Method for determining location accuracy of 3D spatial data

Abstract

A method for determining the location accuracy of 3D spatial data is disclosed. The method for determining the location accuracy of 3D spatial data, according to one embodiment, comprises the steps of: acquiring global navigation satellite system (GNSS) data and 3D spatial data of a specific area; setting one or more reference points in the GNSS data; extracting one or more comparison points corresponding to the one or more reference points by extracting, from the 3D spatial data, the point closest to each reference point as a comparison point corresponding to each reference point; and determining the location accuracy of the 3D spatial data on the basis of the coordinates of the one or more reference points and the coordinates of the one or more comparison points.

Description

Method for judging the positional accuracy of 3D spatial data

[0001] It relates to technology for judging the positional accuracy of three-dimensional spatial data.

[0002] There are 77 fixed GNSS satellite control points in Korea, and the National Geographic Information Institute provides daily observation data for each satellite control point through the National Geospatial Information Platform. Furthermore, since 2005, it has offered a network RTK service that utilizes satellite control points to enable high-precision positioning. To obtain the most accurate positioning of a specific area, additional GNSS data is first collected in the area. The 3D spatial data acquired for modeling is then augmented with GNSS data to track the relative position from the existing GNSS satellite control points.

[0003] Meanwhile, the positional accuracy of 3D spatial data is severely affected by factors such as surveying equipment and the surveying environment, and this is especially true for outdoor surveys. Furthermore, conventional methods for determining the positional accuracy of 3D spatial data involve manually matching specific points in the surveyed data with GNSS data within a GIS program. This method not only reduces precision, but also inevitably increases the human resources and time required to assess positional accuracy as the number of matching points increases.

[0004] The purpose is to provide a method for judging the positional accuracy of three-dimensional spatial data.

[0005] A method for determining positional accuracy of three-dimensional spatial data performed by a computing device may include: acquiring GNSS (Global Navigation Satellite System) data and three-dimensional spatial data of a specific region; setting one or more reference points in the GNSS data; extracting one or more comparison points corresponding to the one or more reference points by extracting a point closest to each reference point in the three-dimensional spatial data as a comparison point corresponding to each reference point; and determining positional accuracy of the three-dimensional spatial data based on coordinates of the one or more reference points and coordinates of the one or more comparison points.

[0006] The extracting step may include: a step of mapping the one or more reference points and the three-dimensional space data onto a three-dimensional space; a step of generating a sphere centered on each reference point; and a step of gradually increasing the radius of the generated sphere and extracting a point of the three-dimensional space data that first meets the surface of the sphere as a comparison point corresponding to each reference point.

[0007] The method for determining the positional accuracy of the above three-dimensional spatial data may further include a step of unifying the coordinate systems of the GNSS data and the three-dimensional spatial data.

[0008] The above judging step can judge the horizontal accuracy and vertical accuracy of the 3D spatial data using the root mean square error.

[0009] By automatically searching and extracting comparison points corresponding to reference points of GNSS data in 3D spatial data and judging the positional accuracy of 3D spatial data through comparison of the reference points and comparison points, the precision of positional accuracy inspection of 3D spatial data can be improved.

[0010] FIG. 1 is a block diagram illustrating a device for determining the positional accuracy of three-dimensional spatial data according to an exemplary embodiment.

[0011] FIG. 2 is a flowchart illustrating a method for determining positional accuracy of three-dimensional spatial data according to an exemplary embodiment.

[0012] FIG. 3 is a block diagram illustrating a computing environment including a computing device according to one embodiment.

[0013] Hereinafter, an embodiment of the present invention will be described in detail with reference to the attached drawings. When designating components in each drawing, it should be noted that, where possible, identical components will be given the same reference numerals, even if they appear in different drawings. Furthermore, when describing the present invention, detailed descriptions of known functions or configurations will be omitted if they are deemed to unnecessarily obscure the gist of the present invention.

[0014] Meanwhile, for each step, unless the context clearly dictates a specific order, the steps may occur in a different order than stated. That is, the steps may be performed in the same order as stated, may be performed substantially simultaneously, or may be performed in the opposite order.

[0015] The terms described below are defined based on their functions within the present invention, and may vary depending on the intent or custom of the user or operator. Therefore, their definitions should be based on the contents of this specification.

[0016] Terms such as first, second, etc. may be used to describe various components, but the components should not be limited by the terms. Terms are used only to distinguish one component from another. The singular expression includes the plural expression unless the context clearly indicates otherwise, and the terms such as "comprises" or "has" should be understood to specify the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but not to exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0017] Furthermore, the division of components in this specification is merely a division based on the main function of each component. In other words, two or more components may be combined into a single component, or a single component may be further subdivided into two or more components with more detailed functions. In addition to its own main function, each component may additionally perform some or all of the functions of other components, and some of the main functions of each component may be exclusively performed by other components. Each component may be implemented in hardware or software, or in a combination of hardware and software.

[0018] FIG. 1 is a block diagram illustrating a device for determining the positional accuracy of three-dimensional spatial data according to an exemplary embodiment.

[0019] Referring to FIG. 1, a device (100) for determining position accuracy of three-dimensional space data according to an exemplary embodiment (hereinafter, position accuracy determination device) may include a data acquisition unit (110), a reference point setting unit (120), a coordinate system unification unit (130), a comparison point extraction unit (140), and a position accuracy determination unit (150).

[0020] The data acquisition unit (110) can acquire GNSS (Global Navigation Satellite System) data and 3D spatial data of a specific region. Here, the spatial data may be information about the geographical location and characteristics of a terrain feature. Generally, spatial data may be composed of geometric information indicating the shape or geographical location and correlation of an object in space, and attribute information indicating the characteristics of the object. 3D spatial data is spatial data with 3D coordinates, and may be data that can be combined / integrated with various fields such as smart cities, digital twins, and VR / AR by making 2D spatial data three-dimensional. For example, the 3D spatial data may be point cloud data or digital terrain data (e.g., DEM (Digital Elevation Model) data, DSM (Digital Surface Model) data, DTM (Digital Terrain Model), etc.), but this is only one example and is not limited thereto. According to exemplary embodiments, 3D spatial data can be constructed using aerial images captured by aircraft equipped with aerial photography cameras, satellite images captured using optical cameras mounted on national observation satellites, or ground images captured using drones. Drones, in particular, offer the advantage of rapidly capturing high-resolution images of small areas at low altitudes, enabling immediate use.

[0021] According to an exemplary embodiment, the data acquisition unit (110) may acquire GNSS data and 3D spatial data of a specific region from one or more external devices or external databases using wired or wireless communication means. Alternatively, the data acquisition unit (110) may acquire GNSS data and 3D spatial data of a specific region through user input using a predetermined input means.

[0022] Meanwhile, the data acquisition unit (110) may simply acquire pre-built 3D spatial data, but may also acquire aerial images, satellite images, or ground images, etc. and directly construct and acquire 3D spatial data using the acquired images.

[0023] The reference point setting unit (120) can set one or more reference points in GNSS data. Here, the reference point may be a location point that serves as a reference for relative comparison with three-dimensional spatial data. The coordinates of the reference point are expressed as (x, y, z), where x represents longitude, y represents latitude, and z represents altitude.

[0024] According to an exemplary embodiment, the reference point setting unit (120) may extract the longitude, latitude, and altitude of one or more location points from GNSS data based on user input or predetermined criteria, and set the longitude, latitude, and altitude of each extracted location point as the coordinates of each reference point. For example, the reference point setting unit (120) may set a location point of a terrain / object that does not change due to the external environment as a reference point.

[0025] The coordinate system unification unit (130) can unify the coordinate systems of GNSS data and 3D spatial data. The coordinate systems of acquired GNSS data and acquired 3D spatial data may differ. In this case, for accurate data analysis, the coordinate system unification unit (120) can unify the coordinate systems of GNSS data and 3D spatial data.

[0026] The comparison point extraction unit (140) can extract one or more comparison points corresponding to one or more reference points from three-dimensional spatial data.

[0027] For example, the comparison point extraction unit (140) can extract the point closest to each reference point in the 3D space data as the comparison point corresponding to each reference point. Specifically, the comparison point extraction unit (140) can map one or more reference points and 3D space data onto a 3D space, and generate a sphere centered on each reference point on the 3D space where one or more reference points and 3D space data are mapped. In addition, the comparison point extraction unit (140) can gradually increase the radius of the sphere until the surface of the sphere meets the point of the 3D space data, and extract the point of the 3D space data that first meets the surface of the sphere as the comparison point corresponding to each reference point.

[0028] The position accuracy judgment unit (150) can judge the position accuracy of 3D spatial data by comparing one or more set reference points with one or more extracted comparison points.

[0029] Specifically, the position accuracy judgment unit (150) can judge the horizontal accuracy and vertical accuracy of 3D spatial data using the root mean square error (RMSE) based on the coordinates of each reference point and the coordinates of the comparison point corresponding to each reference point.

[0030] According to the ASPRS National Standard for Spatial Data Accuracy (NSSDA), root mean square error (RMSE) is used to measure the positional accuracy of spatial data. In one embodiment, the positional accuracy determination unit (150) may utilize RMSE according to the ASPRS National Standard for Spatial Data Accuracy.

[0031] For example, the position accuracy judgment unit (150) can judge the horizontal accuracy and vertical accuracy of 3D spatial data using mathematical expressions 1 to 6.

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038] Here, i is the index of the reference point, n is the total number of reference points, and x a,i, y a,i and z a,i is the coordinate data of the reference point i, x b,i, y b,i and z b,i can represent the coordinate data of the comparison point corresponding to the reference point i. The horizontal accuracy can be the horizontal accuracy at a 95% confidence level, and the vertical accuracy can be the vertical accuracy at a 95% confidence level.

[0039] Meanwhile, according to the "Precision Road Map Quality Inspection Manual (April 2020)" provided by the National Geographic Information Institute, the horizontal / vertical positional accuracy within the 95% confidence interval of RMSE (m) is within 0.2 m, and the maximum allowable error can be 0.4 m. In one embodiment, the quality of 3D spatial data can be assessed by determining whether the horizontal and vertical accuracy of the 3D spatial data are within the maximum allowable error.

[0040] Fig. 2 is a flowchart illustrating a method for determining the positional accuracy of three-dimensional spatial data according to an exemplary embodiment. The method for determining the positional accuracy of three-dimensional spatial data of Fig. 2 can be performed by the positional accuracy determination device (100) of Fig. 1.

[0041] Referring to FIG. 2, the position accuracy determination device can obtain GNSS data and 3D spatial data of a specific region (210). For example, the position accuracy determination device can obtain GNSS data and 3D spatial data of a specific region from one or more external devices or an external database using wired or wireless communication means, or can obtain GNSS data and 3D spatial data of a specific region through user input using a predetermined input means.

[0042] The position accuracy determination device can set one or more reference points from GNSS data (220). For example, the position accuracy determination device can extract the longitude, latitude, and altitude of one or more location points from the GNSS data based on user input or predetermined criteria, and set the longitude, latitude, and altitude of each extracted location point as the coordinates of each reference point.

[0043] The position accuracy determination device can unify the coordinate system of GNSS data and 3D spatial data (230).

[0044] The position accuracy determination device can extract one or more comparison points corresponding to one or more reference points from the three-dimensional space data (240). For example, the position accuracy determination device can extract the point closest to each reference point from the three-dimensional space data as the comparison point corresponding to each reference point. For example, the position accuracy determination device can map one or more reference points and the three-dimensional space data onto a three-dimensional space, and generate a sphere centered on each reference point on the three-dimensional space to which the one or more reference points and the three-dimensional space data are mapped. In addition, the position accuracy determination device can gradually increase the radius of the sphere until the surface of the sphere meets a point of the three-dimensional space data, and extract the point of the three-dimensional space data that first meets the surface of the sphere as the comparison point corresponding to each reference point.

[0045] The position accuracy judgment device can judge the position accuracy of 3D spatial data by comparing one or more set reference points with one or more extracted comparison points (250). For example, the position accuracy judgment device can judge the horizontal accuracy and vertical accuracy of 3D spatial data using the root mean square error (RMSE) based on the coordinates of each reference point and the coordinates of the comparison point corresponding to each reference point. For example, the position accuracy judgment device can judge the horizontal accuracy and vertical accuracy of 3D spatial data using the above-described mathematical equations 1 to 6.

[0046] Meanwhile, although the method or process is described as being divided into multiple steps in FIG. 2, at least some of the steps may be performed in a different order, combined with other steps and performed together, omitted, divided into sub-steps and performed, or one or more steps not shown may be added and performed. For example, the order of performing steps 220 and 230 in FIG. 2 may be interchanged. That is, the method for determining position accuracy according to the exemplary embodiment may be performed in the following order: steps 210, 230, 220, 240, and 250.

[0047] FIG. 3 is a block diagram illustrating a computing environment including a computing device according to one embodiment. In the illustrated embodiment, each component may have different functions and capabilities other than those described below, and may include additional components other than those described below.

[0048] The illustrated computing environment (10) includes a computing device (12). The computing device (12) may be one or more components included in a position accuracy determination device (100) according to one embodiment.

[0049] A computing device (12) includes at least one processor (14), a computer-readable storage medium (16), and a communication bus (18). The processor (14) may cause the computing device (12) to operate according to the exemplary embodiments mentioned above. For example, the processor (14) may execute one or more programs stored in the computer-readable storage medium (16). The one or more programs may include one or more computer-executable instructions, which, when executed by the processor (14), may be configured to cause the computing device (12) to perform operations according to the exemplary embodiments.

[0050] A computer-readable storage medium (16) is configured to store computer-executable instructions or program code, program data, and / or other suitable forms of information. A program (20) stored in the computer-readable storage medium (16) includes a set of instructions executable by the processor (14). In one embodiment, the computer-readable storage medium (16) may be a memory (volatile memory such as random access memory, non-volatile memory, or a suitable combination thereof), one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, any other form of storage medium that can be accessed by the computing device (12) and store desired information, or a suitable combination thereof.

[0051] A communication bus (18) interconnects various other components of the computing device (12), including the processor (14) and computer-readable storage media (16).

[0052] The computing device (12) may also include one or more input / output interfaces (22) that provide interfaces for one or more input / output devices (24) and one or more network communication interfaces (26). The input / output interfaces (22) and the network communication interfaces (26) are connected to the communication bus (18). The input / output devices (24) may be connected to other components of the computing device (12) via the input / output interfaces (22). Exemplary input / output devices (24) may include input devices such as pointing devices (such as a mouse or a trackpad), a keyboard, a touch input device (such as a touchpad or a touchscreen), a voice or sound input device, various types of sensor devices and / or photographing devices, and / or output devices such as display devices, printers, speakers and / or network cards. The exemplary input / output devices (24) may be included within the computing device (12) as a component constituting the computing device (12), or may be connected to the computing device (12) as a separate device distinct from the computing device (12).

[0053] The present invention has been described above, focusing on preferred embodiments thereof. Those skilled in the art will appreciate that the present invention can be implemented in modified forms without departing from its essential characteristics. Therefore, the scope of the present invention is not limited to the aforementioned embodiments, but should be interpreted to encompass various embodiments within the scope equivalent to the claims.

Claims

1. A method for determining the positional accuracy of three-dimensional spatial data performed by a computing device, A step of acquiring GNSS (Global Navigation Satellite System) data and 3D spatial data of a specific area; A step of setting one or more reference points in the above GNSS data; A step of extracting one or more comparison points corresponding to one or more reference points by extracting the point closest to each reference point in the three-dimensional space data as a comparison point corresponding to each reference point; and A method for determining positional accuracy of three-dimensional space data, comprising: a step of determining positional accuracy of the three-dimensional space data based on coordinates of the one or more reference points and coordinates of the one or more comparison points; 2. In claim 1, The above extracting step is, A step of mapping the one or more reference points and the three-dimensional space data onto a three-dimensional space; A step of generating a sphere centered on each reference point; and A method for judging the positional accuracy of three-dimensional space data, comprising: a step of gradually increasing the radius of the generated sphere and extracting a point of three-dimensional space data that first meets the surface of the sphere as a comparison point corresponding to each reference point; 3. In claim 1, A method for determining positional accuracy of three-dimensional space data, further comprising: a step of unifying the coordinate systems of the GNSS data and the three-dimensional space data.

4. In claim 1, The above judging steps are: A method for judging the positional accuracy of three-dimensional spatial data, which judges the horizontal accuracy and vertical accuracy of the three-dimensional spatial data using the root mean square error.

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