CN116188671A - River course and land integrated three-dimensional real scene modeling method - Google Patents
River course and land integrated three-dimensional real scene modeling method Download PDFInfo
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Abstract
The invention relates to a river course and water land integrated three-dimensional real scene modeling method, which comprises the following steps: an intelligent inversion method of river underwater three-dimensional topography of active and passive remote sensing data fusion, a construction method of a river land three-dimensional topography model of unmanned aerial vehicle on-board LiDAR technology, a hydraulic building regularization and structuring fine modeling technology based on BIM technology, a water-on-water-underwater integrated fusion and scene construction technology and the like. The invention can form the construction capability of the river course amphibious three-dimensional live-action model, expand the informatization solution of the river length system, support the requirements of intelligent perception of river, lake and reservoir management, full life cycle monitoring of hydraulic engineering and the like on basic geographic information data, and serve the digitized and intelligent construction of water conservancy.
Description
Technical Field
The invention relates to a terrain feature-based self-adaptive water depth model partition weighted fusion method, which obtains a higher-quality seamless south sea water depth dataset through steps of multisource water depth data and model pretreatment (comprising steps of chart vectorization, mathematical foundation unification, data cleaning and the like), digital water depth model (DBM) quality verification and comparison, multiscale terrain segmentation and partition, optimal spatial domain weighted fusion, actual measurement point recovery and self-adaptive neighborhood statistical filtering, and provides valuable references for timely reconstruction and update of a large-scale submarine topography dataset.
Background
Since the comprehensive promotion of the river growth in 2016, the requirements for the real-scene basic geographic information data are still outstanding in the aspects of intelligent perception of river, lake and reservoir management, full life cycle monitoring of hydraulic engineering and the like, and the river, lake and reservoir management system cannot adapt to the hydraulic digitization and intelligent construction process.
The river underwater measurement is basic underwater mapping work, aims to obtain three-dimensional coordinates of river topography points, mainly measures information such as position, water depth, water level, sound velocity, attitude and azimuth, and the core is water depth measurement. Currently, GNSS-RTK technology and multi-beam echo sounding technology are commonly used to acquire underwater three-dimensional coordinates. In recent years, optical inversion and acoustic detection are fused into hot spots, and are mainly focused on optimization of underwater topography inversion algorithms integrating hyperspectral and sonar data, and focusing is performed to explore the nonlinear relationship between water depth and hyperspectral data (Cheng et al, 2014;Poursanidis et al, 2019). In the aspect of visible light remote sensing sounding, with the penetration of machine learning and deep learning in the remote sensing field, empirical models such as BP neural network algorithm and the like are widely applied, and the extraction precision is higher (Collin et al, 2017). The effective data fusion can overcome the limitation of single observation data and can improve the utilization efficiency of the data.
The problem of repairing the data cavity in the land and water integrated three-dimensional terrain transition area is one of hot spots in the aspect of digital terrain model production. The integrated production level of the topography under water and the rapid construction capability of the high-fidelity three-dimensional scene still need to be improved, and research such as a seamless fusion method supported by the topography data under water of multiple sources is carried out by utilizing complementary information of the topography data of the topography of different types, different sources and different precision. Currently, project information and basic data are combined by means of unmanned plane, depth finder, BIM technology and the like, and an information sharing and integrated application management platform (Ren Cheng and the like, 2019; wenjuan and the like, 2019) is constructed. Aiming at the problems of low informatization degree, lag in supervision means and the like in project management of construction engineering, an on-water and underwater integrated river scene is established through seamless fusion of unmanned aerial vehicle oblique photography and BIM technology, and the informatization level of engineering management is improved to a certain extent (Zhang Xiaoqing and the like, 2020); the unmanned aerial vehicle aerial survey technology is used in reverse modeling engineering of the urban viaduct, and the digital surface model (Liu Shangwei, 2016) of the viaduct can be built by quickly obtaining and fusing data such as DEM, orthophoto map, BIM and the like; the unmanned aerial vehicle captured image is combined with the position data to obtain a real-scene three-dimensional model with geographic coordinates, and the real-scene three-dimensional model can be used for related applications (Zhang Huiying, 2019, etc.) such as surface features and area measurement. Obviously, the real land and water three-dimensional live-action construction can be realized only by deep fusion of land and water three-dimensional live-action modeling and remote sensing geographic information technology, however, the research and invention for quickly constructing the water-on-water-under-water integrated scene required by the water conservancy industry are relatively less.
Virtual reality is a means of simulating and reflecting the real world, and modeling techniques are core techniques in virtual reality (Yuan Ting, et al, 2021). Therefore, the practical demands of a series of digital hydraulic engineering such as hydrologic perception horizontal lifting, river space layout optimization, water conservancy monitoring function perfection and the like are oriented, the construction of a water conservancy 'new foundation' is promoted, and development of construction and application demonstration of a river and land integrated three-dimensional real model based on remote sensing and geographic information technology is urgently needed. In order to exert the advantages of three-dimensional live-action terrains and monomerized models in hydraulic engineering, the regularization and structuring fine modeling of hydraulic buildings based on the BIM technology is required to be carried out, a regularized modeling method based on CityEngine is adopted as a main part, a third party BIM software (Revit, 3D Max, blender and the like) structuring modeling method is adopted as an auxiliary part, and a plurality of modeling means (such as SFM photogrammetry) are matched with each other to study, invent and apply the collaborative modeling method.
Disclosure of Invention
The invention aims to solve the technical problems that: in the fields of intelligent sensing of river, lake and reservoir management, automatic monitoring of full life cycle of hydraulic engineering and the like, integration and fusion of multi-source remote sensing and geographic data are needed, so that the capability of integrated production of underwater topography on water and rapid construction of fine three-dimensional scenes is formed, and a feasible river course amphibious three-dimensional real model construction method system is constructed, and the technical flow is shown in figure 1.
In order to solve the technical problems, the invention provides a river course and water land integrated three-dimensional real scene modeling method, which comprises the following steps:
step 1, intelligent inversion of underwater three-dimensional topography, namely carrying out inversion of river underwater topography by utilizing ICESat-2 satellite-borne laser point cloud and Sentinel-2 high-resolution satellite remote sensing images;
step 3, land-water integrated seamless three-dimensional terrain fusion, namely repairing a transition region data hole at a land-water and underwater terrain joint by adopting a TIN differential curved surface terrain hole filling algorithm, so as to realize the land-water integrated seamless three-dimensional terrain seamless fusion;
and 4, constructing an amphibious integrated live-action model, namely, on the basis of the amphibious integrated seamless three-dimensional terrain, and carrying out regularization and structuring fine modeling on a hydraulic building by utilizing a CityEngine regularization modeling method, a BIM software structuring modeling method and an SFM photogrammetry modeling method so as to construct a river three-dimensional scene.
The invention has the following effective benefits:
(1) The river course water-land integrated three-dimensional live-action modeling framework provided by the invention can integrate a 'space-sky-ground-ship' multi-platform mapping means, integrate satellite-borne laser and multispectral active and passive remote sensing data to invert the river course underwater three-dimensional terrain, construct a river course land three-dimensional terrain model by using an unmanned aerial vehicle-borne LiDAR technology, and construct water-borne and underwater integrated seamless terrain by using multisource terrain data, so that the advanced water-borne and underwater terrain integrated production and the rapid construction capability of a fine three-dimensional scene in the industry are formed. The fusion framework can be extended to other regions.
(2) The invention provides a river underwater topography inversion method based on active and passive fusion under the support of measured water depth data, and the problems of low efficiency and poor topography modeling precision of a traditional mapping means are solved by fusing multisource data such as ICESat-2 data and Sentinel-2 data and the like, establishing a self-adaptive inversion model, improving a TIN differential curved surface algorithm, and establishing a river region high-fidelity underwater three-dimensional topography model.
(3) The invention provides a hydraulic building regularization and structuring fine modeling method based on BIM technology, which is characterized in that a cooperative modeling method with cooperation of multiple modeling means (such as SFM photogrammetry) is utilized, wherein the method is mainly a CityEngine platform regularization modeling method, a third party BIM software (Revit, 3D Max, blender and the like) structuring modeling method is assisted, and the hydraulic building regularization and structuring fine modeling can be realized.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a general flow chart of an embodiment of the present invention.
FIG. 2 is a schematic diagram of the inversion principle of the river underwater topography of the active and passive data fusion of the present invention.
FIG. 3 is a schematic view of LiDAR point cloud and high-resolution image data of the river land according to the present invention.
FIG. 4 is a schematic diagram of the digital terrain modeling of the present invention.
Figure 5 is a schematic view of an amphibious integrated seamless three-dimensional terrain fusion according to the present invention.
Figure 6 is a diagram of the expected effect of the amphibious integrated seamless three-dimensional terrain of the present invention.
FIG. 7 is a schematic diagram of the regularized and structured fine modeling of a hydraulic building according to the present invention.
FIG. 8 is a diagram showing expected effects of the river course water-land integrated live-action model of the invention.
Detailed Description
The technical route and operation steps of the present invention will be more apparent from the following detailed description of the present invention with reference to the accompanying drawings.
The embodiment of the technical scheme is carried out on a Zhejiang typical river channel (the key point is a new river upstream river section), and a river channel amphibious three-dimensional real-scene model construction method system of 'intelligent extraction of water and water topography-hydraulic building fine modeling-amphibious real-scene model construction'. By forming the capability of integrated production of underwater topography on water and rapid construction of a fine three-dimensional scene, a river channel amphibious integrated three-dimensional real model is built, the technical flow is shown in figure 1, and the method specifically comprises the following steps:
step 1, intelligent inversion of underwater three-dimensional topography, namely carrying out river underwater topography inversion of active and passive data fusion by utilizing ICESat-2 satellite-borne laser point cloud and Sentinel-2 high-resolution satellite remote sensing images, wherein the method comprises the following steps of:
1.1 And (3) denoising and extracting the ICESat-2 satellite-borne laser point cloud. ICESat-2 ATLAS satellite-borne laser radar data is used as reference data for active and passive remote sensing fusion shallow water underwater terrain extraction, and ICESat-2 satellite-borne laser point cloud denoising and extraction are required to be carried out in order to reduce interference of environmental noise on terrain extraction. And carrying out data downloading, format conversion, photon point cloud denoising, sea bottom point cloud extraction, water refraction correction, tide correction and other processing on the active laser satellite data.
1.2 ICESat-2 terrain inversion adaptation capability verification based on measured water depth data). In an important river channel region, multi-beam sonar sounding data and airborne LiDAR sounding data are collected, correlation analysis is carried out on ICESat-2 effective water depth points subjected to point cloud denoising and extraction through space superposition, and the large-scale terrain inversion self-adaption capability of satellite-borne laser point cloud data of different water areas is verified.
1.3 River topography inversion with active and passive fusion of ICESat-2 and Sentinel-2. Aiming at the problems of difficult implementation and measurement in the field of a complex river channel and low efficiency of the traditional surveying and mapping means, the Sentinel-2 remote sensing image data is used as a multispectral image extracted by active and passive fusion of the terrain, and active sounding data such as ICESat-2 point cloud data, ship sounding data and the like are fused to develop the inversion of the river channel terrain of the active and passive remote sensing fusion. And (3) carrying out denoising, extraction and other processing on ICESat-2 water depth data by using the point cloud, randomly selecting part of water depth points as a training set, using the rest points as a test set, establishing an inversion model (neural network algorithm), inverting the underwater topography, and generating the 10m resolution three-dimensional topography of the water bottom of the river channel (figure 2).
2.1 And (3) collecting space data by using an unmanned aerial vehicle. And (3) carrying out field surveying on the river course, and acquiring land LiDAR point cloud and high-resolution image data by adopting an unmanned aerial vehicle surveying and mapping means. And (3) performing route design according to the ground resolution required by practice, and setting technical parameters (including altitude design, course coverage, course overlapping, side overlapping, photo tilt angle, maximum flight tilt angle, altitude difference of adjacent photos and the like).
2.2 A LiDAR point cloud, and image data processing. And (3) performing internal processing on the data acquired in the last step, wherein the internal processing comprises unmanned aerial vehicle overlapping route cutting, map projection transformation and data coordinate conversion, point cloud data filtering and classification (comprising ground points, lower vegetation points, medium vegetation points, high and large vegetation points, building points, model key points and the like), spatial data resampling, data result accuracy analysis and the like (figure 3).
2.3 Digital terrain model establishment). Firstly, carrying out interpolation calculation on ground point cloud data obtained by filtering by using airborne LiDAR point cloud data, and constructing a high-fidelity DEM by an interpolation result; then, a river course DOM is manufactured by combining the high-fidelity DEM with the aerial image, and the DOM and the DEM are registered and fused; finally, registering based on the characteristic point cloud and the image data is carried out by utilizing the point cloud data and obvious characteristic points (such as road inflection points, river lifting, and the like) in the image, and registering and fusing of DOM and DEM are completed (fig. 4).
And 3, performing land-water integrated seamless three-dimensional terrain fusion, namely aiming at the problem of data hollows in a transition region of a river course land-water integrated three-dimensional terrain model, taking a public digital elevation product as filling data, repairing the data hollows in the transition region possibly existing at the joint of the water and underwater terrains by adopting a terrain hollowness filling algorithm based on a TIN differential curved surface, and realizing the land-water integrated seamless three-dimensional terrain seamless fusion. The method comprises the following steps:
3.1 And extracting the model to be filled. First, the mathematical basis of land three-dimensional terrain and underwater three-dimensional terrain data is unified. Then, selecting a public digital elevation product (such as a TanDEM-X DEM, an AW3D30 and the like) as an auxiliary model for cavity filling of the amphibious integrated model, and constructing buffer areas with different distances in the amphibious junction area to serve as a model to be filled of the amphibious transition area.
3.2 Land and water transition zone correction). And respectively extracting 15 pixel radius neighborhood pixel points around the underwater and land area transition areas to construct TIN, establishing a TIN differential curved surface by using the land and water transition areas, performing null seamless filling on the underwater three-dimensional terrain model, and correcting uncertainty of the land and water integrated three-dimensional terrain transition areas.
3.3 Model smoothing filtering). In order to further eliminate possible outliers, noise and holes, a neighborhood statistics-based adaptive filtering method is adopted to perform fusion model re-smoothing, so that the filling of holes in a NoData region in the model is realized, and the purpose of filtering the water depth outliers is achieved (figure 5).
Step 4, constructing an amphibious integrated live-action model, namely repairing a data hole of a transition area possibly existing at a water and underwater terrain joint by adopting a terrain hole filling algorithm of a TIN differential curved surface, so as to realize seamless fusion of the amphibious integrated seamless three-dimensional terrain, wherein the method comprises the following steps of:
4.1 BIM technology-based hydraulic building regularization and structured fine modeling. A regularized modeling method is adopted based on CityEngine, a third party BIM software (Revit, 3D Max, blender and the like) structured modeling method is adopted as an auxiliary, and a collaborative modeling method with a plurality of modeling means (such as SFM photogrammetry) matched with each other is adopted to carry out the regularized and structured fine modeling of the hydraulic building (figure 7). The CityEngine is used for large-scale three-dimensional modeling, perfect combination with ArcGIS can be achieved, the existing GIS construction result is fully utilized, and dynamic and parameterized BIM modeling is carried out through rules on the basis of two-dimensional space data. The reconstructed data sources of the CityEngine hydraulic building are oblique images obtained by aerial shooting and ground feature textures acquired by field industry.
4.2 A) scene data processing. The scene data includes map vector data, map image data, texture map data, individual structured model data, and the like. For complex hydraulic building models, three-dimensional scenes can be imported in the form of File GDB after the building modeling, and the positions, the sizes and the shapes of the models are adjusted to the optimal state through tools such as translation, scaling and rotation.
4.3 Three-dimensional scene construction and analysis based on citylengine). Based on the registration and fusion results of DOM and DEM, the model can be created for the whole scene after rule definition and model import of each part of the scene are completed. According to different layers (regular buildings, roads, water areas, trees, lawns and the like) of the scene, corresponding rules are given for modeling. Wherein, the water area layer can add dynamic water effect. The partial codes are as follows:
attrWaterPath＝"River/water.png"
Water-->
extrude(0.5)
comp(f){top:TopFacade_Water|side:Side}
TopFacade_Water-->
setupProjection(0,scope.xy,scope.sy,'1)
texture(WaterPath)
projectUV(0)
three-dimensional visibility analysis is performed using a CityEngine analysis module, including a visual field analysis (Viewspeed Tool), an opening degree analysis (View Dome Tool), a gallery analysis (View Corridor Tool), and the like.
Based on the generated WebScene amphibious real model, a CityEngine analysis module is utilized to carry out three-dimensional visibility analysis, including visual field analysis (ViewshedTool), opening degree analysis (ViewDomeTool), and vision gallery analysis (ViewCorridorTool) of the CityEngine, and the like, which are used for identifying and analyzing visible and invisible areas of the three-dimensional model and assisting operation, maintenance and decision of the hydraulic engineering.
The expected effect of the river course and water land integrated live-action model is shown in fig. 8.
In addition to the embodiments described above, other embodiments of the invention are possible. All technical schemes formed by equivalent substitution or equivalent transformation fall within the protection scope of the invention.
Claims (6)
1. A river course water and land integrated three-dimensional real scene modeling method comprises the following steps:
step 1, intelligent inversion of underwater three-dimensional topography, namely carrying out inversion of river underwater topography by utilizing ICESat-2 satellite-borne laser point cloud and Sentinel-2 high-resolution satellite remote sensing images;
step 2, constructing a river channel land three-dimensional terrain model, namely constructing a river channel digital terrain model by utilizing unmanned aerial vehicle to map a river channel land LiDAR point cloud and a high-resolution image in the field;
step 3, land-water integrated seamless three-dimensional terrain fusion, namely repairing a transition region data hole at a land-water and underwater terrain joint by adopting a TIN differential curved surface terrain hole filling algorithm, so as to realize the land-water integrated seamless three-dimensional terrain seamless fusion;
and 4, constructing an amphibious integrated live-action model, namely, on the basis of the amphibious integrated seamless three-dimensional terrain, and carrying out regularization and structuring fine modeling on a hydraulic building by utilizing a CityEngine regularization modeling method, a BIM software structuring modeling method and an SFM photogrammetry modeling method so as to construct a river three-dimensional scene.
2. The river course and water land integrated three-dimensional real scene modeling method according to claim 1, wherein the method comprises the following steps: the specific steps of the step 1 are as follows:
1.1 Denoising and extracting the ICESat-2 satellite-borne laser point cloud, and carrying out data downloading, format conversion, photon point cloud denoising, submarine point cloud extraction, water refraction correction and tide correction on the ICESat-2 ATLAS satellite-borne laser radar data;
1.2 Carrying out correlation analysis on the ICESat-2 effective water depth points subjected to point cloud denoising and extraction by space superposition, and verifying the large-scale terrain inversion self-adaption capability of the satellite-borne laser point cloud data of different water areas;
1.3 And (3) carrying out river terrain inversion of active and passive remote sensing fusion on the ICESat-2 and the Sentinel-2 by fusing ICESat-2 point cloud data, ship measured water depth data and Sentinel-2 remote sensing images.
3. The river course and water land integrated three-dimensional real scene modeling method according to claim 1, wherein the method comprises the following steps: the specific steps of the step 2 are as follows:
2.1 Spatial data unmanned aerial vehicle acquisition): designing a ground resolution ratio to carry out a route, setting flight technical parameters, and obtaining land LiDAR point cloud and high-resolution image data;
2.2 Processing LiDAR point cloud and image data, and performing internal processing on the data acquired in the last step, wherein the internal processing comprises unmanned aerial vehicle overlapping route cutting, map projection transformation and data coordinate conversion, point cloud data filtering and classification, spatial data resampling and data result precision analysis;
2.3 And establishing a digital terrain model, performing interpolation calculation on the ground point cloud data obtained by filtering, constructing a high-fidelity DEM (digital elevation model) by using an interpolation result, manufacturing a river course DOM by using the high-fidelity DEM in combination with an aerial image, registering and fusing the DOM and the DEM, and registering and fusing the DOM and the DEM by using the point cloud data and obvious characteristic points in the image.
4. The river course and water land integrated three-dimensional real scene modeling method according to claim 1, wherein the method comprises the following steps: the specific steps of the step 3 are as follows:
3.1 Extracting a model to be filled, namely firstly unifying mathematical foundations of three-dimensional land topography and underwater three-dimensional topography data; then, selecting a public digital elevation product as an auxiliary model for cavity filling of an amphibious integrated model, and constructing buffer areas with different distances in an amphibious junction area to serve as a model to be filled of an amphibious transition area;
3.2 Land and water transition zone correction-utilizing the above three types of topographic data to extract the periphery of the land and water transition zone respectivelyNConstructing TIN by pixel points of each pixel radius neighborhood, constructing a TIN differential curved surface by using an amphibious transition area, performing null seamless filling on an underwater three-dimensional terrain model, and correcting uncertainty of the amphibious integrated three-dimensional terrain transition area;
3.3 And model smoothing filtering, namely carrying out fusion model re-smoothing based on a neighborhood statistics self-adaptive filtering method, so as to fill cavities in a hollow value region of the model, thereby achieving the purpose of filtering abnormal water depth values.
5. The river course and water land integrated three-dimensional real scene modeling method according to claim 1, wherein the method comprises the following steps: the specific steps of the step 4 are as follows:
4.1 The method comprises the following steps of) carrying out hydraulic building regularization and structuring fine modeling based on BIM technology, and carrying out hydraulic building regularization and structuring fine modeling based on a CityEngine regularization modeling method, a BIM software structuring modeling method and an SFM photogrammetry modeling method;
4.2 Scene data processing, processing scene data such as map vector data, map image data, texture map data, and monomer structured model data.
4.3 Based on the three-dimensional scene construction and analysis of the CityEngine, based on the registration and fusion results of the DOM and the DEM, importing rule definition and model of each part of the scene, and carrying out model creation and three-dimensional visibility analysis on the whole scene.
6. The river course and water land integrated three-dimensional real scene modeling method according to claim 1, wherein the method comprises the following steps: in the step 3.2 of the process,Nthe value is 15.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116626685A (en) * | 2023-07-20 | 2023-08-22 | 山东大禹水务建设集团有限公司 | River sediment real-time monitoring method and system based on machine learning |
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| CN117496084A (en) * | 2024-01-03 | 2024-02-02 | 江西师范大学 | Large lake scene modeling method, system, computer equipment and storage medium |
| CN117853678A (en) * | 2024-03-08 | 2024-04-09 | 陕西天润科技股份有限公司 | Method for carrying out three-dimensional materialization transformation on geospatial data based on multi-source remote sensing |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116626685A (en) * | 2023-07-20 | 2023-08-22 | 山东大禹水务建设集团有限公司 | River sediment real-time monitoring method and system based on machine learning |
| CN116626685B (en) * | 2023-07-20 | 2023-09-29 | 山东大禹水务建设集团有限公司 | River sediment real-time monitoring method and system based on machine learning |
| CN116883611A (en) * | 2023-09-07 | 2023-10-13 | 中交天航南方交通建设有限公司 | Channel silt distribution active detection and identification method combining GIS channel information |
| CN116883611B (en) * | 2023-09-07 | 2023-12-15 | 中交天航南方交通建设有限公司 | Channel silt distribution active detection and identification method combining GIS channel information |
| CN117496084A (en) * | 2024-01-03 | 2024-02-02 | 江西师范大学 | Large lake scene modeling method, system, computer equipment and storage medium |
| CN117853678A (en) * | 2024-03-08 | 2024-04-09 | 陕西天润科技股份有限公司 | Method for carrying out three-dimensional materialization transformation on geospatial data based on multi-source remote sensing |
| CN117853678B (en) * | 2024-03-08 | 2024-05-17 | 陕西天润科技股份有限公司 | Method for carrying out three-dimensional materialization transformation on geospatial data based on multi-source remote sensing |
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