Three-dimensional geographic entity space-time identification coding method based on Beidou grid code

Abstract

The invention provides a three-dimensional geographic entity space-time identification coding method based on a Beidou grid code, and belongs to the field of live-action three-dimensional, and the method employs a classification identification + space identification + time identification structure, and rapidly calculates an outsourcing 3D convex hull of a three-dimensional geographic entity through KD tree pruning and principal component analysis. The method comprises the following steps of: determining a subdivision hierarchy of a maximum inner packet grid by using neighborhood seed growth, calculating an entity space identifier which takes a Beidou three-dimensional grid position code as description by using a six-point method, further calculating an entity time identifier in a form of geographic entity ID + timestamp, realizing accurate identification of a geographic entity three-dimensional space position and time information, and realizing accurate identification of the geographic entity three-dimensional space position and time information. The problems that traditional geographic entity coding is insufficient in identification precision in three-dimensional space and time dimension, data integration is difficult and the like are solved, and the method has extremely high application value in the fields of live-action three dimensions, smart cities, low-altitude economy and the like.

Description

Technical Field

[0001] This invention relates to the fields of real-scene 3D, smart cities, and low-altitude economy, and in particular to a 3D geographic entity spatiotemporal identification encoding method based on BeiDou grid code. Background Technology

[0002] With the development of fields such as 3D reality, smart cities, and low-altitude economy, traditional geocoding methods (such as latitude and longitude coordinates and 2D grids) are mainly used for locating point, line, and surface elements in 2D space, and are difficult to handle information in 3D space and time dimensions. Currently, the demand for accurate identification of the 3D spatial location and temporal information of geographic entities is increasingly urgent. On the one hand, 3D geographic entities lack a spatiotemporally integrated coding system, making it difficult to support real-time management and analysis after dynamic data updates; on the other hand, traditional 2D Earth grids cannot effectively identify geographic entities such as building layers, unit divisions, and low-altitude areas in 3D space. The BeiDou grid location code is a grid location coding system developed based on the theory of Earth spatial partitioning. It is compatible with the positioning accuracy of the BeiDou satellite navigation system and can achieve unified identification and expression of global spatial location grids and one-dimensional integers, making it suitable for the spatial identification of geographic entities. Summary of the Invention

[0003] To address the aforementioned technical challenges, this invention provides a three-dimensional geographic entity spatiotemporal identification coding method based on BeiDou grid codes. By constructing a spatiotemporally integrated three-dimensional geographic entity identification system, it resolves the problem of interoperability and mutual recognition of spatiotemporal information caused by inconsistent spatiotemporal identification. The upgrade from two-dimensional to three-dimensional spatiotemporal identification incorporates the three-dimensional space of the earth's surface, underground, and airspace into a unified coding system, breaking through the limitations of spatial expression and enabling more precise spatial positioning. This supports the core requirements of major national projects such as real-scene 3D, smart cities, and low-altitude economy for the management of geographic entities across all spaces, all times, and all elements.

[0004] The technical solution of this invention is:

[0005] A spatiotemporal identification encoding method for three-dimensional geographic entities based on BeiDou grid codes is proposed. This method adopts a structure of "classification identifier + spatial identifier + time identifier". It quickly calculates the outer 3D convex hull of three-dimensional geographic entities through KD tree pruning and principal component analysis. It determines the subdivision level of the maximum inner hull grid by using neighborhood seed growth. It calculates the spatial identifier of the entity described by the BeiDou three-dimensional grid location code using the "six-point method". It further calculates the entity time identifier in the form of "geographic entity ID + timestamp" to achieve accurate identification of the three-dimensional spatial location and time information of geographic entities.

[0006] Specifically, it includes:

[0007] Determining the classification identifier code for geographic entities;

[0008] Calculation of spatial identifiers for geographic entities;

[0009] Calculation of geographic entity time identifier codes;

[0010] Define the structure and composition of the spatiotemporal identifier code for geographic entities;

[0011] Furthermore,

[0012] The determination of the geographic entity classification identifier code includes:

[0013] Based on the classification scheme, coding scheme, and classification and code extension principles stipulated in the "Classification and Code of Basic Geographic Information Elements" (GB / T 13923-2022), a 6-digit entity classification code for the geographic entity is generated.

[0014] Furthermore,

[0015] The calculation of the geographic entity spatial identifier code includes:

[0016] Calculation of the outer 3D convex hull of a geographic entity;

[0017] Determination of the hierarchical structure of the three-dimensional BeiDou grid;

[0018] The "six-point method" determines the spatial identifier of an entity.

[0019] Furthermore,

[0020] The calculation of the 3D convex hull of geographic entities includes:

[0021] Surface nodes of 3D geographic entities are extracted, and a KD-tree is constructed to store the point set. The Qhull algorithm is used to calculate the convex hull. During computation, KD-tree pruning strategies and dynamic segmentation based on principal component analysis are employed to improve algorithm efficiency.

[0022] Furthermore,

[0023] The determination of the hierarchical structure of the three-dimensional BeiDou grid includes:

[0024] During the hierarchical subdivision, neighboring seeds are grown from the initial grid where the entity's center point is located. The ray method is used to determine whether the grid is inside the convex hull, and the maximum inner grid is calculated. The level to which this grid belongs is determined as the subdivision level.

[0025] Furthermore,

[0026] The "six-point method" for determining the spatial identifier of an entity includes:

[0027] The BeiDou 3D grid location codes of the six maximum and minimum points of a geographic entity in the three dimensions of the geodetic coordinate system are calculated, and the resulting one-dimensional array is the spatial identifier code of the geographic entity.

[0028] Furthermore,

[0029] The calculation of the geographic entity time identifier code includes:

[0030] It adopts the encoding format of "geographic entity ID + timestamp". The timestamp uses a fixed-length decimal code element and can be accurate to the second.

[0031] Furthermore,

[0032] The structure and composition of the spatiotemporal identifier code for geographic entities include:

[0033] A three-segment coding structure of "classification identifier + spatial identifier + time identifier" is adopted to form a unique three-dimensional geographic entity spatiotemporal identifier code.

[0034] The beneficial effects of this invention are

[0035] This invention integrates the spatial location (BeiDou grid), structure (geometric / semantic) of three-dimensional geographic entities, and time dimension into a unified code to form a "one-dimensional spatiotemporal identifier." This identifier can record the dynamic changes of geographic entities in real time, solving the problems of low association efficiency and difficulty in spatiotemporal tracing of geographic entities. It achieves unified coding, efficient management, refined expression, and domestic application, providing a high-precision, scalable, and autonomously controllable spatiotemporal data identifier solution for major projects such as real-scene 3D, smart cities, and low-altitude economy. This represents a key technological breakthrough in the evolution of geographic information from "two-dimensional expression" to "three-dimensional control." Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0037] Figure 2 This is a schematic diagram of the spatiotemporal identifier encoding structure and example. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0039] The purpose of this invention is to construct a globally unified, multi-scale, and computable three-dimensional geographic entity spatiotemporal identification system, and to solve the bottlenecks of traditional two-dimensional spatiotemporal identification in three-dimensional space, dynamic changes, and big data processing. To this end, a three-dimensional geographic entity spatiotemporal identification encoding method based on the BeiDou grid is proposed.

[0040] Example 1: Using the BeiDou Global Positioning System (GeoSOT) grid system as the spatial reference, and combining timestamps and entity feature classification codes, a three-segment coding structure of "classification identifier + spatial identifier + time identifier" is constructed. In the spatial identifier, this method not only quickly calculates the 3D convex hull of the entity and finds the entity's maximum inner grid, but also determines the spatial location description of the three-dimensional geographic entity using the "six-point method," facilitating the reverse calculation of the spatial range and location of the three-dimensional geographic entity through the spatial identifier code.

[0041] Step 1: Determining the category identifier code, the specific process is as follows:

[0042] According to the classification scheme, coding scheme and classification and code extension principles specified in the "Classification and Code of Basic Geographic Information Elements" (GB / T 13923-2022), a 6-digit entity classification code is generated for the corresponding geographic entity, such as: street light (380501) and gas pipeline (545000).

[0043] Step 2: Calculation of spatial identifier codes, involving the calculation of the 3D convex hull and maximum inner mesh of the 3D geographic entity, such as... Figure 1 As shown, the specific process is as follows:

[0044] 1. Extract the surface (triangular mesh, 3D volume element) node point cloud of 3D geographic entities and use it as the input point set. Calculate the convex hull using the Qhull algorithm. To further improve the efficiency of convex hull generation, a KD-tree is constructed in the preprocessing stage to store the point set, accelerating subsequent normal vector calculation and farthest point search. A KD-tree pruning strategy is adopted to directly skip points inside the convex hull, reducing unnecessary distance calculations. During segmentation, the segmentation hyperplane is not fixed; principal component analysis is used to select the segmentation direction that maximizes the reduction of point count for dynamic segmentation.

[0045] 2. The center point of the entity is approximately determined by taking the average value of the nodes on the convex shell surface in the three dimensions of B, L, and H of the geodetic coordinate system.

[0046] 3. Calculate the minimum and maximum coordinates of the convex hull in the three dimensions B, L, and H of the geodetic coordinate system. Based on the coordinate range of the convex hull in the three dimensions, select the maximum range to initially determine the level of the three-dimensional grid. According to the three-dimensional grid coding rules defined in "BeiDou Grid Position Code" (GB / T39409-2020), the grid is divided into ten levels, with the highest level grid achieving an accuracy of 1.5cm.

[0047] 4. The BeiDou grid adopts an octree partitioning structure to further determine the hierarchy of the 3D grid. If a grid at a given level is contained within a convex hull, the level is determined; otherwise, the grid at that level is partitioned downwards level by level for determination. When determining the grid at a certain level, the ray method (a ray is emitted from the point to be measured in any direction in space; if the number of intersections with the convex hull is odd, the point is inside) is used to determine the vertices of the grid where the center point is located. If it is not inside the convex hull, the adjacent grids opposite it are further determined using seed growth. This neighborhood growth ends when a grid is completely outside the convex hull, reaching the growth boundary. If a grid is completely contained within the convex hull during the process, the current level is determined as the final level; otherwise, the process continues to partition and determine the next lower level.

[0048] 5. Calculate the six maximum and minimum points of the surface point cloud of the 3D entity in the three dimensions of B, L, and H of the geodetic coordinate system, so as to facilitate the determination of the spatial range of the entity through subsequent coding.

[0049] 6. Using the grid level determined in step 4, calculate the location codes of the 6 points in step 5 according to the calculation rules of the BeiDou 3D grid location code. For specific calculation process, refer to the 3D grid coding defined in "BeiDou Grid Location Code" (GB / T 39409-2020). For example, the BeiDou 3D grid location code under the 10th level grid with an accuracy of 1.5cm is "N036J0093000780B3010010520430140". Combining these six codes into a one-dimensional array is the spatial identifier code of the geographic entity.

[0050] Step 3: Calculation of the time identifier code, the specific process is as follows:

[0051] The encoding format is "geographic entity ID + timestamp". The time precision level can be accurate to the year, month, day, hour, minute and second. For example, if an entity ID is "G12345" and the timestamp is "20250430123000" (meaning 12:30:00 on April 30, 2025), then its time identification code is "G12345_20250430123000".

[0052] Step 4: Define the spatiotemporal identifier structure and composition of 3D geographic entities. The specific process is as follows:

[0053] The spatiotemporal identifier coding structure is a three-segment coding structure of "category identifier + spatial identifier + time identifier". Specific structure and examples are provided below. Figure 2 As shown, changes to 3D geographic entities can trigger a recalculation of the grid code and update the corresponding timestamp, retain historical spatiotemporal identifier codes, establish version associations, and support spatiotemporal evolution retrospection.

[0054] The above description is merely a preferred embodiment of the present invention and is used only to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A three-dimensional geographic entity spatiotemporal identification encoding method based on BeiDou grid codes, characterized in that, The outer 3D convex hull of a 3D geographic entity is calculated by KD tree pruning and principal component analysis. The subdivision level of the maximum inner hull grid is determined by using neighborhood seed growth. The spatial identifier of the entity described by the BeiDou 3D grid location code is calculated by the six-point method. The entity time identifier is further calculated in the form of geographic entity ID + timestamp.

2. The method according to claim 1, characterized in that, include: Determining the classification identifier code for geographic entities; Calculation of spatial identifiers for geographic entities; Calculation of geographic entity time identifier codes; Define the structure and composition of the spatiotemporal identifier code for geographic entities.

3. The method according to claim 2, characterized in that, The determination of the geographic entity classification identifier code includes: Based on the classification scheme, coding scheme, and classification and code extension principles stipulated in the "Classification and Code of Basic Geographic Information Elements" (GB / T 13923-2022), a 6-digit entity classification code for the geographic entity is generated.

4. The method according to claim 2, characterized in that, The calculation of the spatial identifier code for a geographic entity includes: Calculation of the outer 3D convex hull of a geographic entity; Determination of the hierarchical structure of the three-dimensional BeiDou grid; The six-point method is used to determine the spatial identifier of an entity.

5. The method according to claim 4, characterized in that, The calculation of the outer 3D convex hull of the geographic entity includes: Surface nodes of 3D geographic entities are extracted, a KD-tree is constructed to store the point set, and the Qhull algorithm is used to calculate the convex hull. During the calculation, a KD-tree pruning strategy and dynamic segmentation based on principal component analysis are adopted to improve the efficiency of the algorithm.

6. The method according to claim 4, characterized in that, The determination of the hierarchical structure of the three-dimensional BeiDou grid includes: During the hierarchical subdivision, neighboring seeds are grown from the initial grid where the entity's center point is located. The ray method is used to determine whether the grid is inside the convex hull, and the maximum inner grid is calculated. The level to which this grid belongs is determined as the subdivision level.

7. The method according to claim 4, characterized in that, The six-point method for determining the spatial identifier of an entity includes: The BeiDou 3D grid location codes of the six maximum and minimum points of a geographic entity in the three dimensions of the geodetic coordinate system are calculated, and the resulting one-dimensional array is the spatial identifier code of the geographic entity.

8. The method according to claim 1, characterized in that, The encoding format is geographic entity ID + timestamp. The timestamp uses fixed-length decimal characters to be accurate to the second.

9. The method according to claim 2, characterized in that, The structure and composition of the spatiotemporal identifier code for geographic entities include: A three-segment coding structure of classification identifier + spatial identifier + time identifier is adopted to form a unique three-dimensional geographic entity spatiotemporal identifier code.

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