Construction method, system and equipment of space terrain model, medium and program product

Abstract

The invention provides a space terrain model construction method, system and device, a medium and a program product, and the construction method comprises the steps: obtaining target region terrain information of a target region; wherein different target areas correspond to different levels of preset requirements; the preset demand is used for constraining the spatial feature granularity corresponding to the terrain information of the target area; performing frame line extraction on the terrain information of the target area based on the preset demand to obtain a target terrain frame line; and determining at least two preset data sources corresponding to the target area according to the preset demand, and filling the target terrain frame line based on target data collected by the at least two preset data sources to form a target space terrain model corresponding to the target area. Through the construction method of the space terrain model provided by the invention, automatic, rapid and accurate construction of various space terrain models is realized.

Description

Technical Field

[0001] The present disclosure relates to the field of modeling technology, and in particular to a method, system, device, medium and program product for constructing a spatial terrain model. Background Art

[0002] In recent years, my country's real-scene 3D has been rapidly promoted and developed. Real-scene 3D is a kind of 3D image processing technology that can be used to analyze the human production, life and environment within a certain range. The digital space that reflects and expresses things in a real, three-dimensional and time-series manner is an important new infrastructure that provides a unified spatial foundation for the informatization of various departments. The real-life three-dimensional construction will provide a unified digital space base for applications such as digital twins and city information models (CIM). It can be applied to natural resources, tourism, transportation, national defense, water conservancy and other aspects, and will truly restore the real world.

[0003] Among them, the spatial feature terrain model is a very important element in real-life three-dimensional images. It is a spatial model that describes the changes in terrain, spatial forms and spatial shape characteristics in various real-world environments.

[0004] However, the current model results are difficult to accurately express the shape characteristics of spatial terrain for some characteristic terrains, such as river and lake embankments, urban underpass terrain, sunken squares, tunnel entrances and exits, garage entrances and exits, road shoulders, etc. Summary of the invention

[0005] The technical problem to be solved by the present disclosure is to overcome the defect in the prior art that the shape characteristics of the spatial terrain cannot be reasonably and finely expressed, and to provide a method, system, device, medium and program product for constructing a spatial terrain model.

[0006] The present invention solves the above technical problems through the following technical solutions:

[0007] According to a first aspect of the present disclosure, a method for constructing a spatial terrain model is provided, the method comprising:

[0008] Acquire target area terrain information of the target area; wherein different target areas correspond to different levels of preset requirements; the preset requirements are used to constrain the spatial feature granularity corresponding to the target area terrain information;

[0009] Extracting the frame line of the target area terrain information based on the preset requirements to obtain the frame line of the target terrain;

[0010] According to the preset requirements, it is determined that the target area corresponds to at least two preset data sources, and the target terrain framework line is filled based on the target data collected by at least two preset data sources to form a target space terrain model corresponding to the target area.

[0011] Preferably, the preset requirements under different levels of the spatial feature granularity are correspondingly provided with different types of the preset data sources; wherein the number of types of the preset data sources is positively correlated with the level of the spatial feature granularity under the preset requirements;

[0012] and / or;

[0013] Each of the preset requirement matching is configured with a corresponding different preset data source and a processing order between the target terrain framework line.

[0014] Preferably, when the preset requirement corresponds to the spatial feature granularity of the first level, the target terrain framework line is a first-level terrain framework line;

[0015] The step of filling the target terrain framework line based on the target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes:

[0016] Based on the two preset data sources, first target data information and second target data information corresponding to the terrain information of the target area are respectively obtained;

[0017] Merging the first target data information with the first-level terrain framework line to form a first initial spatial terrain model;

[0018] The second target data information is integrated into the first initial spatial terrain model to form the target spatial terrain model.

[0019] Preferably, when the preset requirement corresponds to the second level of the spatial feature granularity, the target terrain framework line is a secondary terrain framework line; wherein the second level of the spatial feature granularity is finer than the first level of the spatial feature granularity;

[0020] The step of filling the target terrain framework line based on the target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes:

[0021] Based on the three preset data sources, third target data information, fourth target data information and fifth target data information corresponding to the terrain information of the target area are respectively obtained;

[0022] Merging the third target data information with the secondary terrain framework line to form a second initial spatial terrain model;

[0023] fusing the fourth target data information into the second initial spatial terrain model to form a third initial spatial terrain model;

[0024] The fifth target data information is integrated into the third initial spatial terrain model to form the target spatial terrain model.

[0025] Preferably, when the preset requirement corresponds to the spatial feature granularity of the third level, the target terrain framework line is a third-level terrain framework line; wherein the spatial feature granularity of the third level is finer than the spatial feature granularity of the second level;

[0026] The step of filling the target terrain framework line based on the target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes:

[0027] Based on the four preset data sources, respectively obtain sixth target data information, seventh target data information, eighth target data information and ninth target data information corresponding to the terrain information of the target area;

[0028] Merging the sixth target data information with the third-level terrain framework line to form a fourth initial spatial terrain model;

[0029] fusing the seventh target data information into the fourth initial spatial terrain model to form a fifth initial spatial terrain model;

[0030] fusing the eighth target data information into the fourth initial spatial terrain model to form a sixth initial spatial terrain model;

[0031] The ninth target data information is integrated into the sixth initial spatial terrain model to form the target spatial terrain model.

[0032] Preferably, after the step of filling the target terrain framework line based on the target data collected from at least two preset data sources, the construction method further comprises:

[0033] Performing Delaunay (a method of dividing a point set on a plane into triangular meshes) triangulation on the filled target terrain framework line to form a target spatial terrain model corresponding to the terrain information of the target area;

[0034] and / or,

[0035] The target data collected by the preset data source includes data collected by remote sensing images, data collected by laser radar, vehicle-mounted point cloud data or terrain map data within the same period;

[0036] and / or,

[0037] The data collected by the two preset data sources include data collected by remote sensing images and data collected by laser radar in the same period of time;

[0038] and / or,

[0039] The data collected by the three preset data sources include data collected by remote sensing images, data collected by laser radar, and vehicle-mounted point cloud data within the same period of time;

[0040] and / or,

[0041] The data collected by the four preset data sources include data collected by remote sensing images within the same period of time, data collected by lidar, vehicle-mounted point cloud data and topographic map data.

[0042] According to a second aspect of the present disclosure, a system for constructing a spatial terrain model is provided, the system comprising:

[0043] A data acquisition module, used to acquire target area terrain information of a target area; wherein different target areas correspond to different levels of preset requirements; and the preset requirements are used to constrain the spatial feature granularity corresponding to the target area terrain information;

[0044] A terrain frame line extraction module, used to extract frame lines from the target area terrain information based on the preset requirements to obtain target terrain frame lines;

[0045] The target model building module is used to determine that the target area corresponds to at least two preset data sources according to the preset requirements, and fill the target terrain framework line based on the target data collected by at least two of the preset data sources to form a target space terrain model corresponding to the target area.

[0046] Preferably, the preset requirements under different levels of the spatial feature granularity are correspondingly provided with different types of the preset data sources; wherein the number of types of the preset data sources is positively correlated with the level of the spatial feature granularity under the preset requirements;

[0047] and / or;

[0048] Each of the preset requirement matching is configured with a corresponding different preset data source and a processing order between the target terrain framework line.

[0049] Preferably, when the preset requirement corresponds to the spatial feature granularity of the first level, the target terrain framework line is a first-level terrain framework line;

[0050] The target model building module is specifically used for:

[0051] Based on the two preset data sources, first target data information and second target data information corresponding to the terrain information of the target area are respectively obtained;

[0052] Merging the first target data information with the first-level terrain framework line to form a first initial spatial terrain model;

[0053] The second target data information is integrated into the first initial spatial terrain model to form the target spatial terrain model.

[0054] Preferably, when the preset requirement corresponds to the second level of the spatial feature granularity, the target terrain framework line is a secondary terrain framework line; wherein the second level of the spatial feature granularity is finer than the first level of the spatial feature granularity;

[0055] The target model building module is specifically used for:

[0056] Based on the three preset data sources, third target data information, fourth target data information and fifth target data information corresponding to the terrain information of the target area are respectively obtained;

[0057] Merging the third target data information with the secondary terrain framework line to form a second initial spatial terrain model;

[0058] fusing the fourth target data information into the second initial spatial terrain model to form a third initial spatial terrain model;

[0059] The fifth target data information is integrated into the third initial spatial terrain model to form the target spatial terrain model.

[0060] Preferably, when the preset requirement corresponds to the spatial feature granularity of the third level, the target terrain framework line is a third-level terrain framework line; wherein the spatial feature granularity of the third level is finer than the spatial feature granularity of the second level;

[0061] The target model building module is specifically used for:

[0062] Based on the four preset data sources, respectively obtain sixth target data information, seventh target data information, eighth target data information and ninth target data information corresponding to the terrain information of the target area;

[0063] Merging the sixth target data information with the third-level terrain framework line to form a fourth initial spatial terrain model;

[0064] fusing the seventh target data information into the fourth initial spatial terrain model to form a fifth initial spatial terrain model;

[0065] fusing the eighth target data information into the fourth initial spatial terrain model to form a sixth initial spatial terrain model;

[0066] The ninth target data information is integrated into the sixth initial spatial terrain model to form the target spatial terrain model.

[0067] Preferably, the target model construction module is further used for: after the step of filling the target terrain framework line with the target data collected based on at least two of the preset data sources, constructing a Delaunay triangulation network on the filled target terrain framework line to form a target space terrain model corresponding to the terrain information of the target area;

[0068] and / or,

[0069] The target data collected by the preset data source includes data collected by remote sensing images, data collected by laser radar, vehicle-mounted point cloud data or terrain map data within the same period;

[0070] and / or,

[0071] The data collected by the two preset data sources include data collected by remote sensing images and data collected by laser radar in the same period of time;

[0072] and / or,

[0073] The data collected by the three preset data sources include data collected by remote sensing images, data collected by laser radar, and vehicle-mounted point cloud data within the same period of time;

[0074] and / or,

[0075] The data collected by the four preset data sources include data collected by remote sensing images within the same period of time, data collected by lidar, vehicle-mounted point cloud data and topographic map data.

[0076] According to a third aspect of the present disclosure, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and used to run on the processor, wherein when the processor executes the computer program, the method for constructing a spatial terrain model described in the first aspect of the present disclosure is implemented.

[0077] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for constructing a spatial terrain model described in the first aspect of the present disclosure is implemented.

[0078] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the method for constructing a spatial terrain model according to the first aspect of the present disclosure is implemented.

[0079] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present disclosure.

[0080] The positive and progressive effects of this disclosure are:

[0081] The method for constructing a spatial terrain model provided by the present disclosure aims at fast, high-precision, high-level of refinement, and precise feature description, utilizes multiple data sources, takes into account the shape characteristics and topological relationships of terrain elements, and realizes the automatic, fast and precise construction of a spatial feature terrain model. The method for constructing a spatial terrain model provided by the present disclosure can be widely used in the construction of regional or city-level spatial feature terrain models, and can efficiently realize the construction of a coarse model, a relatively fine model, and then a fine model. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 A schematic diagram of a flow chart of a method for constructing a spatial terrain model provided in Embodiment 1 of the present disclosure;

[0083] Figure 2 A schematic diagram of a process for obtaining a terrain framework line provided in Embodiment 1 of the present disclosure;

[0084] Figure 3 The structure diagram after extracting the terrain framework line provided in Example 1 of the present disclosure Figure 1 ;

[0085] Figure 4 The structure diagram after extracting the terrain framework line provided in Example 1 of the present disclosure Figure 2 ;

[0086] Figure 5 A flowchart of a construction method when the preset requirement provided in Embodiment 1 of the present disclosure is the first level;

[0087] Figure 6 A flowchart of a construction method when the preset requirement provided in Embodiment 1 of the present disclosure is the second level;

[0088] Figure 7 A schematic diagram of a model 1 constructed by the method for constructing a spatial terrain model provided in Example 1 of the present disclosure;

[0089] Figure 8 A flowchart of a construction method when the preset requirement provided in Embodiment 1 of the present disclosure is the third level;

[0090] Fig. 9A schematic diagram of a model 2 constructed by the method for constructing a spatial terrain model provided in Example 1 of the present disclosure;

[0091] Fig.10 A schematic diagram of modules of a system for constructing a spatial terrain model provided in Embodiment 2 of the present disclosure;

[0092] Fig.11 This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present disclosure. DETAILED DESCRIPTION

[0093] The present disclosure is further described below by way of examples, but the present disclosure is not limited to the scope of the examples.

[0094] Prefixes such as "first" and "second" are used in the embodiments of the present disclosure only to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects. The use of prefixes such as ordinal numbers to distinguish description objects in the embodiments of the present disclosure does not constitute a limitation on the described objects. For the statement of the described objects, please refer to the description in the context of the claims or embodiments, and no unnecessary limitation should be constituted due to the use of such prefixes. In addition, in the description of the present embodiment, unless otherwise specified, the meaning of "plurality" is two or more.

[0095] In the urban planning industry, spatial characteristic terrain models are important basic data for urban planning. They can be used for land use assessment, water source protection area planning, water system planning, landscape planning, and three-dimensional planning approval scheme effect display and scheme comparison; in municipal management departments, they can be used to extract contour and slope distribution information, assist in road design and construction, road cross-section and longitudinal section analysis, underground pipeline design and underground space management; in water conservancy and meteorological departments, they can be used for water flow analysis, watershed analysis, urban waterlogging analysis, etc., which plays a positive role in urban flood and rainstorm warnings.

[0096] However, the current method of constructing spatial feature terrain models still has the following problems to be solved:

[0097] (1) The data source is single, mostly using single methods such as aerial images, topographic maps or field measurements;

[0098] (2) The construction process is time-consuming, costly, and difficult to update;

[0099] (3) The construction method is not intelligent enough and often requires manual intervention and inspection;

[0100] (4) The model results are difficult to accurately express the shape characteristics of spatial terrain, especially for some characteristic terrains, such as river and lake embankments, urban underpass terrain, sunken squares, tunnel entrances and exits, garage entrances and exits, road shoulders, etc.

[0101] In view of this, the present disclosure provides a method, system, device, medium and program product for constructing a spatial terrain model, so as to realize automatic, rapid and accurate construction of various spatial terrain models.

[0102] Example 1

[0103] Figure 1 This is a flow chart of a method for constructing a spatial terrain model provided in Example 1 of the present disclosure.

[0104] like Figure 1 As shown, the method for constructing the spatial terrain model includes:

[0105] S11: Obtaining target area terrain information of the target area; wherein different target areas correspond to different levels of preset requirements; the preset requirements are used to constrain the spatial feature granularity corresponding to the target area terrain information.

[0106] The preset requirements in this embodiment determine different spatial feature granularities based on the size of the area to be described, the degree of sophistication for different applications, the actual data collection capability, etc.

[0107] This disclosure establishes the basic criteria for determining the level of spatial feature granularity:

[0108] (1) Applicability criteria, that is, to determine whether the description is oriented towards specific applications. Different applications have different description emphases.

[0109] (2) Applicability criterion, that is, it must meet the application requirements without blindly pursuing high precision.

[0110] (3) Practicality criterion, that is, combining actual data collection methods. The level is determined based on the data collection conditions of remote sensing images, topographic maps, lidar and vehicle-mounted point clouds.

[0111] (4) Regional criteria: the description granularity of different regions can be slightly different, with emphasis on key areas.

[0112] From the perspective of spatial description scope, for example, when constructing large-area landforms, the focus should be on macro-terrain undulations, such as mountains, rivers, lakes, roads, etc., and the granularity of feature description is relatively coarse; when facing city-level applications, the focus is on urban landscapes, which require finer details than macro-terrain. It is necessary to finely express the terrain undulations of urban road landscapes, green belts, and parks and green spaces, and the granularity of feature description should be finer; further, when facing local key areas, such as key scenic spots, historical and cultural protection areas, urban core areas and other areas, the demand for spatial terrain characteristics is more refined, and it is necessary to express fine terrain features such as road shoulders, underpass terrain, tunnel entrances and exits, and garage entrances and exits, and the granularity of feature description is required to be very fine.

[0113] From the perspective of application fields and application needs, for example, in urban planning analysis, there is no need to pay attention to the detailed description of spatial terrain features, and the granularity of feature description is suitable for a coarse level. The corresponding extracted terrain framework line is as follows: Figure 3 As shown, otherwise it will waste resources. In urban refined management applications, such as urban waterlogging analysis, detailed descriptions of spatial features are required, such as shoulders, underpasses, tunnel entrances and exits, etc. At this time, the corresponding fine feature granularity level is obtained. The corresponding extracted terrain framework line is as follows Figure 4 shown.

[0114] S12: Extracting the framework line of the target area terrain information based on preset requirements to obtain the target terrain framework line.

[0115] like Figure 2 As shown, in this embodiment, after determining the level of the corresponding spatial feature granularity according to the preset requirements, different remote sensing images are loaded respectively, and the terrain framework line data of the corresponding level is extracted according to the level through the remote sensing image data, and the terrain framework data lines corresponding to different remote sensing images are merged to obtain the target terrain framework data lines.

[0116] S13: According to preset requirements, determine that the target area corresponds to at least two preset data sources, and fill the target terrain framework line based on the target data collected by the at least two preset data sources to form a target space terrain model corresponding to the target area.

[0117] In this embodiment, different types of preset data sources are provided corresponding to preset requirements at different levels of spatial feature granularity; wherein the number of types of preset data sources is positively correlated with the level of spatial feature granularity at the preset requirements.

[0118] In this embodiment, each preset requirement matching is configured with a corresponding different preset data source and a processing order between the target terrain framework line.

[0119] In one implementation, the target data collected by the preset data source includes data collected by remote sensing images, data collected by lidar, vehicle-mounted point cloud data, or topographic map data within the same period of time.

[0120] By utilizing multiple data sources, taking into account the shape characteristics and topological relationships of terrain elements, and aiming at fast, high-precision, high-level of detail, and accurate feature description, the automatic, fast, and accurate construction of spatial feature terrain models can be achieved.

[0121] In this embodiment, after the step of filling the target terrain framework line based on the target data collected from at least two preset data sources, the construction method further includes:

[0122] The filled target terrain framework line is subjected to Delaunay triangulation to form a target spatial terrain model corresponding to the terrain information of the target area.

[0123] In this embodiment, the spatial feature granularity is divided into three levels based on the degree of refinement of the spatial feature terrain model description and application requirements and other factors. Each level contains spatial terrain feature elements of different degrees of refinement. Considering the seamless continuity of the spatial feature terrain, the first level to the third level are progressive inclusion relationships from coarse to fine. Among them, the spatial feature terrain elements described in the first level include mountains, rivers, lakes, roads, residential areas, etc. The spatial feature terrain elements described in the second level are based on the first level and also include green belts, building bases, slopes, steep slopes, parks and green spaces, etc. The spatial feature terrain elements described in the third level are based on the second level and also include road shoulders, underpass terrain, tunnel entrances and exits, garage entrances and exits, bridge undulations, etc.

[0124] like Figure 5 As shown, in this embodiment, when the preset requirement corresponds to the first level of spatial feature granularity, the target terrain framework line is a first-level terrain framework line; the step of filling the target terrain framework line based on target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes:

[0125] S21: Acquire first target data information and second target data information corresponding to the terrain information of the target area based on two preset data sources respectively.

[0126] The data collected by the two preset data sources include data collected by remote sensing images and data collected by lidar in the same period of time.

[0127] S22: Fusing the first target data information with the primary terrain framework line to form a first initial spatial terrain model.

[0128] S23: Fusing the second target data information into the first initial spatial terrain model to form a target spatial terrain model.

[0129] In one implementation, the spatial feature granularity level is obtained according to preset requirements, and terrain framework line data of corresponding levels are extracted from the remote sensing image data according to different levels. If the spatial feature granularity is the first level, the terrain framework line extracted in the previous step is fused with the lidar data, that is, the elevation value of the terrain framework line is re-interpolated based on the lidar data, and finally a Delaunay triangulation is constructed to complete the construction of the spatial feature terrain model.

[0130] like Figure 6 As shown, in this embodiment, when the preset requirement corresponds to the second level of spatial feature granularity, the target terrain framework line is a secondary terrain framework line; wherein the second level of spatial feature granularity is finer than the first level of spatial feature granularity; the step of filling the target terrain framework line based on target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes:

[0131] S31: obtaining third target data information, fourth target data information and fifth target data information corresponding to the terrain information of the target area based on three preset data sources respectively.

[0132] Among them, the data collected by the three preset data sources include data collected by remote sensing images within the same period of time, data collected by lidar, and vehicle-mounted point cloud data.

[0133] S32: Fusing the third target data information with the secondary terrain framework line to form a second initial spatial terrain model.

[0134] S33: integrating the fourth target data information into the second initial spatial terrain model to form a third initial spatial terrain model.

[0135] S34: Fusing the fifth target data information into the third initial spatial terrain model to form a target spatial terrain model.

[0136] Among them, the target space terrain model is formed as follows Figure 7 shown.

[0137] In one implementation, the spatial feature granularity level is obtained according to preset requirements, and terrain framework line data of corresponding levels are extracted according to different levels. If the spatial feature granularity is the second level, the first level fusion processing is completed first, and then the data after the first level fusion processing is fused with the vehicle-borne point cloud data, that is, the elevation value of the terrain framework line is re-interpolated according to the vehicle-borne point cloud data, and finally the Delaunay triangulation is constructed to complete the construction of the spatial feature terrain model.

[0138] like Figure 8 As shown, in this embodiment, when the preset requirement corresponds to the third level of spatial feature granularity, the target terrain framework line is a third level terrain framework line; wherein the third level of spatial feature granularity is finer than the second level of spatial feature granularity; the target terrain framework line is filled with target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area, including:

[0139] S41: Acquire sixth target data information, seventh target data information, eighth target data information and ninth target data information corresponding to the terrain information of the target area based on four preset data sources respectively.

[0140] Among them, the data collected by the four preset data sources include data collected by remote sensing images within the same period of time, data collected by lidar, vehicle-mounted point cloud data, and topographic map data.

[0141] S42: Fusing the sixth target data information with the third-level terrain framework line to form a fourth initial spatial terrain model.

[0142] S43: integrating the seventh target data information into the fourth initial spatial terrain model to form a fifth initial spatial terrain model.

[0143] S44: integrating the eighth target data information into the fourth initial spatial terrain model to form a sixth initial spatial terrain model.

[0144] S45: Fusing the ninth target data information into the sixth initial spatial terrain model to form a target spatial terrain model.

[0145] Among them, the target space terrain model is formed as follows Fig. 9 shown.

[0146] In this embodiment, corresponding to the spatial feature granularity level, the terrain framework line data are also divided into three levels. The first-level terrain framework line data are the spatial characteristic lines of the topography and landforms in a large area, such as water edges, road edges, ridge lines, valley lines, residential edges, etc.; the second-level terrain framework line data are the spatial characteristic lines of the topography and landforms at the city or regional level, such as the building base edges, green belt edges, slope lines, steep slope lines, etc.; the third-level terrain framework line data are the spatial characteristic lines of the topography and landforms of local key areas, historical style areas, urban core areas, etc., such as road shoulder lines, underpass edges, tunnel entrance and exit edges, garage entrance and exit edges, bridge edges, etc.

[0147] In one implementation, the spatial feature granularity level is obtained according to preset requirements, and terrain framework line data of corresponding levels are extracted according to different levels. If the spatial feature granularity is the third level, the vehicle-borne point cloud data is first used to further extract the third-level terrain framework line data, such as road shoulder edge lines, underpass edge lines, tunnel entrance and exit edge lines, bridge edge lines and other framework lines, and then the second-level fusion processing is completed. Next, the second-level fusion processing results are merged with the third-level framework lines extracted from the vehicle-borne point cloud, and finally a Delaunay triangulation is constructed to complete the construction of the spatial feature terrain model.

[0148] In this embodiment, different target data information is integrated with different initial spatial terrain models by interpolation.

[0149] The method for constructing a spatial terrain model provided by the present disclosure aims at fast, high-precision, high-level of refinement, and precise feature description, utilizes multiple data sources, takes into account the shape characteristics and topological relationships of terrain elements, and realizes the automatic, fast and precise construction of a spatial feature terrain model. The method for constructing a spatial terrain model provided by the present disclosure can be widely used in the construction of regional or city-level spatial feature terrain models, and can efficiently realize the construction of a coarse model, a relatively fine model, and then a fine model.

[0150] The method for constructing a spatial terrain model provided by the present disclosure aims at fast, high-precision, high-level of refinement, and precise feature description, utilizes multiple data sources, takes into account the shape characteristics and topological relationships of terrain elements, and realizes the automatic, fast and precise construction of a spatial feature terrain model. The method for constructing a spatial terrain model provided by the present disclosure can be widely used in the construction of regional or city-level spatial feature terrain models, and can efficiently realize the construction of a coarse model, a relatively fine model, and then a fine model.

[0151] The following is a specific implementation method to illustrate the implementation principle of the method for constructing a spatial terrain model in the embodiment of the present disclosure:

[0152] In the construction and implementation of the spatial characteristic terrain model of Suzhou Gusu District, the basic information of Gusu District was obtained: Suzhou Gusu District is located in , Taihu Lake Basin, located in a historical and cultural city Center, with a total area of ​​85.1 square kilometers, Gusu District is mainly composed of gentle plains, with low terrain, slowly sloping from west to east, the plain's altitude is 3 to 4 meters, and the Yangcheng Lake and Wujiang area is only 2 meters. Low mountains and hills are scattered, 100 to 300 meters high. Gusu District has abundant large and small river resources, forming a complete river network and lake system with a total length of 1,457 kilometers. In addition, Gusu District also has a large number of underpass terrain and various bridges.

[0153] Through the analysis of the above data, the preset requirements for the construction of the spatial terrain model in Gusu District are as follows:

[0154] For the entire Gusu District, the first level of fine spatial feature granularity was adopted. After extracting the corresponding terrain framework lines, the data obtained by the lidar was loaded and fused with the terrain framework lines. Specifically, the data obtained by the lidar was interpolated into the terrain framework lines, and the Delaynay triangulation was constructed according to the fusion results to complete the construction of the spatial terrain of the entire Gusu District.

[0155] Taking into account the characteristics and importance of the 14.2 square kilometers within the moat of Gusu District, the second-level spatial feature granularity was adopted. After extracting the corresponding terrain framework lines, the terrain framework lines were first fused with the data obtained by the lidar, and then the terrain framework lines were fused again by loading the vehicle-borne point cloud data. The Delaynay triangulation was constructed based on the fusion results, thus completing the spatial terrain construction of the moat of Gusu District.

[0156] For key protection areas such as Pingjiang Road, Shantang Street, and Lion Grove, the third level of fine spatial feature granularity was adopted. After the corresponding terrain framework lines were extracted, the terrain framework lines were first fused with the data obtained by the lidar, and then fused for the second time by loading the vehicle-mounted point cloud data. Finally, the terrain framework lines were fused for the third time by loading the topographic map data. The Delaynay triangulation was constructed based on the fusion results, thus completing the spatial terrain construction of different key protection areas.

[0157] The framework lines of Gusu District are extracted according to the preset requirements of different levels, and the framework lines are fused with the data collected from different data sources to construct a spatial terrain model of Gusu District.

[0158] Example 2

[0159] Corresponding to the aforementioned embodiment of the method for constructing a spatial terrain model, the present disclosure also provides an embodiment of a system for constructing a spatial terrain model.

[0160] Fig.10 A schematic diagram of a module of a system for constructing a spatial terrain model provided in Embodiment 2 of the present disclosure, the system comprising:

[0161] The data acquisition module 100 is used to acquire the target area terrain information of the target area; wherein different target areas correspond to different levels of preset requirements; the preset requirements are used to constrain the spatial feature granularity corresponding to the target area terrain information;

[0162] A terrain frame line extraction module 200 is used to extract frame lines from the target area terrain information based on preset requirements to obtain target terrain frame lines;

[0163] The target model building module 300 is used to determine that the target area corresponds to at least two preset data sources according to preset requirements, and fill the target terrain framework line based on the target data collected by the at least two preset data sources to form a target space terrain model corresponding to the target area.

[0164] In this embodiment, different types of preset data sources are correspondingly set for preset requirements at different levels; wherein the number of types of preset data sources is positively correlated with the level of the preset requirements.

[0165] Different preset requirement matching settings have different preset data sources and processing orders with respect to the target terrain framework line.

[0166] When the preset requirement in this embodiment is the first level of spatial feature granularity, the target terrain framework line is the first level terrain framework line;

[0167] The target model building module 300 is specifically used for:

[0168] Based on two preset data sources, first target data information and second target data information corresponding to the terrain information of the target area are respectively obtained;

[0169] Merging the first target data information with the primary terrain framework line to form a first initial spatial terrain model;

[0170] The second target data information is fused into the first initial spatial terrain model to form a target spatial terrain model.

[0171] When the preset requirement in this embodiment is the second-level spatial feature granularity, the target terrain framework line is a secondary terrain framework line; wherein the second-level spatial feature granularity is finer than the first-level spatial feature granularity;

[0172] The target model building module 300 is specifically used for:

[0173] Based on the three preset data sources, third target data information, fourth target data information and fifth target data information corresponding to the terrain information of the target area are respectively obtained;

[0174] Merging the third target data information with the secondary terrain framework line to form a second initial spatial terrain model;

[0175] fusing the fourth target data information into the second initial spatial terrain model to form a third initial spatial terrain model;

[0176] The fifth target data information is integrated into the third initial spatial terrain model to form a target spatial terrain model.

[0177] When the preset requirement in this embodiment is the third level of spatial feature granularity, the target terrain framework line is the third level of terrain framework line; wherein the third level of spatial feature granularity is finer than the second level of spatial feature granularity;

[0178] The target model building module 300 is specifically used for:

[0179] Based on four preset data sources, sixth target data information, seventh target data information, eighth target data information and ninth target data information corresponding to the terrain information of the target area are respectively obtained;

[0180] fusing the sixth target data information with the third-level terrain framework line to form a fourth initial spatial terrain model;

[0181] fusing the seventh target data information into the fourth initial spatial terrain model to form a fifth initial spatial terrain model;

[0182] fusing the eighth target data information into the fourth initial spatial terrain model to form a sixth initial spatial terrain model;

[0183] The ninth target data information is integrated into the sixth initial spatial terrain model to form a target spatial terrain model.

[0184] The target model construction module 300 in this embodiment is further used to: after the step of filling the target terrain framework line based on the target data collected from at least two preset data sources, construct a Delaunay triangulation network on the filled target terrain framework line to form a target spatial terrain model corresponding to the terrain information of the target area;

[0185] The target data collected by the preset data source includes data collected by remote sensing images within the same period of time, data collected by lidar, vehicle-mounted point cloud data or topographic map data.

[0186] As for the system embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The system embodiment described above is only illustrative, wherein the units described as separate components may or may not be physically separated, and the components as units may or may not be physical units, that is, they may be located in one place, or they 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 disclosed solution.

[0187] The spatial terrain model construction system provided by the present disclosure aims at fast, high-precision, high-level of refinement, and precise feature description, utilizes multiple data sources, takes into account the shape characteristics and topological relationships of terrain elements, and realizes the automatic, fast and precise construction of spatial feature terrain models. The spatial terrain model construction method provided by the present disclosure can be widely used in the construction of regional or city-level spatial feature terrain models, and the construction from coarse models to relatively fine models and then to fine models can be efficiently realized.

[0188] Example 3

[0189] Fig.11 The present invention is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present disclosure. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the method in the above embodiment is implemented when the processor executes the program. Fig.11 The electronic device 30 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0190] like Fig.11 As shown, the electronic device 30 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including the memory 32 and the processor 31).

[0191] The bus 33 includes a data bus, an address bus, and a control bus.

[0192] The memory 32 may include a volatile memory, such as a random access memory (RAM) 321 and / or a cache memory 322 , and may further include a read-only memory (ROM) 323 .

[0193] The memory 32 may also include a program / utility 325 having a set (at least one) of program modules 324, such program modules 324 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0194] The processor 31 executes various functional applications and data processing by running the computer programs stored in the memory 32, such as the method in the above-mentioned embodiment of the present disclosure.

[0195] The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 35. Furthermore, the model generating device 30 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 36. Fig.11 As shown, the network adapter 36 communicates with other modules of the model-generated device 30 via the bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0196] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0197] Example 4

[0198] The embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the method for constructing a spatial terrain model provided in the above-mentioned embodiment 1 is implemented.

[0199] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0200] Example 5

[0201] The embodiment of the present disclosure also provides a computer program product, including a computer program, which, when executed by a processor, implements the method for constructing a spatial terrain model provided in the above-mentioned embodiment 1.

[0202] Among them, the program code for executing the computer program product of the present disclosure can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0203] Although the specific embodiments of the present disclosure are described above, those skilled in the art should understand that this is only an example, and the protection scope of the present disclosure is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present disclosure, but these changes and modifications all fall within the protection scope of the present disclosure.

Claims

1. A method for constructing a spatial terrain model, characterized in that: The construction method comprises: Acquire target area terrain information of the target area; wherein different target areas correspond to different levels of preset requirements; the preset requirements are used to constrain the spatial feature granularity corresponding to the target area terrain information; Extracting the frame line of the target area terrain information based on the preset requirements to obtain the frame line of the target terrain; According to the preset requirements, it is determined that the target area corresponds to at least two preset data sources, and the target terrain framework line is filled based on the target data collected by at least two preset data sources to form a target space terrain model corresponding to the target area.

2. The method for constructing a spatial terrain model according to claim 1, characterized in that: Different types of preset data sources are correspondingly provided for the preset requirements under different levels of the spatial feature granularity; wherein the number of types of the preset data sources is positively correlated with the level of the spatial feature granularity under the preset requirements; and / or; Each of the preset requirement matching is configured with a corresponding different preset data source and a processing order between the target terrain framework line.

3. The method for constructing a spatial terrain model according to claim 2, characterized in that: When the preset requirement corresponds to the spatial feature granularity of the first level, the target terrain framework line is a first-level terrain framework line; The step of filling the target terrain framework line based on the target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes: Based on the two preset data sources, first target data information and second target data information corresponding to the terrain information of the target area are respectively obtained; Merging the first target data information with the first-level terrain framework line to form a first initial spatial terrain model; The second target data information is integrated into the first initial spatial terrain model to form the target spatial terrain model.

4. The method for constructing a spatial terrain model according to claim 3, characterized in that: When the preset requirement corresponds to the second level of the spatial feature granularity, the target terrain framework line is a secondary terrain framework line; wherein the second level of the spatial feature granularity is finer than the first level of the spatial feature granularity; The step of filling the target terrain framework line based on the target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes: Based on the three preset data sources, third target data information, fourth target data information and fifth target data information corresponding to the terrain information of the target area are respectively obtained; Merging the third target data information with the secondary terrain framework line to form a second initial spatial terrain model; fusing the fourth target data information into the second initial spatial terrain model to form a third initial spatial terrain model; The fifth target data information is integrated into the third initial spatial terrain model to form the target spatial terrain model.

5. The method for constructing a spatial terrain model according to claim 4, characterized in that: When the preset requirement corresponds to the spatial feature granularity of the third level, the target terrain framework line is a third-level terrain framework line; wherein the spatial feature granularity of the third level is finer than the spatial feature granularity of the second level; The step of filling the target terrain framework line based on the target data collected from at least two preset data sources to form a target spatial terrain model corresponding to the target area includes: Based on the four preset data sources, respectively obtain sixth target data information, seventh target data information, eighth target data information and ninth target data information corresponding to the terrain information of the target area; Merging the sixth target data information with the third-level terrain framework line to form a fourth initial spatial terrain model; fusing the seventh target data information into the fourth initial spatial terrain model to form a fifth initial spatial terrain model; fusing the eighth target data information into the fourth initial spatial terrain model to form a sixth initial spatial terrain model; The ninth target data information is integrated into the sixth initial spatial terrain model to form the target spatial terrain model.

6. The method for constructing a spatial terrain model according to claim 5, characterized in that: The step of filling the target terrain framework line based on the target data collected by at least two preset data sources comprises: Constructing a Delaunay triangulation network on the filled target terrain framework line to form a target spatial terrain model corresponding to the terrain information of the target area; and / or, The target data collected by the preset data source includes data collected by remote sensing images, data collected by laser radar, vehicle-mounted point cloud data or terrain map data within the same period; and / or, The data collected by the two preset data sources include data collected by remote sensing images and data collected by laser radar in the same period of time; and / or, The data collected by the three preset data sources include data collected by remote sensing images, data collected by laser radar, and vehicle-mounted point cloud data within the same period of time; and / or, The data collected by the four preset data sources include data collected by remote sensing images within the same period of time, data collected by lidar, vehicle-mounted point cloud data and topographic map data.

7. A system for constructing a spatial terrain model, characterized in that: The build system includes: A data acquisition module, used to acquire target area terrain information of a target area; wherein different target areas correspond to different levels of preset requirements; and the preset requirements are used to constrain the spatial feature granularity corresponding to the target area terrain information; A terrain frame line extraction module, used to extract frame lines from the target area terrain information based on the preset requirements to obtain target terrain frame lines; The target model building module is used to determine that the target area corresponds to at least two preset data sources according to the preset requirements, and fill the target terrain framework line based on the target data collected by at least two of the preset data sources to form a target space terrain model corresponding to the target area.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and used to run on the processor, characterized in that: When the processor executes the computer program, the method for constructing a spatial terrain model according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for constructing a spatial terrain model according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for constructing a spatial terrain model as described in any one of claims 1 to 6 is implemented.

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