CN111260714B - Flood disaster recovery assessment method, device and equipment and computer storage medium - Google Patents

Flood disaster recovery assessment method, device and equipment and computer storage medium Download PDF

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CN111260714B
CN111260714B CN202010055630.4A CN202010055630A CN111260714B CN 111260714 B CN111260714 B CN 111260714B CN 202010055630 A CN202010055630 A CN 202010055630A CN 111260714 B CN111260714 B CN 111260714B
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grid
flooded area
area
map
flooded
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CN111260714A (en
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何朝阳
肖金武
巨能攀
许强
敖仪斌
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Chengdu Univeristy of Technology
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    • Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
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Abstract

The invention discloses a flood disaster evaluation method, a flood disaster evaluation device, flood disaster evaluation equipment and a computer storage medium, wherein a DSM image map of an area to be evaluated is firstly established, a grid map of a flooded area is directly obtained from the DSM image map, and vector conversion is carried out on the grid map of the flooded area to obtain a vector map of the flooded area; meanwhile, the invention also carries out interference elimination of the vector image of the flooded area, only the area which is communicated with the river in the vector image of the flooded area is proposed, and the proposed area is taken as the vector image of the actual flooded area. Through the design, the evaluation method provided by the invention not only maintains the rapidity of passive analysis, but also has the accuracy of active analysis, and can rapidly and accurately obtain the flood inundation range.

Description

Flood disaster recovery assessment method, device and equipment and computer storage medium
Technical Field
The invention relates to the technical field of flood disaster assessment, in particular to a flood disaster-stricken assessment method, a device, equipment and a computer storage medium.
Background
Flood disasters are one of 15 main natural disasters which are released by united nations and are focused worldwide, and have the characteristics of large influence range, high occurrence frequency, large loss and the like. For village towns in the river basin, if the collapse of the river levee occurs, huge threats are caused to the life and property safety of residents, and the economic development condition and the ecological environment of a disaster-stricken area are seriously influenced, so that the inundation analysis of the flood in the village basin has great significance to flood disaster assessment.
At present, the influence characteristics and disaster condition evaluation methods on flood disasters generally adopt two modes of active analysis and passive analysis.
The active analysis is that in a specified range, the source of flood burst (usually in a specified river area) is determined, 9 grid searches are performed through the thought of a seed spreading algorithm, the flood submerged area is simulated according to the thought of flood spreading, the connectivity of the flood submerged area is ensured by the method, the real situation of flood flooding is more met, but the 9 grid searches are adopted, so that the calculation amount of the whole analysis process is large, and the efficiency is low.
The passive analysis is to judge the flooded area by comparing the flood level with the elevation in a designated area without specifying the source of the flood burst, and the analysis method has high processing speed, but does not consider the connectivity of the flood burst, so the calculated flooded range is always larger than the actual flooded range, and the error is larger and the accuracy is not high. Therefore, how to quickly and accurately analyze the flooding range of the flood becomes a urgent problem to be solved.
Disclosure of Invention
In order to solve the problem that the existing flood disaster recovery assessment cannot simultaneously have analysis speed and accuracy, the invention aims to provide a flood disaster recovery assessment method, device, equipment and computer storage medium with the rapidity of passive analysis and the accuracy of active analysis.
The technical scheme adopted by the invention is as follows:
a flood disaster recovery assessment method comprises the following steps:
s101, acquiring oblique image data of an area to be evaluated, and establishing a DSM image of the area to be evaluated by utilizing the oblique image data;
s102, extracting grid elements belonging to a flooded area in the DSM image according to the DSM image to form a flooded area grid;
s103, carrying out vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area;
s104, performing interference elimination on all areas in the flooded area vector diagram, and extracting areas communicated with the river in the flooded area vector diagram to form a real flooded area vector diagram;
s105, carrying out grid conversion on the vector diagram of the real flooded area to obtain a grid diagram of the real flooded area;
s106, subtracting the actual flooded area grid map from the flooded area grid map to obtain a flood submerged depth map.
As a preferable aspect of the foregoing technical solution, the grid elements in the flooded area in step S102 are obtained by:
s102a, determining water line data of the river in the region to be evaluated;
s102b, obtaining DSM data of each grid in the DSM image according to the DSM image;
s102c, comparing the DSM data of each grid in the DSM image map with the size of the water line data, extracting the grid corresponding to the DSM data smaller than the water line data, and taking the extracted grid as a grid element of the flooded area.
As a preferable aspect of the foregoing disclosure, the step S104 specifically includes the following steps:
s104a, determining flood burst points of the region to be evaluated;
s104b, intersecting the flooded area vector diagram with the flood burst points, extracting an area intersecting with the flood burst points in the flooded area vector diagram, taking the extracted area as a real flooded area, and forming the real flooded area vector diagram.
As a preferable aspect of the foregoing technical solution, the step S106 specifically includes the following steps:
s106a, obtaining pixel values of each grid in the real flooded area grid graph according to the real flooded area grid graph, and taking the pixel values of each grid as the flood level height of each grid;
s106b, obtaining pixel values of each grid in the flooded area grid graph according to the flooded area grid graph, and taking the pixel values of each grid as the flood level height of each grid;
and S106c, subtracting the pixel value of each grid in the real flooded area grid map from the pixel value of each grid in the flooded area grid map to obtain the height difference between the real flooded area grid map and the flooded area grid map, wherein the height difference is the flood flooding depth map.
As the preferable choice of the technical scheme, the pixel value of each grid in the grid map of the flooded area is the water line data.
As a preferable mode of the above technical solution, in step S101, the following steps are adopted to create a DSM image map of the region to be evaluated:
s101a, performing aerial triangulation calculation on the inclined image data to obtain control points of the region to be evaluated;
s101b, performing image dense matching according to the control points to obtain point cloud data of the region to be evaluated;
s101c, constructing a TIN three-dimensional grid according to the point cloud data, and generating a three-dimensional model of blank textures of the region to be evaluated;
s101d, performing texture mapping on the three-dimensional model to obtain a three-dimensional scene of the region to be evaluated;
s101e, generating a DSM image map of the region to be evaluated according to the three-dimensional scene.
The invention also provides another technical scheme:
the flood disaster evaluation device comprises a DSM image generation module, a grid processing module, an interference elimination module and a flooded water map calculation module;
the DSM image generation module is used for acquiring the inclined image data and generating a DSM image map of the region to be evaluated;
the grid processing module is in communication connection with the DSM image generating module and is used for obtaining a grid image of a flooded area according to the DSM image and carrying out vector conversion on the grid image of the flooded area to obtain a vector image of the flooded area;
the interference elimination module is in communication connection with the grid processing module and is used for eliminating interference of the flooded area vector diagram to obtain a true flooded area vector diagram;
the flooded water map calculation module is in communication connection with the interference elimination module and is used for carrying out grid conversion on the real flooded area vector map to obtain a real flooded area grid map, and subtracting the real flooded area grid map from the flooded area grid map to obtain a flood submerged depth map.
The invention also provides another technical scheme:
the flood disaster assessment device comprises a memory and a processor which are in communication connection, wherein the memory is used for storing a computer program, and the processor is used for executing the computer program to realize the flood disaster assessment method.
The invention also provides another technical scheme:
a computer storage medium having a computer program stored thereon, which when executed by a processor, implements the flood damage assessment method described above.
The beneficial effects of the invention are as follows:
(1) The invention provides a flood disaster evaluation method, a flood disaster evaluation device, flood disaster evaluation equipment and a computer storage medium, firstly, a DSM image map of an area to be evaluated is established, a grid map of the area to be evaluated can be directly obtained from the DSM image map, vector conversion is carried out on the grid map of the area to be flooded, and a vector map of the area to be flooded can be obtained; meanwhile, the invention also carries out interference elimination of the vector image of the flooded area, only the area which is communicated with the river in the vector image of the flooded area is proposed, and the proposed area is taken as the vector image of the actual flooded area.
Through the design, the evaluation method provided by the invention not only maintains the rapidity of passive analysis, but also has the accuracy of active analysis, and can rapidly and accurately obtain the flood inundation range.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of steps of a flood disaster recovery assessment method provided by the invention.
Fig. 2 is a flow chart of the DSM image creation according to the present invention.
Fig. 3 is a schematic diagram of the flood disaster assessment device provided by the invention.
Fig. 4 is a schematic diagram of flood disaster recovery assessment equipment provided by the invention.
Detailed Description
The invention is further illustrated below in connection with specific examples. It should be noted that the description of these examples is for aiding in understanding the present invention, but is not intended to limit the present invention.
The term "and/or" is merely an association relationship describing an associated object, and means that three relationships may exist, for example, a and/or B may mean: the terms "/and" herein describe another associative object relationship, indicating that there may be two relationships, e.g., a/and B, may indicate that: the character "/" herein generally indicates that the associated object is an "or" relationship.
Example 1
As shown in fig. 1-2, the flood disaster recovery assessment method provided by the embodiment includes the following steps:
s101, acquiring oblique image data of the region to be evaluated, and establishing a DSM image map of the region to be evaluated by using the oblique image data.
Step S101 is to obtain a DSM image of the region to be evaluated, correct the DSM (DigitalSurface Model, digital earth model) image by pixel projection difference, and then mosaic according to the influence, and cut out the generated data image according to the scope of the image, which can display the ground heights of earth surface buildings, bridges, trees, etc.
In this embodiment, oblique image data of the region to be evaluated is used as a data base to obtain a DSM image map of the region to be evaluated. The specific construction method will be described in detail below.
Meanwhile, in this embodiment, in order to analyze the flooding range by using the DSM image, the DSM generates according to the blocks, i.e. the tiles are embedded in the DSM image. In this embodiment, the tile is inlaid by using the grid inlaying tool provided in the AcrMap software, and the inlaying operator selects the LAST (the output pixel value of the overlapped area is the value in the LAST grid data set inlaid to the position), so as to finally obtain the high-precision DSM image, and meanwhile, the analysis of the flooded range can also be directly performed according to the pixel value of the grid in the DSM image, specifically, as shown in step S102 and the specific operation steps contained in the same.
In this embodiment, acrMap software is an existing software, which is a user desktop component, has powerful functions of map making, spatial analysis, spatial database building and the like, can be used for application programs with functions of data input, editing, query, analysis and the like, and belongs to the existing operation technology.
S102, extracting grid elements belonging to the flooded area in the DSM image graph according to the DSM image graph to form a flooded area grid graph.
Step S102, flood disaster analysis can be performed through the DSM image graph, and the flooded areas in the areas to be evaluated can be obtained.
Since the DSM image is generated according to the blocks, i.e. the tiles are embedded, the obtaining of the flooded area can be directly performed by the grids (i.e. the grid elements) in the DSM image, and then the grid image of the flooded area is obtained, which comprises the following specific steps:
s102a, determining water level line data of the river in the region to be evaluated.
S102b, obtaining DSM data of each grid in the DSM image according to the DSM image.
S102c, comparing the DSM data of each grid in the DSM image map with the size of the water line data, extracting the grid corresponding to the DSM data smaller than the water line data, and taking the extracted grid as a grid element of the flooded area.
In this embodiment, the pixel value of each grid in the DSM image is directly compared with the size of the water line data, so that it can be determined that the grid in the DSM image is located below the water line, i.e., is submerged by flood.
In this embodiment, since the original data is a DSM image, and is generated by blocks, the pixel value of each grid in the DSM image is the DSM data of the grid. Therefore, the DSM data and the water line data of each grid can be directly compared, the flooded grids are selected, and the areas represented by the grids are areas submerged by floods.
In this embodiment, the water line data of the region to be evaluated may be based on the official water level data of the hydrologic bureau of the region to be evaluated.
In this embodiment, the grid calculation tool provided by map algebra in ArcMap software is also used to perform the comparison calculation of GSM data and hydrological data of each grid in the DSM image map, which also belongs to the operation using the existing software.
Meanwhile, the python sentence can be written by the user for execution, and the operation is performed through the CON condition analysis tool, wherein the specific sentence expression is as follows:
con (in_ras, { false_ras }) fills in conditional expressions at in_ras, and when the conditions are satisfied, the part of true_ras is executed, otherwise the part of false_ras is executed. The sentences we fill in should be: con ("rastercalc 2" <= 490.5,1), wherein rastercalc2 is DSM data of each grid in the DSM image, and "<=490.5" is water level screening condition, i.e. less than or equal to 490.5, and the water level screening condition is also the water level line data. "1" indicates that the condition is satisfied, the DSM data is assigned as the water line data.
Through the steps S102 a-S102 c, the flooded area in the DSM image map can be obtained, and the grid map of the flooded area is obtained, so that the subsequent analysis is facilitated.
S103, carrying out vector conversion on the flooded area raster image to obtain a flooded area vector image.
S104, performing interference elimination on all areas in the flooded area vector diagram, and extracting areas communicated with the river in the flooded area vector diagram to form a real flooded area vector diagram.
Step S103 and step S104 are error analysis and elimination, and because we compare the size relationship between the DSM data of each grid of the DSM and the water line data to extract the grids of the flooded area, so as to obtain a grid map of the flooded area, the obtained flooded area cannot determine whether the extracted flooded area is connected to the river, i.e. whether the extracted flooded area satisfies the spreading of the flood, the method is substantially as follows: if the river in the area to be evaluated is flood, there is a channel spreading to each flooded area, that is, a connectivity relationship exists between the flood area and the river, if the extracted flooded area does not have a connectivity relationship with the river, it is indicated that the area is an interference area and does not belong to the flooded area. And the judgment of connectivity of flood spreading can be performed through the step S103 and the step S104, so that the accuracy of the disaster-stricken area obtained by analysis is improved.
In this embodiment, step S103 is to convert the grid map of the flooded area into a stereoscopic disaster vector map, so as to perform the subsequent processing of flood spreading connectivity.
In this embodiment, the error analysis of the vector diagram of the flooded area specifically includes the following steps:
s104a. determining the flood burst points of the region to be assessed.
S104b, intersecting the flooded area vector diagram with the flood burst points, extracting an area intersecting with the flood burst points in the flooded area vector diagram, taking the extracted area as a real flooded area, and forming the real flooded area vector diagram.
Steps S104a to S104b are to determine whether the flood burst points are connected to the area in the vector diagram of the flooded area by determining whether the flood burst points intersect the surface of the flooded area.
In this embodiment, the flood burst point is selected in the upstream area of the river, and artificial selection can be performed according to the field.
Meanwhile, step S104b also adopts ArcMap software to perform operation, that is, the intersection judgment of the flood burst point and each region in the flooded area vector diagram is performed through a selection tool provided in the ArcMap software, and finally, the intersected region can be extracted to obtain the true flooded area vector diagram.
Through the steps, the judgment of flood spreading connectivity can be realized, the purpose of active analysis is realized, the areas which do not have connectivity relation with rivers are eliminated, and the accuracy of analysis results is greatly improved.
After the error elimination, step S105 and step S106 may be performed to obtain a final flood submerged depth map, which specifically includes the following steps:
s105, carrying out grid conversion on the vector diagram of the real flooded area to obtain a grid diagram of the real flooded area.
S106, subtracting the actual flooded area grid map from the flooded area grid map to obtain a flood submerged depth map.
In this embodiment, the raster pattern is adopted for analysis, so after error elimination, the actual flooded area raster pattern needs to be converted into the raster pattern again after the actual flooded area raster pattern is obtained, so that the subsequent data analysis is convenient, and in the same way, the conversion between the vector pattern and the raster pattern is realized in step S105, and in this example, the conversion is realized by using the existing software ArcMap.
After converting the actual grid map of the flooded area into the grid map by Arcmap software, the following steps are adopted to process so as to obtain a flood submerged depth map, specifically:
s106a, obtaining pixel values of each grid in the real flooded area grid graph according to the real flooded area grid graph, and taking the pixel values of each grid as the flood level height of each grid.
S106b, obtaining pixel values of each grid in the flooded area grid graph according to the flooded area grid graph, and taking the pixel values of each grid as the flood level height of each grid.
And S106c, subtracting the pixel value of each grid in the real flooded area grid map from the pixel value of each grid in the flooded area grid map to obtain the height difference between the real flooded area grid map and the flooded area grid map, wherein the height difference is the flood flooding depth map.
Since the actual flooded area vector diagram is the actual flooded area, the pixel value of each grid in the grid diagram is converted into the actual water level value of the corresponding flooded area of the grid.
Meanwhile, when the flooded area is determined from the DSM image, it has been described that the GSM data and the water line data of each grid in the DSM image are determined, and after the condition is satisfied, the pixel value of the grid that meets the condition is changed to the water line data, that is, the pixel value of each grid in the grid image of the flooded area in step S106b is the water line data.
And finally, subtracting the pixel value of each grid in the grid map of the directly real flooded area from the pixel value of each grid in the grid map of the flooded area, wherein the obtained height difference is the flood flooding depth map.
In this embodiment, the subtracted grids are corresponding grids in the two raster images, that is, the grids corresponding to the same region in the two raster images are indicated. Meanwhile, since two raster images are subtracted (substantially, the internal raster pixel values are subtracted), one raster image is also obtained, that is, the flood submerged depth image mentioned in step S106.
In this embodiment, the ArcMap software is also used to perform subtraction of the two layers.
Through the design, a final flood submerging depth map can be obtained, and accurate data are provided for flood disaster assessment. The invention not only maintains the rapidity of passive analysis, but also has the accuracy of active analysis, and makes up the defects of flood active analysis and object source analysis at present.
Example two
As shown in fig. 2, the present embodiment provides a specific implementation manner for specifically creating a DSM image, which specifically includes the following steps:
s101a, performing aerial triangulation calculation on the inclined image data to obtain control points of the region to be evaluated.
S101b, performing image dense matching according to the control points to obtain point cloud data of the region to be evaluated.
S101c, constructing a TIN three-dimensional grid according to the point cloud data, and generating a three-dimensional model of the blank texture of the region to be evaluated.
S101d, performing texture mapping on the three-dimensional model to obtain a three-dimensional scene of the region to be evaluated.
S101e, generating a DSM image map of the region to be evaluated according to the three-dimensional scene.
In this embodiment, the oblique image data of the region to be evaluated is obtained by unmanned aerial vehicle aerial photography, specifically, a small unmanned aerial vehicle of the type 4Pro of the Dajiang eidolon is used, and the route planning is performed by DJI GS Pro software provided by the Dajiang company.
In this embodiment, the image acquisition of the region to be evaluated is performed on the unmanned aerial vehicle platform by using a five-component mirror, and the five-component mirror includes 4 azimuth inclined lenses and an ortholens, so that more complete and accurate information of the ground object can be obtained. The images shot at the vertical ground angle are a group of images which are vertically downward, called positive films, and the four groups of images shot at a certain included angle between the lens orientation and the ground are respectively pointed to the southeast, the northwest and the northwest, called oblique films.
In this embodiment, the oblique image data includes three data, which are the oblique image raw data, pos data included in the oblique image raw data, and related parameters of the camera during shooting. The original data of the oblique image is the original image file data of the oblique image shot by the image head, and the pos data is xyz position information contained in each photo.
After the information is obtained, the information can be used for carrying out the aerial triangle calculation, the aerial triangle calculation is based on the coordinates of the measured pixel points on the image, a tighter mathematical model is adopted, a small number of ground control points are used as adjustment conditions according to the least square method principle, the space coordinates of the ground control points required by the image measurement are calculated by a computer, finally the control points of the evaluation area can be obtained, the aerial triangle calculation is used as the control points of the DSM image, the basis of which is constructed, and then the DSM image is obtained through steps S101 b-S101 e.
After the control points of the region to be evaluated are obtained, dense image matching can be performed, point cloud data of the region to be evaluated are constructed, then a TIN three-dimensional grid is constructed according to the point cloud data, a three-dimensional model of blank textures of the region to be evaluated is obtained, texture mapping is performed, a three-dimensional scene of the region to be evaluated can be obtained, and finally a DSM image map can be obtained on which scene of the pattern.
In this embodiment, dense matching of images is a prior art, and is currently divided into two main categories, namely: gray-scale based matching and feature-based matching, but in this embodiment, SIFT algorithm is used for image dense matching.
The SIFT algorithm extracts feature points in different scale spaces and calculates feature vectors, and finally obtains homonymous points of a stereopair, so that the SIFT algorithm has invariance of scale, rotation and translation, has certain robustness to illumination change, affine transformation and three-dimensional projection transformation, and has strong image matching capability.
And the three-dimensional grid of the TIN (Triangulated Irregular Network, irregular triangular net) is constructed by using the point cloud data, and the three-dimensional model can be realized by using the existing algorithm, so that the DSM image map of the region to be evaluated can be obtained finally.
In this embodiment, the generation of DSN image data may be directly obtained using existing software, specifically: the method uses ContextCapture software as modeling software of the inclined image, and specifically comprises the following steps:
the first step: importing software for importing tilt influence data;
and a second step of: adjusting camera attribute;
and a third step of: performing aerial triangulation calculation in software by using a tool;
fourth step: reconstructing;
fifth step: the production of DSM image is performed.
Example III
As shown in fig. 3, the present embodiment provides an apparatus for implementing the flood disaster assessment method in the first embodiment, which includes a DSM image generating module, a grid processing module, an interference rejection module, and a flooding water map calculating module.
The DSM image generation module is used for acquiring the inclined image data and generating a DSM image map of the region to be evaluated.
The grid processing module is in communication connection with the DSM image generating module and is used for obtaining a grid image of a flooded area according to the DSM image and carrying out vector conversion on the grid image of the flooded area to obtain a vector image of the flooded area.
The interference elimination module is in communication connection with the grid processing module and is used for eliminating interference of the flooded area vector diagram to obtain a true flooded area vector diagram.
The flooded water map calculation module is in communication connection with the interference elimination module and is used for carrying out grid conversion on the real flooded area vector map to obtain a real flooded area grid map, and subtracting the real flooded area grid map from the flooded area grid map to obtain a flood submerged depth map.
The working process, working details and technical effects of the evaluation device provided in this embodiment can be referred to in the first embodiment, and will not be repeated herein.
Example IV
As shown in fig. 4, the present embodiment provides a hardware device for implementing the flood disaster assessment method in the first embodiment, which includes a memory and a processor that are communicatively connected, where the memory is configured to store a computer program, and the processor is configured to execute the computer program to implement the flood disaster assessment method described in the first embodiment.
The working process, working details and technical effects of the hardware device provided in this embodiment may refer to the first embodiment, and are not described herein again.
Example five
The present embodiment provides a computer storage medium including the flood disaster assessment method in the first embodiment, where the computer storage medium stores a computer program, and when the computer program is executed by a processor, the flood disaster assessment method in the first embodiment is implemented.
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 ipad).
The working process, working details and technical effects of the present embodiment can be referred to as embodiment one, and will not be described herein.
The various embodiments described above are illustrative only, and the elements described as separate elements may or may not be physically separate, and elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device to perform the method described in the embodiments or some parts of the embodiments.
In summary, the flood disaster recovery assessment method, the flood disaster recovery assessment device, the flood disaster recovery assessment equipment and the computer storage medium provided by the invention have the following technical effects:
(1) Firstly, building a DSM image map of a region to be evaluated, directly obtaining a grid map of the flooded region from the DSM image map, and carrying out vector conversion on the grid map of the flooded region to obtain a vector map of the flooded region, wherein the mode is equivalent to the traditional passive analysis, and can rapidly obtain the flooded range of the region to be evaluated; meanwhile, the invention also carries out interference elimination of the vector image of the flooded area, only the area which is communicated with the river in the vector image of the flooded area is proposed, and the proposed area is taken as the vector image of the actual flooded area.
Through the design, the evaluation method provided by the invention not only maintains the rapidity of passive analysis, but also has the accuracy of active analysis, and can rapidly and accurately obtain the flood inundation range.
The invention is not limited to the above-described alternative embodiments, and any person who may derive other various forms of products in the light of the present invention, however, any changes in shape or structure thereof, all falling within the technical solutions defined in the scope of the claims of the present invention, fall within the scope of protection of the present invention.

Claims (7)

1. The flood disaster recovery assessment method is characterized by comprising the following steps of:
s101, acquiring oblique image data of an area to be evaluated, and establishing a DSM image of the area to be evaluated by utilizing the oblique image data;
s102, extracting grid elements belonging to a flooded area in the DSM image according to the DSM image to form a flooded area grid;
s103, carrying out vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area;
s104, performing interference elimination on all areas in the flooded area vector diagram, and extracting areas communicated with the river in the flooded area vector diagram to form a real flooded area vector diagram;
s105, carrying out grid conversion on the vector diagram of the real flooded area to obtain a grid diagram of the real flooded area;
s106, subtracting the actual flooded area grid map from the flooded area grid map to obtain a flood submerged depth map;
the grid elements of the flooded area in the step S102 are obtained by the following steps:
s102a, determining water line data of the river in the region to be evaluated;
s102b, obtaining DSM data of each grid in the DSM image according to the DSM image;
s102c, comparing the DSM data of each grid in the DSM image map with the size of the water line data, extracting the grid corresponding to the DSM data smaller than the water line data, and taking the extracted grid as a grid element of a flooded area;
the step S104 specifically includes the following steps:
s104a, determining flood burst points of the region to be evaluated;
s104b, intersecting the flooded area vector diagram with the flood burst points, extracting an area intersecting with the flood burst points in the flooded area vector diagram, taking the extracted area as a real flooded area, and forming the real flooded area vector diagram.
2. The flood disaster recovery assessment method according to claim 1, wherein the step S106 specifically comprises the steps of:
s106a, obtaining pixel values of each grid in the real flooded area grid graph according to the real flooded area grid graph, and taking the pixel values of each grid as the flood level height of each grid;
s106b, obtaining pixel values of each grid in the flooded area grid graph according to the flooded area grid graph, and taking the pixel values of each grid as the flood level height of each grid;
and S106c, subtracting the pixel value of each grid in the real flooded area grid map from the pixel value of each grid in the flooded area grid map to obtain the height difference between the real flooded area grid map and the flooded area grid map, wherein the height difference is the flood flooding depth map.
3. The flood disaster recovery assessment method according to claim 2, wherein: and the pixel value of each grid in the grid map of the flooded area is the water line data.
4. The flood damage assessment method according to claim 1, wherein the step S101 is to build a DSM image of the area to be assessed by:
s101a, performing aerial triangulation calculation on the inclined image data to obtain control points of the region to be evaluated;
s101b, performing image dense matching according to the control points to obtain point cloud data of the region to be evaluated;
s101c, constructing a TIN three-dimensional grid according to the point cloud data, and generating a three-dimensional model of blank textures of the region to be evaluated;
s101d, performing texture mapping on the three-dimensional model to obtain a three-dimensional scene of the region to be evaluated;
s101e, generating a DSM image map of the region to be evaluated according to the three-dimensional scene.
5. The flood disaster-stricken assessment device is characterized in that: the system 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 for acquiring the inclined image data and generating a DSM image map of the region to be evaluated;
the grid processing module is in communication connection with the DSM image generating module and is used for extracting grid elements belonging to a flooded area in the DSM image according to the DSM image to form a flooded area grid, and carrying out vector conversion on the flooded area grid to obtain a flooded area vector diagram;
the interference elimination module is in communication connection with the grid processing module and is used for eliminating interference of the flooded area vector diagram to obtain a true flooded area vector diagram;
the flooded water map calculation module is in communication connection with the interference elimination module and is used for carrying out grid conversion on the real flooded area vector map to obtain a real flooded area grid map, and subtracting the real flooded area grid map from the flooded area grid map to obtain a flood submerged depth map;
extracting grid elements belonging to a flooded area in the DSM image according to the DSM image, and obtaining the grid elements by adopting the following steps:
s102a, determining water line data of the river in the region to be evaluated;
s102b, obtaining DSM data of each grid in the DSM image according to the DSM image;
s102c, comparing the DSM data of each grid in the DSM image map with the size of the water line data, extracting the grid corresponding to the DSM data smaller than the water line data, and taking the extracted grid as a grid element of a flooded area;
performing interference elimination on the flooded area vector diagram to obtain a true flooded area vector diagram, wherein the method comprises the following steps:
s104a, determining flood burst points of the region to be evaluated;
s104b, intersecting the flooded area vector diagram with the flood burst points, extracting an area intersecting with the flood burst points in the flooded area vector diagram, taking the extracted area as a real flooded area, and forming the real flooded area vector diagram.
6. Flood disaster recovery assessment equipment, characterized in that: comprising a memory in communication with a processor, wherein the memory is configured to store a computer program, and wherein the processor is configured to execute the computer program to implement the flood disaster assessment method according to any one of claims 1 to 4.
7. A computer storage medium, characterized by: the computer storage medium stores a computer program which, when executed by a processor, implements the flood disaster recovery assessment method according to any one of claims 1 to 4.
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