Method for constructing three-dimensional geographic entity and three-dimensional electronic map

Abstract

The invention discloses a method for constructing a three-dimensional geographic entity and a three-dimensional electronic map, which comprises the following steps of: firstly, classifying acquired basic surveying and mapping data based on a constructed multi-level classification framework, and determining an entity category to which each element in the basic surveying and mapping data belongs; then, according to entity category design mapping data corresponding to the elements, converting the mapping data into a geometric mapping relation and an attribute mapping relation of a two-dimensional geographic entity, and through the geometric mapping relation and the attribute mapping relation, converting the mapping data and the attribute information corresponding to the elements into geographic entity geometry and geographic entity attributes; semantized geographic two-dimensional entities are generated to effectively inherit and structurally reuse stock data, and massive waste and repeated construction of data resources are avoided. And then, selecting a corresponding three-dimensional conversion method according to the type of the two-dimensional geographic entity, and converting the two-dimensional geographic entity into a three-dimensional geographic entity. And finally, constructing a corresponding three-dimensional electronic map according to the three-dimensional geographic entities corresponding to all the elements.

Description

Technical Field

[0001] The present invention relates to the technical field of processing three-dimensional maps, and specifically relates to a method for constructing three-dimensional geographical entities and three-dimensional electronic maps. Background Art

[0002] The three-dimensional transformation of two-dimensional electronic maps can deeply explore the potential value of existing two-dimensional data. This process can not only inherit the spatial information and attribute information of existing two-dimensional data, but also enhance the ability to analyze spatial relationships through three-dimensional entity and semantic expressions, thereby providing a high-precision and multi-dimensional dynamic data carrier for national land space planning and urban refined management. This paradigm innovation from plane to three-dimensional can support more scientific decision-making analysis and promote the upgrade of urban governance from plane control to three-dimensional intelligent governance. However, the current methods for constructing three-dimensional electronic maps have problems such as low utilization rate of two-dimensional data and disconnection between three-dimensional scene construction and two-dimensional data. This results in the spatial geometric information and attribute information of a large amount of two-dimensional geographical information data not being fully utilized during the construction of three-dimensional maps, leading to low modeling efficiency and resource waste. Summary of the Invention

[0003] In view of the deficiencies of the prior art, the present invention proposes a method for constructing three-dimensional geographical entities and three-dimensional electronic maps, which can avoid a large amount of waste of data resources and duplicate construction. The specific technical solutions are as follows:

[0004] In a first aspect, a method for constructing three-dimensional geographical entities is provided. In a first possible implementation manner of the first aspect, it includes:

[0005] Classify the obtained basic surveying and mapping data based on the constructed multi-level classification framework to obtain basic surveying and mapping data with entity classification codes;

[0006] Design the mapping relationship between the basic surveying and mapping data and geographical entities according to the entity classification codes, and convert the basic surveying and mapping data into two-dimensional geographical entities based on the mapping relationship;

[0007] Select a corresponding three-dimensional conversion method based on the type to which the two-dimensional geographical entity belongs, and convert the two-dimensional entity into a three-dimensional geographical entity.

[0008] Combined with the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, converting the basic surveying and mapping data into two-dimensional geographical entities includes:

[0009] Uniquely encode the two-dimensional geographical entity according to the following encoding rules:

[0010] Code gridcode =Code level &Code grid &Codecategory &Code time &Code serial ;

[0011] Among them, Code level is the geographical grid level identification code, Code grid is the geographical grid row and column number, Code category is the geographical entity classification code, Code time is the timestamp code, Code serial is the serial number.

[0012] Combined with the first implementation manner of the first aspect, in the third implementation manner of the first aspect, converting the basic surveying and mapping data into two-dimensional geographical entities includes:

[0013] Construct the internal semantic relationship of the two-dimensional geographical entity according to its own attribute information and the semantic relationship with other entities.

[0014] Combined with the first implementation manner of the first aspect, in the fourth implementation manner of the first aspect, the three-dimensional conversion method corresponding to the point entity includes:

[0015] Determine the entity elevation of the point entity according to the elevation value of the digital elevation model grid to which the point entity belongs;

[0016] According to the entity elevation of the point entity, use the i function to insert the point entity into the corresponding model to replace the original point, and generate the three-dimensional geographical entity corresponding to the point entity.

[0017] Combined with the first implementation manner of the first aspect, in the fifth implementation manner of the first aspect, the three-dimensional conversion method corresponding to the line entity includes:

[0018] Determine the elevation value corresponding to each line node according to the elevation value of the digital elevation model grid to which the line node in the line entity belongs;

[0019] Based on the elevation values of all line nodes, use the alignScopeToAxes function to align the line entity with the three-dimensional coordinates, use the split function to split the line entity, and use the extrude function to stretch the road surface;

[0020] Determine the intersection and road section through the internal semantic relationship of the line entity, and generate the corresponding three-dimensional geographical entity.

[0021] Combined with the first implementation manner of the first aspect, in the sixth implementation manner of the first aspect, the three-dimensional conversion method corresponding to the surface entity includes:

[0022] When the face entity is a non-composite building, obtain the bottom elevation and top elevation of the building, and stretch the face entity based on the bottom elevation and top elevation to obtain the corresponding three-dimensional geographic entity, and / or;

[0023] When the face entity is a composite building, obtain the bottom elevation and top elevation of each component of the building;

[0024] Based on the bottom elevation and top elevation, stretch the face entities of each component to obtain the corresponding three-dimensional entities;

[0025] Merge the corresponding three-dimensional entities according to the internal semantic relationships of each component to generate the corresponding three-dimensional geographic entity, and / or;

[0026] When the face entity is not a building, divide the face entity using a triangulated irregular network (TIN), and determine the elevation value of the face nodes using linear interpolation based on the three vertex coordinates of the triangulation network to which the face nodes belong;

[0027] Connect all the face nodes to generate the corresponding three-dimensional geographic entity.

[0028] In a second aspect, a method for constructing a three-dimensional electronic map is provided. In a first implementable manner of the second aspect, it includes:

[0029] Obtain the basic surveying and mapping data of the area to be constructed, and use the three-dimensional geographic entity construction method described in any one of the first to sixth implementable manners of the first aspect to construct the three-dimensional geographic entities corresponding to each element;

[0030] Construct the corresponding three-dimensional electronic map based on the three-dimensional geographic entities corresponding to all elements.

[0031] Combined with the first implementable manner of the second aspect, in a second implementable manner of the second aspect, it further includes:

[0032] Perform lightweight compression on the basic surveying and mapping data, and / or;

[0033] Perform lightweight compression on the three-dimensional electronic map.

[0034] Combined with the second implementable manner of the second aspect, in a third implementable manner of the second aspect, performing lightweight compression on the basic surveying and mapping data includes:

[0035] Use a clustering method to perform clustering processing on the point elements in the basic surveying and mapping data, and / or;

[0036] Use the coordinate precision truncation method to compress the coordinate precision of the point elements, and / or;

[0037] The line elements in the basic surveying and mapping data are compressed using the Douglas-Peucker algorithm and the Visvalingam-Whyatt algorithm, and / or;

[0038] The surface elements in the basic surveying and mapping data are merged according to a set area threshold, and the Douglas-Peucker algorithm and the Visvalingam-Whyatt algorithm are used to process the merged surface elements.

[0039] Combined with the second implementation manner of the second aspect, in the fourth implementation manner of the second aspect, lightweight compression of the 3D electronic map includes:

[0040] Determine the 3D geographical entities to be displayed according to the set scale and the internal semantic relationship of the 3D geographical entities;

[0041] Use the triangular surface simplification method to reduce the number of faces of the 3D geographical entities to be displayed, and compress the texture of the processed 3D geographical entities;

[0042] Use the LOD method to dynamically select models with different levels of detail for rendering of the compressed 3D geographical entities.

[0043] Beneficial effects: By using the method for constructing 3D geographical entities and 3D electronic maps of the present invention, the basic surveying and mapping data can be classified through the constructed multi-level classification framework, and the corresponding categories of each element in the basic surveying and mapping data can be determined. Then, according to the element categories, the geometric mapping relationship and attribute mapping relationship for the conversion of surveying and mapping data into geographical entities are determined, and through the geometric mapping relationship, the geometric data of the elements are converted into geographical entity geometry according to the geometric rules of the geographical entities, and at the same time, through the attribute mapping relationship, the attribute information of the elements is converted into geographical entity attributes, so as to reconstruct the basic surveying and mapping data into semantic geographical entities, in order to deeply explore the potential of surveying and mapping data and avoid a large amount of waste of data resources and duplicate construction. Finally, by using the 3D conversion method corresponding to the type of 2D geographical entities, the spatial geometric information and attribute information in the semantic geographical entities are fully utilized to quickly convert 2D geographical entities into 3D entities, realizing the rapid modeling of 3D geographical entities. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the specific embodiments of the present invention, the drawings required for use in the specific embodiments will be briefly introduced below. In all the drawings, the components or parts do not necessarily draw according to the actual proportion.

[0045] Figure 1 It is a flowchart of the method for constructing 3D geographical entities provided by an embodiment of the present invention;

[0046] Figure 2Flowchart of a 3D electronic map construction method provided by an embodiment of the present invention. Detailed implementation manners

[0047] Hereinafter, embodiments of the technical solution of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and thus are only examples and cannot be used to limit the protection scope of the present invention.

[0048] As Figure 1 shown in the flowchart of the 3D geographical entity construction method, the construction method includes:

[0049] Step 1: Classify the acquired basic surveying and mapping data based on the constructed multi-level classification framework to obtain basic surveying and mapping data with entity classification codes;

[0050] Step 2: Design the mapping relationship between the basic surveying and mapping data and geographical entities according to the entity classification codes, and convert the basic surveying and mapping data into 2D geographical entities based on the mapping relationship;

[0051] Step 3: Select the corresponding 3D conversion method based on the type to which the 2D geographical entity belongs, and convert the 2D entity into a 3D geographical entity.

[0052] Specifically, the basic surveying and mapping data focuses on the expression of spatial positions and forms with geometric elements such as points, lines, and surfaces as the core, but lacks the semantic encapsulation and multi-dimensional association of real-world objects, resulting in low data utilization efficiency and limited cross-domain analysis capabilities. Geographical entities support cross-level logical reasoning, dynamic attribute association, and multi-scale adaptive expression by aggregating discrete surveying and mapping elements into independent units with complete semantic attributes, and can deeply explore the potential of surveying and mapping data. To effectively inherit and structurally reuse the stock data and avoid a large amount of waste of data resources and repeated construction, the basic surveying and mapping data can be converted into 2D geographical entities and then into 3D entities.

[0053] Specifically, first, the acquired basic surveying and mapping data can be classified based on the constructed multi-level classification framework to determine the entity categories to which the elements in the basic surveying and mapping data belong. Then, the geometric mapping relationship and attribute mapping relationship for converting the surveying and mapping data into 2D geographical entities can be designed according to the entity categories corresponding to the elements. Then, through the corresponding geometric mapping relationship and attribute mapping relationship respectively, the geometric surveying and mapping data and attribute information corresponding to the elements are respectively converted into geographical entity geometry and geographical entity attributes to obtain semantic geographical 2D entities. Finally, the corresponding 3D conversion method can be selected according to the type to which the 2D geographical entity belongs to convert the 2D geographical entity into a 3D geographical entity, realizing the 3D geographical entity conversion of the surveying and mapping data.

[0054] In this embodiment, the multi-level classification framework can be constructed according to the entity functions, forms, and spatial relationships. Specifically, first, geographical entities can be divided into natural entities and artificial entities. Among them, natural entities can be mountains, water systems, vegetation, etc. Artificial entities can be roads, buildings, etc. Then, the entities can be further subdivided according to functions and structures. The classification system can be compatible with national standards and support dynamic expansion.

[0055] After constructing the multi-level classification framework, the mapping relationships between different types of elements and geographical entities can be designed based on the classification framework. The mapping relationships include geometric mapping relationships and attribute mapping relationships. The attribute mapping relationship is used to convert the original attributes of the elements in the surveying and mapping data into the basic attributes and semantic labels of geographical entities, realizing the standardization of geographical entity attributes. The geometric mapping relationship is used to modify the geometric elements in the basic surveying and mapping data that are inconsistent with the rules of geographical entities.

[0056] Based on the attribute mapping relationship and the geometric mapping relationship, the surveying and mapping data of the elements can be converted into corresponding two-dimensional geographical entities. Specifically: First, the elements that need to be modified can be corrected through human-computer interaction according to the geometric mapping relationship. For example, in the basic surveying and mapping data, a house is split into multiple parts, including balconies, door tops, rain covers, etc., while the geometric rules of geographical entities require these components to be merged with the main building as a geographical entity object. Therefore, the corresponding elements in the basic surveying and mapping data need to be merged or deleted, and the geographical elements with geometric forms consistent with the geographical entities are retained.

[0057] Then, read the surveying and mapping data that needs to be converted into entities and the corresponding attribute mapping relationship, and convert the attribute mapping relationship into a dictionary. Traverse each element in the data, and group and export each type of element according to the element category. After the exported data, new entity attribute fields are created according to the attribute mapping relationship, and the original attributes in the surveying and mapping data are batch-mapped into the entity attributes, realizing the attribute mapping of geographical entities.

[0058] In this embodiment, optionally, converting the basic surveying and mapping data into two-dimensional geographical entities includes:

[0059] Perform unique coding on the two-dimensional geographical entity according to the following coding rules:

[0060] Code gridcode =Code level &Code grid &Code category &Code time &Code serial ;

[0061] Among them, Code level is the geographical grid level identification code, Code grid is the geographical grid row and column number, Codecategory is the classification code for geographical entities, Code time is the timestamp code, Code serial is the serial number.

[0062] After converting the surveying and mapping data into two-dimensional geographical entities, the above coding rules can be used to uniquely code the two-dimensional geographical entities. The constructed code can be: G1A3B5-010101-20231015-0001, where G1 represents the global level, A3B5 represents the third row and fifth column of the grid row and column number; 010101 represents that the geographical entity is classified as a residential building, 20231015 represents the timestamp, and 0001 represents the entity serial number, that is, the first residential building entity in the grid.

[0063] In this embodiment, optionally, converting the basic surveying and mapping data into two-dimensional geographical entities includes:

[0064] Construct the internal semantic relationship of the two-dimensional geographical entity according to its own attribute information and the semantic relationship with other entities.

[0065] Specifically, after assigning a unique code to all entities, the internal semantic relationship of the two-dimensional geographical entity can be constructed according to the code of the two-dimensional geographical entity, combined with its own attribute information, and the semantic relationship between the two-dimensional geographical entity and the same type of entities. Thus, different entities are organically integrated to form a deep association between entities, which is conducive to the rapid linkage query between entities. And the internal semantic relationship can be abstracted as a separate data storage, which is not only convenient for subsequent modification of the semantic relationship, improves the query depth and breadth of users during the use of the map, and greatly improves the usability of the three-dimensional electronic map.

[0066] Among them, the attribute information of the two-dimensional geographical entity includes the name, use, address, etc. of the entity. It can be expressed as: the unique code of entity A, attribute A: value A; attribute B: value B; attribute C: value C... The attributes can be obtained from the corresponding surveying and mapping data of the entity.

[0067] The semantic relationship between the same type of entities can include spatial semantic relationship and humanistic semantic relationship. Among them, the spatial semantic relationship includes adjacent, inclusion, connection, etc., and can be expressed as: the unique code of entity A, the unique code of entity B, spatial relationship. The spatial relationship can be calculated using ArcGIS.

[0068] The humanistic semantic relationship is a semantic relationship inferred based on entity features combined with thematic data from various industries. For example, according to the judgment criteria of historical buildings, if a certain building belongs to a historical building, its humanistic semantic relationship is that the historical building contains this building. Through the humanistic semantic relationship, a bridge can be established between geographical entities and various industries, which is an important basis for 3D electronic maps to support different industry applications. The humanistic semantic relationship can be expressed as: the unique code of entity A, the unique code of entity B, and the humanistic relationship C.

[0069] In this embodiment, optionally, the 3D conversion method corresponding to the point entity includes:

[0070] Determine the entity elevation of the point entity according to the elevation value of the digital elevation model grid to which the point entity belongs;

[0071] According to the entity elevation of the point entity, use the i function to insert the point entity into the corresponding model to replace the original point, and generate the 3D geographical entity corresponding to the point entity.

[0072] Specifically, after converting the surveying and mapping data into 2D geographical entities, the 2D geographical entities can be divided into various different types of entities according to their geometric features. In this embodiment, the entities can be divided into point entities, line entities, and surface entities. For these three types of entities, corresponding conversion methods can be used to convert the 2D geographical entities into 3D geographical entities.

[0073] Among them, for the point entity, the elevation value of the DEM grid where the point entity is located can be obtained as the point entity elevation. The 3D expression is the point entity expressed by modeling, such as signal lights, street trees, etc. The 3D points can be imported into CityEngine, and the CGA script is written to use the i function to insert the corresponding model to replace the original point, and the model is exported as the 3D point entity. The 3D expression form is the point entity expressed symbolically. For example, for the POI point, a suitable 3D expression symbol is designed to complete the 3D conversion of the point entity.

[0074] For the line entity, the elevation value of each line node of the line entity can be extracted from the DEM grid where the line node is located and assigned to the node as the elevation value of the line node. After the elevation extraction is completed, the line entity with the elevation assigned can be imported into CityEngine, the CGA script is written, the alignScopeToAxes function is used to align the line entity with the 3D coordinates, and then the split function is used to split the line entity to distinguish the sidewalk and the roadway of the road surface. The extrude function is used to stretch the road surface, and then according to the spatial semantic relationship of the line entity, the intersection and the road section are distinguished, and the 3D model is exported to complete the 3D conversion of the line entity.

[0075] For surface entities, first, it is possible to determine whether a surface entity belongs to a building or a non-building based on its attribute information. When the surface entity belongs to a building, the bottom elevation and top elevation of the building can be obtained, and it can be determined whether the building belongs to a non-composite building or a composite building. If it belongs to a non-composite building, the 3DForce and Extruder tools in FME can be used to stretch the two-dimensional building entity to generate a three-dimensional building entity.

[0076] If it belongs to a composite building, first, the 3D Force and Extruder tools in FME can be used to stretch each component, and then, according to the spatial relationship of the surface entity, the SolidDissolver tool can be used to merge the building blocks belonging to the same entity to generate a three-dimensional composite building entity. Finally, the generated three-dimensional building entity is imported into CityEngnie, and the comp function is used to split the building into multiple walls, and by setting the heights of the sides and the top surface respectively, multiple types of roofs such as parapets are generated to complete the three-dimensional entity conversion of the composite building.

[0077] In this embodiment, the Zonal statistics as Table tool of ArcGIS can be used to calculate the average values of the DEM (Digital Elevation Model) and DSM (Digital Surface Model) within the building surface, and then the calculation results are attached to the corresponding building entity according to the unique code of the surface entity. Among them, the average value of the DEM is used as the bottom elevation of the building, the average value of the DSM is used as the top elevation of the building, and the difference between the two is used as the overall elevation of the building.

[0078] In addition, the bottom elevation of the building can be obtained from the DEM data, and the top elevation of the building is obtained by multiplying the height of each floor of the building by the total number of floors of the building according to the floor attribute information of the surface entity, and then adding it to the bottom elevation of the building to obtain the top elevation of the building.

[0079] The composite building includes a podium and a tower. The bottom elevation of the podium can be selected as the bottom elevation of the entire building, and the calculation of the top elevation of the podium is the same as the above two methods. The bottom elevation of the tower can directly use the top elevation of the podium as the bottom elevation, and the top elevation can be obtained by multiplying the height of each floor of the building by the total number of floors of the building to obtain the overall height of the building, and then adding it to the bottom elevation of the building to obtain the top elevation of the building.

[0080] When the on-site entity is a non-building, multiple types of entity models can be generated according to the semantic relationships of the surface entities. For example, if a cultivated land plot contains four dry land plots and one paddy field plot, a three-dimensional entity of the large cultivated land category needs to be generated, and three-dimensional entities of the subdivided small categories also need to be generated. Then, the irregular triangular network is used to divide different surface entities, and based on the coordinates of the three vertices of the triangular surface where the surface node is located, the linear interpolation method is used to calculate the elevation value of each surface node of the surface entity, and then each surface node is connected to generate a three-dimensional surface entity of the real surface features. The calculation method of the elevation value of the surface node is as follows:

[0081]

[0082] where x and y are the longitude and latitude coordinates of the surface node, x A 、y A 、z A are the longitude and latitude coordinates and elevation value of vertex A respectively, N x 、N y 、N z are vector cross products, which are respectively:

[0083] N x =(y B -y B )(z C -z A )-(z B -z A )(y C -y A );

[0084] N y =(z B -z A )(x C -x A )-(x B -x A )(z C -z A );

[0085] N z =(x B -x A )(y C -y A )-(y B -y A )(x C -x A );

[0086] where x A 、x B 、x C are the longitude values of vertices A, B, and C respectively, y A 、yB , y C are the latitude values of vertices A, B, and C respectively, and z A , z B , z C are the elevation values of vertices A, B, and C respectively.

[0087] As Figure 2 shown in the flowchart of the three-dimensional electronic map construction method, the construction method includes:

[0088] Step S1, obtain the basic surveying and mapping data of the area to be constructed, and adopt the above three-dimensional geographical entity construction method to construct the three-dimensional geographical entities corresponding to each element;

[0089] Step S2, construct the corresponding three-dimensional electronic map according to the three-dimensional geographical entities corresponding to all elements.

[0090] Specifically, first, the above three-dimensional geographical entity construction method can be used to perform three-dimensional entity conversion on each element in the basic surveying and mapping data of the area to be constructed to obtain the corresponding three-dimensional geographical entities. Then, the corresponding three-dimensional electronic map can be constructed according to the three-dimensional geographical entities corresponding to all elements.

[0091] In this embodiment, optionally, it further includes:

[0092] perform lightweight compression on the basic surveying and mapping data, and / or;

[0093] perform lightweight compression on the three-dimensional electronic map.

[0094] Specifically, since the three-dimensional electronic map is used frequently, the constructed three-dimensional electronic map can be lightweight processed. In this embodiment, the lightweight processing of the three-dimensional electronic map can include the lightweight processing of the basic surveying and mapping data and the lightweight processing of the three-dimensional electronic map.

[0095] Among them, the lightweight processing of the basic surveying and mapping data includes the lightweight processing of point elements, line elements, and surface elements. For point elements, it includes deleting redundant points and compressing coordinate accuracy. For dense point elements, such as woods, the DBSCAN clustering method can be used for clustering processing, and the redundant redundant points can be deleted. For non-dense points, the coordinate accuracy truncation method can be used to compress the data coordinate accuracy.

[0096] For line elements, for line elements such as roads and administrative boundaries that need to retain obvious turning features, the Douglas-Peucker algorithm can be used to retain key inflection points and eliminate redundant nodes. Specifically, first, the distance from any point between the two end points of the line element to the initial line segment L is calculated using the specific calculation formula:

[0097]

[0098] Among them, P0(x0, y0) and P1(x1, y1) are the coordinates of the two end points of the initial line segment L respectively, and P(x, y) is the coordinate of any node of the line feature.

[0099] Compare the maximum distance value with the simplification threshold. If the maximum distance value is less than the simplification threshold, delete all nodes. Otherwise, use the node corresponding to the maximum distance value as the end point, and calculate the distance from all nodes between the end node and the initial point of the line feature to the initial line segment again. Take the maximum value again and compare it with the simplification threshold, and repeat the above steps until all nodes are processed.

[0100] For natural curves such as rivers, the Visvalingam-Whyatt algorithm can be used to simplify by removing the points with the least influence on the shape. The specific algorithm is as follows:

[0101] For three consecutive nodes P i-1 (x i-1 , y i-1 ), P i (x i , y i ), P i (x i+1 , y i+1 ), calculate the area of the triangle formed by each node and the two adjacent nodes. The specific calculation formula is as follows:

[0102]

[0103] The calculated triangle area A i is used as the weight of each node. Compare the weight with the threshold. If it is less than the threshold, delete the node and recalculate the weights of all points. Repeat this process until the weights of all points are greater than the threshold, and the compression of the natural curve can be completed.

[0104] For the surface feature, first, an area threshold can be set, and the area of the surface feature is calculated. If the area of the feature is less than the threshold, it is directly merged with the adjacent surface. Then, check the angle of the surface feature and correct the features with some abnormally sharp angles. After that, for artificial management features such as buildings and administrative regions, the Douglas-Peucker algorithm is used for compression. For natural features such as plots and water systems, the Visvalingam-Whyatt algorithm is used for compression. After compression, topological checks need to be performed again to ensure that the surface does not self-intersect and the hole relationship remains unchanged.

[0105] In this embodiment, optionally, lightweight compression of the three-dimensional electronic map includes:

[0106] Determine the 3D geographical entities to be displayed according to the set scale and the internal semantic relationships of the 3D geographical entities;

[0107] Use the triangular face simplification method to reduce the number of faces of the 3D geographical entities to be displayed, and compress the texture of the processed 3D geographical entities;

[0108] Use the LOD method to dynamically select models with different levels of detail for rendering the 3D geographical entities after compression processing.

[0109] Specifically, for the lightweight processing of 3D entities, first, the semantic relationships of the entities can be referred to determine the 3D geographical entities to be displayed, so as to differentially display 3D entities at small and large scales. At small scales, 3D entities at the subdivision level are not displayed, and coarse-level 3D entities are used instead. For 3D building entities, at small scales, if a building entity includes a podium, a tower, and a turret, the podium, the tower, and the turret can be merged into a complete building entity without distinguishing each component, and at the same time, each floor of the building is merged to generate a complete building. At large scales, the merged building can be sliced into each subdivision entity and displayed at the floor scale.

[0110] For other 3D surface entities, at small scales, display the entity with the largest inclusion relationship. For example, a green space entity includes a forest land entity and a grassland entity, and only the green space entity is displayed at small scales. At large scales, the forest land entity and the grassland entity are displayed.

[0111] After determining the 3D geographical entities to be displayed, the triangular face simplification method can be used to directly reduce the data volume of the 3D entities, which can effectively compress the data. Since some 3D entities also have texture maps, the texture quality can be compressed to reduce the data storage space and transmission bandwidth. When operating specifically, an appropriate compression format can be selected according to the texture type, such as JPEG, PNG, etc., and the compression quality can be set to compress the data while ensuring the visual effect.

[0112] Finally, the LOD technology can be used to dynamically adjust the level of detail of the model to balance the visual effect and rendering efficiency. The principle is to dynamically select models with different levels of detail for rendering according to the distance between the object and the observer. When the object is far from the observer, a simplified model is used to reduce the rendering burden. When the object is close to the observer, switch to a high-detail model to maintain the visual quality. Specifically, the 3D geographical entities after compressed texture can be imported into the UE5 engine. UE5 supports directly adding LOD to static models, setting the LOD level according to the size of the entity and then exporting, so as to achieve the lightweight compression of the 3D electronic map.

[0113] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present invention, and they should all be covered within the scope of the claims and the description of the present invention.

Claims

1. A method for constructing a three-dimensional geographic entity, characterized in that: include: Based on the constructed multi-level classification framework, the acquired basic surveying and mapping data are classified to obtain basic surveying and mapping data with entity classification codes; Determining a mapping relationship between basic surveying and mapping data and geographic entities according to the entity classification code, and converting the basic surveying and mapping data into a two-dimensional geographic entity based on the mapping relationship; A corresponding three-dimensional conversion method is selected based on the type of the two-dimensional geographic entity to convert the two-dimensional entity into a three-dimensional geographic entity.

2. The three-dimensional geographic entity construction method according to claim 1, characterized in that: Convert basic surveying and mapping data into 2D geographic entities, including: The two-dimensional geographic entity is uniquely encoded according to the following encoding rules: Code gridcode =Code level &Code grid &Code category &Code time &Code serial ; Among them, Code level Code is the geographic grid level identification code. grid is the row and column number of the geographic grid, Code category Code for geographic entity classification time is the timestamp code, Code serial is the serial number.

3. The three-dimensional geographic entity construction method according to claim 1, characterized in that: Convert basic surveying and mapping data into 2D geographic entities, including: The internal semantic relationship of the two-dimensional geographic entity is constructed according to its own attribute information and the semantic relationship with other entities.

4. The three-dimensional geographic entity construction method according to claim 1, characterized in that: The 3D transformation methods corresponding to point entities include: Determine the entity elevation of the point entity according to the elevation value of the digital elevation model grid to which the point entity belongs; According to the entity elevation of the point entity, the i function is used to insert the point entity into the corresponding model to replace the original point, so as to generate a three-dimensional geographic entity corresponding to the point entity.

5. The three-dimensional geographic entity construction method according to claim 1, characterized in that: The 3D conversion methods corresponding to line entities include: According to the elevation value of the digital elevation model grid to which the line node belongs in the line entity, the elevation value corresponding to each line node is determined; Based on the elevation values ​​of all line nodes, the alignScopeToAxes function is used to align the line entity with the three-dimensional coordinates, the split function is used to split the line entity, and the extrude function is used to stretch the road surface; The intersections and road sections are determined through the internal semantic relations of line entities, and the corresponding three-dimensional geographic entities are generated.

6. The three-dimensional geographic entity construction method according to claim 1, characterized in that: The 3D conversion methods corresponding to surface entities include: When the surface entity is a non-combined building, the bottom elevation and the top elevation of the building are obtained, and the surface entity is stretched based on the bottom elevation and the top elevation to obtain a corresponding three-dimensional geographic entity, and / or; When the surface entity is a composite building, obtain the bottom elevation and top elevation of each component of the building; Based on the bottom elevation and the top elevation, the surface entity of each component is stretched to obtain a corresponding three-dimensional entity; Merging corresponding three-dimensional entities according to internal semantic relationships of each component to generate corresponding three-dimensional geographic entities, and / or; When the surface entity is not a building, the surface entity is divided by using an irregular triangulated network, and the elevation value of the surface node is determined by using a linear interpolation method according to the coordinates of the three vertices of the triangulated network to which the surface node belongs; Connect all surface nodes to generate corresponding three-dimensional geographic entities.

7. A method for constructing a three-dimensional electronic map, characterized in that: include: Obtain basic surveying and mapping data of the area to be constructed, and use the three-dimensional geographic entity construction method described in any one of claims 1 to 7 to construct the three-dimensional geographic entity corresponding to each element; The corresponding three-dimensional electronic map is constructed based on the three-dimensional geographic entities corresponding to all elements.

8. The method for constructing a three-dimensional electronic map according to claim 7, characterized in that: Also includes: Performing lightweight compression on the basic surveying and mapping data, and / or; The three-dimensional electronic map is lightly compressed.

9. The method for constructing a three-dimensional electronic map according to claim 8, characterized in that: The basic surveying and mapping data is lightly compressed, including: Using a clustering method to cluster the point elements in the basic surveying and mapping data, and / or; Using coordinate precision truncation to compress the coordinate precision of point features, and / or; Using Douglas-Peucker algorithm and Visvalingam-Whyatt algorithm to compress line elements in the basic surveying and mapping data, and / or; The surface elements in the basic surveying and mapping data are merged according to the set area threshold, and the merged surface elements are processed by using the Douglas-Peucker algorithm and the Visvalingam-Whyatt algorithm.

10. The method for constructing a three-dimensional electronic map according to claim 8, characterized in that: Lightweight compression of the three-dimensional electronic map includes: Determine the 3D geographic entities to be displayed according to the set scale and the internal semantic relationship of the 3D geographic entities; The triangular surface simplification method is used to reduce the surface of the three-dimensional geographic entity to be displayed, and the texture of the processed three-dimensional geographic entity is compressed; The LOD method is used to dynamically select models with different levels of detail for rendering of compressed 3D geographic entities.

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