A data processing system and data processing method for visualizing the movement of fluids in three dimensions.

Abstract

Providing technology to perform the tasks necessary for creating height maps accurately and efficiently. [Solution] In System 1, the first processing unit 10 extracts the necessary data items from the mesh data MA and MT in a specified format according to a predefined workflow to obtain terrain data 41 and analysis data 42, and then creates intermediate data 43 based on these. Next, the second processing unit 20 fills in any missing values ​​in the intermediate data 43. Then, the third processing unit 30 optimizes multiple vertices that overlap on the same planar coordinate system and have different heights from the water surface reference plane to become one, and then generates and optimizes a water surface model (TIN surface) 44 based on the optimized intermediate data 43, and finally generates a height map 45 from the obtained water surface model 44. Since most of the processing is performed automatically, highly skilled manual work is not required, and data of a certain quality or higher can be efficiently created.

Description

[Technical Field]

[0001] The present invention relates to a data processing system and method for creating data necessary to visualize in three dimensions the movement of a predetermined fluid that may cover and flow over the Earth's surface due to natural phenomena. [Background technology]

[0002] Digital twin platforms utilizing 3D city models have proven effective in various fields, and numerous public-private initiatives are underway, including Project PLATEAU led by the Ministry of Land, Infrastructure, Transport and Tourism (Non-Patent Literature 1). Within these platforms, there is a need to visualize flood risk for purposes such as checking the validity of land development plans and flood control plans, and examining disaster prevention plans and evacuation routes. Visualizing flood risk requires handling two types of mesh data: topographic data from the 3D city model and analysis results data of flood risk.

[0003] By the way, handling map data is fraught with difficulties. For example, Reference 1 discloses a method to address the fact that in digital maps, elevation data is shown discretely in numerical values ​​of a predetermined unit, and as a result of truncating values ​​below that unit, errors are included in the elevation data. This method involves interpolating the elevation data of mesh coordinate values ​​based on the digital map data to approximate the actual terrain. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2003-208094 [Non-patent literature]

[0005] [Non-Patent Document 1] PLATEAU website, "PLATEAU: A project to realize digital twins of cities throughout Japan, promoted by the Ministry of Land, Infrastructure, Transport and Tourism in collaboration with various players," https: / / www.mlit.go.jp / plateau / , Ministry of Land, Infrastructure, Transport and Tourism, accessed August 8, 2024. [Overview of the Initiative] [Problems that the invention aims to solve]

[0006] To visualize flood risk on the platform described above, the temporal changes in the flood risk analysis results are converted into the shape of the water surface, etc., and superimposed on a 3D city model. For example, based on the topographic data of the 3D city model and the flood risk analysis results, the temporal changes in the flood risk analysis results can be converted into a two-dimensional grayscale image called a heightmap, where white indicates the highest point and black indicates the lowest point, and this can be imported into the platform for use.

[0007] However, the terrain data of the 3D city model and the flood risk analysis results data differ not only in their geodetic systems, coordinate systems, and height standards, but also in their data formats, mesh coarseness, and shape. Therefore, workers must understand these differences and the meaning of each data point, properly assemble the work procedure, and unify the differences before performing the various tasks necessary to create the height map. This requires considerable skill and experience from the workers, and differences in experience can affect the quality of the deliverables. In addition, it is necessary to create a natural-looking water surface model without compromising the accuracy of the flood risk analysis results as much as possible, which requires a lot of manual work. If corrections are noticed after the model is close to completion, the work has to be redone, resulting in an enormous amount of time required to complete the height map.

[0008] This invention has been made in view of these problems, and aims to provide a technology that can perform the tasks necessary for creating height maps accurately and efficiently. [Means for solving the problem]

[0009] To solve the above problems, the present invention employs the following data processing system and method implemented by this system. Note that the following statements in parentheses are merely illustrative and the present invention is not limited thereto.

[0010] In other words, the data processing system of the present invention is a data processing system that creates data necessary to visualize in three dimensions the movement of a predetermined fluid that may cover and flow over the Earth's surface due to natural phenomena, and comprises: a first processing unit that acquires first data having ground height information at each vertex based on topographic data and second data having coverage height information of the fluid at each vertex included in the analysis mesh based on analysis data related to the fluid, and adds vertices corresponding to planar coordinates that are included in the first data but not in the second data to the second data to create intermediate data; a second processing unit that, with respect to the intermediate data, adds coverage height information to the vertices added by the first processing unit in accordance with predetermined rules, adds ground height information to the other vertices based on the first data, and then adds height information from a reference plane of the fluid surface obtained by adding the ground height and coverage height to each vertex to refine the intermediate data; and a third processing unit that optimizes the refined intermediate data for discontinuities or unnatural parts that would occur if it were made three-dimensional, based on predetermined conditions, and then creates a fluid model representing the surface of the fluid based on the optimized intermediate data.

[0011] While manually creating the target data requires considerable experience and skill and takes an enormous amount of time, this type of data processing system automates most of the processes involved in data creation. As a result, operators do not need to perform highly skilled manual work, and data of a certain quality or higher can be created efficiently and in a short amount of time.

[0012] Preferably, in the data processing system of the above-described aspect, prior to creating the intermediate data, the first processing unit extracts data items necessary for creating the intermediate data from a plurality of external data that may have different data formats and converts them into a predetermined data format. Along a predefined flow, it acquires first data in a predetermined data format from topographic data while acquiring second data in a predetermined data format from analysis data, and unifies the geodetic system and coordinate system of these data.

[0013] According to the data processing system of this aspect, since the necessary data is extracted from the topographic data and the analysis data in a predetermined data format along a predefined flow and their geodetic system and coordinate system are unified, even without knowledge of the data structure and content, the data necessary for creating the intermediate data can be easily prepared.

[0014] More preferably, in the data processing system of any of the above-described aspects, when adding the ground height information, the second processing unit selects three vertices adjacent to and surrounding each of the other vertices described above, and calculates the height corresponding to the coordinate value of the vertex on the plane of the triangle formed by connecting these three vertices, and sets the height as the ground height for the vertex.

[0015] According to the data processing system of this aspect, since the ground height for a vertex without ground height information is calculated based on three vertices with ground height information adjacent to and surrounding this vertex, a value close to the actual ground height can be stored for the vertex without ground height information.

[0016] Even more preferably, in the data processing system of any of the above-described aspects, the third processing unit performs optimization by adjusting the number and height of vertices located on the boundary between two cells sharing the same planar coordinates at the boundary divided by the mesh. Also, the third processing unit performs optimization in consideration of the change in the height from the reference plane of the surface of the fluid over time between two cells sharing the same planar coordinates at the boundary divided by the mesh.

[0017] According to this data processing system, optimization is performed for multiple vertices of the fluid surface that overlap on the same planar coordinate system and have different heights from the reference plane. As a result, a single vertex for each planar coordinate system, and consequently the height of the fluid surface from the reference plane, can be determined. Therefore, when creating a fluid model based on intermediate data, the fluid surface can be made to appear continuous and natural.

[0018] Preferably, in any of the data processing systems described above, the third processing unit generates a fluid model in which the surface of the fluid is represented by an irregular triangular network formed by Delaunay triangulation, based on the optimized intermediate data. If a specification is made regarding the number of vertices or polygons constituting the fluid model, the third processing unit optimizes the fluid model based on this specification and finally generates a height map corresponding to the fluid model.

[0019] According to this data processing system, the surface of the fluid is represented by a combination of triangles without sharp angles, thus forming a natural surface with smooth changes in height. Furthermore, since the fluid model is optimized based on specified conditions, the rendering load of the fluid model can be reduced, and processing can be sped up.

[0020] More preferably, in any of the data processing systems described above, the first processing unit is capable of receiving an operation to display intermediate data before and after adding vertices and to specify the content of the correction thereof, and when such an operation is received, it corrects the intermediate data according to the specification, and the third processing unit is capable of receiving an operation to display the fluid model before and after optimization and to specify the content of the correction thereof, and when such an operation is received, it regenerates the fluid model according to the specification.

[0021] According to this data processing system, during the process of creating intermediate data and fluid models, operators can visually check the status of the object being created and make detailed corrections, allowing for meticulous manual adjustments as needed. This prevents situations where corrections are only noticed at the final stage, and consequently, prevents extensive rework, thereby significantly reducing the time required to complete the height map.

[0022] More preferably, in any of the data processing systems described above, all processing, from the processing by the first processing unit to the processing by the third processing unit, can be performed automatically without human intervention.

[0023] According to this type of data processing system, all processing can be performed automatically, making it possible to efficiently and quickly create data with a certain level of quality necessary for visualizing the movement of fluids in three dimensions. This also makes it possible to streamline the development work of functions and content on a digital twin platform that uses the created data and shorten the development period. [Effects of the Invention]

[0024] As described above, the present invention makes it possible to perform the tasks necessary for creating a height map accurately and efficiently. [Brief explanation of the drawing]

[0025] [Figure 1] This is a block diagram showing the configuration of a data processing system 1 according to one embodiment. [Figure 2] This is a flowchart showing an overview of the processing in data processing system 1. [Figure 3] This flowchart shows an example of the procedure for creating intermediate data. [Figure 4] This diagram provides supplementary information about the intermediate data creation process. [Figure 5] This figure shows an example of a confirmation screen during the creation process of intermediate data 43. [Figure 6] This flowchart shows an example of the procedure for supplementing intermediate data. [Figure 7] This diagram supplements the details of the intermediate data replenishment process. [Figure 8] This diagram simply shows the contents of the intermediate data 43 after the intermediate data supplementation process has been executed. [Figure 9] This diagram illustrates the overlap of vertices at the mesh boundary. [Figure 10] This flowchart shows an example of the procedure for creating a water surface model. [Figure 11] This is a diagram (1 / 3) illustrating the intermediate data optimization process. [Figure 12] This is a diagram (2 / 3) illustrating the intermediate data optimization process. [Figure 13] This is a diagram (3 / 3) illustrating the intermediate data optimization process. [Figure 14] This figure shows an example of a confirmation screen for the TIN surface 44 on the water surface. [Figure 15] This figure shows an example of the TIN surface 44 and height map 45 of the water surface displayed on the confirmation screen. [Modes for carrying out the invention]

[0026] Embodiments of the present invention will be described below with reference to the drawings. Note that the following embodiments are preferred examples of data processing systems, and the present invention is not limited to these examples.

[0027] [Configuration of the data processing system] Figure 1 is a block diagram showing the configuration of a data processing system 1 according to one embodiment. Figure 2 is a flowchart showing the general flow of processing performed in the data processing system 1.

[0028] Data processing system 1 is a system that creates data necessary to visualize in three dimensions the risk of flooding due to a levee breach, that is, how water flows and how the flooding situation changes when a levee breach occurs due to rainfall. To facilitate understanding of the invention, in Figure 1, the direction of signal and data flow is indicated by black arrows, and the changes in the form of data created by the system are indicated by white arrows.

[0029] As shown in Figure 1(A), the data processing system 1 is broadly composed of three processing units 10, 20, and 30, each responsible for a series of processes necessary for data creation, and a storage unit 40 that stores the data created by each of these processing units. The storage unit 40 is, for example, a memory, disk, database, or other storage device.

[0030] The first processing unit 10 extracts necessary data items in a predetermined data format from mesh data MA (hereinafter abbreviated as "analysis mesh data MA"), which is the result of an analysis of the flood risk in the event of a levee breach due to rainfall of a predetermined magnitude (assumed maximum magnitude or planned magnitude), obtained from an external server or website (for example, the Ministry of Land, Infrastructure, Transport and Tourism's Flood Navigator), and from terrain mesh data MT (hereinafter simply referred to as "terrain mesh data MT"), which is obtained from an external server or website (for example, the Geospatial Information Authority of Japan's Fundamental Geospatial Information (Digital Elevation Model)) or created based on a development plan for a 3D urban model, and creates intermediate data 43 based on the data extracted from these two types of mesh data MA and MT.

[0031] In the following explanation, the data extracted from the terrain mesh data MT will be referred to as "terrain data 41," the data extracted from the analysis mesh data MA will be referred to as "analysis data 42," the mesh (grid) in the analysis data will be referred to as "analysis mesh," and the individual regions divided by the analysis mesh in the analysis data will be referred to as "cells."

[0032] The second processing unit 20 supplements the planar coordinates contained in the intermediate data 43 with height-related information, specifically values ​​for inundation depth, ground elevation, and height from the water surface reference plane.

[0033] The third processing unit 30, with respect to the supplemented intermediate data 43, optimizes the vertices on the boundary of the analysis mesh where multiple vertices exist on the same planar coordinate plane with different heights from the reference plane of the water surface, determining that there is one vertex for each planar coordinate plane. Based on the optimized intermediate data 43, it creates a three-dimensional model representing the water surface (hereinafter referred to as the "water surface model") 44. After optimizing the water surface model 44 as necessary, it generates a height map 45 based on the water surface model 44.

[0034] To reiterate the overview of the processes performed in the data processing system 1, following the flowchart shown in Figure 2, first, the first processing unit 10 receives terrain mesh data MT and analysis mesh data MA (step S100), and creates intermediate data 43 based on terrain data 41 and analysis data 42 extracted from these two types of mesh data (step S200). Next, the second processing unit 20 supplements the intermediate data 43 with height information (step S300). Then, the third processing unit 30 optimizes the intermediate data 43 and creates a water surface model 44 based on it (step S400), and finally generates a height map 45 from the obtained water surface model 44 (specifically, a TIN surface of the water surface) and outputs it to a file in the specified format (step S500). The specific details of each process will be described in detail later with reference to other diagrams.

[0035] By performing the series of processes shown in Figure 2, a number of heightmaps 45 are generated corresponding to the number of time points t corresponding to the elapsed time t since the levee breach in the analysis data 42. For example, if the number of time points is 1000, in other words, if the analysis data 42 corresponds to the elapsed time t0 to t 999If the system corresponds to point 1000, then 1000 height maps 45 will be generated. The generated height maps 45 will be used in the Digital Twin Platform DP.

[0036] As shown in Figure 1(B), the Digital Twin Platform DP has an Application AP implemented to overlay the temporal changes in flooding conditions onto a 3D city model in the form of water surface, water flow, heat map, etc. The height map 45 generated by the data processing system 1 is imported into the Digital Twin Platform DP, and the Application AP overlays CG of water flow and heat map based on the height map 45 onto the 3D city model. For this purpose, the height map 45 is generated to a size that matches the display range of the 3D city model. Through its functions, the Application AP creates fluctuations in the water surface and realizes natural connections and movements of the water surface, realistically representing the state of the water surface.

[0037] The application AP can be used by connecting from the user terminal UT to the digital twin platform DP. By using the application AP, users can visualize the risk of flooding due to river overflow in a target area in 3D. Using the operation menu displayed on the screen, users can arbitrarily change the viewpoint position, line of sight height (overhead or eye level), zoom in and out of the display, the elapsed time after a levee breach, etc., and check the flooding risk of the area they wish to check in detail.

[0038] The data processing system 1 may implement all of the above-mentioned functional units 10, 20, 30, and 40 on a single computer, or it may be implemented in a distributed manner across multiple computers. For example, the first processing unit 10 and the second processing unit 20 may be implemented on one computer, and the third processing unit 30 may be implemented on another computer, with storage accessible from both computers used as the storage unit 40. In either case, once the programs and software necessary for processing in the data processing system 1 are set up on the target computer, the processor of that computer becomes the primary operator of the three processing units 10, 20, and 30. In addition, each computer may be connected and used as appropriate, with display devices such as displays and input devices such as keyboards and mice.

[0039] [Intermediate data creation process] Figure 3 is a flowchart showing an example of the intermediate data creation process (step S200 in Figure 2). The following explanation will follow this example procedure.

[0040] Step S210: The first processing unit 10 accepts the specification of conditions for extracting / converting data from the analysis mesh data MA and terrain mesh data MT. Specifically, the first processing unit 10 generates a screen for specifying data extraction / conversion conditions for the two types of mesh data MA and MT that will be the source of extraction / conversion, and accepts the operator's specifications regarding the location where each mesh data is stored, the file format of each mesh data, the geodetic system, the coordinate system, and which point within each cell divided by the mesh the coordinate values ​​in the analysis mesh data MA represent. On the condition specification screen, the data storage location can be specified from the file selection box, and other items can be specified from the candidates displayed in the pull-down menus for each item. Therefore, the operator does not need to type text and can easily and reliably specify the conditions by simply selecting the relevant information.

[0041] When the operator specifies the extraction / conversion conditions, the first processing unit 10 reads the analysis mesh data MA and terrain mesh data MT from the specified data storage location, determines the representative point of each cell in the analysis mesh data MA, extracts and converts the necessary data (steps S220-S222), and extracts and converts the necessary data from the terrain mesh data MT (steps S231-S232).

[0042] Step S220: The first processing unit 10 selects a representative point (the base point for analysis for each cell) for each cell divided by the mesh, based on the coordinate values ​​in the analysis mesh data MA specified in step S210, and calculates its coordinate values. The mesh shape in the analysis mesh data MA is assumed to be a square of the same size, which is common in flood risk analysis software.

[0043] Specifically, if the coordinate values ​​in the analysis mesh data MA indicate the position of the top-left vertex of each cell, the first processing unit 10 uses each vertex of the square surrounding the cell as a representative point of the cell and calculates the coordinate values ​​of each representative point from the coordinate values ​​of the top-left of the cell and the mesh size. On the other hand, if the coordinate values ​​in the analysis mesh data MA indicate the position of the center of each cell, the first processing unit 10 uses each vertex of the square surrounding the cell as a representative point of the cell and calculates the coordinate values ​​of each representative point from the coordinate values ​​of the center of the cell and the mesh size. In this way, four representative points are selected for each individual cell, and the coordinate values ​​of each representative point are calculated.

[0044] Since each cell is adjacent to another with the mesh as its boundary, there will be a maximum of four representative points (vertices) on the planar coordinates of each vertex, corresponding to the number of cells that share those planar coordinates. This point will be explained further later using another diagram.

[0045] Step S221: The first processing unit 10, based on the file format of the analysis mesh data MA specified in step S210 above, extracts the planar coordinates (horizontal x and vertical y coordinate values) of each representative point and the elapsed time t (t0, t1, t2, ...) from the analysis mesh data MA according to a predefined workflow. max ) Flood depth z d The data is extracted, converted to a predetermined data format (e.g., CSV format), and saved as analysis data 42.

[0046] Step S222: The first processing unit 10 also unifies the measurement system and coordinate system for the analysis data 42. Specifically, if the geodetic system of the analysis data 42 does not correspond to either the Japanese Geodetic System 2000 or 2011 (JGD2000, 2011), the first processing unit 10 converts it to the Japanese Geodetic System 2011 (JGD2011), and if the coordinate system of the analysis data 42 is not a geographic coordinate system, it converts it to a geographic coordinate system. As a result, the coordinate value x of the plane coordinate (x,y) included in the analysis data 42 represents latitude, and the coordinate value y represents longitude.

[0047] Step S231: The first processing unit 10, based on the file format of the terrain mesh data MT specified in step S210 above, extracts the planar coordinates (horizontal x and vertical y coordinate values) and ground height (GH) z of each vertex from the terrain mesh data MT according to a predefined workflow. h The data is extracted, converted to a predetermined data format (e.g., CSV format), and saved as terrain data 41.

[0048] Step S232: The first processing unit 10 also unifies the measurement system and coordinate system for the terrain data 41. Specifically, if the geodetic system of the terrain data 41 does not correspond to either the Japanese Geodetic System 2000 or 2011 (JGD2000, 2011), the first processing unit 10 converts it to the Japanese Geodetic System 2011 (JGD2011), and if the coordinate system of the terrain data 41 is not a geographic coordinate system, it converts it to a geographic coordinate system. As a result, the coordinate value x of the planar coordinate (x,y) included in the terrain data 41 represents latitude, and the coordinate value y represents longitude.

[0049] Generally, terrain mesh data and analysis mesh data use various data formats depending on the field and context in which they are used. For example, analysis mesh data uses data formats such as Shapefile, SFC, SXF, CityGML, and GeoTIFF, while terrain mesh data uses data formats such as LandXML, FBX, and CityGML. The terrain mesh data MT and analysis mesh data MA used in this embodiment also do not have a fixed data format, so it is necessary to understand each data format, extract the necessary data items, and convert them to a predetermined data format.

[0050] In contrast, in this embodiment, the workflow predefines how to extract the necessary data items from the files of the terrain mesh data MT and analysis mesh data MA, and what data format to convert them to, with respect to the possible data formats for each data format. Therefore, in steps S221 and S231 above, the operator only needs to provide the file format of each mesh data MA and MT specified in step S210 above, and the necessary data items can be extracted and converted to the predetermined data format.

[0051] Next, the first processing unit 10 creates intermediate data 43 based on the terrain data 41 and the analysis data 42.

[0052] Step S240: The first processing unit 10 first removes from the analysis data 42 information related to planar coordinates that are outside the target range of the terrain data 41, i.e., data associated with vertices (representative points) located outside the target range that are not to be displayed as terrain, and uses this as the basis for the intermediate data 43.

[0053] For example, as shown in Figure 4 (A-1), the analysis data 42 is divided into 7x7 cells by a mesh, and each cell corresponds to a cell, with the terrain data 41 overlapping within the central 5x5 cell area. In this case, the cells forming the outermost row of the analysis data 42 are excluded from the display, so the first processing unit 10 deletes the data associated with the vertices of these cells from the analysis data 42. As a result, as shown in Figure 4 (A-2), the analysis data 42 is reduced to data corresponding to a 5x5 cell area, with the data corresponding to the area indicated by the dashed line deleted. The shades of gray in each cell of the analysis data 42 shown in Figure 4 represent the depth of the flooding.

[0054] At this time, the first processing unit 10 generates a screen (for example, (A) in Figure 5) that allows the user to check the state of the data to be deleted from the analysis data 42 before and after deletion. The user can check the analysis data 42 before and after deletion in a two-dimensional display via the confirmation screen, and can manually correct the range to be deleted on the correction screen that is displayed by pressing the [Correction] button. When a correction is made on the correction screen, the corrected content is reflected in the figure on the right side of the confirmation screen (the display area for [Deletion / Correction]). Also, pressing the [Clear Correction] button cancels the previous correction.

[0055] Step S250: The first processing unit 10 adds information about planar coordinates that are included in the terrain data 41 but not in the analysis data 42, namely the values ​​of the vertices and their ground elevations for those planar coordinates, to the intermediate data 43.

[0056] For example, as shown in the lower part of Figure 4 (B-1), suppose that none of the vertices included in the terrain data 41 have the same planar coordinates as the vertices included in the analysis data 42 (=intermediate data 43 at this point) (this is merely an example for illustrative purposes). In this case, all the vertices included in the terrain data 41 and their ground elevation values ​​are added to the intermediate data 43. The white circles in Figure 4 (B-2) that are included in the intermediate data 43 indicate the vertices that were added from the terrain data 41.

[0057] At this time, the first processing unit 10 generates a screen (for example, (B) in Figure 5) that allows the user to check the state of the intermediate data 43 before and after adding the information to be added. The user can check the intermediate data 43 before and after the addition in a two-dimensional display via the confirmation screen, or manually correct the information to be added on the correction screen that is displayed by pressing the [Correct] button. When a correction is made on the correction screen, the corrected content is reflected in the figure on the right side of the confirmation screen (the display area for [After Addition / Correction]). Also, pressing the [Clear Correction] button cancels the previous correction.

[0058] Once the above steps are completed, the intermediate data creation process will be finished. The intermediate data 43 at this point includes the coordinate values ​​x and y forming the planar coordinates of the vertex, the elapsed time t since the levee breach, and the ground height z. h , immersion depth z d The data has five data columns, but the inundation depth values ​​are not stored for the vertex planar coordinates derived from terrain data 41, and the ground height values ​​are not stored for the vertex planar coordinates derived from analysis data 42. These values ​​will be stored in the intermediate data supplementation process that is performed later.

[0059] [Intermediate data supplementation process] Figure 6 is a flowchart showing an example of the intermediate data supplementation process (step S300 in Figure 2). The following explanation will follow this example procedure.

[0060] Step S310: The second processing unit 20 processes the planar coordinates of the vertices added in step S250 from the terrain data 41, i.e., the planar coordinates for which the flood depth value is not stored, and the flood depth z d This stores the inundation depth value of the cell containing the added vertex.

[0061] For example, in Fig. 7(A), with the x-axis as the xy plane and the y-axis as the position (height) in the z direction, the height information in four adjacent cells divided by the analysis mesh is shown. The analysis data is expressed such that the submergence depth is constant within each cell. As shown in the figure, since the vertex P added from the terrain data 41 is included in cell c2, the value of the submergence depth of cell c2 is stored for the planar coordinates of vertex P.

[0062] Step S320: The second processing unit 20 stores, for other planar coordinates that were not the target of processing in step S310 above, that is, planar coordinates from which the ground height value is not stored in the analysis data 42, the ground height z h as a value calculated based on geometric processing.

[0063] For example, vertex Q located on the boundary between cell c3 and cell c4 shown in Fig. 7(A) is a vertex derived from the analysis data 42. For these planar coordinates, the submergence depth is stored, but the ground height is not stored. For such a vertex Q, its ground height can be calculated by performing geometric processing.

[0064] Specifically, as shown in Fig. 7(B), the second processing unit 20 selects three vertices R1(x1, y1, z1), R2(x2, y2, z2), and R3(x3, y3, z3) derived from the terrain data 41 that are adjacent to and surround the planar coordinates (x4, y4) of vertex Q for which the ground height value is not stored, connects them with straight lines to create a triangular plane, and obtains the equation (ax + by + cz + d = 0) of that plane. Then, the coordinates x4 and y4 of vertex Q are substituted into this equation to calculate the height z4 of vertex Q, which is stored as the value of the ground height.

[0065] [[ID=1​This is the ground height z for each planar coordinate. h Flood depth z d (z) can be obtained by adding the values ​​of hd =z h +z d ). Note that the ground height z h This value becomes negative at locations corresponding to land, rivers, lakes, etc., below sea level, in which case the ground height z h It becomes lower than the reference level.

[0066] Step S340: The second processing unit 20 executes the replenishment result confirmation process. In this process, the second processing unit 20 generates a screen on which the replenished intermediate data 43 can be confirmed, requests confirmation from the operator, and accepts operation on the buttons provided on the screen. The operator can confirm the replenished intermediate data 43 or manually correct it through this screen. When the operator has completed the confirmation and pressed the [Proceed] button provided on the confirmation screen, the intermediate data replenishment process ends. This then triggers the start of the subsequent process (water surface model creation process).

[0067] Figure 8 shows a simplified representation of the contents of the intermediate data 43 after the intermediate data supplementation process (Figure 6) has been performed. The flood depth values ​​enclosed by the dashed lines in the figure were stored in step S310 in Figure 6, the ground height values ​​enclosed by the dashed lines were stored in step S320 in Figure 6, and the water surface height from the ground surface values ​​enclosed by the dashed lines were stored in step S330 in Figure 6. Although not shown in the figure, in addition to the data series shown, the intermediate data 43 also contains another data series for creating a height map, which stores the height of the water surface from the reference plane. In the process described later (specifically, immediately before creating the height map), values ​​obtained by converting the water surface height from the reference plane into 256 levels are stored in this data series.

[0068] As shown in Figure 8, in the intermediate data 43 after the intermediate data supplementation process, the values ​​for ground height, inundation depth, and height from the water surface reference plane are stored for the planar coordinates of all vertices. However, due to the selection of representative points for each cell as described above (step S220 in Figure 3), there may be multiple vertices on the same planar coordinate plane with different heights from the water surface reference plane, for example, as shown in the area enclosed by the dashed line in Figure 7 (C).

[0069] Figure 9(A) schematically illustrates this. The four cells, upper left, upper right, lower right, and lower left, which are divided into 2x2 sections by the analysis mesh, each have four representative points (vertices), and the vertices indicated by the black circles in the center are located on the same planar coordinate system. The numerical values ​​within the cells represent the inundation depth z in that cell. d (Unit: m) is shown. In the example shown, the inundation depths of the four cells are all different, and therefore, on the planar coordinates of the black circles, there are four vertices with different inundation depths and, consequently, different heights from the reference plane of the water surface. Figure 9(B) shows the maximum number of vertices that can overlap at the mesh boundary when the analysis mesh is divided into 6x6 cells.

[0070] If a water surface model 44 were to be generated based on intermediate data 43 in which multiple vertices exist on the same planar coordinate system at different heights from the water surface reference plane, discontinuities or unnatural areas would occur, resulting in a discontinuous or unnatural representation of the water surface's continuity. Therefore, before generating the water surface model 44, optimization is performed on such vertices at the beginning of the water surface model creation process.

[0071] [Water surface model creation process] Figure 10 is a flowchart showing an example of the procedure for creating a water surface model (step S400 in Figure 2). The following explanation will follow this example procedure.

[0072] Step S410: The third processing unit 30 performs intermediate data optimization processing. In this process, the third processing unit 30 optimizes multiple vertices in the intermediate data 43 that overlap on the same planar coordinate system and have different heights from the reference plane of the water surface, based on conditions specified by the operator, and determines each vertex on the planar coordinate system to be one.

[0073] First, the third processing unit 30 determines the height z from the reference plane of the water surface that is on the same planar coordinate system. hd The number of vertices with different values ​​is tallied. Of these, locations where two or more vertices overlap on the same plane coordinate system are targeted for optimization. During optimization, the process is executed based on the principle of "processing from the outside of the analysis mesh, and from the areas with the fewest overlapping vertices, until each vertex on the plane coordinate system is determined to be unique."

[0074] For example, suppose the number of vertices overlapping on the same planar coordinate system is tallied as shown in Figure 11(A). In this case, the third processing unit 30 will optimize the system in the order of Group 1 → Group 2 → Group 3, treating the locations on the outermost edge of the analysis mesh with "2" overlapping vertices as Group 1, the locations inside the outermost edge of the analysis mesh with "3" overlapping vertices as Group 2, and the locations inside the outermost edge of the analysis mesh with "4" overlapping vertices as Group 3, as shown in Figure 11(B).

[0075] Optimization is performed based on the relationship between the two sides of a point in planar coordinates where multiple vertices overlap (hereinafter referred to as the "optimization target point"). In this embodiment, two optimization conditions are provided: a) the difference in ground height (GH) on both sides of the optimization target point, and b) the fluctuation of the water level on both sides of the optimization target point. The operator can specify the optimization conditions and input numerical values ​​related to each optimization condition via the optimization condition specification screen generated by the third processing unit 30. Both a and b may be specified as optimization conditions, or only one of them may be specified.

[0076] In any optimization based on any of the conditions, the third processing unit 30 defines a cross-section passing through the two cells and the optimization target point for a combination of two cells having vertices of different heights at the optimization target point. At this time, the ends of the cross-section are the vertices with the shortest planar distance from the optimization target point. The third processing unit 30 then examines this cross-section and optimizes the vertices based on the relationship between the two sides of the optimization target point.

[0077] More specifically, the third processing unit 30 selects one point each from two cells having vertices of different heights at the optimization target point, that are located on a straight line (including cases where they can be considered to be approximately on a straight line; the same applies hereinafter) flanking the optimization target point, and defines a cross section passing through the optimization target point and the two points flanking it. A case where they can be considered to be approximately on a straight line is, for example, when the two points mentioned above are located within a range with a predetermined width in a direction perpendicular to the line passing through the optimization target point (this is merely an example, and it is also possible to select two points according to other criteria). A cross section can be defined for each combination of two points that flank the optimization target point on a straight line.

[0078] For example, as shown in Figure 11 (C-1), suppose points A1 to A9 and points T1 and T4 are on the boundary of the analysis mesh, and points T2, T3, T5 and T6 are inside the cells divided by the analysis mesh. Point A, shown as a black circle in the figure, corresponds to a point corresponding to a vertex derived from analysis data 42, and point T, shown as a white circle, corresponds to a point corresponding to a vertex derived from terrain data 41. In such a region, if points A2, A4 and A5 are the target of optimization, then a cross section is defined passing through each target point and two points located on a straight line flanking it, as shown in Figure 11 (C-2).

[0079] For example, for point A2, a cross-section is defined with points T1 and A3 as the ends, which are the closest points that enclose it in a straight line. For point A4, a cross-section is defined with points A1 and T4 as the ends, which are the closest points that enclose it in a straight line. For point A5, since there are multiple combinations of points that enclose it in a straight line, a cross-section is defined for each. Specifically, a cross-section is defined with points A4 and A6 as the ends, which are the closest points that enclose point A5 in a straight line along the horizontal lines of the mesh, and a cross-section is defined with points A2 and A8 as the ends, which are the closest points that enclose point A5 in a straight line along the vertical lines of the mesh. In addition, a cross-section is defined with points T2 and T6 as the ends, which are the closest points that enclose point A5 in a straight line between the top-left cell and the bottom-right cell. Furthermore, a cross-section is defined with points T3 and T5 as the ends, which are the closest points that enclose point A5 in a straight line between the top-right cell and the bottom-left cell. In this way, four cross-sections can be defined for point A5.

[0080] Then, the third processing unit 30 performs optimization using the defined cross-section and based on the optimization conditions specified by the operator.

[0081] First, let's explain optimization based on optimization condition a. Optimization based on optimization condition a is performed under the principles that "water flows from higher to lower ground" and "water collects in lower areas," taking into account the difference in ground elevation on both sides of the optimization target site. In the optimization condition specification screen described above, along with specifying optimization condition a, it is possible to specify the upper limit and percentage of the difference in ground elevation that will be considered the same. If the difference in ground elevation on both sides of the optimization target site is less than or equal to the specified upper limit (e.g., 10 cm) or within the specified percentage (e.g., ±0.5%), the ground elevation on both sides of the optimization target site will be considered the same.

[0082] The optimization process based on optimization condition a will be explained below with reference to Figure 12. In Figure 12, the horizontal axis represents the position in the xy plane, and the vertical axis represents the position (height) in the z direction. The optimization target point is A, and the two points at both ends of the cross section containing the optimization target point A are S1 and S2. The elapsed time t from the dam failure is t. nThis shows the height information at each point in the region.

[0083] As shown in Figure 12 (A), if the ground heights at points S1 and S2 on either side of optimization target point A are the same or can be considered the same, the third processing unit 30 defines the height from the water surface reference plane as the height of the vertex with the higher height (the vertex of point S2 in the illustrated example) and the vertex with the lower height (the vertex of point S1 in the illustrated example), and the height at the intersection of the connecting line and the line indicating optimization target point A as the height from the water surface reference plane at optimization target point A. Then, the two existing vertices at optimization target point A are deleted, and a new vertex is added with the above intersection as the new representative point.

[0084] Furthermore, if the ground elevations at points S1 and S2 on either side of optimization target point A are different (the difference in ground elevation exceeds the range in which they can be considered the same), as shown in Figure 12 (B), if the elevations from the water surface reference plane at points S1 and S2 on both sides are different, the third processing unit 30 connects the vertex with the higher elevation (the vertex of point S1 in the illustrated example) and the vertex with the lower elevation (the vertex of point S2 in the illustrated example). If the elevations from the water surface reference plane at points S1 and S2 on both sides are the same, as shown in Figure 12 (C), the vertices of these points are connected. The connecting line is then defined as the elevation from the water surface reference plane, and the elevation at the intersection of the connecting line and the line indicating optimization target point A is defined as the elevation from the water surface reference plane at optimization target point A. The two existing vertices at optimization target point A are then deleted, and a new vertex is added with the above intersection as the new representative point.

[0085] Next, we will explain optimization based on optimization condition b. Optimization based on optimization condition b is performed under the principle that "vertical fluctuations in wave height on the water surface are energy fluctuations, and wave propagation and vertical fluctuations are caused by energy propagation," taking into account the water surface fluctuations over time on both sides of the optimization target point. In the optimization condition specification screen described above, along with specifying optimization condition b, it is possible to specify a threshold for the magnitude of displacement that will be considered to indicate water surface fluctuation. If the magnitude of the water surface displacement is within the specified threshold (for example, ±0.15m), the water surface is considered not to be fluctuating.

[0086] In optimization based on optimization condition b, the elapsed time t since the dam failure is calculated. n With respect to the water surface, the time immediately preceding t n-1 and the time t immediately following n+1 The displacement of the water surface on both sides of the optimization target point and its direction (upward or downward displacement) are calculated, and the method of leveling the water surface is determined according to the relative fluctuations of the water surface on both sides of the optimization target point. However, if n=0, since there is no data for the previous time, the calculation is based on the water surfaces at t0 and t1.

[0087] The optimization process based on optimization condition b will be explained below with reference to Figure 13. In Figure 13, as shown in the left figure, the horizontal axis represents the position in the xy plane, the vertical axis represents the position (height) in the z direction, and the optimization target point is A, with elapsed time t n Of the two sides of the cross-section where point A is the target of optimization, the side with the relatively lower water level is designated as the L-side, and the side with the higher water level is designated as the H-side. Of the two points at both ends of the cross-section, the point on the L-side is designated as S. L , point S on the H side H This shows the height information at each point.

[0088] There are three ways to level the water surface. First, if water flows relatively more into the L surface over time, that is, if the amount of upward fluctuation of the water surface is greater on the L surface than on the H surface, the third processing unit 30 applies pattern 1 and, as shown in Figure 13 (A), deletes the vertex with the lower height of the water surface from the reference plane at optimization target point A, and adopts the vertex with the higher height of the water surface from the reference plane as the representative point, and this vertex and point S on the L surface side L A line is drawn connecting the vertices of the plane, and this connecting line is defined as the height of the water surface from the reference plane on the L-plane.

[0089] Pattern 1 applies more specifically to cases where, over time, the L-plane moves upward while the H-plane moves downward; the L-plane moves upward while the H-plane remains unchanged; and the L-plane remains unchanged while the H-plane moves downward.

[0090] Furthermore, if there is no relative fluctuation of the water surface between the L and H surfaces even after time has passed, that is, if the amount of upward fluctuation of the water surface is equal for the L and H surfaces, the third processing unit 30 applies pattern 2 and deletes the two existing vertices at optimization target point A, as shown in Figure 13 (B), and moves to point S on the H surface side. H The vertex and point S on the L-face side L The connecting line between the vertices is defined as the height from the water surface reference plane, and the height at the intersection of the connecting line and the line indicating optimization target point A is defined as the height from the water surface reference plane at optimization target point A. A new vertex is added, with this intersection point serving as the representative point.

[0091] Pattern 2 applies more specifically to cases where both the L-plane and H-plane move upward over time and the amount of movement is the same, cases where neither the L-plane nor the H-plane moves, and cases where both the L-plane and the H-plane move downward and the amount of movement is the same.

[0092] Then, if water flows relatively more towards the H surface over time, that is, if the amount of upward fluctuation of the water surface is greater on the H surface than on the L surface, the third processing unit 30 applies pattern 3 and, as shown in Figure 13 (C), deletes the vertex at the optimization target point A that is higher in height from the reference plane of the water surface, and adopts the vertex at the lower in height from the reference plane of the water surface as the representative point, and connects this vertex to point S on the H surface side. H A line is drawn connecting the vertices of the plane, and this connecting line is defined as the height of the water surface from the reference plane on the H plane.

[0093] Pattern 3 applies more specifically to cases where, over time, the L-plane moves downward while the H-plane moves upward; the L-plane moves downward while the H-plane remains unchanged; and the L-plane remains unchanged while the H-plane moves upward.

[0094] By the way, in Figures 12 (Optimization flow based on optimization condition a) and 13 (Optimization flow based on optimization condition b), the case where two vertices overlap at the optimization target point was used as an example to facilitate understanding of the invention. When there are two overlapping vertices, the height of the vertex, and thus the height from the reference plane of the water surface, can be determined to be one in a single optimization process. However, as mentioned above, the maximum number of vertices that can overlap at the same point is four. In the case of four vertices, two vertices are selected from the four vertices and the same process is repeated. As a result of repeating the above optimization process six times (= 4C2 times), there are six vertices.

[0095] In this case, the third processing unit 30 takes the arithmetic mean of the heights (in meters) from the water surface reference plane at the six vertices obtained through the six optimization processes. Since the decimal part of the cm is not needed, the value obtained by rounding up the third decimal place of the arithmetic mean is determined as the height from the water surface reference plane at the optimization target point. Similarly, if there are three overlapping vertices, the height from the water surface reference plane at the optimization target point is determined based on the arithmetic mean of the heights from the water surface reference plane at the three vertices obtained by repeating the above optimization process three times (=3C2 times).

[0096] Furthermore, when performing optimization based on both optimization conditions a and b, it is desirable to perform optimization based on optimization condition a first, followed by optimization based on optimization condition b, from the viewpoint of processing efficiency. Also, when performing optimization based on both optimization conditions a and b, each optimization process will be performed up to six times, for a total of twelve optimization processes. In this case, the arithmetic mean of all processes may be defined as the height of the water surface from the reference plane at the optimization target point, or the height of the water surface from the reference plane may be calculated by calculating the arithmetic mean of the optimization processes based on optimization condition a and the optimization processes based on optimization condition b, and then weighting each result with different coefficients.

[0097] Once the intermediate data optimization process (step S410 in Figure 10) is completed, the third processing unit 30 proceeds to the next step. Returning to Figure 10, the steps from step S420 onwards in the water surface model creation process will now be explained.

[0098] Step S420: The third processing unit 30 generates a water surface model 44 based on the optimized intermediate data 43. In the data processing system 1, when generating the water surface model 44, a Delaunay triangulation irregular triangular network (TIN), which is often used when modeling terrain in situations where BIM / CIM is used in the civil engineering field, is used as a spatial interpolation method. In other words, the water surface model 44 is a TIN surface of the water surface, and a polygon mesh corresponding to it. By using the above method, the output can be directly used as CG data for the water surface in the digital twin platform DP.

[0099] Specifically, the third processing unit 30 calculates the elapsed time t(t0, t1, t2, ... t) since the dam breach based on the optimized intermediate data 43. max For each step, a TIN surface 44 of the water surface is created, represented by an irregular triangular network using Delaunay triangulation.

[0100] Incidentally, Delaunay triangulation is a method of dividing a surface into triangles such that the circumcircle of each of the three vertices does not enclose any of the other vertices. This maximizes the minimum interior angle of the triangles that make up the water surface, and since the water surface is represented by a combination of triangles without sharp angles, it is possible to create a natural water surface with smooth changes in height. However, on the other hand, it can result in angular shapes, so if necessary, the water surface may be formed as a curved surface using spline interpolation, or the TIN surface 44 of the water surface may be smoothed by adding vertices or increasing polygons using methods such as Natural Neighbor after creating an irregular triangular network.

[0101] Step S430: The third processing unit 30 executes the TIN surface verification process. In this process, the third processing unit 30 generates a screen on which the TIN surface 44 of the water surface can be viewed. If the TIN surface 44 of the water surface is optimized in step S460 (described later) and the process returns to step S430, the third processing unit 30 generates a screen on which the state of the TIN surface 44 of the water surface before and after optimization can be viewed in two dimensions (for example, (A) in Figure 14) or in three dimensions (for example, (B) in Figure 14). Through these screens, the operator can compare and verify the TIN surface 44 of the water surface before and after optimization, or manually perform corrections to specific areas (for example, changing vertex positions, adding vertices or polygons, etc.) on the correction screen displayed by pressing the [Correction] button. If corrections are made on the correction screen, the corrected TIN surface 44 is displayed on the right side of the confirmation screen (the [Optimized / Corrected] display area). Pressing the [Clear Correction] button cancels the previous correction.

[0102] Step S440: The third processing unit 30 checks whether optimization of the TIN surface 44 on the water surface is necessary. Specifically, if the [Specify Optimization Conditions] button is pressed on the confirmation screen for the TIN surface 44 on the water surface, the third processing unit 30 determines that optimization is necessary (Step S440: Yes) and proceeds to Step S450. On the other hand, if the [Proceed] button is pressed on the confirmation screen (Step S440: No), the third processing unit 30 proceeds to Step S470.

[0103] Step S450: The third processing unit 30 accepts the specification of optimization conditions for the TIN surface 44 of the water surface. Specifically, the third processing unit 30 generates a screen for specifying the optimization conditions for the TIN surface 44 of the water surface and accepts the operator's specifications regarding conditions related to the number of vertices and conditions related to the number of polygons that make up the polygon mesh. On this specification screen, for example, regarding the conditions for the number of vertices, it is possible to specify whether or not to set an upper limit on the number of vertices and the upper limit value, and whether or not to merge vertices when the distance between adjacent vertices is within a specified distance and the distance. Also, regarding the conditions for the number of polygons, for example, it is possible to specify whether or not to set an upper limit on the number of polygons and the upper limit value, and whether or not to divide (merge) polygons when the height of adjacent polygons is less than or equal to a specified upper limit value or within a specified percentage range, and the upper limit value and percentage can be specified.

[0104] The more complex the shape, the greater the number of vertices and polygons. If the number of vertices and polygons exceeds the processing capacity of the Digital Twin Platform (DP), rendering the water surface shape may take a long time when the application (AP) displays it in response to user input, potentially causing display delays. In contrast, by optimizing the TIN surface 44 of the water surface by specifying appropriate conditions in the above-mentioned screen, the rendering process can be accelerated, enabling smooth and uninterrupted display of the application (AP).

[0105] Step S460: The third processing unit 30 optimizes the TIN surface 44 of the water surface according to the conditions specified by the operator on the optimization conditions specification screen. Then, the third processing unit 30 returns to the TIN surface confirmation process (step S430) and executes the subsequent processes again.

[0106] Step S470: The third processing unit 30 calculates the elapsed time t(t0, t1, t2, ... t) since the dam breach based on the latest TIN surface 44 of the water surface. max Generate a height map 45 for each of the following:

[0107] Step S480: The third processing unit 30 executes the height map verification process. In this process, the third processing unit 30 generates a screen on which the individual height maps 45 generated in step S470 can be viewed. Through this screen, the operator can compare the height map 45 at each point in time with the TIN surface 44 of the water surface and specify the file format for outputting the height map 45. On this verification screen, the TIN surface 44 of the water surface is displayed as a 3D representation, for example, as shown in Figure 15 (A), and the height map 45 is displayed as a 2D image, for example, as shown in Figure 15 (B). Note that these figures are merely examples, and the TIN surface 44 of the water surface and the height map 45 shown in Figure 15 do not correspond to the water surface at the same point in time. Also, Figure 15 (A) shows a magnified view of a part of the TIN surface 44 of the water surface, but on the verification screen, the operator can change the displayed area, magnification, etc.

[0108] Step S490: The third processing unit 30 checks whether the height map 45 needs to be modified. Specifically, if the [Return to Optimization / Correction Process] button is pressed on the height map 45 confirmation screen, the third processing unit 30 determines that the height map 45 needs to be modified (Step S490: Yes) and returns to the TIN surface confirmation process (Step S430) to repeat the subsequent processing. On the other hand, if the [Output Height Map] button is pressed on the height map 45 confirmation screen (Step S490: No), the third processing unit 30 terminates the water surface model creation process.

[0109] In this way, during the water surface model creation process, the operator visually checks the generated TIN surface 44 and height map 45 of the water surface on the screen, and the series of processes are repeated until data in the desired state is obtained.

[0110] Once the water surface model creation process is complete, the final process (step S500 in Figure 2) is executed.

[0111] Step S500: The third processing unit 30 outputs the height map 45 to a file in a format specified by the operator (e.g., raw, png, etc.). In the height map 45, each pixel value corresponding to a point in the planar coordinates is assigned a grayscale value with 256 levels, from 0 (black) to 255 (white), corresponding to the height of the water surface from the reference plane at that point. Therefore, by importing the height map 45 into the digital twin platform DP and overlaying it onto the 3D city model on the application AP (specifically, by applying the height map 45 as a texture to a rectangular surface geometry model of the water surface formed to match the display range of the 3D city model), the undulating water surface is visualized in three dimensions.

[0112] The above procedure example is merely an example and can be modified as needed. For example, in step S420 in Figure 10, an irregular triangular network using Delaunay triangulation is used to generate the water surface model 44, but other spatial interpolation methods may be used depending on the distribution of vertex data, etc. For example, methods such as IDW (inverse distance weighting), spline interpolation (regular, tension), natural nearest neighbor method, kriging, and trend method can be selected.

[0113] As explained above, the following effects can be obtained using the data processing system 1 described above.

[0114] (1) Since workflows for terrain mesh data MT and analysis mesh data MA are predefined, even if the operator does not have knowledge of these data, they can easily extract the necessary data items from each data and convert them to the desired data format by following the workflow.

[0115] (2) In the case where there are multiple vertices on the same planar coordinate system in the intermediate data 43 that have different heights from the reference plane of the water surface, the planar coordinate system is used as the optimization target point, and optimization is performed based on the difference in ground height between two points that are approximately in a straight line on either side of the optimization target point, and the fluctuation of the water surface over time on both sides of the optimization target point, in order to determine a single vertex (height from the reference plane of the water surface) at the optimization target point. By using the optimized intermediate data 43, a TIN surface 44 of the water surface can be generated in a natural way.

[0116] (3) By using an irregular triangular mesh created by Delaunay triangulation to generate the TIN surface 44 of the water surface, it is possible to create a natural water surface with smooth changes in height and minimal unnaturalness.

[0117] (4) During the creation of intermediate data 43 and the TIN surface 44 of the water surface, the operator can visually check the object to be created via a confirmation screen and make adjustments to the details, allowing for more precise adjustments as needed. Furthermore, it eliminates situations where corrections are not noticed until the final stage, thereby preventing major rework and significantly shortening the time to complete the height map.

[0118] (5) The data processing system 1 automates or semi-automates a series of processes required to create the height map 45, which previously required considerable experience and skill from the worker. As a result, highly skilled manual work is no longer necessary, and even workers with little experience or skill can efficiently create deliverables (intermediate data 43, TIN surface 44 of the water surface, height map 45, etc.) in a short time while maintaining a certain level of quality.

[0119] (6) As a result of the data processing system 1 efficiently creating data of a certain quality or higher in a short time, the development work of the functions and content of the application AP in the digital twin platform DP can be streamlined, and the development period can be shortened.

[0120] (7) By optimizing the TIN surface 44 of the water surface by specifying appropriate optimization conditions, the rendering load of the water surface shape in the Digital Twin Platform DP can be reduced and processing can be accelerated. This can contribute to reducing hardware costs and optimizing resources on the server hosting the Digital Twin Platform DP, as well as improving the performance of application APs.

[0121] The present invention can be implemented in various ways without being limited to the embodiments described above.

[0122] In the embodiment described above, a workflow for data input to the data processing system 1 (input of terrain mesh data MT and analysis mesh data MA) is predefined. However, a workflow for data output from the data processing system 1 may also be predefined, and when data conversion / output conditions are specified, the system may be configured to output the target data (height map, intermediate data at each stage of processing, water surface model, etc.) in the specified file format according to the workflow.

[0123] In the embodiments described above, the data to be processed (intermediate data 43, water surface model 44, height map 45) is displayed on a confirmation screen at various points during the series of processing steps for the operator to confirm. However, a [File Output] button may be added to these confirmation screens, and the system may be configured to output the data to be processed to a file in a specified format according to a predefined workflow.

[0124] In the embodiment described above, a series of processes from receiving external data to generating a height map are executed sequentially according to the flow shown in Figure 2. However, instead of this, or in conjunction with this, the system may be configured to allow only selected specific processes to be executed individually. In that case, the system will be configured to read the data necessary for the selected process, that is, the data output in the process immediately preceding that process, via the screen each time.

[0125] In the above-described embodiment, each processing unit 10, 20, and 30 accepts information input from an operator at various points during the series of processing steps, executes processing according to the input content, and allows operator verification at each point before proceeding to the next processing step. However, instead, the information necessary for processing may be pre-entered in a configuration file, and settings may be made to eliminate the need for operator verification, allowing the series of processes to proceed automatically according to the contents of the configuration file. With such a configuration, it becomes possible to execute all processes automatically without human intervention.

[0126] In the embodiment described above, for the sake of explanation, intermediate data 43 is created separately based on terrain data 41 and analysis data 42. However, intermediate data may be obtained by adding some of the terrain data 41 to the analysis data 42. This makes it possible to reduce the amount of memory used.

[0127] In the embodiments described above, data is created to visualize the risk of flooding due to rainfall (changes in water level over time). However, the objects of visualization are not limited to the movement of water. It is also possible to visualize the movement of fluids that can cover and flow over the earth's surface due to various natural phenomena (e.g., rainfall, snowfall, storm surges, tsunamis, volcanic eruptions, etc.), such as liquids or solids with small particle sizes, including water, snow, soil, volcanic ash, and lava.

[0128] In the embodiment described above, intermediate data 43 is created based on data extracted / converted from two external data (analysis mesh data MA and terrain mesh data MT), but if necessary, data may be extracted / converted from three or more external data.

[0129] Furthermore, all other examples shown with illustrations in the embodiments are merely preferred examples and can be modified as appropriate when implementing the present invention. [Explanation of symbols]

[0130] 1. Data Processing System 10. First Processing Unit 20 Second Processing Unit 30 Third Processing Unit 40 Storage section 41. Topographic data (Data 1) 42. Analysis Data (Second Data) 43 Intermediate data 44. Water surface model (fluid model) 45 Height Map

Claims

1. A data processing system that creates data necessary to visualize in three dimensions the movement of a predetermined fluid that may cover and flow over the Earth's surface due to natural phenomena, A first processing unit obtains first data containing ground height information at each vertex based on terrain data, and second data containing information on the covering height of the fluid at each vertex included in the analysis mesh based on analysis data of the fluid, and creates intermediate data by adding vertices corresponding to planar coordinates that are included in the first data but not in the second data to the second data. Regarding the aforementioned intermediate data, a second processing unit adds the information on the covering height to the vertices added by the first processing unit in accordance with a predetermined rule, and adds the information on the ground height to the other vertices based on the first data, and then adds the information on the height from the reference plane of the surface of the fluid obtained by adding the ground height and the covering height to each vertex, thereby preparing the intermediate data. A third processing unit optimizes the prepared intermediate data for any discontinuities or unnatural areas that may arise when it is converted to three dimensions, based on predetermined conditions, and then creates a fluid model representing the surface of the fluid based on the optimized intermediate data. A data processing system equipped with [specific features / equipment].

2. In the data processing system described in claim 1, The first processing unit is, Prior to creating the aforementioned intermediate data, a data processing system characterized by extracting data items necessary for creating the intermediate data from multiple external data that may have different data formats and converting them into a predetermined data format, in accordance with a predefined flow, obtaining first data in the predetermined data format from the terrain data and second data in the predetermined data format from the analysis data, and unifying the geodetic system and coordinate system of these data.

3. In the data processing system described in claim 1, The second processing unit is, A data processing system characterized by, when adding the aforementioned ground height information, selecting three vertices adjacent to and surrounding each of the aforementioned other vertices, calculating the height corresponding to the coordinate value of the vertex on the plane of the triangle formed by connecting these three vertices, and setting that height as the ground height for that vertex.

4. In the data processing system described in claim 1, The third processing unit is, A data processing system characterized by performing the optimization by adjusting the number and height of vertices located on the boundary between cells based on the relationship between two cells that share the same planar coordinates at the boundary divided by the mesh.

5. In the data processing system described in claim 1 or 4, The third processing unit is, A data processing system characterized by performing the optimization based on the change in height from a reference plane of the surface of the fluid over time between two cells that share the same planar coordinates at the boundary divided by the mesh.

6. In the data processing system described in claim 5, The third processing unit is, A data processing system characterized by generating a fluid model in which the surface of the fluid is represented by an irregular triangular network formed by Delaunay triangulation, based on the optimized intermediate data, optimizing the fluid model based on the specified number of vertices or polygons constituting the fluid model, and finally generating a height map corresponding to the fluid model.

7. In the data processing system described in claim 6, The first processing unit is, The system can accept operations to display the intermediate data before and after adding a vertex and to specify the correction content thereof. Upon receiving such an operation, the system corrects the intermediate data according to the specifications. The third processing unit is, A data processing system that can accept operations to display the fluid model before and after optimization and to specify the correction content thereof, and when such operations are accepted, regenerates the fluid model according to the specifications.

8. In the data processing system described in claim 7, A data processing system characterized in that all processing, from the processing by the first processing unit to the processing by the third processing unit, can be performed automatically without human intervention.

9. A data processing method for creating data necessary to visualize in three dimensions the movement of a predetermined fluid that may cover and flow over the Earth's surface due to natural phenomena, The first step involves obtaining first data containing ground height information at each vertex based on topographic data, and second data containing information on the covering height of the fluid at each vertex included in the analysis mesh based on analysis data of the fluid, and then creating intermediate data by adding vertices corresponding to planar coordinates that are included in the first data but not in the second data to the second data. With respect to the aforementioned intermediate data, a second step is performed to refine the intermediate data by adding the information on the covering height to the vertices added in the first step in accordance with a predetermined rule, while adding the information on the ground height to the other vertices based on the first data, and then adding the information on the height from the reference plane of the surface of the fluid obtained by adding the ground height and the covering height to each vertex, The third step involves optimizing the prepared intermediate data for any discontinuities or unnatural areas that would arise if it were to be converted to three dimensions, based on predetermined conditions, and then creating a fluid model representing the surface of the fluid based on the optimized intermediate data. A data processing method that includes this.

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