at the current node, and they do not intersect, all child nodes under that node are skipped. If they intersect, the child nodes of that node are traversed until a leaf node is reached. The building indices corresponding to all leaf nodes that intersect with the minimum bounding rectangles of geometric features in the flooded feature layer are collected as the initial intersecting building index. The initial intersecting buildings are only potentially intersecting because the intersection of the minimum bounding rectangles does not mean that the corresponding geometric objects actually intersect. Further geometric intersection verification is required. The indexes that pass the verification are collected as the actual intersecting building index. For the actual intersecting buildings, the intersection area Aym between the building and the flooded feature layer is calculated. Figure 5 The diagram shown is a flowchart for establishing an R-tree spatial index for buildings in the Nantong River embankment flood control protection area.

[0112] Perform step 5: Figure 6 The diagram shown is a composite image of the inundation depth distribution, building vectors, and population density grid in the region. First, the effective foundation area of ​​buildings within the inundation range for different water depth levels is calculated. Finally, the inundated population for different water depth levels (<0.5m, 0.5m~1.0m, 1.0m~2.0m, 2.0m~3.0m, >3.0m) is calculated based on the population density grid.

[0113] Step 6: Group and aggregate the inundated population according to the regional administrative divisions. The administrative division where the center point of the grid is located represents the administrative region to which the entire grid belongs. Output the statistical results of the inundated population and the total inundated population for each division and water depth level in .csv format, as shown in Table 2. This is a statistical table of the number of inundated people in different water depth levels in various towns and streets of Nantong City.

[0114] Table 2 shows the statistics of the number of people submerged under different water depth levels in various administrative divisions.

[0115] city county Townships / Subdistricts <0.5m flood population 0.5-1.0m submerged population 1.0-2.0m submerged population 2.0-3.0m submerged population >3.0m submerged population Total submerged population Nantong City Qidong City Donghai Town 1415 0 12 556 64 2047 Nantong City Qidong City Beicheng District Street 56623 0 1331 3622 739 62315 Nantong City Qidong City Beixin Town 14322 16 280 2139 121 16878 Nantong City Qidong City Nancheng District Subdistrict 51707 1329 439 3255 156 56886 Nantong City Qidong City Nanyang Town 38998 62 668 2628 219 42575 Nantong City Qidong City Cooperation Town 15283 38 785 1483 613 18202 Nantong City Qidong City Lvsi Port Economic Development Zone 0 0 0 0 0 0 Nantong City Qidong City Lüsi Port Town 61284 886 2507 4257 1076 70010 Nantong City Qidong City Qidong Jianghai Industrial Park 0 0 0 0 0 0 Nantong City Qidong City Qidong Marine Engineering & Shipbuilding Industrial Park 8703 0 2869 3330 222 15124 Nantong City Qidong City Qidong Life and Health Industry Park 0 0 0 0 0 0 Nantong City Qidong City Qidong Life and Health Science and Technology Park 0 0 0 0 0 0 Nantong City Qidong City Qidong Economic Development Zone 23624 20 65 228 70 24007 Nantong City Qidong City Qilong Town 0 0 0 0 0 0 Nantong City Qidong City Yuandaojiao Tourist Resort 0 0 0 0 0 0 Nantong City Qidong City Huiping Town 266 10 884 845 118 2123 Nantong City Qidong City Huilong Town 43835 10 482 3092 184 47603 Nantong City Qidong City Haifu Town 20748 244 1432 2535 1150 26109 Nantong City Qidong City Wang Baozhen 25331 422 1509 4952 1080 33294 … … … … … … … … …

Claims

1. A method for assessing the population impact of floods based on three-dimensional building features and spatial indexing, characterized in that, Includes the following steps: Step 1: Within the study area: The total number of buildings is N. B The total number of population grids is N. G The number of people in the j-th grid is P. j Based on the spatial intersection relationship between buildings and population grids, it can be known that the j-th grid includes N. jB There are 1 building, and the i-th building in the j-th grid is denoted as B. ji N G N B All are natural numbers, 0≤j≤N G , 0≤i≤N jB ≤N B ; Based on building vector data, the vector data includes the average floor height h, and the i-th building B in the j-th grid. ji Height H ji With the area A ji Calculate the i-th building B in the j-th grid. ji Effective base area S ji Calculate the value of grid N in the j-th grid. jB The total effective base area Sj of the buildings; Step 2: Based on the number of people P in the j-th grid j , the j-th grid N jB Calculate the total effective base area Sj of all buildings, and the population density ρ of the j-th grid. j ; Step 3: Establish a hydrodynamic model for the study area, simulate the flood process based on the model, calculate the flood inundation elements, including inundation depth, inundation duration, inundation range and arrival time, and generate a vector file of flood inundation elements; Step 4: Divide the maximum inundation depth into several levels, use R-tree spatial indexing technology to perform spatial analysis of the flood inundation feature layer and buildings, and then calculate the intersection area between the inundation range of the inundation feature layer and the buildings to obtain the i-th building B in the j-th grid. ji The flooded area is Aym ji ; Step 5: Based on the intersection area Aym of the flooded area and the building. ji And the i-th building B in the j-th grid ji Floor F ji Calculate the submerged building B in the j-th grid. ji Effective base area Sym ji ; According to Sym ji Calculate the total effective base area (Sym) of the submerged buildings in the j-th grid. j ; According to Sym j Population density ρ in grid j j Calculate the inundated population under different inundation depth classifications; Step 6: Group and aggregate the inundated population according to administrative divisions, and output the statistical results of the inundated population at different inundation depth levels and the total inundated population for each division.

2. The evaluation method as described in claim 1, characterized in that: Step 1 includes: Step 11: Collect building vector data, including the height H of the i-th building. ji ; Step 12: Calculate the number of floors F for each building based on the average single-floor height h. ji : Among them, F ji Let F be the number of floors of the i-th building in the j-th grid within the study area, and F ji ≥1; H ji Let be the height of the i-th building within the study area; h is the average floor height, typically taken as 3.0m. Step 13: Based on the footprint and number of floors F of the i-th building in the j-th grid. ji Calculate the effective base area of ​​the i-th building in the j-th grid: S ji =F ji ×A ji Among them, S ji Let A be the effective base area of ​​the i-th building in the j-th grid within the study area; ji Let represent the area occupied by the i-th building in the j-th grid within the study area.

3. The evaluation method as described in claim 1, characterized in that: Step 2 includes: Step 21: Obtain population grid data within the study area, including the population P of the j-th grid. j ; Step 22: Calculate the total effective base area of ​​buildings within the j-th population grid using spatial intersection relationships, and calculate the building population density: S j =ΣS ji Where, ρ j Let P be the population density of the j-th grid within the study area; j S represents the number of people in the j-th grid within the study area; j The effective base area of ​​the j-th grid in the study area is the sum of the effective base areas of all buildings that intersect with the j-th grid. In step 22: the building vector surface layer overlaps with multiple population grid surface layers. That is, if the building vector overlaps with multiple population grids, the population grid where the centroid of the building vector is located is taken as the intersecting population grid to ensure that the building and the population grid correspond one-to-one.

4. The evaluation method as described in claim 1, characterized in that: Step 3 includes: Step 31: Collect basic data for the study area, including hydrological data such as rainfall, water level and flow, as well as river cross-section data, DEM data and underlying surface data; Step 32: Construct a hydrodynamic model based on existing data, and first calibrate and verify it to ensure that the model accuracy meets the specifications. Step 33: Simulate the regional flood process based on the model and generate a vector file containing inundation elements such as inundation depth, inundation duration, inundation range, and arrival time.

5. The evaluation method as described in claim 1, characterized in that: Step 4 includes: Step 41: According to relevant specifications, establish different water depth classifications as follows: <0.5m, 0.5m~1.0m, 1.0m~2.0m, 2.0m~3.0m, >3.0m; Step 42: Build an R-tree spatial index for buildings. For each building element, calculate its minimum bounding rectangle. Group the minimum bounding rectangles of all buildings into different regions and sort the regions. Build a balanced binary tree for each region. Each leaf node of the tree corresponds to a minimum bounding rectangle of a building and the original index. Non-leaf nodes correspond to the minimum bounding rectangle of a large region, which is the minimum bounding rectangle containing all child nodes within that region. Step 43: Calculate the minimum bounding rectangle for each geometric feature in the flood-inundated feature layer; starting from the root node of the R-tree spatial index, determine whether the minimum bounding rectangle of each geometric feature intersects with the minimum bounding rectangle of the building of the current node. If they do not intersect, skip all child nodes under that node; if they intersect, continue traversing the child nodes of that node until a leaf node is reached; the building indices corresponding to all leaf nodes that intersect with the minimum bounding rectangles of the geometric features in the flood-inundated feature layer are collected as the initial intersecting building indexes. Step 44: The initial screening of intersecting buildings in Step 43 only indicates possible intersection, because the intersection of the smallest bounding rectangle does not mean that the corresponding geometric objects actually intersect. Further geometric intersection verification is required. The indexes that pass the verification are collected as the index of actual intersecting buildings. Step 45: For the actual intersecting buildings in Step 44, calculate the intersection area between the buildings and the flooded feature layer, where the flooded area of ​​the i-th building in the j-th grid is Aym. ji .

6. The evaluation method as described in claim 1, characterized in that: Step 5 includes: Step 51: Calculate the effective foundation area of ​​buildings within the inundation range of different water depth levels: Sym ji =Aym ji ×F ji Among them, Sym ji Let be the effective flooded base area of ​​the i-th building within the study area. Step 52: Calculate the inundated population within the inundation range of different water depth levels: Among them, Pym j Let ΣSym represent the inundated population within the j-th grid of the study area. ji This represents the sum of the effective flooded base areas of all buildings within the j-th grid in the study area.

7. The evaluation method as described in claim 1, characterized in that: Step 6 includes: Step 61: Group and aggregate the submerged population according to the regional administrative divisions, and use the administrative division where the center point of the grid is located to represent the administrative region to which the entire grid belongs. Step 62: Output the statistical results of the inundated population and total inundated population for each zone and water depth level in .csv format.

8. The evaluation method as described in claim 1, characterized in that, The hydrodynamic model includes a continuity equation and a momentum equation: Where u is the velocity vector; ρ is the fluid density; • is the divergence operator; p is the fluid pressure; v is the kinematic viscosity; F is the force per unit mass.

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