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CN114048943A - Urban waterlogging analysis method, device and medium based on unmanned aerial vehicle BIM and SWMM - Google Patents

Urban waterlogging analysis method, device and medium based on unmanned aerial vehicle BIM and SWMM Download PDF

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CN114048943A
CN114048943A CN202111173548.2A CN202111173548A CN114048943A CN 114048943 A CN114048943 A CN 114048943A CN 202111173548 A CN202111173548 A CN 202111173548A CN 114048943 A CN114048943 A CN 114048943A
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刘学明
葛建华
朱志华
邓洪
朱帅
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Guangzhou Zhuhe Engineering Technology Co ltd
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Guangzhou Zhuji Technology Co ltd
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Abstract

The invention provides an urban waterlogging analysis method based on unmanned aerial vehicles BIM and SWMM, which comprises the following steps: s1, generating a three-dimensional live-action model according to the aerial data; s2, generating a BIM model of the urban waterlogging area according to the various facility data and the three-dimensional real scene model; s3, constructing an SWMM model according to the SWMM model data; s4, fusing the ponding point and the ponding area calculated by the SWMM model with the BIM model of the urban waterlogging area according to the web to form urban waterlogging; and S5, obtaining the affected area of the waterlogging, the number of the affected population of the waterlogging and the affected road mileage of the waterlogging under different schemes based on the data statistical analysis of the GIS. The invention can rapidly analyze the monitoring of the urban inland inundation disaster range and the disaster degree by fusing the three-dimensional live-action data, the building model data and the SWMM model data shot by the unmanned aerial vehicle.

Description

Urban waterlogging analysis method, device and medium based on unmanned aerial vehicle BIM and SWMM
Technical Field
The invention relates to the technical field of data analysis, in particular to a city waterlogging analysis method, device and medium based on unmanned aerial vehicle BIM and SWMM.
Background
Because urban waterlogging disasters caused by rainstorm occur in all big cities almost every year, great material loss is caused, and daily life of urban residents is seriously influenced, so that the research on urban rainstorm flood forming mechanisms and the simulation of the rainstorm flooding process are important for guiding urban flood control and disaster reduction.
Urban underlying surface data plays a crucial role in urban rainfall flood simulation, but the precision of the urban underlying surface data acquired by the currently commonly used Remote Sensing (RS) technology is difficult to meet the research requirement. Unmanned Aerial Vehicle (UAV) oblique photogrammetry is an emerging method in the digital photogrammetry field in recent years, integrates the advantages of the Unmanned Aerial Vehicle technology and the oblique photogrammetry technology, and can conveniently and efficiently construct an urban high-precision underlying model. With the development of comprehensive planning concepts such as smart cities and sponge cities, the connection between future construction projects and the surrounding environment is inevitably deeper and deeper. The problem with this is the large information input requirements. The method for acquiring the information by utilizing the oblique photography technology is an effective means for acquiring the information, and the information is incorporated into the BIM platform in an auxiliary form, so that the method is necessary for development and provides data support for urban rainstorm and flood simulation. Although urban rainstorm flood is also a flood disaster, due to the special underlying surface condition of cities, many runoff models are not suitable for the simulation of urban rainfall-runoff at present, and a Storm flood Management Model (SWMM) is a set of models specially developed for solving the problems of urban runoff and Water quality simulation, is not only suitable for the simulation of urban rainfall-runoff, but also has high calculation precision.
The domestic research on urban storm runoff simulation and ponding calculation models has achieved great results, and some research results have played an important role in actual urban flood control and disaster reduction. However, from the current theoretical analysis and practical application results, firstly, it is assumed that accumulated water at the nodes of the model pipe network cannot flow out of a research area, and the accumulated water in practice flows out to an area with a lower elevation along with the terrain; secondly, the SWMM model does not take into account the water storage capacity of natural lakes, ponds and the like; finally, the accuracy of the digital elevation model DEM and the sub-catchment areas divided based on the DEM have great influence on the simulation result of the model. Therefore, the method for integrally analyzing urban rainfall-runoff-pipe network ponding-flooding is still lacked.
The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, material described in this section is not prior art to the claims in this application and is not admitted to be prior art by inclusion in this section.
Disclosure of Invention
Aiming at the technical problems in the related art, the invention provides an urban waterlogging analysis method based on unmanned aerial vehicles BIM and SWMM, which comprises the following steps:
s1, acquiring unmanned aerial vehicle aerial photography data of urban inland inundation areas, and generating a three-dimensional live-action model according to the aerial photography data;
s2, acquiring various facility data of the urban waterlogging area, and generating a BIM (building information modeling) model of the urban waterlogging area according to the various facility data and the three-dimensional real scene model;
s3, obtaining SWMM model data, and constructing an SWMM model according to the SWMM model data;
s4, fusing the ponding point and the ponding area calculated by the SWMM model with the BIM model of the urban waterlogging area according to the web to form urban waterlogging;
and S5, performing statistical analysis on the waterlogging influence of the forecasting schemes with different durations according to respective calculation methods of the waterlogging influenced area, the number of the waterlogging influenced population and the waterlogging influenced road mileage based on GIS data statistical analysis to obtain the waterlogging influenced area, the number of the waterlogging influenced population and the waterlogging influenced road mileage under different schemes.
Specifically, the analysis of the influence area of waterlogging comprises the following steps:
a. calculating a result according to the urban waterlogging model to obtain the flooding condition of the urban waterlogging area;
b. carrying out statistics on the grid attributes to obtain the type and the area of the flooded land;
c. and carrying out time sequence modeling on the influence inundated area, and dynamically displaying on the web end.
Specifically, the analysis of the number of affected population of the waterlogging comprises the following steps:
aa, calculating a result according to the urban inland inundation model to obtain the area of the flooded residential area;
carrying out time sequence modeling on the area of the submerged residential area;
cc. calculating the population of each study residential area, comparing the population of each residential area with the area, calculating the population density of each residential area, and storing the population density in the grid attribute;
dd. multiplying the flooded residential area of each grid by the population density of the residential area to obtain the flooded population number of each grid;
ee. the number of flooded population for each grid within the statistical range is summed to obtain the number of affected population for waterlogging.
Specifically, the affected waterlogging road mileage can be obtained through distribution calculation and analysis in the three-dimensional real-scene model, and the affected road mileage change can be dynamically displayed according to the model time sequence.
Specifically, a new solution is planned through GIS analysis according to the analyzed submerging area and accumulated water point data, and the accuracy and the feasibility of planning contents are obtained through waterlogging analysis;
planning the diameter of the rainwater pipe network by combining the terrain and the water accumulation point data through the GIS;
combining the terrain and the accumulated water area data, planning and adding a new rainwater pipe network and a ground engineering building by the GIS;
and ccc, verifying the modified rainwater pipe network again by using the waterlogging geographic model, and repeatedly modifying the modification scheme.
To achieve the above object, according to another embodiment of the present invention, there is provided an urban waterlogging analysis device based on unmanned BIM and SWMM, including:
the three-dimensional live-action model generation unit is used for acquiring unmanned aerial vehicle aerial photography data of urban inland inundation areas and generating a three-dimensional live-action model according to the aerial photography data;
the BIM model generation unit of the urban waterlogging area is used for acquiring various facility data of the urban waterlogging area and generating a BIM model of the urban waterlogging area according to the various facility data and the three-dimensional real scene model;
the SWMM model generation unit is used for acquiring SWMM model data and constructing a SWMM model according to the SWMM model data;
the urban waterlogging generation unit is used for fusing the ponding point and the ponding area calculated by the SWMM model with the BIM model of the urban waterlogging area according to the web to form the urban waterlogging;
and the urban waterlogging analysis unit is used for carrying out statistical analysis on the waterlogging influence of different long forecasting schemes according to respective calculation methods of the waterlogging influenced area, the waterlogging influenced population number and the waterlogging influenced road mileage based on GIS data statistical analysis to obtain the waterlogging influenced area, the waterlogging influenced population number and the waterlogging influenced road mileage under different schemes.
Specifically, each item of facility data of the urban inland inundation area comprises: underground rainwater pipeline planning data and above-ground building planning data.
Specifically, the SWMM model data includes: detailed data of a rainwater pipe network, ground impervious surface data, climate data, rainfall data and geographic data; the geographic data comprises: topographic data, land use type.
Specifically, the urban waterlogging analysis unit is further configured to divide the waterlogging urban waterlogging area into a plurality of grids, and input an attribute value of the land type of each grid.
To achieve the object of the present invention, another embodiment of the present invention provides a non-volatile memory having stored thereon executable instructions, which when executed by a processor, are adapted to implement the method as described above.
By fusing three-dimensional live-action data, building model data and SWMM model data shot by the unmanned aerial vehicle, the method can quickly analyze the monitoring of urban inland inundation disaster range and the disaster degree.
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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 embodiments will be briefly described below, and 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 these drawings without creative efforts.
FIG. 1 is provided in the practice of the present invention;
FIG. 2 is a schematic illustration provided in the practice of the present invention;
FIG. 3 is a schematic illustration provided in the practice of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
Example one
Referring to fig. 1, the present embodiment provides an urban waterlogging analysis method based on the BIM and SWMM of unmanned aerial vehicles, which includes the following steps:
s1, acquiring unmanned aerial vehicle aerial photography data of urban inland inundation areas, and generating a three-dimensional live-action model according to the aerial photography data;
adopt the surveying system of big jiangjiang PHANTOM 4RTK unmanned aerial vehicle, it possesses centimetre level navigation positioning system and high performance imaging system. Firstly, preliminarily estimating the area and the boundary of waterlogging of a residential area according to the actual situation of the residential area on site, planning the flight area through DJI GS RTK course planning software, designing 4 aerial survey routes, wherein the course overlapping rate is 80%, the lateral overlapping rate is 70%, the control points are laid in the survey area by adopting area mesh, and the network RTK provides high-precision image control point coordinate information for aerial triangulation. The unmanned aerial vehicle automatically finishes aerial flight and residential area waterlogging field image data acquisition according to the uploaded set flight route.
And after aerial photography is finished, information such as POS (point of sale), focal length and the like can be directly extracted from the photo file shot by the unmanned aerial vehicle by adopting DJI Terra software. The DJI Terra obtains complete point cloud data from the unmanned aerial vehicle image data and the control point coordinate data through an aerial triangulation technology, and converts a three-dimensional live-action model; the Acute3D Viewe is used for browsing three-dimensional real scene models, and can measure distance, area, volume and the like. And importing the point cloud data into Autodesk CAD software to output point and line data with elevation properties. Based on a series of pictures shot by the unmanned aerial vehicle, a three-dimensional model of a real waterlogging residential area is constructed, and a live-action three-dimensional model is generated after picture textures are superimposed.
S2, acquiring various facility data of the urban waterlogging area, and generating a BIM (building information modeling) model of the urban waterlogging area according to the various facility data and the three-dimensional real scene model;
the BIM model is created through Autodesk Revit, DEM data generated through Context Capture in S1 are imported into Revit software to generate a three-dimensional original terrain model, a residential area building model is constructed through the Revit software, the three-dimensional real scene model and BIM model data are loaded and fused through a Terra Explore Pro module in Skyline Global software to form a BIM model of an urban waterlogging area, and various facilities on the waterlogging site of the residential area are simulated.
The specific facility data of the urban waterlogging area comprise: underground rainwater pipeline planning data and overground building planning data.
S3, obtaining SWMM model data, and constructing an SWMM model according to the SWMM model data;
the SWMM model data include: detailed data of a rainwater pipe network, ground impervious surface data, climate data, rainfall data, geographic data and the like; the geographic data includes: terrain data, land use type, etc.
The SWMM model is based on SWMM software and comprises the following steps: 1, generating wmf text elements; amplifying to the maximum condition of the full screen by utilizing the provided CAD file; selecting the whole drawing area (instead of the place where the drawing information exists) and recording the coordinates of the lower left corner and the upper right corner of the CAD page (the whole drawing area), clicking an output button to output wmf file, 2 drawing a CAD paper recognizable by DXF-epa software, drawing a circle at each place needing to be used as a node, suggesting the same specification, copying all circles into a new CAD file, using a button copied to the original coordinates to ensure the coordinates to be unchanged, connecting the circles with a plurality of lines according to the flow direction of water in a pipeline marked in the original CAD paper from the upstream to the downstream, wherein the picked point only has the circle center, only one multi-line is arranged between two adjacent nodes, no disconnected place can be formed or two or even a plurality of multi-line can be formed, storing the file into DXF format, recording the layer names of the circles and the line segments; the DXF file is generated as an inp file using DXF-epa software. 3, arranging the format of the inp file to be recognized by SWMM, copying each element in the generated inp file by using the mature inp file as much as possible, and generally using excel to realize the method. 4, opening the stored inp file by using the SWMM, loading a map, and inputting coordinates of a lower left corner and an upper right corner under a size change option, wherein only a first column needs to be input, and the option is a first button; 5 modifying node and pipe segment information in SWMM against CAD, here including editing work on the discharge ports; 6, creating a rain gauge and compiling a time sequence; 7, drawing a catchment area, and modifying elements of the catchment area; 8, modifying the position with the problem in the file according to the state report, wherein the problem in the input process is mainly referred to; 9, rerunning, and writing a report and proposing an improvement suggestion according to the running result.
S4, fusing the ponding point and the ponding area calculated by the SWMM model with the BIM model of the urban waterlogging area according to the web to form an urban waterlogging model;
the multi-model coupling is to fit an underground pipe network model, an overground building model and a three-dimensional live-action image by means of a web end and by means of a terrain model as a base map, and to combine data such as accumulated water points and accumulated water areas calculated by an SWMM model with the model for coupling analysis to obtain an urban inland inundation model.
The method is characterized in that loading and fusion are carried out by means of a Terra explicit Pro module of Skyline Global software, meanwhile, 3DMAX is used for cutting the unmanned aerial vehicle image, the cut image is subjected to mapping processing on a BIM model in a mapping mode, and the three-dimensional image is subjected to single processing. Geographic coordinate registration is carried out on the BIM model of the residential area and the three-dimensional image of the unmanned aerial vehicle through geographic coordinate conversion, centimeter-level precision is achieved, and the whole process of occurrence of the waterlogging of the residential area is displayed through a demonstration module of the Wish 3D.
And S5, performing statistical analysis on the waterlogging influence of the forecasting schemes with different durations according to respective calculation methods of the waterlogging influenced area, the number of the waterlogging influenced population and the waterlogging influenced road mileage based on GIS data statistical analysis to obtain the waterlogging influenced area, the number of the waterlogging influenced population and the waterlogging influenced road mileage under different schemes.
The analysis of the influence of waterlogging generally comprises the analysis of the influence area of the waterlogging, the number of people with the influenced waterlogging, the mileage of roads with the influenced waterlogging and the like.
By means of the data statistics function of the GIS, the inland inundation city inland inundation area is divided into a plurality of grids, and the type of land of each grid is recorded, wherein the attribute values comprise roads, communities, schools, hospitals and the like. And (3) combining the multi-model coupling calculation results, carrying out statistical analysis on the influence of the waterlogging of the forecasting schemes with different durations according to respective calculation methods of the influenced waterlogging area, the influenced population number of the waterlogging, the influenced road mileage of the waterlogging and the like to obtain the influenced waterlogging area, the influenced population number of the waterlogging and the influenced road mileage of the waterlogging under different schemes as shown in a table 4. The problem of urban waterlogging is solved by analyzing and planning a new solution through a GIS.
Figure BDA0003292514070000081
Further, the waterlogging affected area analysis comprises the following steps:
a. calculating a result according to the urban waterlogging model to obtain the flooding condition of the urban waterlogging area;
b. carrying out statistics on the grid attributes to obtain the type and the area of the flooded land;
c. and carrying out time sequence modeling on the influence inundated area, and dynamically displaying on the web end.
Further, the analysis of the number of affected population of the waterlogging comprises the following steps:
aa, calculating a result according to the urban inland inundation model to obtain the area of the flooded residential area;
carrying out time sequence modeling on the area of the submerged residential area;
cc. calculating the population of each study residential area, comparing the population of each residential area with the area, calculating the population density of each residential area, and storing the population density in the grid attribute;
dd. multiplying the flooded residential area of each grid by the population density of the residential area to obtain the flooded population number of each grid;
ee. the number of flooded population for each grid within the statistical range is summed to obtain the number of affected population for waterlogging.
Furthermore, the waterlogging affected road mileage can be obtained according to distribution calculation analysis of the waterlogging affected road mileage in the three-dimensional real-scene model, and affected road mileage changes can be dynamically displayed according to model time sequence.
Furthermore, the accuracy and the feasibility of planning contents are obtained through analyzing the waterlogging by analyzing and planning a new solution through the analyzed data such as the inundation area, the ponding point and the like and through analyzing the waterlogging through a GIS.
Planning the diameter of the rainwater pipe network by combining the terrain and the water accumulation point data through the GIS;
combining the terrain and the accumulated water area data, planning and adding a new rainwater pipe network and constructing a ground project by the GIS;
and ccc, verifying the modified rainwater pipe network again by using the waterlogging geographic model, and repeatedly modifying the modification scheme.
Further, the geographical model of waterlogging in the step 4 and the analysis result in the step 5 are coupled through GIS software, and the data are published on the web end on line by using the publishing function of GIS.
By fusing three-dimensional live-action data, building model data and SWMM model data shot by the unmanned aerial vehicle, the method can quickly analyze the monitoring of urban inland inundation disaster range and the disaster degree.
Example two
Referring to fig. 2, the present embodiment provides an urban waterlogging analysis device based on unmanned aerial vehicle BIM and SWMM, which includes:
the three-dimensional live-action model generation unit is used for acquiring unmanned aerial vehicle aerial photography data of urban inland inundation areas and generating a three-dimensional live-action model according to the aerial photography data;
the BIM model generation unit of the urban waterlogging area is used for acquiring various facility data of the urban waterlogging area and generating a BIM model of the urban waterlogging area according to the various facility data and the three-dimensional real scene model;
the SWMM model generation unit is used for acquiring SWMM model data and constructing a SWMM model according to the SWMM model data;
the urban waterlogging generation unit is used for fusing the ponding point and the ponding area calculated by the SWMM model with the BIM model of the urban waterlogging area according to the web to form the urban waterlogging;
and the urban waterlogging analysis unit is used for carrying out statistical analysis on the waterlogging influence of different long forecasting schemes according to respective calculation methods of the waterlogging influenced area, the waterlogging influenced population number and the waterlogging influenced road mileage based on GIS data statistical analysis to obtain the waterlogging influenced area, the waterlogging influenced population number and the waterlogging influenced road mileage under different schemes.
By means of the data statistics function of the GIS, the inland inundation city inland inundation area is divided into a plurality of grids, and the type of land of each grid is recorded, wherein the attribute values comprise roads, communities, schools, hospitals and the like. And (3) combining the multi-model coupling calculation results, carrying out statistical analysis on the influence of the waterlogging of the forecasting schemes with different durations according to respective calculation methods of the influenced waterlogging area, the influenced population number of the waterlogging, the influenced road mileage of the waterlogging and the like to obtain the influenced waterlogging area, the influenced population number of the waterlogging and the influenced road mileage of the waterlogging under different schemes as shown in a table 4. The problem of urban waterlogging is solved by analyzing and planning a new solution through a GIS.
Figure BDA0003292514070000101
Figure BDA0003292514070000111
Further, the waterlogging affected area analysis comprises the following steps:
a. calculating a result according to the urban waterlogging model to obtain the flooding condition of the urban waterlogging area;
b. carrying out statistics on the grid attributes to obtain the type and the area of the flooded land;
c. and carrying out time sequence modeling on the influence inundated area, and dynamically displaying on the web end.
Further, the analysis of the number of affected population of the waterlogging comprises the following steps:
aa, calculating a result according to the urban inland inundation model to obtain the area of the flooded residential area;
carrying out time sequence modeling on the area of the submerged residential area;
cc. calculating the population of each study residential area, comparing the population of each residential area with the area, calculating the population density of each residential area, and storing the population density in the grid attribute;
dd. multiplying the flooded residential area of each grid by the population density of the residential area to obtain the flooded population number of each grid;
ee. the number of flooded population for each grid within the statistical range is summed to obtain the number of affected population for waterlogging.
Furthermore, the waterlogging affected road mileage can be obtained according to distribution calculation analysis of the waterlogging affected road mileage in the three-dimensional real-scene model, and affected road mileage changes can be dynamically displayed according to model time sequence.
Furthermore, the accuracy and the feasibility of planning contents are obtained through analyzing the waterlogging by analyzing and planning a new solution through the analyzed data such as the inundation area, the ponding point and the like and through analyzing the waterlogging through a GIS.
Planning the diameter of the rainwater pipe network by combining the terrain and the water accumulation point data through the GIS;
combining the terrain and the accumulated water area data, planning and adding a new rainwater pipe network and constructing a ground project by the GIS;
and ccc, verifying the modified rainwater pipe network again by using the waterlogging geographic model, and repeatedly modifying the modification scheme.
By fusing three-dimensional live-action data, building model data and SWMM model data shot by the unmanned aerial vehicle, the method can quickly analyze the monitoring of urban inland inundation disaster range and the disaster degree.
EXAMPLE III
Referring to fig. 3, fig. 3 is a schematic structural diagram of an urban waterlogging area analysis device based on the unmanned aerial vehicles BIM and SWMM according to this embodiment. The unmanned aerial vehicle BIM and SWMM based regional urban inland inundation analysis device 20 of this embodiment comprises a processor 21, a memory 22, and a computer program stored in said memory 22 and executable on said processor 21. The processor 21, when executing the computer program, implements the steps in the above embodiments of the method for analyzing urban waterlogging areas based on the unmanned aerial vehicles BIM and SWMM. Alternatively, the processor 21 implements the functions of the modules/units in the above-mentioned device embodiments when executing the computer program.
Illustratively, the computer program may be divided into one or more modules/units, which are stored in the memory 22 and executed by the processor 21 to accomplish the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program in the drone BIM and SWMM based regional urban waterlogging analysis device 20. For example, the computer program may be divided into the modules in the second embodiment, and please refer to the working process of the urban waterlogging area analysis device based on the unmanned aerial vehicle BIM and SWMM described in the foregoing embodiment for specific functions of each module, which is not described herein again.
The city waterlogging area analysis device 20 based on the unmanned aerial vehicles BIM and SWMM may include, but is not limited to, a processor 21 and a memory 22. It will be understood by those skilled in the art that the schematic diagram is merely an example of the urban waterlogging area analysis device 20 based on the drones BIM and SWMM, and does not constitute a limitation of the urban waterlogging area analysis device 20 based on the drones BIM and SWMM, and may include more or less components than the schematic diagram, or combine some components, or different components, for example, the urban waterlogging area analysis device 20 based on the drones BIM and SWMM may further include an input and output device, a network access device, a bus, etc.
The Processor 21 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general processor may be a microprocessor or the processor may be any conventional processor, and the processor 21 is a control center of the urban waterlogging area analysis device 20 based on the drones BIM and SWMM, and various interfaces and lines are used to connect various parts of the entire urban waterlogging area analysis device 20 based on the drones BIM and SWMM.
The memory 22 may be used to store the computer programs and/or modules, and the processor 21 implements various functions of the unmanned aerial vehicle BIM and SWMM-based regional urban inland analysis device 20 by running or executing the computer programs and/or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required by at least one function, and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 22 may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the integrated modules/units of the urban waterlogging area analysis device 20 based on the unmanned aerial vehicles BIM and SWMM can be stored in a computer readable storage medium if they are implemented in the form of software functional units and sold or used as independent products. Based on such understanding, all or part of the flow of the method of the embodiments described above can be realized by the present invention, and the method can also be realized by the relevant hardware instructed by a computer program, which can be stored in a computer-readable storage medium, and the steps of the method embodiments described above can be realized when the computer program is executed by the processor 21. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc. It should be noted that the computer readable medium may contain content that is appropriately increased or decreased according to the requirements of legislation and patent practice in a jurisdiction, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to legislation and patent practice.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple 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. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement the method without inventive effort.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (10)

1. An urban waterlogging analysis method based on unmanned aerial vehicles BIM and SWMM comprises the following steps:
s1, acquiring unmanned aerial vehicle aerial photography data of the urban inland inundation area, and generating a three-dimensional live-action model according to the aerial photography data;
s2, acquiring various facility data of the urban waterlogging area, and generating a BIM (building information modeling) model of the urban waterlogging area according to the various facility data and the three-dimensional real scene model;
s3, obtaining SWMM model data, and constructing an SWMM model according to the SWMM model data;
s4, fusing the ponding point and the ponding area calculated by the SWMM model with the BIM model of the urban waterlogging area according to the web to form urban waterlogging;
and S5, performing statistical analysis on the influence of waterlogging of different duration forecasting schemes according to respective calculation methods of the influenced area of waterlogging, the number of the influenced population of the waterlogging and the influenced road mileage based on GIS data statistical analysis to obtain the influenced area of waterlogging, the number of the influenced population of the waterlogging and the influenced road mileage of the waterlogging under different schemes.
2. The method of claim 1, wherein the analysis of the affected area of waterlogging comprises the steps of:
a. calculating a result according to the urban waterlogging model to obtain the flooding condition of the urban waterlogging area;
b. carrying out statistics on the grid attributes to obtain the type and the area of the flooded land;
c. and carrying out time sequence modeling on the influence inundated area, and dynamically displaying on the web end.
3. The method of claim 1, wherein the analysis of the number of affected populations of waterlogging comprises the steps of:
aa, calculating a result according to the urban inland inundation model to obtain the area of the flooded residential area;
carrying out time sequence modeling on the area of the submerged residential area;
cc. calculating the population of each study residential area, comparing the population of each residential area with the area, calculating the population density of each residential area, and storing the population density in the grid attribute;
dd. multiplying the flooded residential area of each grid by the population density of the residential area to obtain the flooded population number of each grid;
ee. the number of flooded population for each grid within the statistical range is summed to obtain the number of affected population for waterlogging.
4. The method according to claim 1, wherein the waterlogging affected road mileage can be obtained according to distribution calculation analysis of the waterlogging affected road mileage in the three-dimensional real scene model, and the affected road mileage change can be dynamically displayed according to model time sequence.
5. The method of claim 1, wherein the analyzed data of the inundation area and the water accumulation point is used for planning a new solution through GIS analysis, and the accuracy and the feasibility of planning contents are obtained through waterlogging analysis;
planning the diameter of the rainwater pipe network by combining the terrain and the water accumulation point data through the GIS;
combining the terrain and the accumulated water area data, planning and adding a new rainwater pipe network and constructing a ground project by the GIS;
and ccc, verifying the modified rainwater pipe network again by using the waterlogging geographic model, and repeatedly modifying the modification scheme.
6. The utility model provides an urban waterlogging analytical equipment based on unmanned aerial vehicle BIM and SWMM, it includes the unit:
the three-dimensional live-action model generation unit is used for acquiring unmanned aerial vehicle aerial photography data of urban inland inundation areas and generating a three-dimensional live-action model according to the aerial photography data;
the BIM model generation unit of the urban waterlogging area is used for acquiring various facility data of the urban waterlogging area and generating a BIM model of the urban waterlogging area according to the various facility data and the three-dimensional real scene model;
the SWMM model generation unit is used for acquiring SWMM model data and constructing a SWMM model according to the SWMM model data;
the urban waterlogging generation unit is used for fusing the ponding point and the ponding area calculated by the SWMM model with the BIM model of the urban waterlogging area according to the web to form the urban waterlogging;
and the urban waterlogging analysis unit is used for carrying out statistical analysis on the waterlogging influence of different duration forecasting schemes according to respective calculation methods of the waterlogging influenced area, the waterlogging influenced population number and the waterlogging influenced road mileage based on GIS data statistical analysis to obtain the waterlogging influenced area, the waterlogging influenced population number and the waterlogging influenced road mileage under different schemes.
7. The apparatus of claim 6, the various facility data for the urban waterlogging zone comprising: underground rainwater pipeline planning data and overground building planning data.
8. The apparatus of claim 6, the SWMM model material comprising: detailed data of a rainwater pipe network, ground impervious surface data, climate data, rainfall data and geographic data; the geographic data comprises: topographic data, land use type.
9. The device of claim 6, wherein the urban waterlogging analysis unit is further configured to divide the waterlogging urban waterlogging area into a plurality of grids, and perform attribute value entry for the land type of each grid.
10. A non-volatile memory having stored thereon executable instructions for, when executed by a processor, implementing the method of any one of claims 1-5.
CN202111173548.2A 2021-10-08 2021-10-08 Urban waterlogging analysis method, device and medium based on unmanned aerial vehicle BIM and SWMM Pending CN114048943A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
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CN114840896A (en) * 2022-05-09 2022-08-02 武汉理工大学 Waterlogging simulation analysis method based on urban road BIM
CN115186943A (en) * 2022-09-15 2022-10-14 广东广宇科技发展有限公司 Urban drainage waterlogging prediction modeling method and system and electronic equipment
CN116861317A (en) * 2023-09-04 2023-10-10 北京建筑大学 Cell waterlogging early warning method and system based on BP neural network
CN118447178A (en) * 2024-05-21 2024-08-06 建设综合勘察研究设计院有限公司 Three-dimensional dynamic visualization method, system and device for urban ponding

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114840896A (en) * 2022-05-09 2022-08-02 武汉理工大学 Waterlogging simulation analysis method based on urban road BIM
CN114840896B (en) * 2022-05-09 2024-04-26 武汉理工大学 Waterlogging and ponding simulation analysis method based on urban road BIM
CN115186943A (en) * 2022-09-15 2022-10-14 广东广宇科技发展有限公司 Urban drainage waterlogging prediction modeling method and system and electronic equipment
CN116861317A (en) * 2023-09-04 2023-10-10 北京建筑大学 Cell waterlogging early warning method and system based on BP neural network
CN118447178A (en) * 2024-05-21 2024-08-06 建设综合勘察研究设计院有限公司 Three-dimensional dynamic visualization method, system and device for urban ponding
CN118447178B (en) * 2024-05-21 2024-10-18 建设综合勘察研究设计院有限公司 Three-dimensional dynamic visualization method, system and device for urban ponding

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