CN114119892A - BIM and GIS technology-based three-dimensional digital road network construction method - Google Patents
BIM and GIS technology-based three-dimensional digital road network construction method Download PDFInfo
- Publication number
- CN114119892A CN114119892A CN202111444643.1A CN202111444643A CN114119892A CN 114119892 A CN114119892 A CN 114119892A CN 202111444643 A CN202111444643 A CN 202111444643A CN 114119892 A CN114119892 A CN 114119892A
- Authority
- CN
- China
- Prior art keywords
- model
- dimensional digital
- road network
- building
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000010276 construction Methods 0.000 title claims abstract description 32
- 238000005516 engineering process Methods 0.000 title claims abstract description 16
- 238000000034 method Methods 0.000 claims abstract description 14
- 238000005192 partition Methods 0.000 claims abstract description 6
- 230000001681 protective effect Effects 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 23
- 239000000463 material Substances 0.000 claims description 6
- 238000013461 design Methods 0.000 claims description 4
- 229910000975 Carbon steel Inorganic materials 0.000 claims description 3
- 239000004677 Nylon Substances 0.000 claims description 3
- 239000010962 carbon steel Substances 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 229920001778 nylon Polymers 0.000 claims description 3
- 239000011347 resin Substances 0.000 claims description 3
- 229920005989 resin Polymers 0.000 claims description 3
- NIXOWILDQLNWCW-UHFFFAOYSA-N acrylic acid group Chemical group C(C=C)(=O)O NIXOWILDQLNWCW-UHFFFAOYSA-N 0.000 claims description 2
- 238000005520 cutting process Methods 0.000 claims description 2
- 230000000007 visual effect Effects 0.000 abstract description 7
- 230000000694 effects Effects 0.000 abstract description 3
- 238000012800 visualization Methods 0.000 abstract description 3
- 238000004364 calculation method Methods 0.000 description 7
- 238000013523 data management Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012805 post-processing Methods 0.000 description 3
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 230000008034 disappearance Effects 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 238000013439 planning Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64C—AEROPLANES; HELICOPTERS
- B64C39/00—Aircraft not otherwise provided for
- B64C39/02—Aircraft not otherwise provided for characterised by special use
- B64C39/024—Aircraft not otherwise provided for characterised by special use of the remote controlled vehicle type, i.e. RPV
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64D—EQUIPMENT FOR FITTING IN OR TO AIRCRAFT; FLIGHT SUITS; PARACHUTES; ARRANGEMENT OR MOUNTING OF POWER PLANTS OR PROPULSION TRANSMISSIONS IN AIRCRAFT
- B64D47/00—Equipment not otherwise provided for
- B64D47/08—Arrangements of cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U2101/00—UAVs specially adapted for particular uses or applications
- B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Software Systems (AREA)
- Aviation & Aerospace Engineering (AREA)
- Databases & Information Systems (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Civil Engineering (AREA)
- Architecture (AREA)
- Data Mining & Analysis (AREA)
- Structural Engineering (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Evolutionary Computation (AREA)
- Computer Graphics (AREA)
- Processing Or Creating Images (AREA)
- Instructional Devices (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a three-dimensional digital road network construction method based on BIM and GIS technology, which comprises the following steps: the three-dimensional digital road network construction method comprises a multi-lens unmanned aerial vehicle body, wherein the multi-lens unmanned aerial vehicle body comprises a body, a transparent protective cover is fixed at the lower end of the body, five cameras are arranged in the transparent protective cover, an angle adjusting device is arranged at one end of each camera, undercarriage is fixed on two sides of the lower end of the body, and the three-dimensional digital road network construction method comprises the following steps: and S1, performing partition operation, performing oblique photography aerial survey operation by adopting a multi-lens unmanned aerial vehicle, determining a project aerial survey range, and knowing aerial survey landform. The method can quickly and efficiently complete the construction of the three-dimensional digital road network model, can well fuse and link buildings, road models and terrain models, meets the requirement of visual observation, greatly improves the visualization effect of the three-dimensional digital environment, improves the reliability and fault-tolerant rate, and effectively improves the speed and quality of the construction of the three-dimensional digital road network model.
Description
Technical Field
The invention relates to the technical field of three-dimensional road networks, in particular to a three-dimensional digital road network construction method based on BIM and GIS technologies.
Background
A Geographic Information System (GIS), sometimes also referred to as a "geoscience information system", is a specific and very important spatial information system, which is a technical system for collecting, storing, managing, operating, analyzing, displaying and describing relevant geographic distribution data in the whole or part of the earth's surface (including the atmosphere) space with the support of computer hardware and software systems, and a Building Information Model (BIM) is a complete information model, and can integrate engineering information, processes and resources of engineering projects at different stages in a whole life cycle into one model, so that the building information model can be conveniently used by all engineering participants. The real information of the building is simulated through the three-dimensional digital technology, and an information model which is coordinated with each other and consistent in the interior is provided for engineering design and construction.
The traditional management of roads by using a computer is limited only in the aspect of character form processing, a large amount of information inquiry and information processing are designed, especially the analysis and processing of spatial information still stay on the traditional drawing, the integrated comprehensive processing and analysis of road attributes and spatial data are difficult to realize, the visualization and virtual reality are further impossible to realize, the convenience of planning, designing and managing the road network can be improved by establishing a three-dimensional digital road network, but the existing three-dimensional digital road network based on the BIM and GIS technology is slow in construction speed and low in efficiency, the fusion and connection among models cannot be well realized, the visual observation requirements are difficult to meet, meanwhile, the error rate is high in the complicated process, and the quality cannot be guaranteed.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a three-dimensional digital road network construction method based on BIM and GIS technology.
In order to solve the technical problems, the invention adopts the following technical scheme:
a three-dimensional digital road network construction method based on BIM and GIS technology comprises the following steps:
s1, collecting data: performing partition operation, namely performing oblique photography aerial survey operation by adopting a multi-lens unmanned aerial vehicle, determining a project aerial survey range, knowing aerial survey landform, reasonably dividing a flight frame, optimizing an aerial photography scheme, automatically completing an aerial survey task after ground station setting and unmanned aerial vehicle assembly, automatically completing an aerial survey task according to a designated air route and parameter setting by the unmanned aerial vehicle, and observing the position of the unmanned aerial vehicle and adjusting flight parameters in real time by an operator;
s2, data sorting: adopting CommextCapture to complete GIS data processing of the current aerial survey, generating basic data, strictly registering image positioning information through aerial triangulation computation, automatically and accurately estimating the position, angle elements and camera attributes of each image by selecting parameters, obtaining missing image information, performing single processing on an oblique model, cutting the oblique photography model by utilizing corresponding vector surfaces of buildings, roads, trees and the like, and physically segmenting a continuous triangular patch network;
s3, clustering: building a local area network, taking one computer as a server, taking other computers in the local area network as nodes to be connected to the server to form a group, after the tasks are submitted, the server unifies sub-tasks to each node, after the nodes complete the sub-tasks, the processing result is returned to the server, and new sub-tasks are received until the tasks are completed;
s4, building a model: the method comprises the steps of calculating and generating a rough 3D view through aerial triangulation, understanding a space structure of a photo and a shooting scene through the rough 3D view, manufacturing a building and a road model by adopting three-level mixed precision modeling, importing satellite data of a construction area as a base map, carrying out construction model and model position positioning on the basis of the base map, extracting intersection points and overlapping points from a road center line, segmenting a road, generating a three-dimensional structure at the overlapping points according to a road design specification, generating a plane intersection model at the intersection points, and generating a road surface model at a straight road section;
s5, adjustment and check: superposing image data and elevation data of a construction area and topographic data corresponding to a building, extracting elevation data points in a ground area of the building, calculating an average elevation H of the elevation data points, giving an elevation average H to the bottom surface of the building, participating the bottom surface of the building with elevation attributes in topographic net building of the area, and well fusing and connecting the building, a road model and a topographic model;
and S6, adjusting and checking the finished road network, carrying out format processing, then carrying out three-dimensional model loading, and finally establishing a three-dimensional digital road network model with sense of reality.
Further, the method comprises the following steps of; in S1, many camera lenses unmanned aerial vehicle includes organism (1), the lower extreme of organism (1) is fixed with transparent safety cover (2), be equipped with five cameras (8) in transparent safety cover (2), the one end of camera (8) is equipped with angle adjusting device, the lower extreme both sides of organism (1) all are fixed with undercarriage (3).
Further, the method comprises the following steps of; angle adjusting device is including setting up electric telescopic handle (4) and sleeve (5) at organism (1) lower extreme, and electric telescopic handle (4) are located sleeve (5), the equidistant rotation of lower extreme of sleeve (5) is connected with five connecting rods (7), the one end of connecting rod (7) is fixed with connecting piece (6), and the lower extreme in electric telescopic handle (4) is all fixed to the one end of five connecting pieces (6), the other end in connecting rod (7) is fixed to the one end of camera (8).
Further, the method comprises the following steps of; the landing gear (3) is made of PA nylon resin material.
Further, the method comprises the following steps of; the protective cover (2) is made of acrylic materials.
Further, the method comprises the following steps of; the connecting rod (7) is made of carbon steel.
Compared with the prior art, the invention has at least one of the following beneficial effects:
in the invention, partition operation is carried out when data is collected, a multi-lens unmanned aerial vehicle is adopted to carry out oblique photography aerial survey operation, flight parameters are adjusted in real time through workers and ground stations, the aerial survey precision and efficiency are improved, geographic data and image information in the area are collected, POS data of oblique aerial survey are recorded at the same time, CommextCapture is adopted to complete GIS data processing of the aerial survey, browsing and post-processing are convenient, image positioning information is strictly registered through aerial triangulation calculation, parameters are selected to automatically and accurately estimate the position, angle elements and camera attributes of each image, missing image information is obtained, the quality of a three-dimensional digital road network model is improved, an oblique photography model is cut at the same time, the operations of independent selection, attribute endowment, attribute inquiry, data management and the like of part of buildings in the area are convenient for special conditions, and cluster processing is carried out through a local area network building mode, the reliability and the fault-tolerant rate are improved, the hardware cost can be effectively reduced, the computing capability equivalent to a high-performance computer is better exerted, the space structure of a photo and a shooting scene is understood through a rough 3D view generated by aerial triangulation computing, the model building and the model position positioning are carried out, the buffer zone boundary is generated by utilizing the automatic topological space relationship building, the problem of overlapping and merging among the polygons of the buffer zone is solved by adopting the algorithm of polygon overlapping and merging, the complex computation of determining the acceptance and rejection of the arc section through the judgment of the polygon and curve containing relationship is avoided, the simplicity and the high efficiency are realized, the building, the road model and the terrain model are well fused and linked through overlapping image data, elevation data and terrain data corresponding to the building, the visual observation requirement is met, and the visual effect of the three-dimensional digital environment is greatly improved, the method can quickly and efficiently complete the construction of the three-dimensional digital road network model, reduce the error rate and error rate of the three-dimensional digital road network model, and effectively improve the speed and quality of the construction of the three-dimensional digital road network model.
Drawings
Fig. 1 is a schematic view of the structure of the unmanned aerial vehicle.
Fig. 2 is a schematic structural diagram of a camera angle adjusting device according to the present invention.
In the figure: 1 organism, 2 transparent safety covers, 3 undercarriage, 4 electric telescopic handle, 5 sleeves, 6 connecting pieces, 7 connecting rods, 8 cameras.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1-2, a three-dimensional digital road network construction method based on BIM and GIS technology, including multi-lens unmanned aerial vehicle, multi-lens unmanned aerial vehicle includes organism 1, the lower extreme of organism 1 is fixed with transparent safety cover 2, transparent safety cover 2 adopts the ya keli material to make, transparent safety cover 2 plays the effect of protection camera 8 and help shooting, be equipped with five cameras 8 in the transparent safety cover, the one end of camera 8 is equipped with angle adjusting device, organism 1's lower extreme both sides all are fixed with undercarriage 3, undercarriage 3 adopts PA nylon resin material to make, high strength, high rigidity, excellent performance, make things convenient for unmanned aerial vehicle to rise and fall, five cameras 8 have guaranteed the all-round shooting of camera, conveniently obtain the image information of disappearance through the contrast, three-dimensional digital road network construction method includes the following steps:
s1, partition operation, oblique photography aerial survey operation is carried out by adopting a multi-lens unmanned aerial vehicle, a project aerial survey range is determined, aerial survey landform is known, reasonable flying frame division is carried out, an aerial survey scheme is optimized, factors such as flight control distance, battery consumption, landform and landform, building distribution and measurement accuracy are comprehensively considered before aerial survey operation, flight line planning and parameter setting are carried out by using ground station software, the flight height, the ground resolution and the physical pixel size meet the triangular proportional relation, after ground station setting and unmanned aerial vehicle assembly are completed, aerial survey operation can be started, the unmanned aerial vehicle automatically completes an aerial survey task according to the designated flight line and parameter setting, and data collected by oblique aerial survey comprise multi-angle image information of each shooting point and corresponding POS data. The image information is obtained by a multi-lens camera, the unmanned aerial vehicle carries a camera to take pictures on the ground at a constant speed at an equal distance, photos with 70% of overlapping rate are collected, POS data are generated by a flight control system when the camera takes pictures and are in one-to-one correspondence with the photos, rich information including longitude, latitude, height, altitude, flight direction, flight attitude and the like is given to the photos, an operator observes the position of the unmanned aerial vehicle and adjusts flight parameters in real time by a ground station, and flight parameters of oblique aerial survey include height, speed, shooting interval, course interval, lateral interval and the like, so that the precision and the efficiency of aerial survey are improved;
s2, adopting CommextCapture to complete the GIS data processing of the current navigation survey and generate basic data, wherein the CommextCapture is a parallel software system which is constructed on the basis of an image automation three-dimensional model, a software modeling object is a static object, and is supplemented with information such as camera sensor attribute, photo position and attitude parameter, control point and the like, after air triangulation calculation and model reconstruction calculation, outputting corresponding GIS results for browsing or post-processing, strictly registering image positioning information through air triangulation calculation, automatically and accurately estimating the position, corner element and camera attribute of each image by selecting parameters to obtain missing image information, in the navigation survey process, the accuracy of the corresponding posture of the photo group can be influenced to cause the image information to be missing, and when the CommextCapture is subjected to three-dimensional reconstruction, each photo group is required to have very accurate attribute and corresponding posture parameter to perform singleness processing on an inclined model, the oblique photography model is cut by utilizing the corresponding vector surfaces of buildings, roads, trees and the like, the continuous triangular patch network is physically divided, and special conditions require operations such as individual selection, attribute endowment, attribute query, data management and the like on partial buildings in a patch area;
s3, building a local area network, connecting one computer as a server and other computers in the local area network as nodes to the server to form a group, after the tasks are submitted, the server uniformly allocates subtasks to each node, after the nodes complete the subtasks, processing results are returned to the server, new subtasks are received until the tasks are completed, and data processing is performed relative to a single computer, the cluster processing has higher reliability and fault tolerance rate, and when one node computer in the group breaks down, the subtasks originally allocated to the node are automatically allocated to other nodes to perform calculation; meanwhile, the cluster processing can also reduce the cost and huge GIS data volume, great examination is provided for the storage space and the data processing speed of a single computer, and the hardware cost can be effectively reduced by clustering a common computer, so that the computing capability equivalent to that of a high-performance computer is exerted;
s4, understanding the space structure of the photo and the shooting scene through a rough 3D view, manufacturing a building and a road model by three-level mixed precision modeling, importing satellite data of a construction area as a base map, carrying out construction model and model position positioning on the basis of the base map, extracting intersection points and overlapping points from the central line of the road, segmenting the road, generating a three-dimensional structure at the overlapping points according to the road design specification, generating a plane intersection model at the intersection points, generating a road surface model at straight road sections, utilizing the automatic generation of the buffer zone boundary and the automatic construction of the topological space relationship in the GIS technology, generating the buffer zone boundary by automatically constructing the topological space relationship, solving the problem of overlapping and merging among the buffer zone polygons by utilizing an algorithm of overlapping and merging of polygons based on the deletion rule of directed arc sections on nodes, avoiding the complex calculation of determining the selection of the arc sections through the judgment of the inclusion relationship of the polygons and curves, the method is more concise and efficient;
s5, superposing image data and elevation data of a construction area and topographic data corresponding to a building, extracting elevation data points in a ground area of the building and calculating an average elevation H of the elevation data points, giving an elevation mean H to the bottom surface of the building, participating the bottom surface of the building with elevation attributes in topographic net formation of the area, well fusing and connecting the building, a road model and a topographic model, meeting the requirement of visual observation, and greatly improving the visualization effect of a three-dimensional digital environment;
and S6, adjusting and checking the finished road network, carrying out format processing, then carrying out three-dimensional model loading, finally establishing a three-dimensional digital road network model with sense of reality, finishing the later operation of the three-dimensional digital road network model, reducing the error rate of the road network model and improving the quality of the road network model.
In the invention, the angle adjusting device comprises an electric telescopic rod 4 and a sleeve 5 which are arranged at the lower end of the machine body 1, the electric telescopic rod 4 is driven by a corresponding driving device, and electric telescopic handle 4 is located sleeve 5, the equidistant rotation of sleeve 5's lower extreme is connected with five connecting rods 7, connecting rod 7 adopts the carbon steel to make, it is durable, connecting rod 7's one end is fixed with connecting piece 6, the lower extreme at electric telescopic handle 4 is all fixed to five connecting piece 6's one end, the other end at connecting rod 7 is fixed to camera 8's one end, electric telescopic handle 4 drives connecting rod 7 through connecting piece 6 and rotates simultaneously, then drive camera 8 and rotate simultaneously, it is convenient to rotate in step, the image information of disappearance is obtained through the contrast to the convenience, carry out angle modulation, conveniently carry out multi-angle shooting as required, the degree of difficulty of unmanned aerial vehicle operation has been reduced, and the work efficiency is improved.
In the invention, partition operation is carried out when data is collected, a multi-lens unmanned aerial vehicle is adopted to carry out oblique photography aerial survey operation, flight parameters are adjusted in real time through workers and ground stations, the aerial survey precision and efficiency are improved, geographic data and image information in the area are collected, POS data of oblique aerial survey are recorded at the same time, CommextCapture is adopted to complete GIS data processing of the aerial survey, browsing and post-processing are convenient, image positioning information is strictly registered through aerial triangulation calculation, parameters are selected to automatically and accurately estimate the position, angle elements and camera attributes of each image, missing image information is obtained, the quality of a three-dimensional digital road network model is improved, an oblique photography model is cut at the same time, the operations of independent selection, attribute endowment, attribute inquiry, data management and the like of part of buildings in the area are convenient for special conditions, and cluster processing is carried out through a local area network building mode, the reliability and the fault-tolerant rate are improved, the hardware cost can be effectively reduced, the computing capability equivalent to a high-performance computer is better exerted, the space structure of a photo and a shooting scene is understood through a rough 3D view generated by aerial triangulation computing, the model building and the model position positioning are carried out, the buffer zone boundary is generated by utilizing the automatic topological space relationship building, the problem of overlapping and merging among the polygons of the buffer zone is solved by adopting the algorithm of polygon overlapping and merging, the complex computation of determining the acceptance and rejection of the arc section through the judgment of the polygon and curve containing relationship is avoided, the simplicity and the high efficiency are realized, the building, the road model and the terrain model are well fused and linked through overlapping image data, elevation data and terrain data corresponding to the building, the visual observation requirement is met, and the visual effect of the three-dimensional digital environment is greatly improved, and adjusting and checking the finished road network, finishing the later operation of the three-digit digital road network model, reducing the error rate of the road network model and further improving the quality of the road network model.
Although the invention has been described herein with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More specifically, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, other uses will also be apparent to those skilled in the art.
Claims (6)
1. A three-dimensional digital road network construction method based on BIM and GIS technology is characterized in that: the method comprises the following steps:
s1, collecting data: performing partition operation, namely performing oblique photography aerial survey operation by adopting a multi-lens unmanned aerial vehicle, determining a project aerial survey range, knowing aerial survey landform, reasonably dividing a flight frame, optimizing an aerial photography scheme, automatically completing an aerial survey task after ground station setting and unmanned aerial vehicle assembly, automatically completing an aerial survey task according to a designated air route and parameter setting by the unmanned aerial vehicle, and observing the position of the unmanned aerial vehicle and adjusting flight parameters in real time by an operator;
s2, data sorting: adopting CommextCapture to complete GIS data processing of the current aerial survey, generating basic data, strictly registering image positioning information through aerial triangulation computation, automatically and accurately estimating the position, angle elements and camera attributes of each image by selecting parameters, obtaining missing image information, performing single processing on an oblique model, cutting the oblique photography model by utilizing corresponding vector surfaces of buildings, roads, trees and the like, and physically segmenting a continuous triangular patch network;
s3, clustering: building a local area network, taking one computer as a server, taking other computers in the local area network as nodes to be connected to the server to form a group, after the tasks are submitted, the server unifies sub-tasks to each node, after the nodes complete the sub-tasks, the processing result is returned to the server, and new sub-tasks are received until the tasks are completed;
s4, building a model: the method comprises the steps of calculating and generating a rough 3D view through aerial triangulation, understanding a space structure of a photo and a shooting scene through the rough 3D view, manufacturing a building and a road model by adopting three-level mixed precision modeling, importing satellite data of a construction area as a base map, carrying out construction model and model position positioning on the basis of the base map, extracting intersection points and overlapping points from a road center line, segmenting a road, generating a three-dimensional structure at the overlapping points according to a road design specification, generating a plane intersection model at the intersection points, and generating a road surface model at a straight road section;
s5, adjustment and check: superposing image data and elevation data of a construction area and topographic data corresponding to a building, extracting elevation data points in a ground area of the building, calculating an average elevation H of the elevation data points, giving an elevation average H to the bottom surface of the building, participating the bottom surface of the building with elevation attributes in topographic net building of the area, and well fusing and connecting the building, a road model and a topographic model;
and S6, adjusting and checking the finished road network, carrying out format processing, then carrying out three-dimensional model loading, and finally establishing a three-dimensional digital road network model with sense of reality.
2. The three-dimensional digital road network construction method based on BIM and GIS technology as claimed in claim 1, wherein: in S1, many camera lenses unmanned aerial vehicle includes organism (1), the lower extreme of organism (1) is fixed with transparent safety cover (2), be equipped with five cameras (8) in transparent safety cover (2), the one end of camera (8) is equipped with angle adjusting device, the lower extreme both sides of organism (1) all are fixed with undercarriage (3).
3. The three-dimensional digital road network construction method based on BIM and GIS technology as claimed in claim 2, characterized in that: angle adjusting device is including setting up electric telescopic handle (4) and sleeve (5) at organism (1) lower extreme, and electric telescopic handle (4) are located sleeve (5), the equidistant rotation of lower extreme of sleeve (5) is connected with five connecting rods (7), the one end of connecting rod (7) is fixed with connecting piece (6), and the lower extreme in electric telescopic handle (4) is all fixed to the one end of five connecting pieces (6), the other end in connecting rod (7) is fixed to the one end of camera (8).
4. The three-dimensional digital road network construction method based on BIM and GIS technology as claimed in claim 2, characterized in that: the landing gear (3) is made of PA nylon resin material.
5. The three-dimensional digital road network construction method based on BIM and GIS technology as claimed in claim 2, characterized in that: the protective cover (2) is made of acrylic materials.
6. The three-dimensional digital road network construction method based on BIM and GIS technology as claimed in claim 3, characterized in that: the connecting rod (7) is made of carbon steel.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111444643.1A CN114119892B (en) | 2021-11-30 | 2021-11-30 | Three-dimensional digital road network construction method based on BIM and GIS technologies |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111444643.1A CN114119892B (en) | 2021-11-30 | 2021-11-30 | Three-dimensional digital road network construction method based on BIM and GIS technologies |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114119892A true CN114119892A (en) | 2022-03-01 |
| CN114119892B CN114119892B (en) | 2024-04-30 |
Family
ID=80368688
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111444643.1A Active CN114119892B (en) | 2021-11-30 | 2021-11-30 | Three-dimensional digital road network construction method based on BIM and GIS technologies |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114119892B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117726777A (en) * | 2024-02-18 | 2024-03-19 | 天津云圣智能科技有限责任公司 | Unmanned aerial vehicle route optimization method and device and computer storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018061010A1 (en) * | 2016-09-28 | 2018-04-05 | Pixtier Maps Ltd. | Point cloud transforming in large-scale urban modelling |
| CN108986207A (en) * | 2018-06-29 | 2018-12-11 | 广东星舆科技有限公司 | A kind of road based on true road surface data and emulation modelling method is built along the line |
| CN109410330A (en) * | 2018-11-12 | 2019-03-01 | 中国十七冶集团有限公司 | One kind being based on BIM technology unmanned plane modeling method |
| CN110728752A (en) * | 2019-10-21 | 2020-01-24 | 西南交通大学 | Construction method of three-dimensional terrain scene model of road |
| CN112348952A (en) * | 2020-11-06 | 2021-02-09 | 中铁第一勘察设计院集团有限公司 | Three-dimensional scene construction method for multi-source geographic information data fusion in hard mountainous area |
| CN113298944A (en) * | 2021-05-31 | 2021-08-24 | 台州学院 | Automatic three-dimensional modeling measurement method based on unmanned aerial vehicle oblique photography |
| US20210342585A1 (en) * | 2020-05-01 | 2021-11-04 | Caci, Inc. - Federal | Systems and methods for extracting and vectorizing features of satellite imagery |
-
2021
- 2021-11-30 CN CN202111444643.1A patent/CN114119892B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018061010A1 (en) * | 2016-09-28 | 2018-04-05 | Pixtier Maps Ltd. | Point cloud transforming in large-scale urban modelling |
| CN108986207A (en) * | 2018-06-29 | 2018-12-11 | 广东星舆科技有限公司 | A kind of road based on true road surface data and emulation modelling method is built along the line |
| CN109410330A (en) * | 2018-11-12 | 2019-03-01 | 中国十七冶集团有限公司 | One kind being based on BIM technology unmanned plane modeling method |
| CN110728752A (en) * | 2019-10-21 | 2020-01-24 | 西南交通大学 | Construction method of three-dimensional terrain scene model of road |
| US20210342585A1 (en) * | 2020-05-01 | 2021-11-04 | Caci, Inc. - Federal | Systems and methods for extracting and vectorizing features of satellite imagery |
| CN112348952A (en) * | 2020-11-06 | 2021-02-09 | 中铁第一勘察设计院集团有限公司 | Three-dimensional scene construction method for multi-source geographic information data fusion in hard mountainous area |
| CN113298944A (en) * | 2021-05-31 | 2021-08-24 | 台州学院 | Automatic three-dimensional modeling measurement method based on unmanned aerial vehicle oblique photography |
Non-Patent Citations (3)
| Title |
|---|
| PUHENG ZHANG: "Application of Oblique Photogrammetry in Intelligent Transportation System", 《JOURNAL OF PHYSICS: CONFERENCE SERIES》, 6 June 2021 (2021-06-06), pages 1 - 7 * |
| 侯继伟: "GIS协同BIM的室内路网模型研究", 《中国优秀硕士学位论文全文数据库基础科学辑》, 15 July 2019 (2019-07-15), pages 008 - 63 * |
| 罗睿;黄凯;: "基于GIS的BIM技术在路网优化设计中的应用研究", 城市道桥与防洪, no. 11, 15 November 2019 (2019-11-15) * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117726777A (en) * | 2024-02-18 | 2024-03-19 | 天津云圣智能科技有限责任公司 | Unmanned aerial vehicle route optimization method and device and computer storage medium |
| CN117726777B (en) * | 2024-02-18 | 2024-05-07 | 天津云圣智能科技有限责任公司 | Unmanned aerial vehicle route optimization method and device and computer storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114119892B (en) | 2024-04-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109410327B (en) | BIM and GIS-based three-dimensional city modeling method | |
| CN107194989B (en) | Traffic accident scene three-dimensional reconstruction system and method based on unmanned aerial vehicle aircraft aerial photography | |
| CN102506824B (en) | Method for generating digital orthophoto map (DOM) by urban low altitude unmanned aerial vehicle | |
| CN111091613A (en) | Three-dimensional live-action modeling method based on unmanned aerial vehicle aerial survey | |
| CN113607135B (en) | Unmanned aerial vehicle inclination photogrammetry method for road and bridge construction field | |
| CN107796304B (en) | A kind of rail track tune of three-dimensional laser panorama draws method | |
| CN113192193A (en) | High-voltage transmission line corridor three-dimensional reconstruction method based on Cesium three-dimensional earth frame | |
| CN112652065A (en) | Three-dimensional community modeling method and device, computer equipment and storage medium | |
| CN110765542A (en) | Lightweight method of high-precision digital elevation model | |
| WO2022104251A1 (en) | Image analysis for aerial images | |
| CN114119892B (en) | Three-dimensional digital road network construction method based on BIM and GIS technologies | |
| CN113284239B (en) | Method and device for manufacturing electronic sand table of smart city | |
| CN111006645A (en) | Unmanned aerial vehicle surveying and mapping method based on motion and structure reconstruction | |
| Ren et al. | Future prospects of UAV tilt photogrammetry technology | |
| CN111197986B (en) | Real-time early warning and obstacle avoidance method for three-dimensional path of unmanned aerial vehicle | |
| CN117351162A (en) | Live-action three-dimensional planning design method based on digital twin | |
| CN112785686A (en) | Forest map construction method based on big data and readable storage medium | |
| CN115578525B (en) | Engineering line selection optimization system and method for complex environment | |
| Gu et al. | Surveying and mapping of large-scale 3D digital topographic map based on oblique photography technology | |
| CN112977822A (en) | Airport auxiliary unmanned aerial vehicle site selection system based on GIS + BIM | |
| CN113670266A (en) | Technology for measuring real estate title by utilizing unmanned aerial vehicle oblique photography | |
| JP2017174032A (en) | Traffic obstacle estimation system | |
| Doumit | Structure from motion technology for historic building information modeling of Toron fortress (Lebanon) | |
| Zhang et al. | Research on 3D modeling of UAV tilt photogrammetry | |
| CN115183746B (en) | Space-earth integrated image acquisition method applied to distribution network low-voltage line panoramic transparent user newspaper |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |