CN111260714A - A flood disaster assessment method, device, equipment and computer storage medium - Google Patents

Abstract

The invention discloses a flood disaster-affected assessment method, a flood disaster-affected assessment device, flood disaster-affected assessment equipment and a computer storage medium, wherein the method comprises the steps of firstly establishing a DSM image of an area to be assessed, directly obtaining a grid map of the flooded area from the DSM image, and carrying out vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area, wherein the method is equivalent to the traditional passive analysis and can quickly obtain a flooded range of the area to be assessed; meanwhile, the invention also eliminates the interference of the vector diagram of the flooded area, only the area communicated with the river in the vector diagram of the flooded area is proposed, and the proposed area is used as the vector diagram of the real flooded area. Through the design, the evaluation method provided by the invention not only keeps the rapidity of passive analysis, but also has the accuracy of active analysis, and can quickly and accurately obtain the flood inundation range.

Description

A flood disaster assessment method, device, equipment and computer storage medium

technical field

The invention relates to the technical field of flood disaster assessment, in particular to a flood disaster assessment method, device, equipment and computer storage medium.

Background technique

As one of the 15 major natural disasters released by the United Nations and focused on worldwide, flood disasters have the characteristics of large impact, high frequency, and large losses. For villages and towns in the river basin, if the river bank collapses, it will pose a huge threat to the safety of residents' lives and property, and seriously affect the economic development and ecological environment of the disaster-stricken areas. The analysis is of great significance to the assessment of flood damage.

At present, two methods of active analysis and passive analysis are generally used for the impact characteristics and disaster assessment methods of flood disasters.

Active analysis is to determine the source of the flood (usually in the designated river area) within a specified range, conduct a 9-grid search through the idea of the seed spread algorithm, and simulate the flooded area according to the idea of the flood spread. , this method ensures the connectivity of the flooded area and is more in line with the real situation of flooding, but the use of 9-grid search results in a large amount of calculation and low efficiency in the entire analysis process.

Passive analysis is in a designated area, without specifying the source of the flood, and only by comparing the flood water level and elevation to determine the flooded area. This analysis method has a fast processing speed, but does not consider the flood spread. Therefore, the calculated inundation range is often larger than the actual inundation range, the error is large, and the accuracy is not high. Therefore, how to quickly and accurately analyze the flooded area has become an urgent problem to be solved.

SUMMARY OF THE INVENTION

In order to solve the problem that the existing flood damage assessment cannot have both analysis speed and accuracy, the purpose of the present invention is to provide a flood damage assessment method, device and equipment that have both the rapidity of passive analysis and the accuracy of active analysis and computer storage media.

The technical scheme adopted in the present invention is:

A flood damage assessment method, comprising the following steps:

S101. Obtain oblique image data of the area to be assessed, and use the oblique image data to establish a DSM image map of the area to be assessed;

S102. According to the DSM image map, extract the grid elements belonging to the flooded area in the DSM image map to form a flooded area grid map;

S103. Perform vector conversion on the raster map of the flooded area to obtain a vector diagram of the flooded area;

S104. Eliminate interference for all areas in the vector map of the flooded area, extract the area connected to the river in the vector map of the flooded area, and form a vector map of the real flooded area;

S105. Perform grid conversion on the vector map of the real flooded area to obtain a grid map of the real flooded area;

S106. Subtract the grid map of the real flooded area from the grid map of the flooded area to obtain a flood inundation depth map.

As a preference of the above technical solution, the grid elements of the flooded area in the step S102 are obtained by the following steps:

S102a. Determine the water level data of the river in the area to be assessed;

S102b. Obtain DSM data of each grid in the DSM image according to the DSM image;

S102c. Compare the size of the DSM data and the waterline data of each grid in the DSM image, extract the grid corresponding to the DSM data smaller than the watermark data, and use the extracted grid as the grid element of the flooded area .

As a preference of the above technical solution, the step S104 specifically includes the following steps:

S104a. Identify flood flashpoints in the area to be assessed;

S104b. Intersect the vector map of the flooded area with the flood burst point, extract the area that intersects the flood burst point in the vector map of the flooded area, and use the extracted area as the real flooded area area, And make up the vector map of the real flooded area.

As a preference of the above technical solution, the step S106 specifically includes the following steps:

S106a. According to the grid map of the real flooded area, obtain the pixel value of each grid in the grid map of the real flooded area, and use the pixel value of each grid as the flood value of each grid water level height;

S106b. According to the grid map of the flooded area, obtain the pixel value of each grid in the grid map of the flooded area, and use the pixel value of each grid as the flood water level height of each grid ;

S106c. Subtract the pixel value of each grid in the grid map of the real flooded area with the pixel value of each grid in the grid map of the flooded area to obtain the real flooded area The height difference between the grid map and the grid map of the flooded area, and the height difference is the flood inundation depth map.

As a preference of the above technical solution, the pixel value of each grid in the grid map of the flooded area is the water level data.

As a preference of the above technical solution, the following steps are adopted in the step S101 to establish the DSM image map of the area to be evaluated:

S101a. Perform aerial triangulation calculation on the oblique image data to obtain control points in the area to be assessed;

S101b. Perform image intensive matching according to the control points to obtain point cloud data of the area to be evaluated;

S101c. Construct a TIN three-dimensional grid according to the point cloud data, and generate a three-dimensional model of the blank texture of the area to be evaluated;

S101d. Perform texture mapping on the three-dimensional model to obtain a three-dimensional scene of the area to be evaluated;

S101e. Generate a DSM image of the area to be assessed according to the three-dimensional scene.

The present invention also provides another technical solution:

A flood disaster assessment device, comprising a DSM image generation module, a grid processing module, an interference elimination module and a flooded water level map calculation module;

The DSM image generation module is used to obtain oblique image data and generate a DSM image of the area to be assessed;

The grid processing module is communicatively connected to the DSM image generation module, and is used for obtaining a flooded area grid map according to the DSM image map, and performing vector conversion on the flooded area grid map to obtain a flooded area. vector illustration;

The interference elimination module is communicatively connected to the grid processing module, and is used for interference elimination of the vector map of the flooded area to obtain a real vector map of the flooded area;

The inundated water level map calculation module is communicatively connected to the interference elimination module, and is used for raster conversion of the vector map of the real inundated area to obtain a raster map of the real inundated area, and the grid of the real inundated area. The grid map is subtracted from the grid map of the flooded area to obtain a flood inundation depth map.

The present invention also provides another technical solution:

A flood damage assessment device includes a memory and a processor connected in communication, wherein the memory is used for storing a computer program, and the processor is used for executing the computer program to implement the above flood damage assessment method.

The present invention also provides another technical solution:

A computer storage medium, where a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the above-mentioned flood damage assessment method is implemented.

The beneficial effects of the present invention are:

(1) The present invention provides a flood damage assessment method, device, equipment and computer storage medium. The present invention first establishes a DSM image map of the area to be evaluated, and directly obtains a grid map of the flooded area from the DSM image map. The vector conversion of the grid map of the flooded area can be used to obtain the vector map of the flooded area. This method is equivalent to the traditional passive analysis, which can quickly obtain the flooded area of the area to be assessed. The interference of the vector map of the flooded area is eliminated. Only the area connected to the river in the vector map of the flooded area is proposed, and the proposed area is used as the vector map of the real flooded area. This step takes into account the relationship between the flooded area and the spread of the flood. connectivity, so areas not connected to the river can be excluded, improving the accuracy of the analysis results.

Through the above design, the evaluation method provided by the present invention not only retains the rapidity of passive analysis, but also has the accuracy of active analysis, and can quickly and accurately obtain the flood inundation range.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

FIG. 1 is a flow chart of the steps of the flood disaster assessment method provided by the present invention.

FIG. 2 is a flow chart of establishing a DSM image map provided by the present invention.

FIG. 3 is a schematic diagram of the flood damage assessment device provided by the present invention.

FIG. 4 is a schematic diagram of the flood damage assessment equipment provided by the present invention.

Detailed ways

The present invention will be further described below in conjunction with specific embodiments. It should be noted here that the descriptions of these embodiments are used to help the understanding of the present invention, but do not constitute a limitation of the present invention.

The term "and/or" in the text is only an association relationship to describe related objects, which means that there can be three kinds of relationships, for example, A and/or B, which can mean: A alone exists, B exists alone, and A and B exist at the same time Three cases, the term "/and" in this article is to describe another related object relationship, indicating that there can be two relationships, for example, A/ and B, can indicate: A exists alone, A and B exist alone, In addition, the character "/" in this text generally indicates that the related objects are an "or" relationship.

Example 1

As shown in Figures 1-2, the flood disaster assessment method provided in this embodiment includes the following steps:

S101. Obtain oblique image data of the area to be assessed, and use the oblique image data to create a DSM image map of the area to be assessed.

Step S101 is to obtain the DSM image map of the area to be evaluated. The DSM (Digital Surface Model, digital surface model) image map is a kind of data map generated by pixel-by-pixel projection difference correction, and then according to the influence mosaic, according to the range of the map frame. Ability to display ground heights such as surface buildings, bridges, and trees.

In this embodiment, the oblique image data of the area to be assessed is used as the data basis to obtain the DSM image of the area to be assessed. The specific establishment method will be described in detail below.

Meanwhile, in this embodiment, in order to use the DSM image map to analyze the flooded area, the DSM will be generated according to blocks, that is, the DSM image map will be tiled. In this embodiment, the raster mosaic tool provided in the AcrMap software is used to mosaic the tiles, and the mosaic operator selects LAST (the output pixel value of the overlapping area is the value in the last raster dataset mosaicked at this location). ), and finally a high-precision DSM image can be obtained, and at the same time, the flooded range can be analyzed directly according to the pixel value of the grid in the DSM image, as shown in step S102 and the specific operation steps contained therein.

In this embodiment, AcrMap software is a kind of existing software, which is a user desktop component with powerful functions such as map making, spatial analysis, and spatial data database building, and can be used for data input, editing, query, analysis and other functions , the use of AcrMap software for tiling is also an existing operation technology.

S102. According to the DSM image map, extract the grid elements belonging to the flooded area in the DSM image map to form a flooded area grid map.

In step S102, the flood damage analysis can be performed through the DSM image map, that is, the flooded area in the area to be assessed is obtained.

As explained above, the DSM image map will be generated according to the block, that is, the tile mosaic is performed. Therefore, the flooded area can be obtained directly through the grid (ie, grid element) in the DSM image map, and then get Grid map of flooded areas, the specific steps are as follows:

S102a. Determine the water level data of the river in the area to be assessed.

S102b. Obtain DSM data of each grid in the DSM image according to the DSM image.

S102c. Compare the size of the DSM data and the waterline data of each grid in the DSM image, extract the grid corresponding to the DSM data smaller than the watermark data, and use the extracted grid as the grid element of the flooded area .

In this embodiment, by directly comparing the pixel value of each grid in the DSM image with the size of the waterline data, it can be determined that the grid in the DSM image is below the waterline, which means it is flooded.

In this embodiment, since the original data used is a DSM image and is generated by block, the pixel value of each grid in the DSM image is the DSM data of the grid. Therefore, the size of the DSM data and the water level data of each grid can be directly compared, and the flooded grids can be selected, and the areas represented by these grids are the flooded areas.

In this embodiment, the water level data of the area to be assessed may be based on the official water level data of the hydrological bureau of the area to be assessed.

In this embodiment, the grid calculation tool provided by the map algebra in the ArcMap software is also used to perform the comparison calculation between the GSM data and the hydrological data of each grid in the DSM image, which is also an operation using the existing software.

At the same time, you can also write your own python statements for execution, and operate through the CON condition analysis tool. The specific statement expressions are:

Con(in_raster, true_raster, {false_raster}), fill in the conditional expression at in_raster, when the condition is met, the true_raster part will be executed, otherwise the false_raster part will be executed. The statement we fill in should be: Con("rastercalc2"<=490.5,1), rastercalc2 is the DSM data of each raster in the DSM image, and "<=490.5" is the water level filter condition, that is, less than or equal to 490.5 Then extract, of course, the water level filter condition is also the water level data proposed above. "1" means that when the condition is satisfied, the DSM data is assigned as the watermark data.

Through steps S102a to S102c, the flooded areas in the DSM image map can be obtained, and a grid map of the flooded areas can be obtained, which is convenient for subsequent analysis.

S103. Perform vector conversion on the grid map of the flooded area to obtain a vector diagram of the flooded area.

S104. Eliminate the interference of all areas in the vector map of the flooded area, extract the areas connected to the river in the vector map of the flooded area, and form a vector map of the real flooded area.

Steps S103 and S104 are for error analysis and elimination, because we extract the flooded area grid by comparing the size relationship between the DSM data of each grid of the DSM and the water level data, so as to obtain the flooded area grid. However, the obtained inundated area cannot be judged whether it is connected with the river, that is, it cannot be judged whether the extracted inundated areas all meet the flood spread. The passage that spreads to each flooded area must have a connected relationship with the river. If there is no connected relationship with the river in the flooded area extracted above, it means that this area is a disturbed area and does not belong to a flooded area. Through steps S103 and S104, it is possible to judge the connectivity of the flood spread, and to improve the accuracy of the disaster-affected area obtained by the analysis.

In this embodiment, step S103 is to convert the raster map of the flooded area into a three-dimensional disaster vector map, so as to carry out the processing of the subsequent flood spread connectivity.

In the present embodiment, the following steps are specifically adopted to perform the error analysis of the vector map of the flooded area:

S104a. Determine flood flash points in the area to be assessed.

S104b. Intersect the vector map of the flooded area with the flood burst point, extract the area that intersects the flood burst point in the vector map of the flooded area, and use the extracted area as the real flooded area area, And make up the vector map of the real flooded area.

Steps S104a-S104b are to determine whether the flood eruption point is connected with the area in the vector map of the flooded area by judging whether the flood eruption point intersects with the surface where the flooded area is located.

In this embodiment, the flood flashing point is selected in the upstream area of the river, and can be artificially selected according to the actual situation.

At the same time, step S104b is also operated by ArcMap software, that is, through the selection tool provided in the ArcMap software, the intersection of the flood burst point and each area in the vector map of the flooded area is judged, and finally the intersected area can be extracted to obtain the real flooded area. Flooded area vector illustration.

Through the above steps, the judgment of the connectivity of flood spread can be realized, the purpose of active analysis is realized, the areas that are not connected with the river are excluded, and the accuracy of the analysis results is greatly improved.

After the error is eliminated, step S105 and step S106 can be performed to obtain the final flood submerged depth map. The specific steps are as follows:

S105. Perform grid conversion on the vector map of the real inundated area to obtain a grid map of the real inundated area.

S106. Subtract the grid map of the real flooded area from the grid map of the flooded area to obtain a flood inundation depth map.

Since the grid map is used for analysis in this embodiment, after the grid map of the real flooded area is obtained after error elimination, it needs to be converted into a grid map, which is convenient for subsequent data analysis and analysis. Step S105 is to realize the conversion of the vector graphics and the raster graphics. Similarly, in this example, the existing software ArcMap is also used for implementation.

After converting the raster map of the real flooded area into a raster map through ArcMap software, the following steps are used for processing to obtain the flood inundation depth map, specifically:

S106a. According to the grid map of the real flooded area, obtain the pixel value of each grid in the grid map of the real flooded area, and use the pixel value of each grid as the flood value of each grid water level height.

S106b. According to the grid map of the flooded area, obtain the pixel value of each grid in the grid map of the flooded area, and use the pixel value of each grid as the flood water level height of each grid .

S106c. Subtract the pixel value of each grid in the grid map of the real flooded area with the pixel value of each grid in the grid map of the flooded area to obtain the real flooded area The height difference between the grid map and the grid map of the flooded area, and the height difference is the flood inundation depth map.

Since the vector map of the real inundated area is the actual inundated area, the pixel value of each grid in the converted raster image is the actual water level value of the corresponding inundated area of the grid.

At the same time, when judging the flooded area from the DSM image above, it has been explained that the size of the GSM data and water level data of each grid in the DSM image is judged, and after the conditions are met, the qualified The pixel value of the grid is changed to water level data, that is, the pixel value of each grid in the grid map of the flooded area in step S106b is the water level data.

Finally, the pixel value of each raster in the direct real flooded area raster image is subtracted from the pixel value of each raster in the flooded area raster image, and the obtained height difference is the flood inundation depth map.

In this embodiment, the grids to be subtracted are the grids corresponding to the two grid maps, that is, the grids corresponding to the same region in the two grid maps. At the same time, since the two raster images are subtracted (substantially the subtraction of the pixel values of the internal raster), the result is also a raster image, that is, the flood inundation depth map mentioned in step S106.

In this embodiment, the ArcMap software is also used to perform the subtraction of the two layers.

Through the above design, the final flood inundation depth map can be obtained, which can provide accurate data for the assessment of flood damage. However, the present invention not only retains the rapidity of passive analysis, but also has the accuracy of active analysis, and makes up for the deficiencies of current flood active analysis and provenance analysis.

Embodiment 2

As shown in FIG. 2 , this embodiment provides a specific implementation manner for establishing a DSM image map, which specifically includes the following steps:

S101a. Perform aerial triangulation calculation on the oblique image data to obtain control points in the area to be assessed.

S101b. Perform image intensive matching according to the control points to obtain point cloud data of the area to be evaluated.

S101c. Build a TIN three-dimensional grid according to the point cloud data, and generate a three-dimensional model of the blank texture of the area to be evaluated.

S101d. Perform texture mapping on the three-dimensional model to obtain a three-dimensional scene of the area to be evaluated.

S101e. Generate a DSM image of the area to be assessed according to the three-dimensional scene.

In this embodiment, the oblique image data of the area to be evaluated is obtained by drone aerial photography, specifically, a small drone of the DJI Phantom 4Pro model, and the aerial survey uses the DJI GS Pro software provided by DJI for route planning.

In this embodiment, a pentascope is used on the UAV platform to collect images of the area to be evaluated. The pentascope includes 4 azimuth tilt lenses and an orthophoto lens, which can obtain more complete and accurate information of ground objects. Shooting at a vertical ground angle obtains a set of images vertically downward, called positive films. The four sets of images obtained by shooting at a certain angle between the lens and the ground point to the southeast and northwest respectively, which are called oblique films.

In this embodiment, the oblique image data includes three kinds of data, namely oblique image original data, pos data included in the oblique image original data, and related parameters of the camera when shooting. The original data of the oblique image is the original image file data of the oblique image captured by the camera, and the pos data is the xyz position information contained in each photo.

After obtaining the above information, the above information can be used to perform aerial triangulation calculation. The aerial triangulation calculation is based on the coordinates of the pixel points measured on the image, and adopts a relatively strict mathematical model. Adjustment conditions, use the computer to solve the spatial coordinates of the ground control points required for the survey map, and finally obtain the control points in the evaluation area. The aerial triangulation calculation is the basic control point for the construction of the DSM image map, and then through steps S101b ~ S101e Get DSM image map.

After obtaining the control points of the area to be evaluated, dense image matching can be performed to construct the point cloud data of the area to be evaluated, and then the TIN 3D grid is constructed according to the point cloud data to obtain the 3D model of the blank texture of the area to be evaluated, and then the texture is performed. After mapping, the three-dimensional scene of the area to be evaluated can be obtained, and finally, the DSM image map can be obtained from which scene.

In this embodiment, image dense matching is an existing technology, which is currently mainly divided into two categories: gray-based matching and feature-based matching. In this embodiment, the SIFT algorithm is used for example to perform image matching. Intensive matching.

The SIFT algorithm extracts feature points and calculates feature vectors in different scale spaces, and finally obtains the same name point of the stereo pair. Robustness and strong image matching ability.

Using point cloud data to build TIN (Triangulated Irregular Network) 3D mesh and 3D model can also be implemented using existing algorithms, and finally the DSM image of the area to be assessed can be obtained.

In this embodiment, the generation of DSN image data can be directly obtained by using existing software, specifically: using ContextCapture software as the modeling software of this oblique image, and the specific steps are as follows:

Step 1: Import the tilt-impact data into the software;

Step 2: Adjust the camera properties;

Step 3: Use tools in the software to perform aerial triangulation calculations;

Step 4: Refactoring;

Step 5: Carry out the production of DSM image map.

Embodiment 3

As shown in FIG. 3 , this embodiment provides an apparatus for implementing the flood damage assessment method in Embodiment 1, including a DSM image generation module, a grid processing module, an interference elimination module, and a flooded water bitmap calculation module.

The DSM image generation module is used to acquire oblique image data and generate a DSM image of the area to be assessed.

The grid processing module is communicatively connected to the DSM image generation module, and is used for obtaining a flooded area grid map according to the DSM image map, and performing vector conversion on the flooded area grid map to obtain a flooded area. Vector illustration.

The interference elimination module is communicatively connected to the grid processing module, and is used for interference elimination of the vector map of the flooded area to obtain a real vector map of the flooded area.

The inundated water level map calculation module is communicatively connected to the interference elimination module, and is used for raster conversion of the vector map of the real inundated area to obtain a raster map of the real inundated area, and the grid of the real inundated area. The grid map is subtracted from the grid map of the flooded area to obtain a flood inundation depth map.

For the working process, working details, and technical effects of the evaluation device provided in this embodiment, reference may be made to Embodiment 1, and details are not repeated here.

Embodiment 4

As shown in FIG. 4 , this embodiment provides a hardware device for implementing the flood damage assessment method in Embodiment 1, including a memory and a processor connected in communication, wherein the memory is used to store a computer program, and the processor uses Executing the computer program implements the flood damage assessment method described in Embodiment 1.

For the working process, working details, and technical effects of the hardware device provided in this embodiment, reference may be made to Embodiment 1, and details are not described herein again.

Embodiment 5

This embodiment provides a computer storage medium including the flood damage assessment method in the first embodiment, wherein the computer storage medium stores a computer program, and when the computer program is executed by the processor, the first embodiment is implemented. Flood damage assessment method.

In this embodiment, the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices, or may be a mobile smart device (such as a smart phone, a PAD, or an ipad, etc.).

For the working process, working details, and technical effects of this embodiment, reference may be made to Embodiment 1, and details are not repeated here.

The multiple embodiments described above are only illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, Located in one place, or it can be distributed over multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment. Those of ordinary skill in the art can understand and implement it without creative effort.

From the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on this understanding, the above-mentioned technical solutions can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic Discs, optical discs, etc., including instructions for causing a computer device to perform the methods described in various embodiments or portions of embodiments.

To sum up, using the flood disaster assessment method, device, equipment and computer storage medium provided by the present invention has the following technical effects:

(1) The present invention first establishes a DSM image map of the area to be assessed, and directly obtains a grid map of the flooded area from the DSM image map, and converts the grid map of the flooded area to vector to obtain a vector map of the flooded area, This method is equivalent to the traditional passive analysis, which can quickly obtain the inundated area of the area to be assessed; at the same time, the present invention also eliminates the interference of the vector map of the flooded area, and only connects the vector map of the flooded area with the river. The proposed area is proposed as a vector map of the real inundated area. This step takes into account the connectivity between the inundated area and the flood spread, so the area that is not connected to the river can be excluded, which improves the accuracy of the analysis results. sex.

Through the above design, the evaluation method provided by the present invention not only retains the rapidity of passive analysis, but also has the accuracy of active analysis, and can quickly and accurately obtain the flood inundation range.

The present invention is not limited to the above-mentioned optional embodiments, and anyone can draw other various forms of products under the inspiration of the present invention, but no matter what changes are made in its shape or structure, all fall within the definition of the claims of the present invention. The technical solutions within the scope all fall within the protection scope of the present invention.

Claims (9)

1. a flood disaster assessment method, is characterized in that, comprises the following steps: S101. Obtain oblique image data of the area to be assessed, and use the oblique image data to establish a DSM image map of the area to be assessed; S102. According to the DSM image map, extract the grid elements belonging to the flooded area in the DSM image map to form a flooded area grid map; S103. Perform vector conversion on the raster map of the flooded area to obtain a vector diagram of the flooded area; S104. Eliminate interference for all areas in the vector map of the flooded area, extract the area connected to the river in the vector map of the flooded area, and form a vector map of the real flooded area; S105. Perform grid conversion on the vector map of the real flooded area to obtain a grid map of the real flooded area; S106. Subtract the grid map of the real flooded area from the grid map of the flooded area to obtain a flood inundation depth map. 2. a kind of flood damage assessment method according to claim 1, is characterized in that, the grid element of flooded area in described step S102 adopts following steps to obtain: S102a. Determine the water level data of the river in the area to be assessed; S102b. Obtain DSM data of each grid in the DSM image according to the DSM image; S102c. Compare the size of the DSM data and the waterline data of each grid in the DSM image, extract the grid corresponding to the DSM data smaller than the watermark data, and use the extracted grid as the grid element of the flooded area . 3. a kind of flood damage assessment method according to claim 1, is characterized in that, described step S104 specifically comprises the following steps: S104a. Identify flood flashpoints in the area to be assessed; S104b. Intersect the vector map of the flooded area with the flood burst point, extract the area that intersects the flood burst point in the vector map of the flooded area, and use the extracted area as the real flooded area area, And make up the vector map of the real flooded area. 4. a kind of flood damage assessment method according to claim 2, is characterized in that, described step S106 specifically comprises the following steps: S106a. According to the grid map of the real flooded area, obtain the pixel value of each grid in the grid map of the real flooded area, and use the pixel value of each grid as the flood value of each grid water level height; S106b. According to the grid map of the flooded area, obtain the pixel value of each grid in the grid map of the flooded area, and use the pixel value of each grid as the flood water level height of each grid ; S106c. Subtract the pixel value of each grid in the grid map of the real flooded area with the pixel value of each grid in the grid map of the flooded area to obtain the real flooded area The height difference between the grid map and the grid map of the flooded area, and the height difference is the flood inundation depth map. 5 . The flood damage assessment method according to claim 4 , wherein the pixel value of each grid in the grid map of the flooded area is the water level data. 6 . 6. a kind of flood damage assessment method according to claim 1, is characterized in that, in described step S101, adopts the following steps to establish the DSM image map of the area to be assessed: S101a. Perform aerial triangulation calculation on the oblique image data to obtain control points in the area to be assessed; S101b. Perform image intensive matching according to the control points to obtain point cloud data of the area to be evaluated; S101c. Construct a TIN three-dimensional grid according to the point cloud data, and generate a three-dimensional model of the blank texture of the area to be evaluated; S101d. Perform texture mapping on the three-dimensional model to obtain a three-dimensional scene of the area to be evaluated; S101e. Generate a DSM image of the area to be assessed according to the three-dimensional scene. 7. A flood disaster assessment device, characterized in that: it comprises a DSM image generation module, a grid processing module, an interference elimination module and a flooded water level map calculation module; The DSM image generation module is used to obtain oblique image data and generate a DSM image of the area to be assessed; The grid processing module is communicatively connected to the DSM image generation module, and is used for obtaining a flooded area grid map according to the DSM image map, and performing vector conversion on the flooded area grid map to obtain a flooded area. vector illustration; The interference elimination module is communicatively connected to the grid processing module, and is used for interference elimination of the vector map of the flooded area to obtain a real vector map of the flooded area; The inundated water level map calculation module is communicatively connected to the interference elimination module, and is used for raster conversion of the vector map of the real inundated area to obtain a raster map of the real inundated area, and the grid of the real inundated area. The grid map is subtracted from the grid map of the flooded area to obtain a flood inundation depth map. 8. A flood disaster assessment device, characterized in that it comprises a memory and a processor connected in communication, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to achieve the method according to claims 1 to 6 Any one of the flood damage assessment methods described. 9 . A computer storage medium, wherein a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the flood damage assessment method according to any one of claims 1 to 6 is implemented.

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