A high- and low-precision DEM fusion method and system for three-dimensional digital power grid

Abstract

A method and system for fusing high- and low-precision DEMs for a three-dimensional digital power grid. The method includes obtaining laser point cloud data within the range of a power line channel, generating high-precision DEM terrain data based on the laser point cloud data; obtaining low-precision DEM data within the entire range of the transmission line-related area, cutting the low-precision DEM data based on the TMS global-geodetic rule and the quadtree structure, and obtaining low-precision DEM data slices of different levels; setting the circumscribed rectangle of the high-precision DEM terrain data as a buffer, and filling the low-precision DEM terrain data of the corresponding coordinates into the buffer; cutting the high-precision DEM data and the buffer based on the quadtree structure to form high-precision circumscribed rectangle file data slices with a buffer, and fusing the low-precision DEM terrain data slices and the high-precision circumscribed rectangle file data slices with a buffer into a 3D Tlies terrain data layer. The present invention fuses and publishes the high-precision terrain with the low-precision terrain to achieve a smooth transition.

Description

Technical Field

[0001] The invention belongs to the field of three-dimensional scene reconstruction, is applied to lightweight terrain publishing, and particularly relates to a high- and low-precision DEM fusion method and system for three-dimensional digital power grids. Background Art

[0002] At present, the most commonly used dynamic data loading format for efficient and interactive power 3D systems is 3DTiles, which is an online map tile service based on 3D spatial data. It can classify and organize massive spatial data according to geographical location and provide efficient data storage and transmission capabilities. This service can integrate different types of spatial data into the power 3D map service, allowing users to access and visualize this data on the platform.

[0003] The 3D Tiles service can efficiently process large-scale three-dimensional spatial data, achieve fast data presentation and interaction, and support multiple data formats, including point clouds, models, terrains, etc. In the construction of three-dimensional scenes, terrain data is the skeleton of the overall scene. The refinement of the terrain directly affects the realism of the entire power three-dimensional scene construction and the accuracy of data analysis. Therefore, lightweight publishing and processing of terrain data is an important part of three-dimensional scene construction.

[0004] Terrain data, also known as DEM (digital terrain model), can depict the authenticity and quantitative accuracy of terrain according to its accuracy. High-precision terrain can depict the ups and downs of the terrain more finely, while low-precision depiction is relatively rough. After processing, DEM data forms data tiles with the suffix .b3dm, which realizes the dynamic loading and rendering of front-end data. However, the current use of high-precision terrain data in the construction of large-scale three-dimensional scenes will lead to the problem of excessive data volume. Usually, three-dimensional scenes are only built in local areas, or scattered continuous or discontinuous areas. Therefore, the deployment of high-precision DEM terrain data in the entire scene or the entire range will bring a lot of data redundancy.

[0005] Prior art 1 provides a seamless fusion method for multi-source and multi-scale terrain data, obtaining low-precision DEM-A and high-precision DEM-B that need to be fused; extracting a range surface layer 1 of the high-precision DEM-B and performing a buffer analysis, reclassifying the high-precision terrain raster data, extracting a vector range surface, simplifying the vector range surface to obtain a range surface layer 1 of the high-precision terrain data DEM-B, performing a buffer analysis on layer 1 according to a buffer distance d, and obtaining an outward-expanded buffer vector surface layer 2 after simplification; taking the average value of two resolutions of DEM-A and DEM-B, and performing data fusion using an IDW method according to the range of layer 2 to obtain fused terrain data DEM-C; terrain data fusion, taking the DEM-B elevation value within the range of layer 1, taking the IDW values ​​of DEM-C and DEM-B within the difference range of layer 2 and layer 1, and taking the DEM-A value outside the range of layer 2; S5: performing window smoothing on the elevation values ​​within the difference range of layer 2 and layer 1; and clipping to obtain the fused DEM data according to the range of the operating area.

[0006] The second prior art provides a fusion method for digital earth. The first data LOD layer and the second data LOD layer of the same detail layer LOD layer are fused to obtain a fusion area, wherein the first data is a low-precision digital elevation model DEM data in the digital earth platform database, and the second data is a local high-precision DEM data; the boundary of the second data is extracted in the fusion area, and the boundary is used to expand and construct a second data buffer; characteristic points are obtained in the second data buffer according to a first preset rule, and the characteristic points are weighted and linearly interpolated to obtain smooth data in the buffer, and the smooth data includes a plurality of high- and low-precision fused data blocks; the high- and low-precision fused data blocks simplified by boundary points are geometrically joined according to a second preset rule to obtain a joined edge data block. A triangular mesh is constructed in the joined edge data block according to a third preset rule, and a fusion result is output.

[0007] It can be seen that the traditional lightweight terrain publishing method has the following problems:

[0008] (1) In 3D reconstruction tasks involving large areas, especially in the field of power transmission, the lines usually involve the entire province or city, and the relevant area can reach tens of thousands of square kilometers. In such a large area, the use of high-precision DEM terrain data will result in a huge amount of data, which greatly occupies data storage space and increases the cost of data storage deployment.

[0009] (2) Due to the massive amount of high-precision terrain tile data in a large area, the dynamic loading process on the web side puts a lot of pressure on the client computer and server in terms of data transmission efficiency and front-end webGL rendering efficiency, which seriously affects the loading smoothness and browsing experience of the 3D scene during the front-end 3D reconstruction process.

[0010] (3) The application of high-precision DEM terrain data over a large area results in a large amount of data, which makes lightweight slicing inefficient during the data release process, seriously affecting the timeliness of data release and the workload of internal staff, taking up a lot of manpower and time.

[0011] (4) To obtain a large-scale high-precision DEM, it is necessary to collect a large amount of surveying and mapping data for the relevant area, which is too costly and the production process is time-consuming and labor-intensive, which greatly increases the data cost of the power three-dimensional system.

[0012] (5) If a large area of ​​low-precision DEM data is used, although it can effectively reduce the amount of data, save time and cost, and improve the efficiency of dynamic data loading and rendering, the low-precision data is not accurate enough in subsequent power business data analysis and cannot meet the requirements. Summary of the invention

[0013] In order to address the deficiencies in the prior art, the present invention provides a high- and low-precision DEM fusion method and system for three-dimensional digital power grids, which realizes the fusion of high-precision and low-precision terrains, solves the key problems of excessive data volume and slow processing speed, and ensures the integrity of the three-dimensional reconstruction effect.

[0014] In order to solve the above technical problems, the present invention adopts the following technical solutions.

[0015] The present invention first discloses a method for fusing high-precision and low-precision terrain data, which comprises the following steps:

[0016] Step 1, obtaining laser point cloud data within the range of the power line channel, and generating first precision DEM terrain data according to the laser point cloud data;

[0017] Step 2, obtaining the second precision DEM data in the entire area related to the transmission line, cutting the second precision DEM data based on the TMS global-geodetic rule and the quadtree structure to obtain second precision DEM data slices of different levels; the first precision is higher than the second precision;

[0018] Step 3, setting the circumscribed rectangle of the first precision DEM terrain data as a buffer, and filling the second precision DEM terrain data of the corresponding coordinates into the buffer;

[0019] Step 4: based on the quadtree structure, the first precision DEM terrain data and the buffer are cut to form first precision circumscribed rectangular file data slices with buffers, and the second precision DEM terrain data slices and the first precision circumscribed rectangular file data slices with buffers are merged into a 3D Tlies terrain data layer.

[0020] The present invention further includes the following preferred embodiments:

[0021] The step of setting the bounding rectangle of the first precision DEM terrain data as a buffer zone further comprises:

[0022] A predefined distance is set by parameters, and a circumscribed rectangle of the first precision DEM terrain data at a predefined distance outward is used as a buffer zone.

[0023] The step of filling the buffer with the second precision DEM terrain data corresponding to the coordinates further comprises:

[0024] Filling the second precision DEM terrain data into the buffer, and performing triangular patch interpolation on the second precision DEM terrain data;

[0025] Fill the first precision DEM terrain data and perform morphological dilation operation;

[0026] A KD tree is established according to the data information of the second precision area and the first precision area, a data query index is constructed through the KD tree, the buffer is interpolated according to the inverse distance interpolation algorithm, and each raster image pixel area is filled through interpolation.

[0027] The method of cutting the second precision DEM data based on the TMS global-geodetic rule and the quadtree structure to obtain second precision DEM data slices of different levels further includes:

[0028] Select the WGS84 geodetic coordinate system. For any level n, the tile pixel resolution of the tile set at that level is 0.703125 / 2 n , level 0 is two 256×256 pixel tiles covering the entire world, with the origin Origin being (-180, 90); the tile set of the next level is formed by the quadrilateral division of the previous level.

[0029] The present invention also discloses a high-precision and low-precision DEM fusion system for three-dimensional digital power grids using the high-precision and low-precision DEM fusion method for three-dimensional digital power grids, comprising:

[0030] A high-precision terrain data generation module, used to obtain laser point cloud data within the range of the power line channel, and generate first-precision DEM terrain data according to the laser point cloud data;

[0031] A low-precision terrain data slicing module is used to obtain second-precision DEM data within the entire range of the transmission line related area, and to cut the second-precision DEM data based on the TMS global-geodetic rule and the quadtree structure to obtain second-precision DEM data slices of different levels; the first precision is higher than the second precision;

[0032] A buffer generation module, used to set the circumscribed rectangle of the first precision DEM terrain data as a buffer, and fill the second precision DEM terrain data of corresponding coordinates into the buffer;

[0033] A terrain data fusion module is used to cut the first precision DEM terrain data and the buffer based on a quadtree structure to form a first precision circumscribed rectangular file data slice with a buffer, and fuse the second precision DEM terrain data slice and the first precision circumscribed rectangular file data slice with a buffer into a 3D Tlies terrain data layer.

[0034] Accordingly, the present application also discloses a terminal, including a processor and a storage medium;

[0035] The storage medium is used to store instructions;

[0036] The processor is used to operate according to the instructions to execute the steps of the aforementioned method for fusing high-precision and low-precision DEMs for three-dimensional digital power grids.

[0037] Correspondingly, the present application also discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the aforementioned method for fusing high- and low-precision DEMs for a three-dimensional digital power grid.

[0038] The beneficial effect of the present invention is that, compared with the prior art, the present invention provides a method and system for fusing high-precision and low-precision DEMs for three-dimensional digital power grids, which seamlessly connects high-precision area data with low-precision area data during dynamic loading, and achieves smooth and realistic data transition through a fusion smoothing algorithm, thereby achieving natural connection between high-precision and low-precision areas and overall smooth and non-differential browsing during browsing, effectively reducing the overall data volume, and improving the lightweight tile publishing rate. In the three-dimensional reconstruction of large areas, the terrain effect of the area of ​​concern remains unchanged, maintaining the same rendering effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1It is a flow chart of the method for fusing high-precision and low-precision DEMs for three-dimensional digital power grids in the present invention.

[0040] Figure 2 It is a schematic diagram of the tile map in the present invention.

[0041] Figure 3

[0042] It is a schematic diagram of a blank high-precision terrain file with a buffer zone in the present invention.

[0043] Figure 4 It is a schematic diagram of the morphological expansion in the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present invention more clear, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0045] The embodiments described in this application are only some embodiments of the present invention, not all embodiments. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the protection scope of the present invention.

[0046] In view of the fact that high-precision DEM terrain data for large scenes is difficult to obtain and the quantity is limited, according to the demand for building three-dimensional scenes on the web side of the power grid industry, the present invention proposes a fusion method and system for high- and low-precision DEMs for three-dimensional digital power grids, which fuses and publishes high-precision terrain with low-precision terrain, seamlessly connects high-precision area data with low-precision area data during dynamic loading, and realizes smooth and realistic data transition through a fusion smoothing algorithm, thereby achieving a natural connection between high- and low-precision areas during browsing and overall smooth and indiscriminate browsing.

[0047] See also Figure 1 The present invention discloses a method for fusing high-precision and low-precision DEMs for a three-dimensional digital power grid, comprising the following steps:

[0048] Step 1: Obtain laser point cloud data within the range of the power line channel, and generate first-precision DEM terrain data based on the laser point cloud data.

[0049] The laser point cloud data collected by the power business is used to generate high-precision DEM terrain data. Since the collected laser point cloud data range is mainly related to the power business, the high-precision terrain data is more accurate than the fused low-precision DEM terrain data, and the high-precision terrain data range is significantly smaller than the entire administrative division data.

[0050] Step 2: Obtain the second-precision DEM data in the entire area related to the transmission line, and cut the second-precision DEM data based on the TMS global-geodetic rule and quadtree structure to obtain second-precision DEM data slices of different levels; the first precision is higher than the second precision.

[0051] Low-precision data can be obtained through procurement due to the large design area and wide region. Low-precision DEM data is usually used as macroscopic large scene data in the construction of power three-dimensional scenes. It is an important part of building simulated three-dimensional scenes and can make the overall scene more realistic. The lightweight release of low-precision data adopts the 3D Tlies data format. The cutting method adopts the DEM data cutting tool. By using the quadtree structure, the entire low-precision area is cut into corresponding data levels according to the geographic code, such as 1-13 levels (to be used below).

[0052] The terrain tile format set is segmented according to the international TMS (Tile Map Service) global-geodetic (global geodetic coordinate) rules. In TMS, a tile map (TileMap) consists of a set of tile sets (TileSet) with different scales, and each tile set is tiled with regular tiles of the same size format. The next level of tile sets is formed by the quad-division of the previous level (the entire map is a quadtree structure).

[0053] like Figure 2 As shown, the tile map has a bounding box and an origin. The origin is the lower left corner of the (0, 0) tile (also the upper right corner of the (-1, -1) tile), that is, the axis is to the left and up.

[0054] The global-geodetic segmentation rules are as follows. The coordinate system is the WGS84 geodetic coordinate system ( <srs> EPSG:4326< / srs> ). For any level n, the tile pixel resolution of the tile set at that level is units-per-pixel = 0.703125 / 2 n Level 0 consists of two tiles of 256×256 pixels (geographic size is 180×180 degrees) covering the entire world, with the origin Origin being (-180, 90).

[0055] All tiles have the suffix .terrain. The tile size is 65×65 pixels, and the last row and last column of the actual tile are the first row / first column of the adjacent east / south tile. Because its size is not 256×256, the resolution of its corresponding level is also different.

[0056] The following is an example of a URL for obtaining a tile.

[0057] For the top two tiles:

[0058] (-180°, -90°) - (0°, 90°) - / path / tilesets / terrain / smallterrain / 0 / 0 / 0.terrain

[0059] (0°, -90°) - (180°, 90°) - / path / tilesets / terrain / smallterrain / 0 / 1 / 0.terrain

[0060] The next level of eight tiles:

[0061] (-180°, -90°) - (-90°, 0°) - / path / tilesets / terrain / smallterrain / 1 / 0 / 0.terrain

[0062] (-90°, -90°) - (0°, 0°) - / path / tilesets / terrain / smallterrain / 1 / 1 / 0.terrain

[0063] (0°, -90°) - (90°, 0°) - / path / tilesets / terrain / smallterrain / 1 / 2 / 0.terrain

[0064] (90°, -90°) - (180°, 0°) - / path / tilesets / terrain / smallterrain / 1 / 3 / 0.terrain

[0065] (-180°, 0°) - (-90°, 90°) - / path / tilesets / terrain / smallterrain / 1 / 0 / 1.terrain

[0066] (-90°, 0°) - (0°, 90°) - / path / tilesets / terrain / smallterrain / 1 / 1 / 1.terrain

[0067] (0°, 0°) - (90°, 90°) - / path / tilesets / terrain / smallterrain / 1 / 2 / 1.terrain

[0068] (90°, 0°)-(180°, 90°)- / path / tilesets / terrain / smallterrain / 1 / 3 / 1.terrain

[0069] According to the above terrain tile data rules, the DEM data clipping tool for lightweight publishing is used to achieve slicing of low-precision DEM terrain data.

[0070] Step 3: Set the bounding rectangle of the first precision DEM terrain data as a buffer zone, and fill the second precision DEM terrain data of the corresponding coordinates into the buffer zone.

[0071] Get the latitude, longitude and precision information of low- and high-precision terrain data from the file attributes. Use low-precision terrain data to obtain an outer rectangle by taking the minimum and maximum values ​​of longitude and latitude. Combine the longitude and latitude range of low-precision terrain data with the precision of high-precision terrain data to obtain a blank tif format terrain file that combines high and low-precision terrain, such as Figure 3 As shown in the largest rectangle in the figure, the subsequent operation is to fill the data of this file. The purpose of adding a buffer is to prevent the high-precision terrain data from overflowing at the edge of the low-precision terrain data (such as Figure 3 In the figure, A and B are high-precision terrains, and the gray area is the buffer area, which is located at the edge of the low-precision terrain).

[0072] Initialize the blank high-precision terrain file in the previous step, and fill the low-precision terrain data into the file according to the latitude and longitude range with the altitude data in the terrain file. Filling low-precision data into a blank high-precision terrain file with a buffer will produce multiple holes, so it is necessary to use low-precision data to interpolate the triangles in the high-precision terrain file with a buffer.

[0073] Triangle interpolation is a numerical method for interpolating mesh data. This method uses the properties of triangles to interpolate by calculating the barycentric coordinates of an unknown point.

[0074] The basic idea of ​​the triangular interpolation method is to connect the data points into a triangular mesh through lines and insert an unknown point in each triangle. Then, by calculating the centroid coordinates of the unknown point and linearly combining it with the vertex values ​​of the triangle, the interpolation result of the unknown point is obtained. The specific steps are as follows:

[0075] a. Construct a triangular mesh based on the given data points. You can use a triangulation algorithm (such as Delaunay triangulation) to connect the data points into a continuous triangular mesh.

[0076] b. For each triangle, the interpolation result of the unknown point is determined by calculating the barycentric coordinates of the unknown point and the three vertices, i.e. the scale factor (weights). The barycentric coordinates are calculated based on the area of ​​the triangle.

[0077] c. For a given unknown point, determine the triangle it is in. You can determine the triangle by determining whether the unknown point is inside the triangle.

[0078] d. Calculate the interpolation result of the unknown point through linear combination based on the vertex values ​​and barycentric coordinates of the triangle.

[0079] After the interpolation is completed, the multiple high-precision terrain data to be fused are filled into the high-precision terrain file with buffer. Because pixels are integers, rounding operations are required during the assignment process. During the transformation process of two adjacent pixels of the original high-precision terrain data, one pixel will be separated due to rounding. At this time, the high-precision data after the assignment is morphologically expanded to fill the empty pixel.

[0080] Morphological dilation operation is an operation method in digital image processing. It can fill small holes in the image, reduce the holes in objects, connect objects and make them more connected, and also eliminate small noise points. Figure 4 The figure is a morphological flow chart. The center point of the structural element is slid around the area to be expanded in turn, and the small squares (elements) that just intersect with the shaded area are found. These elements that just intersect are critical small squares. All elements within these elements belong to the expanded area, and the structures outside are not expanded. The center point of the element is aligned with the center point of each set around the shaded area, and is translated and aligned in turn. If the origin of the structural element slides to a small square position and the structural element intersects with the shaded area (the small square of the intersection is represented by dark gray), then the small square (element) corresponding to the origin of the structural element is expanded, and so on.

[0081] Finally, the high-precision terrain file with buffer is assigned. Figure 3 The gray area near the A and B areas is assigned a value. The row and column data of the pixels in the high and low precision areas are used to build a KD tree respectively. The purpose of building the KD tree is to find the point where the pixel in the buffer area is closest to the pixel in the high and low precision areas, and then calculate the altitude of the pixel in the buffer area using the altitude points of the high and low precision pixel positions according to the inverse distance interpolation algorithm.

[0082] The basic idea of ​​the inverse distance interpolation method is that the attribute value of the unknown position is inversely proportional to the attribute value of the known position. The closer the distance, the greater the weight of the point, and the farther the distance, the smaller the weight of the point. Specifically, the inverse distance interpolation method estimates the attribute value of the unknown position as:

[0083] Z(x,y)=Σ(wi *z i ) / Σw i

[0084] Among them, Z(x,y) is the attribute value of the unknown position, z i is the attribute value of the known position i, w i is the reciprocal of the distance between the known position i and the unknown position, and Σ represents the sum of all known positions i.

[0085] Step 4: Based on the quadtree structure, the first precision DEM terrain data and the buffer are cut to form first precision circumscribed rectangular file data slices with buffers, and the second precision DEM terrain data slices and the first precision circumscribed rectangular file data slices with buffers are merged into a 3D Tlies terrain data layer.

[0086] The bounding rectangle area is sliced ​​into high-precision DEM terrain data in accordance with the above-mentioned slicing method to form high-precision bounding rectangle file data slices with buffer zones.

[0087] The low-precision DEM terrain data slices and the high-precision external rectangular file data slices with buffer are merged to form a complete 3D Tlies format terrain data layer.

[0088] The beneficial effect of the present invention is that, compared with the prior art, the present invention provides a method and system for fusing high-precision and low-precision DEMs for three-dimensional digital power grids, which seamlessly connects high-precision area data with low-precision area data during dynamic loading, and achieves smooth and realistic data transition through a fusion smoothing algorithm, thereby achieving natural connection between high-precision and low-precision areas and overall smooth and non-differential browsing during browsing, effectively reducing the overall data volume, and improving the lightweight tile publishing rate. In the three-dimensional reconstruction of large areas, the terrain effect of the area of ​​concern remains unchanged, maintaining the same rendering effect.

[0089] The present invention may be a system, a method and / or a computer program product. The present invention also discloses a high-precision and low-precision DEM fusion system for a three-dimensional digital power grid based on the above-mentioned high-precision and low-precision DEM fusion method for a three-dimensional digital power grid, comprising:

[0090] A high-precision terrain data generation module is used to obtain laser point cloud data within the range of the power line channel and generate high-precision DEM terrain data based on the laser point cloud data;

[0091] A low-precision terrain data slicing module is used to obtain low-precision DEM data in the entire range of the transmission line related area, and to cut the low-precision DEM data based on the TMS global-geodetic rule and quadtree structure to obtain low-precision DEM data slices of different levels;

[0092] A buffer generation module, used to set the circumscribed rectangle of the high-precision DEM terrain data as a buffer, and fill the low-precision DEM terrain data of the corresponding coordinates into the buffer;

[0093] The terrain data fusion module is used to cut the high-precision DEM data and the buffer based on the quadtree structure to form high-precision circumscribed rectangular file data slices with a buffer, and fuse the low-precision DEM terrain data slices and the high-precision circumscribed rectangular file data slices with a buffer into a 3D Tlies terrain data layer.

[0094] Based on the spirit of the present invention, those skilled in the art can easily think that a computer program product can be obtained based on the aforementioned method for fusing high- and low-precision DEMs for three-dimensional digital grids. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for enabling a processor to implement various aspects of the present disclosure are loaded. That is, the present application also includes a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the aforementioned method for fusing high- and low-precision DEMs for three-dimensional digital grids.

[0095] Computer readable storage medium can be a tangible device that can keep and store the instructions used by the instruction execution device. Computer readable storage medium can be, for example, - but not limited to - electrical storage device, magnetic storage device, optical storage device, electromagnetic storage device, semiconductor storage device or any suitable combination of the above. More specific examples (non-exhaustive list) of computer readable storage medium include: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device, such as punch card or groove protrusion structure with instructions stored thereon and any suitable combination of the above. Computer readable storage medium used here is not interpreted as instantaneous signal itself, such as radio wave or other free propagating electromagnetic wave, electromagnetic wave propagated by waveguide or other transmission medium (for example, light pulse by optical fiber cable) or electrical signal transmitted by wire.

[0096] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0097] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect through the Internet). In some embodiments, by using the state information of the computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA) or a programmable logic array (PLA), the electronic circuit may execute the computer-readable program instructions, thereby implementing various aspects of the present disclosure.

[0098] Finally, it should be noted that 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 above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for fusing high-precision and low-precision DEMs for a three-dimensional digital power grid, characterized in that: The following steps are involved: Step 1, obtaining laser point cloud data within the range of the power line channel, and generating first precision DEM terrain data according to the laser point cloud data; Step 2, obtaining the second precision DEM data in the entire range of the transmission line related area, cutting the second precision DEM data based on the TMS global-geodetic rule and the quadtree structure to obtain second precision DEM data slices of different levels; The first precision is higher than the second precision; Step 3, setting the circumscribed rectangle of the first precision DEM terrain data as a buffer, and filling the second precision DEM terrain data of the corresponding coordinates into the buffer; Step 4: based on the quadtree structure, the first precision DEM terrain data and the buffer are cut to form first precision circumscribed rectangular file data slices with buffers, and the second precision DEM terrain data slices and the first precision circumscribed rectangular file data slices with buffers are merged into a 3D Tlies terrain data layer.

2. The method for fusing high-precision and low-precision DEM for three-dimensional digital power grid according to claim 1 is characterized in that: The step of setting the bounding rectangle of the first precision DEM terrain data as a buffer zone further comprises: A predefined distance is set by parameters, and a circumscribed rectangle of the first precision DEM terrain data at a predefined distance outward is used as a buffer zone.

3. The method for fusing high-precision and low-precision DEM for three-dimensional digital power grid according to claim 2 is characterized in that: The step of filling the buffer with the second precision DEM terrain data corresponding to the coordinates further comprises: Filling the second precision DEM terrain data into the buffer, and performing triangular patch interpolation on the second precision DEM terrain data; Fill the first precision DEM terrain data and perform morphological dilation operation; A KD tree is established according to the data information of the second precision area and the first precision area, a data query index is constructed through the KD tree, the buffer is interpolated according to the inverse distance interpolation algorithm, and each raster image pixel area is filled through interpolation.

4. The method for fusing high-precision and low-precision DEM for three-dimensional digital power grid according to claim 3 is characterized in that: The method of cutting the second precision DEM data based on the TMS global-geodetic rule and the quadtree structure to obtain second precision DEM data slices of different levels further includes: Select the WGS84 geodetic coordinate system. For any level n, the tile pixel resolution of the tile set at that level is 0.703125 / 2 n , level 0 is two 256×256 pixel tiles covering the entire world, with the origin Origin being (-180, 90); the tile set of the next level is formed by the quadrilateral division of the previous level.

5. A high-precision and low-precision DEM fusion system for three-dimensional digital power grid, characterized in that: include: A high-precision terrain data generation module, used to obtain laser point cloud data within the range of the power line channel, and generate first-precision DEM terrain data according to the laser point cloud data; A low-precision terrain data slicing module is used to obtain second-precision DEM data within the entire range of the transmission line related area, and to cut the second-precision DEM data based on the TMS global-geodetic rule and the quadtree structure to obtain second-precision DEM data slices of different levels; the first precision is higher than the second precision; A buffer generation module, used to set the circumscribed rectangle of the first precision DEM terrain data as a buffer, and fill the second precision DEM terrain data of corresponding coordinates into the buffer; A terrain data fusion module is used to cut the first precision DEM terrain data and the buffer based on a quadtree structure to form a first precision circumscribed rectangular file data slice with a buffer, and fuse the second precision DEM terrain data slice and the first precision circumscribed rectangular file data slice with a buffer into a 3D Tlies terrain data layer.

6. The high-precision and low-precision DEM fusion system for three-dimensional digital power grid according to claim 5 is characterized in that: The buffer generation module is further used for: A predefined distance is set by parameters, and a circumscribed rectangle of the first precision DEM terrain data at a predefined distance outward is used as a buffer zone.

7. The high-precision and low-precision DEM fusion system for three-dimensional digital power grid according to claim 6 is characterized in that: The buffer generation module is further used for: Filling the second precision DEM terrain data into the buffer, and performing triangular patch interpolation on the second precision DEM terrain data; Fill the first precision DEM terrain data and perform morphological dilation operation; A KD tree is established according to the data information of the second precision area and the first precision area, a data query index is constructed through the KD tree, the buffer is interpolated according to the inverse distance interpolation algorithm, and each raster image pixel area is filled through interpolation.

8. The high-precision and low-precision DEM fusion system for three-dimensional digital power grid according to claim 7 is characterized in that: The low-precision terrain data slicing module is further used for: Select the WGS84 geodetic coordinate system. For any level n, the tile pixel resolution of the tile set at that level is 0.703125 / 2 n , level 0 is two 256×256 pixel tiles covering the entire world, with the origin Origin being (-180, 90); the tile set of the next level is formed by the quadrilateral division of the previous level.

9. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the method for fusing high-precision and low-precision DEMs for a three-dimensional digital power grid according to any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method for fusing high-precision and low-precision DEMs for a three-dimensional digital power grid as described in any one of claims 1 to 4 are implemented.

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