CN111260714A - Flood disaster assessment method, device, equipment and computer storage medium - Google Patents
Flood disaster assessment method, device, equipment and computer storage medium Download PDFInfo
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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
Technical Field
The invention relates to the technical field of flood disaster assessment, in particular to a flood disaster assessment method, a flood disaster assessment device, flood disaster assessment equipment and a computer storage medium.
Background
Flood disasters, one of the 15 major natural disasters released by united nations and focused on worldwide, have the characteristics of large influence range, high occurrence frequency, large loss and the like. For village and towns in the drainage basin, if the river bank collapses, the safety of lives and properties of residents is greatly threatened, and the economic development condition and the ecological environment of the disaster area are seriously influenced, so the flood inundation analysis of the drainage basin has important significance for flood disaster assessment.
At present, two modes of active analysis and passive analysis are generally adopted for the influence characteristics of flood disasters and disaster situation evaluation methods.
The active analysis is that in a specified range, the source of flood burst (usually in a specified river area) is determined, 9-grid search is carried out through the thought of a seed spreading algorithm, and the flood flooding area is simulated according to the thought of flood spreading, so that the connectivity of the flood flooding area is ensured, the actual situation of flood flooding is better met, but 9-grid search is adopted, and the whole analysis process is large in calculated amount and low in efficiency.
The passive analysis is that in a designated area, the source of flood burst is not specified, and the flooded area is judged only by comparing the height of the flood level and the height. Therefore, how to rapidly and accurately analyze the flooding range becomes a problem to be solved urgently.
Disclosure of Invention
In order to solve the problem that the existing flood disaster tolerance assessment cannot simultaneously have both analysis speed and accuracy, the invention aims to provide a flood disaster tolerance assessment method, a flood disaster tolerance assessment device, flood disaster tolerance assessment equipment and a computer storage medium, wherein the flood disaster tolerance assessment method, the flood disaster tolerance assessment device, the flood disaster tolerance assessment equipment and the computer storage medium have both rapidity of passive analysis and active analysis accuracy.
The technical scheme adopted by the invention is as follows:
a flood disaster assessment method comprises the following steps:
s101, acquiring inclined image data of a to-be-evaluated area, and establishing a DSM image map of the to-be-evaluated area by using the inclined image data;
s102, extracting grid elements belonging to a flooded area in the DSM image map according to the DSM image map to form a grid map of the flooded area;
s103, performing vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area;
s104, eliminating interference on all areas in the vector diagram of the flooded area, extracting areas communicated with rivers in the vector diagram of the flooded area, and forming a real vector diagram of the flooded area;
s105, performing grid conversion on the real flooded area vector diagram to obtain a grid diagram of the real flooded area;
and S106, subtracting the grid map of the real flooded area from the grid map of the flooded area to obtain a flood flooding depth map.
Preferably, in the step S102, the grid elements of the flooded area are obtained by:
s102a, determining water level line data of a river in an area to be evaluated;
s102b, obtaining DSM data of each grid in the DSM image map according to the DSM image map;
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.
Preferably, the step S104 specifically includes the following steps:
s104a, determining flood bursting points of an area to be evaluated;
and S104b, intersecting the vector diagram of the flooded area with the flood burst points, extracting an area of the vector diagram of the flooded area, which is intersected with the flood burst points, taking the extracted area as an actual flooded area, and forming the vector diagram of the actual flooded area.
Preferably, the step S106 specifically includes the following steps:
s106a, obtaining a pixel value of each grid in the grid map of the real flooded area according to the grid map of the real flooded area, and taking the pixel value of each grid as the flood water level height of each grid;
s106b, obtaining a pixel value of each grid in the grid map of the flooded area according to the grid map of the flooded area, and taking the pixel value of each grid as the flood water level height of each grid;
and S106c, subtracting the pixel value of each grid in the grid map of the real flooded area from the pixel value of each grid in the grid map of the flooded area to obtain the height difference between the grid map of the real flooded area and the grid map of the flooded area, wherein the height difference is the flood submerging depth map.
Preferably, in the above technical solution, the pixel value of each grid in the grid map of the flooded area is the water line data.
Preferably, in the step S101, the DSM image map of the area to be evaluated is established by adopting the following steps:
s101a, performing aerial triangulation calculation on the oblique image data to obtain a control point of an area to be evaluated;
s101b, carrying out image dense matching according to the control points to obtain point cloud data of the area 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 area to be evaluated;
s101d, performing texture mapping on the three-dimensional model to obtain a three-dimensional scene of the area to be evaluated;
and S101e, generating a DSM image map of the area to be evaluated according to the three-dimensional scene.
The invention also provides another technical scheme:
a flood disaster assessment device comprises a DSM image generation module, a grid processing module, an interference elimination module and a flooded bitmap calculation module;
the DSM image generation module is used for acquiring inclined image data and generating a DSM image map of a 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 map of a flooded area according to the DSM image map and performing vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area;
the interference elimination module is in communication connection with the grid processing module and is used for eliminating interference on the vector diagram of the flooded area to obtain a real vector diagram of the flooded area;
the flooded bitmap calculation module is in communication connection with the interference elimination module and is used for performing grid conversion on the real flooded area vector diagram to obtain a real flooded area grid diagram, and subtracting the real flooded area grid diagram from the flooded area grid diagram to obtain a flood flooding depth diagram.
The invention also provides another technical scheme:
a flood disaster tolerance assessment device comprises a storage and a processor which are connected in a communication mode, wherein the storage is used for storing a computer program, and the processor is used for executing the computer program to realize the flood disaster tolerance assessment method.
The invention also provides another technical scheme:
a computer storage medium having a computer program stored thereon, the computer program, when executed by a processor, implementing the flood disaster assessment method described above.
The invention has the beneficial effects that:
(1) the invention provides 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 a region to be assessed, directly obtaining a grid map of the flooded region from the DSM image, and carrying out vector conversion on the grid map of the flooded region to obtain a vector map of the flooded region, wherein the method is equivalent to the traditional passive analysis and can quickly obtain a flooded range of the region 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.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of steps of a flood disaster assessment method provided by the present invention.
Fig. 2 is a DSM image map creation flow chart provided by the present invention.
Fig. 3 is a schematic diagram of a flood disaster assessment device provided by the present invention.
Fig. 4 is a schematic diagram of a flood disaster evaluation device provided by the present invention.
Detailed Description
The invention will be further illustrated with reference to specific examples. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto.
The term "and/or" herein is merely an association relationship describing an associated object, and means that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, B exists alone, and A and B exist at the same time, and the term "/and" is used herein to describe another association object relationship, which means that two relationships may exist, for example, A/and B, may mean: a alone, and both a and B alone, and further, the character "/" in this document generally means that the former and latter associated objects are in an "or" relationship.
Example one
As shown in fig. 1 to 2, the flood disaster assessment method provided in this embodiment includes the following steps:
s101, obtaining inclined image data of the area to be evaluated, and establishing a DSM image map of the area to be evaluated by using the inclined image data.
Step S101 is to obtain a DSM image of the area to be evaluated, where the DSM image is corrected by pixel projection difference one by one, and then embedded according to the influence, and the generated data map is cut according to the map width range, which can display the ground height of surface buildings, bridges, trees, and the like.
In this embodiment, the inclination image data of the area to be evaluated is used as a data base to obtain a DSM image map of the area to be evaluated. The specific establishment method will be described in detail below.
Meanwhile, in the embodiment, in order to analyze the flooding flooded range by using the DSM image, the DSM is generated according to the block, that is, the DSM image is subjected to mosaic of tiles. In this embodiment, a grid mosaic tool provided in AcrMap software is used to mosaic tiles, a mosaic operator selects LAST (the output pixel value of the overlay area is the value in the LAST grid data set to be mosaic to the position), and finally a high-precision DSM image map can be obtained, and simultaneously, analysis of the flooded range can be directly performed according to the pixel values of the grids in the DSM image map, specifically, step S102 and the specific operation steps included therein.
In this embodiment, the AcrMap software is an existing software, which is a user desktop component, has powerful functions of mapping, spatial analysis, spatial data library construction, and the like, and can be used as an application program with functions of data input, editing, querying, analysis, and the like.
And S102, extracting the grid elements belonging to the flooded area in the DSM image map according to the DSM image map to form a grid map of the flooded area.
Step S102, flood and disaster tolerance analysis can be carried out through the DSM image map, and the flooded area in the area to be evaluated is obtained.
As described above, the DSM image is generated according to the blocks, that is, tiles are embedded, so that the flooded area can be directly obtained through the grids (i.e., grid elements) in the DSM image, and then the grid map of the flooded area is obtained, which includes the following specific steps:
s102a, determining water level line data of a river in an area to be evaluated.
S102b, obtaining DSM data of each grid in the DSM image map according to the DSM image map.
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, by directly comparing the pixel value of each grid in the DSM image map with the size of the water line data, it can be determined that the grid in the DSM image map is located below the water line, i.e. it indicates flooding by flood.
In this embodiment, since the adopted original data is a DSM image map and is generated by blocks, the pixel value of each grid in the DSM image map is the DSM data of the grid. Therefore, the DSM data of each grid can be directly compared with the size of the water line data to select the flooded grid, and the areas represented by these grids are the areas flooded by the flood.
In this embodiment, the water level data of the area to be evaluated may be based on the official water level data of the hydrological office of the area to be evaluated.
In the embodiment, the grid calculation tool provided by map algebra in the ArcMap software is also adopted to perform the comparison calculation of the GSM data and the hydrological data of each grid in the DSM image map, which also belongs to the operation using the existing software.
Meanwhile, a python statement can be written by the user for execution, and the operation is performed through a CON condition analysis tool, wherein the specific statement expression is as follows:
con (in _ raster, true _ raster, { false _ raster }), fill in the conditional expression at in _ raster, will carry out the part of true _ raster when satisfying the condition, otherwise carry out the part of false _ raster. The statements we fill in should be: con ("rastercalc2" < ═ 490.5,1), rastercalc2 is DSM data for each grid in the DSM image map, and "< ═ 490.5" is a water level screening condition, i.e., 490.5 or less, for extraction, of course, the water level screening condition is also the above-mentioned water level line data. A "1" indicates that the condition is satisfied, and the DSM data is assigned to the waterline data.
Through the steps S102 a-S102 c, the areas submerged by the flood in the DSM image map can be obtained, and the grid map of the flooded area can be obtained, so that the subsequent analysis can be conveniently carried out.
And S103, carrying out vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area.
And S104, eliminating interference on all areas in the vector diagram of the flooded area, extracting areas communicated with rivers in the vector diagram of the flooded area, and forming a real vector diagram of the flooded area.
Step S103 and step S104 are to perform error analysis and elimination, since we extract the grids of the flooded area by comparing the magnitude relationship between the DSM data of each grid of the DSM and the water line data to obtain the grid map of the flooded area, however, the obtained flooded area cannot judge whether the flooded area is connected to the river, that is, whether all the extracted flooded areas satisfy the spreading of flood, which is substantially: when flood disaster occurs in the river in the area to be evaluated, there will be paths that spread to each flooded area, that is, there must be a connectivity relationship with the river, for example, if there is no connectivity relationship with the river in the flooded area extracted above, it is stated that this area is an interference area and does not belong to the flooded area. The connectivity of flood spreading can be judged through the step S103 and the step S104, and the accuracy of the disaster area obtained through analysis is improved.
In this embodiment, step S103 is to convert the grid map of the flooded area into a three-dimensional disaster vector map, so as to perform subsequent processing of flood spreading connectivity.
In this embodiment, the following steps are specifically adopted for performing error analysis on the vector diagram of the flooded area:
s104a, determining flood bursting points of the area to be evaluated.
And S104b, intersecting the vector diagram of the flooded area with the flood burst points, extracting an area of the vector diagram of the flooded area, which is intersected with the flood burst points, taking the extracted area as an actual flooded area, and forming the vector diagram of the actual flooded area.
Steps S104 a-S104 b determine whether the flood bursts intersect the surface of the flooded area, so as to determine whether the flood bursts are connected to the area in the vector map of the flooded area.
In this embodiment, the flood burst point is selected in the upstream area of the river, and the artificial selection is possible depending on the actual area.
Meanwhile, step S104b also uses ArcMap software to perform operation, that is, the intersection judgment between the flood burst point and each region in the vector diagram of the flooded area is performed through the selection tool provided in the ArcMap software, and finally, the intersected regions can be extracted to obtain the vector diagram of the real flooded area.
Through the steps, the judgment of flood spreading connectivity can be realized, the purpose of active analysis is realized, the regions which do not have connectivity relation with rivers are eliminated, and the accuracy of the analysis result is greatly improved.
After the error is eliminated, step S105 and step S106 can be performed to obtain a final flood submerging depth map, which includes the following specific steps:
and S105, performing grid conversion on the real flooded area vector diagram to obtain a grid diagram of the real flooded area.
And S106, subtracting the grid map of the real flooded area from the grid map of the flooded area to obtain a flood flooding depth map.
Since the raster image is adopted for analysis in this embodiment, after error elimination, the raster image of the real flooded area is obtained, and then needs to be converted into the raster image, so as to facilitate subsequent data analysis, and step S105 is to realize conversion between the vector diagram and the raster image.
After the raster map of the real flooded area is converted into the raster map through ArcMap software, the following steps are adopted for processing to obtain a flood flooding depth map, and the method specifically comprises the following steps:
and S106a, obtaining a pixel value of each grid in the grid map of the real flooded area according to the grid map of the real flooded area, and taking the pixel value of each grid as the flood water level height of each grid.
And S106b, obtaining a pixel value of each grid in the grid map of the flooded area according to the grid map of the flooded area, and taking the pixel value of each grid as the flood water level height of each grid.
And S106c, subtracting the pixel value of each grid in the grid map of the real flooded area from the pixel value of each grid in the grid map of the flooded area to obtain the height difference between the grid map of the real flooded area and the grid map of the flooded area, wherein the height difference is the flood submerging depth map.
Since the real flooded area vector diagram is the actual flooded area, the pixel value of each grid in the grid diagram is the actual water level value of the flooded area corresponding to the grid.
Meanwhile, when the flooded area is determined from the DSM image map, it is already described that the GSM data and the water line data of each grid in the DSM image map are determined, and after the condition is satisfied, the pixel value of the grid meeting the condition is changed to the water line data, that is, the pixel value of each grid in the grid map of the flooded area in step S106b is the water line data.
And finally, directly and truly subtracting the pixel value of each grid in the grid map of the 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 submerging depth map.
In this embodiment, the grid to be subtracted is the corresponding grid in the two grid graphs, that is, the grid corresponding to the same area in the two grid graphs. Meanwhile, since the two grid maps are subtracted (i.e. the subtraction of the internal grid pixel values), the obtained grid map is also a grid map, that is, the flood submerging depth map mentioned in step S106.
In this embodiment, the subtraction of the two layers is also performed using ArcMap software.
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 keeps the rapidity of passive analysis, but also has the accuracy of active analysis, and makes up the defects of the flood active analysis and the object source analysis at present.
Example two
As shown in fig. 2, the embodiment provides a specific implementation method for specifically establishing a DSM image map, which specifically includes the following steps:
and S101a, carrying out aerial triangulation calculation on the oblique image data to obtain a control point of the area to be evaluated.
And S101b, carrying out image dense matching according to the control points to obtain point cloud data of the area to be evaluated.
And S101c, constructing a TIN three-dimensional grid according to the point cloud data, and generating a three-dimensional model of blank textures of the area to be evaluated.
And S101d, performing texture mapping on the three-dimensional model to obtain a three-dimensional scene of the area to be evaluated.
And S101e, generating a DSM image map of the area to be evaluated according to the three-dimensional scene.
In this embodiment, the oblique image data of the area to be evaluated is acquired by aerial photography by an unmanned aerial vehicle, specifically, a small unmanned aerial vehicle of the type of 4Pro of maing, and aerial survey is performed by using DJI GS Pro software provided by the company of maing.
In this embodiment, use the pentascope to carry out the image acquisition of treating the aassessment area on the unmanned aerial vehicle platform, the pentascope includes the oblique camera lens and the orthographic camera lens in 4 azimuths, can acquire the more complete accurate information of ground object. The shooting at an angle vertical to the ground is carried out to obtain a group of vertically downward images called positive films, and the four groups of images shot by the lens facing to the ground at a certain included angle point to the south, the west and the north respectively called oblique films.
In the present embodiment, the oblique image data includes three types of data, which are the original oblique image data, pos data included in the original oblique image data, and related parameters of the camera during shooting. The raw data of the oblique image is the raw image file data of the oblique image shot by the head, and the pos data is the xyz-position information included in each picture.
After the information is obtained, aerial triangulation calculation can be performed by using the information, the aerial triangulation calculation is based on pixel point coordinates measured on the image, a strict mathematical model is adopted, a small number of ground control points are used as adjustment conditions according to the principle of the least square method, the space coordinates of the ground control points required by mapping are calculated by using a computer, finally, the control points of the evaluation area can be obtained, the aerial triangulation calculation is the control points of the DSM image map on which the foundation is established, and then the DSM image map is obtained through steps S101 b-S101 e.
After the control points of the area to be evaluated are obtained, image dense matching can be carried out, point cloud data of the area 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 area to be evaluated is obtained, texture mapping is carried out, a three-dimensional scene of the area to be evaluated can be obtained, and finally a DSM image map can be obtained according to which scene of the pattern.
In the present embodiment, image dense matching is a prior art, and is mainly divided into two categories, which are: the matching based on gray scale and the matching based on features, but in the present embodiment, a SIFT algorithm is used for dense image matching.
The SIFT algorithm extracts feature points in different scale spaces and calculates feature vectors to finally obtain homonymous points of a stereopair, has invariance of scale, rotation and translation, has certain robustness on illumination change, affine transformation and three-dimensional projection transformation, and has strong image matching capability.
And using the point cloud data to construct a TIN (Irregular triangular Network) three-dimensional grid and a three-dimensional model, and finally obtaining a DSM image map of the area to be evaluated.
In this embodiment, the DSN image data can be generated directly by using the existing software, specifically: ContextCapture software is used as modeling software of the current oblique image, and the specific steps are as follows:
the first step is as follows: importing software for influencing the tilt;
the second step is that: adjusting the camera attribute;
the third step: performing aerial triangulation calculation in software using tools;
the fourth step: carrying out reconstruction;
the fifth step: production of DSM image maps was performed.
EXAMPLE III
As shown in fig. 3, the present embodiment provides an apparatus for implementing the flood disaster tolerance assessment method in the first embodiment, including a DSM image generating module, a grid processing module, an interference eliminating module, and a flooded bitmap calculating module.
The DSM image generation module is used for acquiring the inclined image data and generating a DSM image of the area to be evaluated.
The grid processing module is in communication connection with the DSM image generation module and is used for obtaining a grid map of a flooded area according to the DSM image map and performing vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area.
And the interference elimination module is in communication connection with the grid processing module and is used for eliminating interference on the vector diagram of the flooded area to obtain the vector diagram of the real flooded area.
The flooded bitmap calculation module is in communication connection with the interference elimination module and is used for performing grid conversion on the real flooded area vector diagram to obtain a real flooded area grid diagram, and subtracting the real flooded area grid diagram from the flooded area grid diagram to obtain a flood flooding depth diagram.
For the working process, the working details and the technical effects of the evaluation apparatus provided in this embodiment, reference may be made to embodiment one, which is not repeated herein.
Example four
As shown in fig. 4, this embodiment provides a hardware device implementing the flood disaster tolerance assessment method according to the first embodiment, and the hardware device includes a memory and a processor, which are communicatively connected, where the memory is used to store a computer program, and the processor is used to execute the computer program to implement the flood disaster tolerance assessment method according to the first embodiment.
The working process, the working details, and the technical effects of the hardware device provided in this embodiment may be referred to in embodiment one, and are not described herein again.
EXAMPLE five
The present embodiment provides a computer storage medium including the flood disaster tolerance assessment method according to the first embodiment, wherein the computer storage medium stores a computer program thereon, and the computer program, when executed by a processor, implements the flood disaster tolerance assessment method according to the first embodiment.
In this embodiment, the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices, and may also be a mobile intelligent device (such as a smart phone, a PAD, or an ipad).
The working process, the working details and the technical effects of this embodiment can be referred to as embodiment one, and are not described herein again.
The embodiments described above are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device to perform the methods described in the embodiments or some portions of the embodiments.
In summary, the flood disaster assessment method, device, equipment and computer storage medium provided by the present invention have the following technical effects:
(1) firstly, establishing a DSM image map of a to-be-evaluated area, directly acquiring a grid map of the flooded area from the DSM image map, and performing 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 to-be-evaluated area; 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.
The invention is not limited to the above alternative embodiments, and any other various forms of products can be obtained by anyone in the light of the present invention, but any changes in shape or structure thereof, which fall within the scope of the present invention as defined in the claims, fall within the scope of the present invention.
Claims (9)
1. A flood disaster assessment method is characterized by comprising the following steps:
s101, acquiring inclined image data of a to-be-evaluated area, and establishing a DSM image map of the to-be-evaluated area by using the inclined image data;
s102, extracting grid elements belonging to a flooded area in the DSM image map according to the DSM image map to form a grid map of the flooded area;
s103, performing vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area;
s104, eliminating interference on all areas in the vector diagram of the flooded area, extracting areas communicated with rivers in the vector diagram of the flooded area, and forming a real vector diagram of the flooded area;
s105, performing grid conversion on the real flooded area vector diagram to obtain a grid diagram of the real flooded area;
and S106, subtracting the grid map of the real flooded area from the grid map of the flooded area to obtain a flood flooding depth map.
2. The flood disaster assessment method according to claim 1, wherein the grid elements of the flooded area in step S102 are obtained by the following steps:
s102a, determining water level line data of a river in an area to be evaluated;
s102b, obtaining DSM data of each grid in the DSM image map according to the DSM image map;
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.
3. The flood disaster assessment method according to claim 1, wherein said step S104 specifically comprises the following steps:
s104a, determining flood bursting points of an area to be evaluated;
and S104b, intersecting the vector diagram of the flooded area with the flood burst points, extracting an area of the vector diagram of the flooded area, which is intersected with the flood burst points, taking the extracted area as an actual flooded area, and forming the vector diagram of the actual flooded area.
4. The flood disaster assessment method according to claim 2, wherein said step S106 specifically comprises the steps of:
s106a, obtaining a pixel value of each grid in the grid map of the real flooded area according to the grid map of the real flooded area, and taking the pixel value of each grid as the flood water level height of each grid;
s106b, obtaining a pixel value of each grid in the grid map of the flooded area according to the grid map of the flooded area, and taking the pixel value of each grid as the flood water level height of each grid;
and S106c, subtracting the pixel value of each grid in the grid map of the real flooded area from the pixel value of each grid in the grid map of the flooded area to obtain the height difference between the grid map of the real flooded area and the grid map of the flooded area, wherein the height difference is the flood submerging depth map.
5. The flood disaster assessment method according to claim 4, wherein: and the pixel value of each grid in the grid map of the flooded area is the water line data.
6. The flood disaster assessment method according to claim 1, wherein the step S101 comprises the following steps of establishing a DSM image map of an area to be assessed:
s101a, performing aerial triangulation calculation on the oblique image data to obtain a control point of an area to be evaluated;
s101b, carrying out image dense matching according to the control points to obtain point cloud data of the area 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 area to be evaluated;
s101d, performing texture mapping on the three-dimensional model to obtain a three-dimensional scene of the area to be evaluated;
and S101e, generating a DSM image map of the area to be evaluated according to the three-dimensional scene.
7. A flood disaster 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 bitmap calculation module;
the DSM image generation module is used for acquiring inclined image data and generating a DSM image map of a 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 map of a flooded area according to the DSM image map and performing vector conversion on the grid map of the flooded area to obtain a vector map of the flooded area;
the interference elimination module is in communication connection with the grid processing module and is used for eliminating interference on the vector diagram of the flooded area to obtain a real vector diagram of the flooded area;
the flooded bitmap calculation module is in communication connection with the interference elimination module and is used for performing grid conversion on the real flooded area vector diagram to obtain a real flooded area grid diagram, and subtracting the real flooded area grid diagram from the flooded area grid diagram to obtain a flood flooding depth diagram.
8. A flood disaster assessment device is characterized in that: a memory and a processor, which are communicatively connected, 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 according to any one of claims 1 to 6.
9. A computer storage medium, characterized in that: the computer storage medium has a computer program stored thereon, which when executed by a processor implements the flood disaster assessment method according to any one of claims 1 to 6.
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