Data fusion method and system based on multi-level three-dimensional space grid

Abstract

The invention relates to the technical field of data fusion, in particular to a data fusion method and system based on a multi-level three-dimensional space grid, and the method comprises the steps: building a two-dimensional plane space grid by taking a target coordinate as an original point, building a three-dimensional space grid based on elevation data by taking the two-dimensional plane space grid as a bottom surface, and fusing the multi-source data with the data of the two-dimensional plane space grid and the data of the three-dimensional space grid by using a preset fusion method to obtain multi-source fusion data. According to the method, the two-dimensional plane space grid and the three-dimensional space grid taking the two-dimensional plane space grid as the bottom surface are established, so that data from different sources can be systematically organized and integrated, and the data are more ordered; through a preset fusion method, the data from different sources can be effectively integrated together to form a more comprehensive and abundant data set.

Description

Technical Field

[0001] The present invention relates to the technical field of data fusion, and in particular to a data fusion method and system based on multi-level three-dimensional space grids. Background Art

[0002] Geographic information is the most active factor in national economic construction. It is closely related to production, life and social development, and is an important basis for making macro decisions. In the face of the ever-expanding geographic information resources, how to refine and mine them to meet the needs of users has become an important issue facing the information field, and spatial grid technology will be the most effective means. Geographic information is a comprehensive reflection of the complex system of the earth's surface with multiple characteristics such as positioning, association, continuation, and development. The processing and analysis of spatial information by spatial grid technology can quickly and dynamically reveal the spatiotemporal characteristics and change laws of surface information, and realize the rational use of three-dimensional space on land, sea and air. Spatial grid technology has been proven by relevant researchers at home and abroad to be a technology with unlimited potential and prospects. The research and practice of spatial grids are of special significance for grasping the direction of macro development and coordination mechanisms.

[0003] The existing technology has problems such as a single grid structure, a lack of spatial structure in the processed data, an inability to integrate and quickly display multi-type, multi-dimensional, massive data in space, and a lack of intuitive data presentation. Summary of the invention

[0004] (I) Purpose of the invention

[0005] The purpose of the present invention is to provide a data fusion method and system based on multi-level three-dimensional space grids with multiple grid structure levels, which can fuse and quickly display massive data.

[0006] (II) Technical solution

[0007] To solve the above problems, the present invention provides a data fusion method based on multi-level three-dimensional space grids, comprising:

[0008] Establishing a two-dimensional plane space grid with the target coordinates as the origin, and performing a first identification on each of the two-dimensional plane space grids;

[0009] Taking the two-dimensional plane space grid as the bottom surface and based on the elevation data, a three-dimensional space grid is established, wherein the three-dimensional space grid has multiple levels, and a second mark is performed on each level of the three-dimensional space grid;

[0010] Multi-source data is acquired, and according to the first identifier and the second identifier, the multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data.

[0011] In another aspect of the present invention, preferably, the multi-source fusion data includes terrain fusion data; the multi-source data includes terrain data, and the data source of the terrain data includes original terrain data and track data;

[0012] The method further includes: determining a terrain type of each two-dimensional plane space grid according to a first identifier of the two-dimensional plane space grid, wherein the terrain type includes an open area and a non-open area;

[0013] The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including:

[0014] For an open area, according to the first identifier, any one of the terrain data is merged with the two-dimensional plane space grid based on the spatial position relationship, and according to the second identifier, any one of the terrain data is merged with the three-dimensional space grid to obtain terrain data of the open area;

[0015] For a non-open area, according to the first identifier, the data corresponding to the first identifier in the terrain data is overlapped, according to the second identifier, the overlapping data corresponding to the second identifier in the terrain data is re-fused, and the fusion point is recorded, and the grid terrain data is replaced to form a grid data set of fused terrain to obtain the terrain data of the non-open area;

[0016] The open area terrain data and the non-open area terrain data are integrated to obtain terrain fusion data.

[0017] In another aspect of the present invention, preferably,

[0018] The multi-source fusion data also includes: structured fusion data, the structured fusion data includes land use type fusion data, population fusion data and traffic fusion data; the multi-source data also includes structured data;

[0019] The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including:

[0020] The geographical scope of the data source of the structured data and the first identifier of the two-dimensional plane space grid are intersected using spatial analysis technology, and the data assignment involved in the intersection operation is saved in the corresponding two-dimensional plane space grid. The geographical scope of the data source of the structured data and the second identifier of the three-dimensional space grid are intersected using spatial analysis technology, and the data assignment involved in the intersection operation is saved in the corresponding three-dimensional space grid to obtain structured fusion data.

[0021] In another aspect of the present invention, preferably,

[0022] Using spatial analysis technology to perform intersection operations, structured fusion data is obtained, including:

[0023] According to the first identifier or the second identifier and the geographical location of the data source of the structured data, an intersection area between the two is acquired, and an intersection array of the intersection areas is generated, where the intersection array includes the geographical location of each intersection area;

[0024] Extracting data from a data source of structured data according to the intersecting array, and mapping it to a corresponding two-dimensional plane space grid or a three-dimensional space grid;

[0025] The mapped data is merged with the data in the original two-dimensional plane space grid or three-dimensional space grid, and saved in the corresponding two-dimensional plane space grid or three-dimensional space grid.

[0026] In another aspect of the present invention, preferably,

[0027] The multi-source fusion data also includes: unstructured fusion data, the unstructured fusion data includes spatial fusion data; the multi-source data also includes unstructured data;

[0028] The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including:

[0029] Splitting the data source of the unstructured data according to elements, and using spatial analysis technology to determine the intersection of each element and the second identifier of the three-dimensional spatial grid;

[0030] Extracting data from a data source of unstructured data according to the intersection portion and mapping it into a corresponding three-dimensional spatial grid;

[0031] The mapped data is saved in the form of feature grids in the corresponding three-dimensional space grid.

[0032] In another aspect of the present invention, preferably, generating terrain data using track data includes:

[0033] The track data includes a plurality of track data points, and the track data points are supplemented by using a DTM model to obtain supplemented track data points;

[0034] Extract the elevation value of the supplemented track data point;

[0035] generating terrain data using the elevation value;

[0036] Wherein, the method of supplementing the track data points using the DTM model includes at least one of an irregular triangular grid interpolation method and a Kriging interpolation algorithm.

[0037] In another aspect of the present invention, preferably,

[0038] The first identifier includes a grid number, and a unique grid number is created for each two-dimensional plane space grid. The grid number is encoded according to the Beidou grid coding method, and the grid number includes row and column number + area code + county code + grid sequence code;

[0039] The second identifier is an elevation value added to the end of the grid number.

[0040] In another aspect of the present invention, preferably, the method further comprises: displaying the multi-source fusion data;

[0041] Displaying the multi-source fusion data includes: setting corresponding colors and transparency of the multi-source fusion data according to the magnitude of values.

[0042] In another aspect of the present invention, preferably, the two-dimensional plane space grid includes a first space grid and a second space grid, the size of the first space grid is larger than the second space grid, and the size of the plurality of second space grids is equal to the size of the first space grid;

[0043] The multi-source fusion data is displayed in a first space grid, a second space grid and a three-dimensional space grid.

[0044] In another aspect of the present invention, preferably, a data fusion system based on a multi-level three-dimensional space grid comprises:

[0045] A first establishing module: establishing a two-dimensional plane space grid with the target coordinates as the origin, and performing a first identification on each of the two-dimensional plane space grids;

[0046] The second establishment module: using the two-dimensional plane space grid as the bottom surface, based on the elevation data, establishes a three-dimensional space grid, wherein the three-dimensional space grid is multi-level, and performs a second identification on the three-dimensional space grid at each level;

[0047] Fusion module: acquires multi-source data, and fuses the multi-source data with the data of the two-dimensional plane space grid and the data of the three-dimensional space grid using a preset fusion method according to the first identifier and the second identifier, so as to obtain multi-source fused data.

[0048] (III) Beneficial effects

[0049] The above technical solution of the present invention has the following beneficial technical effects:

[0050] The present invention establishes a two-dimensional plane space grid and a three-dimensional space grid based on the two-dimensional plane space grid. This method can systematically organize and integrate data from different sources, making the data more orderly. The three-dimensional space grid established using elevation data can more accurately describe and locate entities in space. Through a preset fusion method, data from these different sources can be effectively integrated together to form a more comprehensive and rich data set. By displaying multi-source fusion data, complex data information can be presented in an intuitive way, which helps users better understand the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is an overall flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0053] Obviously, the described embodiments are only some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In the description of the present invention, it should be noted that the terms “first”, “second” and “third” are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0055] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0056] The present invention will be described in more detail below with reference to the accompanying drawings. In each of the accompanying drawings, the same elements are represented by similar reference numerals. For the sake of clarity, the various parts in the accompanying drawings are not drawn to scale.

[0057] Embodiment 1

[0058] A data fusion method based on multi-level three-dimensional space grid, Figure 1 FIG. 1 shows an overall flow chart of an embodiment of the present invention, as shown in FIG. Figure 1 As shown, including:

[0059] A two-dimensional plane space grid is established with the target coordinates as the origin, and a first identification is performed on each of the two-dimensional plane space grids; the specific position of the target coordinates is not limited here, nor is the specific number and level of the two-dimensional plane space grids. Optionally, in this embodiment, the two-dimensional plane space grid includes a first space grid and a second space grid, the size of the first space grid is larger than the second space grid, and the size of the multiple second space grids is equal to the size of the first space grid. If the target coordinates are Shanghai 2000 coordinates as the origin, a two-dimensional plane space grid with two levels of 1km*1km for the first space grid and 100m*100m for the second space grid is established; wherein the first space grid data takes each 1km*1km as a whole, and each 1km*1km includes the data of 10 100m*100m second space grids;

[0060] The first identifier includes a grid number. A unique grid number is created for each two-dimensional plane space grid. The grid number is encoded according to the Beidou grid coding method. The grid number includes row and column number + area code + county code + grid sequence code.

[0061] With the two-dimensional plane space grid as the bottom surface, a three-dimensional space grid is established based on the elevation data. The three-dimensional space grid is multi-level, and a second identification is performed on the three-dimensional space grid at each level; three-dimensional space grids of different height layers such as 100m, 200m, and 300m are constructed with reference to the Beidou grid method, and according to the projection coordinates, a two-dimensional plane space grid with 1km*1km and 100m*100m grids as the bottom square is constructed, and a three-dimensional space grid based on a multi-height hierarchical structure is constructed through a layer-by-layer method of pushing at different heights such as 100m, 200m, and 300m. According to the spatial position relationship, the two-dimensional plane space grids of 1km*1km and 100m*100m are merged with each layer of data in turn to generate three-dimensional space grid data at each fine-grained level. The second identification is to add the elevation value at the end of the grid number;

[0062] Acquire multi-source data, and fuse the multi-source data with a two-dimensional plane space grid and a three-dimensional space grid using a preset fusion method according to the first identifier and the second identifier to obtain multi-source fused data;

[0063] In this embodiment, the multi-source fusion data includes terrain fusion data; the multi-source data includes terrain data, and the data source of the terrain data includes original terrain data and track data; the original terrain data is relatively rough terrain data, which can be obtained through the Natural Resources Bureau, and the aircraft data can obtain relatively fine terrain data;

[0064] The method further includes: determining a terrain type of each two-dimensional plane space grid according to a first identifier of the two-dimensional plane space grid, wherein the terrain type includes an open area and a non-open area;

[0065] The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including:

[0066] For an open area, according to the first identifier, any one of the terrain data is merged with the two-dimensional plane space grid based on the spatial position relationship, and according to the second identifier, any one of the terrain data is merged with the three-dimensional space grid to obtain terrain data of the open area;

[0067] For open data, if there are less than two missing points, the existing points are used for fusion processing by numerical interpolation; if there are more than two missing points, Kriging or IDW is used for fusion processing;

[0068] For a non-open area, according to the first identifier, the data corresponding to the first identifier in the terrain data is overlapped, according to the second identifier, the overlapping data corresponding to the second identifier in the terrain data is re-fused, and the fusion point is recorded, and the grid terrain data is replaced to form a grid data set of fused terrain to obtain the terrain data of the non-open area;

[0069] The specific numerical interpolation steps are as follows:

[0070] Two-dimensional data fusion uses bilinear interpolation. For two-dimensional data P(x, y), there are four points Q11, Q12, Q21, and Q22 around it. The interpolation calculation method is as follows:

[0071]

[0072] Three-dimensional data fusion uses trilinear interpolation:

[0073]

[0074] ω is the weight calculated based on the most recent data point, and l is the loop variable;

[0075] The open area terrain data and the non-open area terrain data are integrated to obtain terrain fusion data.

[0076] In open areas, since the terrain is relatively flat, the terrain data from one of the data sources can be selected for fusion to reduce the amount of calculation and improve the processing speed. In non-open areas, especially urban areas, the terrain is complex and changeable, and the data corresponding to the first identifier in the first terrain data from multiple sources is overlapped to improve accuracy.

[0077] In this embodiment, further, the multi-source fusion data also includes: structured fusion data, the structured fusion data includes land use type fusion data, population fusion data and traffic fusion data; the multi-source data also includes structured data; the land use type data in the structured data comes from urban planning, land resource management and other departments, including the type, area, location and other information of various types of land. Population data comes from population census, demographics, etc., including information such as population size, age structure, gender ratio and other information of each region. Traffic data comes from the traffic management department, including information such as road network, traffic flow, public transportation stations and other information.

[0078] The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including:

[0079] The geographical range of the data source of the structured data and the first identifier of the two-dimensional plane spatial grid are intersected by using spatial analysis technology. The general steps of the spatial analysis technology for intersecting operation are as follows:

[0080] (1) Data preparation: Check the geographic accuracy of all data sources and make sure they are consistent with the coordinate system of the two-dimensional spatial grid;

[0081] (2) Select tools: Select the intersection tool in the GIS software or write an SQL query;

[0082] (3) Perform intersection operations: Run the tool or query, and the system automatically identifies the overlapping areas between the data source and the grid;

[0083] (4) Result processing: Process the results of the intersection operation to generate a new dataset containing all intersecting geographic features.

[0084] The data values ​​involved in the intersection operation are saved in the corresponding two-dimensional plane space grid, and the geographical scope of the data source of the structured data and the second identifier of the three-dimensional space grid are intersected using spatial analysis technology, and the data values ​​involved in the intersection operation are saved in the corresponding three-dimensional space grid to obtain structured fusion data.

[0085] Furthermore, in this embodiment, using spatial analysis technology to perform intersection operations to obtain structured fusion data includes:

[0086] According to the first identifier or the second identifier and the geographical location of the data source of the structured data, an intersection area between the two is acquired, and an intersection array of the intersection areas is generated, where the intersection array includes the geographical location of each intersection area;

[0087] Extracting data from a data source of structured data according to the intersecting array, and mapping it to a corresponding two-dimensional plane space grid or a three-dimensional space grid;

[0088] The mapped data is merged with the data in the original two-dimensional plane space grid or three-dimensional space grid, and saved in the corresponding two-dimensional plane space grid or three-dimensional space grid.

[0089] First, it is necessary to match the geographic scope of the data source of the structured data with the first identifier of the two-dimensional plane spatial grid or to match the geographic scope of the data source of the structured data with the second identifier. This can be done through spatial analysis techniques in the Geographic Information System (GIS), such as spatial indexing, spatial query, etc. The intersection operation in the spatial analysis technology is used to determine which structured data intersects with a specific spatial grid. The results of the intersection operation are accurately assigned to the corresponding grid. The data values ​​involved in the intersection operation are saved in the corresponding spatial grid. This includes storing data such as land use type, population, and transportation according to the division of the grid. While saving the data, data integration is also required to ensure that data from different sources are consistent within the grid and there is no omission or duplication.

[0090] Use spatial analysis techniques, such as spatial query and intersection operations in GIS, to determine the intersection area between the two. The intersection area refers to the part where the geographic range of the structured data overlaps with the spatial grid. In order to more accurately represent these areas, an intersection array can be generated, which contains the geographic location information of each intersection area, such as boundary coordinates, area, etc. Based on the generated intersection array, extract the data corresponding to the intersection area from the data source of the structured data. Including land use type, demographic data, traffic flow, etc.

[0091] The extracted data needs to be mapped to the corresponding two-dimensional plane space grid. The mapping process matches the geographic location of the data (such as coordinate points or range) with the geographic location of the grid cell to ensure that the data is accurately placed in the correct grid cell.

[0092] In this embodiment, further,

[0093] The multi-source fusion data also includes: unstructured fusion data, the unstructured fusion data includes spatial fusion data; the multi-source data also includes unstructured data;

[0094] The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including: splitting the data source of the unstructured data according to elements, where the elements may be keywords in the text and objects in the image; using a spatial analysis technique to determine the intersection of each element and the second identifier of the three-dimensional space grid;

[0095] Extracting data from a data source of unstructured data according to the intersection portion and mapping it into a corresponding three-dimensional spatial grid;

[0096] The mapped data is saved in the form of a feature grid to the corresponding three-dimensional spatial grid. The mapped data is saved in the form of a feature grid to the corresponding three-dimensional spatial grid. The feature grid is a data structure used to store and represent each feature in spatial data and its location information.

[0097] In this embodiment, further, generating terrain data using track data includes:

[0098] The track data includes a plurality of track data points, and the track data points are supplemented by using a DTM model to obtain supplemented track data points;

[0099] Extract the elevation value of the supplemented track data point;

[0100] generating terrain data using the elevation value;

[0101] Wherein, the method of supplementing the track data points using the DTM model includes at least one of an irregular triangular grid interpolation method and a Kriging interpolation algorithm.

[0102] The specific calculation method of irregular triangular mesh interpolation method is as follows:

[0103] Use Delaunay triangulation to create a triangular mesh of the point set; for the point P that needs to be interpolated, find the triangle that contains P; use linear interpolation to interpolate the value of P in the triangle. The linear interpolation formula is:

[0104]

[0105] Where (x1,y1,Z1),(x2,y2,Z2),(x3,y3,Z3) are the vertices of the triangle, (x,y) are the coordinates of the interpolation point, and Z is the estimated elevation of the interpolation point.

[0106] The Kriging interpolation algorithm is as follows:

[0107]

[0108] Z(x0) is the estimated value of position x0;

[0109] Z(x i ) is the value of the known sample point;

[0110]

[0111] λ iis the weight coefficient, which is determined by the following system of equations:

[0112] where γ(x i ,x j ) is the sample point x i and x j The semivariogram between .

[0113] Furthermore, the irregular triangular grid interpolation method and the Kriging interpolation algorithm can be fused according to the characteristics and requirements of the data to improve the accuracy and efficiency of interpolation. Partition fusion: The area to be interpolated is divided into multiple sub-areas, and each sub-area selects a suitable interpolation method according to the characteristics and requirements of the data. For example, the irregular triangular grid interpolation method is used in areas with sparse data, and the Kriging interpolation algorithm is used in areas with dense and highly correlated data.

[0114] Weighted fusion: For each interpolation point, the estimated values ​​of the irregular triangular grid interpolation method and the Kriging interpolation algorithm are calculated simultaneously, and then the two estimated values ​​are fused according to a certain weight coefficient to obtain the final interpolation result. The determination of the weight coefficient can be adjusted according to the characteristics and requirements of the data.

[0115] Iterative optimization: You can first use an interpolation method to perform preliminary interpolation, and then perform iterative optimization based on the interpolation results and data characteristics. For example, you can first use the irregular triangular grid interpolation method to perform preliminary interpolation, and then use the Kriging interpolation algorithm to correct and optimize the preliminary interpolation results.

[0116] Displaying the multi-source fusion data includes: setting corresponding colors and transparency of the multi-source fusion data according to numerical values.

[0117] The present invention establishes a two-dimensional plane space grid and a three-dimensional space grid based on the two-dimensional plane space grid. This method can systematically organize and integrate data from different sources, making the data more orderly. The three-dimensional space grid established using elevation data can more accurately describe and locate entities in space. Through a preset fusion method, data from these different sources can be effectively integrated together to form a more comprehensive and rich data set. By displaying multi-source fusion data, complex data information can be presented in an intuitive way, which helps users better understand the data.

[0118] Embodiment 2

[0119] A data fusion system based on multi-level three-dimensional space grids, comprising:

[0120] A first establishing module: establishing a two-dimensional plane space grid with the target coordinates as the origin, and performing a first identification on each of the two-dimensional plane space grids;

[0121] The second establishment module: using the two-dimensional plane space grid as the bottom surface, based on the elevation data, establishes a three-dimensional space grid, wherein the three-dimensional space grid is multi-level, and performs a second identification on the three-dimensional space grid at each level;

[0122] Fusion module: acquires multi-source data, and fuses the multi-source data with the data of the two-dimensional plane space grid and the data of the three-dimensional space grid using a preset fusion method according to the first identifier and the second identifier, so as to obtain multi-source fused data.

[0123] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalent forms of such scope and boundaries.

[0124] The present invention has been described above with reference to the embodiments of the present invention. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. The scope of the present invention is defined by the appended claims and their equivalents. Without departing from the scope of the present invention, a person skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

[0125] Although the embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.

[0126] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A data fusion method based on multi-level three-dimensional space grids, characterized in that: include: Establishing a two-dimensional plane space grid with the target coordinates as the origin, and performing a first identification on each of the two-dimensional plane space grids; Taking the two-dimensional plane space grid as the bottom surface and based on the elevation data, a three-dimensional space grid is established, wherein the three-dimensional space grid has multiple levels, and a second mark is performed on each level of the three-dimensional space grid; Multi-source data is acquired, and according to the first identifier and the second identifier, the multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data.

2. The data fusion method according to claim 1, characterized in that: The multi-source fusion data includes terrain fusion data; the multi-source data includes terrain data, and the data source of the terrain data includes original terrain data and track data; The method further includes: determining a terrain type of each two-dimensional plane space grid according to a first identifier of the two-dimensional plane space grid, wherein the terrain type includes an open area and a non-open area; The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including: For an open area, according to the first identifier, any one of the terrain data is merged with the two-dimensional plane space grid based on the spatial position relationship, and according to the second identifier, any one of the terrain data is merged with the three-dimensional space grid to obtain terrain data of the open area; For a non-open area, according to the first identifier, the data corresponding to the first identifier in the terrain data is overlapped, according to the second identifier, the overlapping data corresponding to the second identifier in the terrain data is re-fused, and the fusion point is recorded, and the grid terrain data is replaced to form a grid data set of fused terrain to obtain the terrain data of the non-open area; The open area terrain data and the non-open area terrain data are integrated to obtain terrain fusion data.

3. The data fusion method according to claim 1, characterized in that: The multi-source fusion data also includes: structured fusion data, the structured fusion data includes land use type fusion data, population fusion data and traffic fusion data; the multi-source data also includes structured data; The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including: The geographical scope of the data source of the structured data and the first identifier of the two-dimensional plane space grid are intersected using spatial analysis technology, and the data assignment involved in the intersection operation is saved in the corresponding two-dimensional plane space grid. The geographical scope of the data source of the structured data and the second identifier of the three-dimensional space grid are intersected using spatial analysis technology, and the data assignment involved in the intersection operation is saved in the corresponding three-dimensional space grid to obtain structured fusion data.

4. The data fusion method according to claim 3, characterized in that: Using spatial analysis technology to perform intersection operations, structured fusion data is obtained, including: According to the first identifier or the second identifier and the geographical location of the data source of the structured data, an intersection area between the two is acquired, and an intersection array of the intersection areas is generated, where the intersection array includes the geographical location of each intersection area; Extracting data from a data source of structured data according to the intersecting array, and mapping it to a corresponding two-dimensional plane space grid or a three-dimensional space grid; The mapped data is merged with the data in the original two-dimensional plane space grid or three-dimensional space grid, and saved in the corresponding two-dimensional plane space grid or three-dimensional space grid.

5. The data fusion method according to claim 1, characterized in that: The multi-source fusion data also includes: unstructured fusion data, the unstructured fusion data includes spatial fusion data; the multi-source data also includes unstructured data; The multi-source data is fused with the two-dimensional plane space grid and the three-dimensional space grid by using a preset fusion method to obtain multi-source fused data, including: Splitting the data source of the unstructured data according to elements, and using spatial analysis technology to determine the intersection of each element and the second identifier of the three-dimensional spatial grid; Extracting data from a data source of unstructured data according to the intersection portion and mapping it into a corresponding three-dimensional spatial grid; The mapped data is saved in the form of feature grids in the corresponding three-dimensional space grid.

6. The data fusion method according to claim 2, characterized in that: Generating terrain data using track data includes: The track data includes a plurality of track data points, and the track data points are supplemented by using a DTM model to obtain supplemented track data points; Extract the elevation value of the supplemented track data point; generating terrain data using the elevation value; Wherein, the method of supplementing the track data points using the DTM model includes at least one of an irregular triangular grid interpolation method and a Kriging interpolation algorithm.

7. The data fusion method according to claim 1, characterized in that: The first identifier includes a grid number, and a unique grid number is created for each two-dimensional plane space grid. The grid number is encoded according to the Beidou grid coding method, and the grid number includes row and column number + area code + county code + grid sequence code; The second identifier is an elevation value added to the end of the grid number.

8. The data fusion method according to claim 2, characterized in that: The method further comprises: displaying the multi-source fusion data; Displaying the multi-source fusion data includes: setting corresponding colors and transparency of the multi-source fusion data according to the magnitude of values.

9. The data fusion method according to claim 1, characterized in that: The two-dimensional plane space grid includes a first space grid and a second space grid, the size of the first space grid is larger than the second space grid, and the size of the plurality of second space grids is equal to the size of the first space grid; The multi-source fusion data is displayed in a first space grid, a second space grid and a three-dimensional space grid.

10. A data fusion system based on multi-level three-dimensional space grid, characterized in that: include: A first establishing module: establishing a two-dimensional plane space grid with the target coordinates as the origin, and performing a first identification on each of the two-dimensional plane space grids; The second establishment module: using the two-dimensional plane space grid as the bottom surface, based on the elevation data, establishes a three-dimensional space grid, wherein the three-dimensional space grid has multiple levels, and performs a second identification on each level of the three-dimensional space grid; Fusion module: acquires multi-source data, and fuses the multi-source data with the data of the two-dimensional plane space grid and the data of the three-dimensional space grid using a preset fusion method according to the first identifier and the second identifier, so as to obtain multi-source fused data.

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