Geographic information surveying and mapping method and device and geographic information surveying and mapping system

Abstract

The invention provides a geographic information surveying and mapping method, a geographic information surveying and mapping device and a geographic information surveying and mapping system. The method comprises the following steps: acquiring geographic data; inputting the track data of the unmanned aerial vehicle into the flight strip adjustment model to obtain flight strip parameter values; performing error correction on the laser data according to the air strip parameter value to obtain laser point cloud data; performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data; generating digital elevation model data according to the ground point cloud data, and extracting ground feature features according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data; and superposing the surface feature data and the contour line data under the same spatial reference to generate a three-dimensional real scene model of the target geographic area. The method solves the problem that in the prior art, geographic information surveying and mapping only depend on space coordinate points to distinguish different objects or scenes, so that surveying and mapping become more difficult.

Description

Technical Field

[0001] The present invention relates to the field of geographic information surveying and mapping technology, and in particular to a geographic information surveying and mapping method, a geographic information surveying and mapping device, a computer-readable storage medium, and a geographic information surveying and mapping system. Background Art

[0002] Geographic information surveying and mapping technology has gradually changed from traditional ground measurement to high-precision and high-efficiency aerial surveying and mapping. As an important breakthrough in the field of modern surveying and mapping, UAV-mounted laser radar (LiDAR) technology is gradually becoming one of the main means of geographic information surveying and mapping due to its advantages of high precision, high resolution, fast and efficient, and all-weather operation. In the Chinese invention application with application publication number CN118279510A, a three-dimensional spatial data processing method, system, electronic device and storage medium are disclosed, including collecting first point cloud data at each station in the target surveying and mapping area by a preset three-dimensional laser scanning method; using a preset precise registration algorithm to register multiple first point cloud data so that multiple first point cloud data are aligned, and using a preset adjustment algorithm to optimize the aligned first point cloud data to obtain second point cloud data; calculating the overlapping area between multiple stations according to the second point cloud data, and performing redundant processing on the second point cloud data in the overlapping area according to a preset similarity measurement algorithm; merging the second point cloud data after removing the redundancy to form a complete point cloud model of the target surveying and mapping area, and displaying the complete point cloud model. In the above invention application, the Beidou positioning data is integrated with the point cloud registration algorithm. Although it improves the site registration efficiency and the overall registration accuracy, there is no texture, color and shape data in the point cloud model. The lack of texture information makes the point cloud model relatively simple in visual perception, and it is difficult to fully restore the richness of the real world. In the absence of texture information, it becomes more difficult to distinguish different objects or scenes only by relying on spatial coordinate points. Summary of the invention

[0003] The main purpose of the present application is to provide a geographic information surveying and mapping method, a geographic information surveying and mapping device, a computer-readable storage medium and a geographic information surveying and mapping system, so as to at least solve the problem in the prior art that geographic information surveying and mapping only relies on spatial coordinate points to distinguish different objects or scenes, making surveying and mapping more difficult.

[0004] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a geographic information surveying and mapping method is provided, including: acquiring geographic data, the geographic data including image data, laser data and drone trajectory data; generating a digital orthophoto map according to the image data; inputting the drone trajectory data into a flight strip adjustment model to obtain flight strip parameter values, wherein the flight strip parameter values ​​are attitude parameters of the drone during flight; performing error correction on the laser data according to the flight strip parameter values ​​to obtain laser point cloud data; performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data; generating digital elevation model data according to the ground point cloud data, and extracting ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data; superimposing the ground feature data and contour line data under the same spatial reference to generate a three-dimensional real scene model of the target geographic area, so as to perform field surveying and mapping according to the three-dimensional real scene model, wherein the contour line data is the data when the digital elevation model data is imported into a predetermined mapping software to generate contour lines.

[0005] Optionally, obtaining geographic data includes: obtaining the image data using a camera mounted on a drone; obtaining the laser data using a lidar; obtaining base station data and POS data using the drone, the base station data including signal strength and distance information of the drone, and the POS data including position data, attitude data and flight data of the drone; preliminarily aligning the base station data and the POS data according to timestamps to obtain a time series number; and fusing the base station data and the POS data in the time series data using a fusion algorithm to generate the drone trajectory data.

[0006] Optionally, a digital orthophoto map is generated according to the image data, including: extracting feature points from the image data, the feature points including at least corner points and edge points in the image; performing feature point matching between different image data to obtain feature point matching results and establish image correspondence relationships, wherein the image correspondence relationship is a correspondence relationship between any two images; performing adjustment calculations based on the feature point matching results and the drone trajectory data to obtain internal and external orientation elements of the camera carried by the drone, wherein the internal and external orientation elements include the position and posture of the camera and the relative position relationship between the images; performing tilt correction and projection difference correction on the image data using a digital elevation model to obtain an orthophoto image; and splicing the orthophoto images according to the relative position relationship and the image correspondence relationship to obtain the digital orthophoto map.

[0007] Optionally, the laser data is error corrected according to the flight strip parameter value to obtain laser point cloud data, including: transforming the laser data from an original coordinate system to a target coordinate system according to the flight strip parameter value to obtain precise laser data, wherein the target coordinate system is a coordinate system that is more precise than the original coordinate system; utilizing the UAV trajectory data and system calibration data, and adopting a point cloud solution method to solve and correct the precise laser data to obtain the laser point cloud data, wherein the system calibration data is used to correct a system error and flight strip offset of the UAV during flight, wherein the flight strip offset is an error in the laser data obtained due to a trajectory offset of the UAV during the surveying and mapping process, wherein the system error is an elevation difference caused by discontinuous data elevations of multiple flight strips, and the flight strip is obtained by dividing the target geographical area into multiple strips.

[0008] Optionally, a point cloud solution method is used to solve and correct the precise laser data to obtain the laser point cloud data, including: obtaining the mean error of the plane position and the mean error of the elevation of the precise laser data, the mean error of the plane position being the mean error between the ground control point and the theoretical value in the plane position of the precise laser data between each flight strip, and the mean error of the elevation being the mean error between the elevation value in the precise laser data between each flight strip and the true elevation value on the ground; when the error judgment condition is met, the system error is corrected by laying out ground control points until the error judgment condition is no longer met, and all the flight strips are spliced ​​to obtain the laser point cloud data, and the error judgment condition is that the plane position error is greater than the average point cloud spacing, the elevation error is greater than the elevation point cloud accuracy, and the system error exists.

[0009] Optionally, extracting ground feature features according to the digital orthophoto image and the non-ground point cloud data to obtain ground feature data includes: registering the digital orthophoto image and the non-ground point cloud data so as to locate the digital orthophoto image and the non-ground point cloud data in the same spatial reference coordinates to obtain the registered digital orthophoto image and the registered non-ground point cloud data; extracting texture information and color information from the registered digital orthophoto image using texture analysis technology, and extracting ground feature shape information from the registered digital orthophoto image using edge detection method; extracting height information from the registered non-ground point cloud data; and obtaining the ground feature data by fusing the texture information, the color information, the ground feature shape information and the height information.

[0010] Optionally, after superimposing the object data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, the method further includes: using a measuring tool to measure the object information of the object to be measured on the three-dimensional real scene model of the target geographical area, the measuring tool at least including a measuring ruler and an angle measurer, and the object information at least including the size and angle of the object to be measured; comparing and analyzing the object information with the reference object data to obtain data differences; judging whether the data differences meet the accuracy requirements of the three-dimensional real scene model; and correcting the three-dimensional real scene model if it is judged that the data differences do not meet the accuracy requirements of the three-dimensional real scene model.

[0011] According to another aspect of the present application, a geographic information surveying and mapping device is provided, the device comprising: an acquisition unit for acquiring geographic data, the geographic data comprising image data, laser data and drone trajectory data; a first generation unit for generating a digital orthophoto map based on the image data; an input unit for inputting the drone trajectory data into a flight track adjustment model to obtain flight track parameter values, the flight track parameter values ​​being attitude parameters of the drone during flight; a first correction unit for performing error correction on the laser data based on the flight track parameter values ​​to obtain laser point cloud data; and a filtering unit for filtering the laser data using the flight track parameter values. The laser point cloud data is point cloud filtered to obtain ground point cloud data and non-ground point cloud data; the second generating unit is used to generate digital elevation model data according to the ground point cloud data, and extract ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground object data; the third generating unit is used to superimpose the ground object data and the contour line data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying according to the three-dimensional real scene model, and the contour line data is the data when the digital elevation model data is imported into the predetermined mapping software to generate contour lines.

[0012] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0013] According to another aspect of the present application, a geographic information mapping system is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of the methods described.

[0014] Applying the technical solution of the present application, in a geographic information surveying and mapping method, first, geographic data is acquired, the above-mentioned geographic data includes image data, laser data and drone trajectory data; then, a digital orthophoto map is generated according to the above-mentioned image data; then, the above-mentioned drone trajectory data is input into a flight strip adjustment model to obtain flight strip parameter values, and the above-mentioned flight strip parameter values ​​are attitude parameters of the above-mentioned drone during flight; then, the above-mentioned laser data is error corrected according to the above-mentioned flight strip parameter values ​​to obtain laser point cloud data; then, the above-mentioned laser point cloud data is point cloud filtered to obtain ground point cloud data and non-ground point cloud data; then, digital elevation model data is generated according to the above-mentioned ground point cloud data, and ground feature is extracted according to the above-mentioned digital orthophoto map and the above-mentioned non-ground point cloud data to obtain ground object data; finally, the ground object data and contour line data are superimposed under the same spatial reference to generate a three-dimensional real scene model of the target geographic area, so as to perform field surveying and mapping according to the above-mentioned three-dimensional real scene model, and the above-mentioned contour line data is the data when the above-mentioned digital elevation model data is imported into a predetermined mapping software to generate contour lines. This application uses drones to obtain image data, laser data, POS data and base station data, and fuses the base station data and POS data to generate drone trajectory data; establishes a corresponding relationship between image data, generates a continuous digital orthophoto map, and performs error correction on the original laser data to output a laser point cloud; performs point cloud filtering on the laser point cloud to separate ground points and non-ground points, constructs digital elevation model data from the ground point cloud data, aligns the non-ground point laser point cloud with the digital orthophoto map, and outputs the extracted ground object information; superimposes the ground object data and contour line data in the same spatial reference system to construct a three-dimensional real scene model of the target area. It can accurately reflect the shape, texture and position of the ground object, and can also reduce unnecessary calculations and resource consumption. This application solves the problem that geographic information surveying and mapping in the prior art only relies on spatial coordinate points to distinguish different objects or scenes, making surveying and mapping more difficult. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A hardware structure block diagram of a mobile terminal for executing a geographic information surveying and mapping method provided in an embodiment of the present application is shown;

[0016] Figure 2 A schematic diagram of a process of a geographic information surveying and mapping method provided according to an embodiment of the present application is shown;

[0017] Figure 3 A schematic diagram of a flow chart of a specific geographic information surveying and mapping method provided according to an embodiment of the present application is shown;

[0018] Figure 4 A schematic diagram of the structure of a geographic information surveying and mapping system provided according to an embodiment of the present application is shown;

[0019] Figure 5 A structural block diagram of a geographic information surveying and mapping device provided according to an embodiment of the present application is shown.

[0020] The above drawings include the following reference numerals:

[0021] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0022] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0026] Ground Control Points: Reference points that determine the position and shape of the ground. They are usually marked or set on the ground by geographic surveyors for use in areas such as map making and land surveying. The location and elevation data of ground control points can be used to correct aerial photography images, digital maps and other geographic information system data to improve the precision and accuracy of the data.

[0027] Mean error: The difference between a measurement and the true value, usually expressed as an average. In statistics and data analysis, the mean error is a measure of the difference between a sample mean and a population mean. A smaller mean error indicates that the measurement is more accurate, while a larger mean error indicates that the measurement may be biased or inaccurate. In experimental design and data analysis, the mean error is often considered and controlled to ensure the reliability and accuracy of the results.

[0028] Flight strip adjustment model: The flight strip adjustment model is a model used to control the heading of an aircraft in aviation navigation. During flight, the aircraft needs to adjust according to the heading instructions to ensure that it flies according to the predetermined route. The flight strip adjustment model takes into account factors such as the dynamic characteristics of the aircraft, environmental factors, and route constraints. By modeling these factors, accurate control and adjustment of the aircraft can be achieved.

[0029] As introduced in the background technology, the point cloud model in the prior art does not have texture, color and shape data. The lack of texture information makes the point cloud model relatively simple in visual perception, and it is difficult to fully restore the richness of the real world. In the absence of texture information, it becomes more difficult to distinguish different objects or scenes only by relying on spatial coordinate points. In order to solve the problem that geographic information surveying and mapping in the prior art only relies on spatial coordinate points to distinguish different objects or scenes, making surveying and mapping more difficult, the embodiments of the present application provide a geographic information surveying and mapping method, a geographic information surveying and mapping device, a computer-readable storage medium and a geographic information surveying and mapping system.

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0031] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal of a geographic information surveying and mapping method according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0032] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the geographic information surveying and mapping method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0033] In this embodiment, a geographic information mapping method running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] Figure 2 is a flow chart of a geographic information surveying and mapping method according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0035] Step S201, obtaining geographic data, the geographic data including image data, laser data and drone trajectory data.

[0036] Specifically, Figure 3 As shown, the camera carried by the drone is used to obtain low-altitude high-resolution image data, the lidar obtains low-altitude laser data, the GPS module and inertial measurement unit inside the drone obtain the drone POS data, and the signal receiving device inside the drone obtains the base station data. The base station data and POS data are fused and processed to generate the drone trajectory data to obtain the above-mentioned geographic data.

[0037] Step S202: Generate a digital orthophoto map based on the image data.

[0038] Specifically, Figure 3 As shown, the data preprocessing stage uses Figure 4 The image data processing module in the image data extracts feature points from the image data, establishes the corresponding relationship between the image data, performs adjustment calculation based on the feature point matching results and the drone trajectory data, splices the image data according to the position relationship obtained by the adjustment calculation, and generates a continuous digital orthophoto map, which also corresponds to Figure 3 DOM in . DOM, or Digital Orthophoto Map, is a high-resolution image data taken by drones, which is processed through a series of processes to generate an image map with precise geographic coordinates and scale.

[0039] Step S203, inputting the above-mentioned UAV trajectory data into the flight strip adjustment model to obtain the flight strip parameter value, and the above-mentioned flight strip parameter value is the attitude parameter of the above-mentioned UAV during the flight process.

[0040] Specifically, the flight strip adjustment model can be a model such as the "twelve parameter model". The UAV trajectory data is imported into the flight strip adjustment model. Based on the conjugate points or ground control points in the flight strip overlapping area, the observation equation is established, and the observation equation is solved using mathematical methods such as the least squares method to obtain the parameter values ​​of the flight strip adjustment model.

[0041] Step S204, performing error correction on the laser data according to the flight path parameter value to obtain laser point cloud data.

[0042] Specifically, the point cloud coordinates are corrected for each flight strip according to the flight strip parameter values, that is, the error of the laser data is corrected, and the laser data after flight strip adjustment is output as the laser point cloud data.

[0043] Step S205 , performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data.

[0044] Specifically, Figure 3 As shown, the CoProcess2.0 software is used to perform point cloud filtering on the laser point cloud data to separate ground points and non-ground points, thereby obtaining ground point cloud data and non-ground point cloud data.

[0045] Step S206, generating digital elevation model data according to the ground point cloud data, and extracting ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data.

[0046] Specifically, using Figure 4The ground data analysis module in the software separates the ground points by repeatedly building a triangulated surface network model, and repeatedly adds new laser points to expand the model, ensuring that each added laser point makes the model closer to the ground surface, so as to finally obtain an approximate ground surface, build the ground point cloud data into a TIN model, and further generate DEM data in a regular grid format. DEM is the abbreviation of "Digital Elevation Model". It is a mathematical model used to describe the elevation information of the earth's surface. DEM represents the elevation values ​​of different locations on the surface in the form of grid points and is used to build a terrain model. DEM realizes the digital simulation of the ground terrain through limited terrain elevation data, that is, the digital expression of the terrain surface morphology. It is also a physical ground model that represents the ground elevation in the form of a set of ordered numerical arrays. It is a branch of the digital terrain model, and various other terrain feature values ​​can be derived from it. The image information of the above-mentioned digital orthophoto map and the height information of the non-ground point cloud data are used to extract and identify the ground feature to obtain the ground feature data. Figure 4 The ground data analysis module in the system filters the laser point cloud to separate ground points and non-ground points, and constructs DEM data from the ground point cloud data. The non-ground data analysis module aligns the non-ground point cloud data with the digital orthophoto map, and uses the image information of the digital orthophoto map and the height information of the non-ground point cloud data to extract and identify the ground object features and obtain the ground object data.

[0047] It should be noted that by dividing point cloud data into ground points and non-ground points, different processing methods and optimization strategies can be used for different types of point cloud data. The fusion of non-ground point cloud data and image data (i.e., digital orthophotos) can make full use of the texture information of the image and the geometric information of the point cloud to generate a more detailed ground model that can accurately reflect the shape, texture and position of the ground object. The ground point cloud data only needs to process the geometric information, which can not only improve the efficiency of data processing, but also reduce unnecessary calculations and resource consumption.

[0048] Step S207, superimpose the feature data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying based on the three-dimensional real scene model. The contour data is the data generated when the digital elevation model data is imported into a predetermined mapping software to generate contour lines.

[0049] Specifically, Figure 4As shown, the model generation module is used to import the digital elevation model data into the predetermined mapping software to generate contour data, and the object data and the contour data are superimposed in the same spatial reference system to construct a three-dimensional real-scene model of the target area. Superimposing the object data and the contour data in the same spatial reference system can ensure that the relative position relationship between the terrain and the objects is accurate.

[0050] It should be noted that the predetermined mapping software can be commonly used mapping software, as long as the mapping software can be based on basic surveying and mapping results and applied to the vector collection and editing of aerial survey data in industries such as land, electricity, water conservancy, and transportation. The predetermined mapping software uses a computer-assisted interactive guidance mode, with plane DOM, various aerial triangulation stereo pairs, real-scene models, etc. as input data sources, to achieve rapid collection and editing, batch processing, linkage update, operation inspection, results storage and mapping of elements such as land features, landforms, and monomer models.

[0051] In the present embodiment, first, geographic data is acquired, and the geographic data includes image data, laser data and drone trajectory data; then, a digital orthophoto map is generated according to the image data; then, the drone trajectory data is input into a flight strip adjustment model to obtain flight strip parameter values, and the flight strip parameter values ​​are attitude parameters of the drone during flight; then, the laser data is error corrected according to the flight strip parameter values ​​to obtain laser point cloud data; then, the laser point cloud data is point cloud filtered to obtain ground point cloud data and non-ground point cloud data; then, digital elevation model data is generated according to the ground point cloud data, and ground feature is extracted according to the digital orthophoto map and the non-ground point cloud data to obtain ground object data; finally, the ground object data and contour line data are superimposed under the same spatial reference to generate a three-dimensional real scene model of the target geographic area, so as to perform field surveying and mapping according to the three-dimensional real scene model, and the contour line data is the data when the digital elevation model data is imported into a predetermined mapping software to generate contour lines. This application uses drones to obtain image data, laser data, POS data and base station data, and fuses the base station data and POS data to generate drone trajectory data; establishes a corresponding relationship between image data, generates a continuous digital orthophoto map, and performs error correction on the original laser data to output a laser point cloud; performs point cloud filtering on the laser point cloud to separate ground points and non-ground points, constructs digital elevation model data from the ground point cloud data, aligns the non-ground point laser point cloud with the digital orthophoto map, and outputs the extracted ground object information; superimposes the ground object data and contour line data in the same spatial reference system to construct a three-dimensional real scene model of the target area. It can accurately reflect the shape, texture and position of the ground object, and can also reduce unnecessary calculations and resource consumption. This application solves the problem that geographic information surveying and mapping in the prior art only relies on spatial coordinate points to distinguish different objects or scenes, making surveying and mapping more difficult.

[0052] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the geographic information surveying and mapping method of the present application will be described in detail below in conjunction with specific embodiments.

[0053] In order to improve the positioning accuracy and reliability of the UAV, in an optional implementation manner, the above step S201 includes:

[0054] Step S2011, using the camera carried by the drone to obtain the above image data;

[0055] Step S2012, acquiring the above laser data through a laser radar;

[0056] Step S2013, using the drone to obtain base station data and POS data, the base station data includes the signal strength and distance information of the drone, and the POS data includes the location data, attitude data and flight data of the drone;

[0057] Step S2014, preliminarily aligning the base station data and the POS data according to the timestamps to obtain time series data;

[0058] Step S2015: Using a fusion algorithm, the base station data and the POS data in the time series data are fused to generate the drone trajectory data.

[0059] In the above embodiment, the drone is equipped with an orthographic camera and an oblique camera to obtain low-altitude high-resolution image data, a laser radar is equipped to obtain low-altitude laser data, the GPS module and inertial measurement unit (IMU) inside the drone obtain the drone POS data, and the signal receiving device inside the drone obtains the base station data. POS (Position and Orientation System) data, that is, position and attitude system data, is the key information recorded by the drone during flight, including the three-dimensional coordinates (longitude, latitude, altitude), speed, acceleration and attitude information (heading angle, pitch angle, roll angle) of the drone. The base station data and POS data are preliminarily aligned according to the timestamp to form a time series data containing two data sources, and the base station data and POS data are fused using a fusion algorithm (such as Kalman filtering and particle filtering) to generate drone trajectory data.

[0060] In order to eliminate image distortion caused by terrain undulations and camera posture changes, in an optional implementation, the above step S202 includes:

[0061] Step S2021, extracting feature points from the image data, wherein the feature points at least include corner points and edge points in the image;

[0062] Step S2022, performing feature point matching between different image data, obtaining feature point matching results and establishing image correspondence, wherein the image correspondence is a correspondence between any two images;

[0063] Step S2023, performing adjustment calculation based on the feature point matching result and the drone trajectory data to obtain the internal and external orientation elements of the camera carried by the drone, wherein the internal and external orientation elements include the position and posture of the camera and the relative position relationship between the images;

[0064] Step S2024, using a digital elevation model to perform tilt correction and projection error correction on the image data to obtain an orthophoto;

[0065] Step S2025, stitching the orthophotos according to the relative position relationship and the image correspondence relationship to obtain the digital orthophoto map.

[0066] In the above embodiment, feature points, such as corner points, edge points, etc., are automatically extracted from the pre-processed image data, and feature point matching is performed between different images to establish a corresponding relationship between images (the corresponding relationship is used to splice images); using the aerial triangulation encryption software, adjustment calculation is performed based on the feature point matching results and the drone trajectory data to solve the internal and external orientation elements of the camera, that is, the position and posture of the camera and the relative position relationship between the images. The image is orthorectified using the digital elevation model (that is, using the RPC (Rational Polynomial Coefficients) parameters and digital elevation model data of the image itself to correct the tilt and projection difference of the image, thereby obtaining an orthophoto.) to eliminate the image distortion caused by the undulating terrain and the change of the camera posture, and the corrected image is spliced ​​according to the relative position relationship obtained by the adjustment calculation and the corresponding relationship between the images to generate the above-mentioned continuous digital orthophoto map, which not only has a high spatial resolution, but also can accurately reflect the real morphology and texture information of the surface.

[0067] Adjustment is an optimization technique used to minimize the difference between observations (such as feature point matches) and model predictions. In photogrammetry, this is usually done by minimizing the reprojection error.

[0068] In order to improve the accuracy and reliability of laser point cloud data, in an optional implementation, the above step S204 includes:

[0069] Step S2041, transforming the laser data from the original coordinate system to the target coordinate system according to the flight path parameter value to obtain accurate laser data, wherein the target coordinate system is a coordinate system more accurate than the original coordinate system;

[0070] Step S2042, using the above-mentioned UAV trajectory data and system calibration data, adopting the point cloud solution method to solve and correct the above-mentioned precise laser data to obtain the above-mentioned laser point cloud data. The above-mentioned system calibration data is used to correct the system error and flight strip deviation of the above-mentioned UAV during the flight process. The above-mentioned flight strip deviation is the error in the above-mentioned laser data obtained due to the trajectory deviation of the above-mentioned UAV during the surveying and mapping process. The above-mentioned system error is the elevation difference caused by the discontinuous data elevation of multiple flight strips. The above-mentioned flight strip is obtained by dividing the above-mentioned target geographical area into multiple strips.

[0071] In the above embodiment, the laser data is corrected according to the solved parameter values, and the laser data is transformed from the original coordinate system to a more accurate geographic coordinate system according to the solved parameter values, and the original laser data is error corrected by combining the above-mentioned UAV trajectory data and system calibration data, and the laser data after flight zone adjustment is output as laser point cloud data. The accuracy and reliability of the laser point cloud data can be improved by error correction of the initial laser data. The laser point cloud data is stored in LAS format.

[0072] In order to accurately correct the point cloud data, in an optional implementation, the above step S2042 includes:

[0073] Step S20421, obtaining the mean error of the plane position and the mean error of the elevation of the above-mentioned precise laser data, wherein the mean error of the plane position is the mean error between the ground control point and the theoretical value in the plane position of the above-mentioned precise laser data between each flight strip, and the mean error of the elevation is the mean error between the elevation value in the above-mentioned precise laser data between each flight strip and the true elevation value on the ground;

[0074] Step S20422, when the error judgment conditions are met, the system error is corrected by deploying ground control points until the error judgment conditions are no longer met, and all the above-mentioned flight strips are spliced ​​to obtain the above-mentioned laser point cloud data. The above-mentioned error judgment conditions are that the above-mentioned plane position error is greater than the average point cloud spacing, the above-mentioned elevation error is greater than the elevation point cloud accuracy, and the above-mentioned system error exists.

[0075] In the above embodiment, when the flight strips are spliced, the flight strips are automatically spliced ​​in the airborne LiDAR data post-processing software. The mean error of the plane position of the same-name points in the point cloud data between different flight strips (including the same flight and different flights) should be less than the average point cloud spacing, and the mean error of the elevation should be less than the point cloud elevation accuracy requirement specified in the technical requirements. If the mean error exceeds the limit and there is a system error, the system error is corrected by laying out ground control points until the system error is less than the error, and then the flight strips are spliced ​​to obtain the above laser point cloud data.

[0076] In order to accurately reflect the shape, texture and position of the ground object, in an optional implementation, the above step S206 includes:

[0077] Step S2061, registering the digital orthophoto image and the non-ground point cloud data, so that the digital orthophoto image and the non-ground point cloud data are located in the same spatial reference coordinates, and obtaining the registered digital orthophoto image and the registered non-ground point cloud data;

[0078] Step S2062, using texture analysis technology to extract texture information and color information in the digital orthophoto image after registration, and using edge detection method to extract shape feature information of ground objects in the digital orthophoto image after registration;

[0079] Step S2063, extracting height information from the registered non-ground point cloud data;

[0080] Step S2064, obtaining the above-mentioned ground object data by fusing the above-mentioned texture information, the above-mentioned color information, the above-mentioned ground object shape feature information and the above-mentioned height information.

[0081] In the above embodiment, the digital orthophoto image is registered with the non-ground point laser point cloud data based on the ground control point (GCP) or other feature points by using GIS software, the texture and color information in the digital orthophoto image is extracted by using texture analysis technology (such as gray level co-occurrence matrix, local binary pattern, etc.), the shape features of the objects in the digital orthophoto image are extracted by edge detection, region segmentation, etc., and the image information of the digital orthophoto image and the height information of the non-ground point laser point cloud are extracted to extract and identify the features of the objects, and the extracted texture, color, shape and height information of the objects are output. Among them, the digital orthophoto image provides the texture, color and shape information of the objects, while the non-ground point laser point cloud provides accurate height and three-dimensional morphological information, which can make full use of the texture information of the image and the geometric information of the point cloud to generate a more sophisticated object model, which can accurately reflect the shape, texture and position of the objects.

[0082] In order to improve the accuracy of the three-dimensional real scene model generated for the target geographical area, in an optional implementation manner, after the above step S207, the method further includes:

[0083] Step S301, measuring the object information of the object to be measured on the three-dimensional real scene model of the target geographical area by using a measuring tool, the measuring tool at least comprising a measuring ruler and an angle measuring device, and the object information at least comprising the size and angle of the object to be measured;

[0084] Step S302, comparing and analyzing the above-mentioned feature information with reference feature data to obtain data differences;

[0085] Step S303, determining whether the data difference meets the accuracy requirement of the three-dimensional real scene model;

[0086] Step S304: when it is determined that the data difference does not meet the accuracy requirement of the 3D real scene model, the 3D real scene model is corrected.

[0087] In the above embodiment, if Figure 3 As shown, use automated tools or scripts to check the integrity of the 3D real scene model of the target geographic area, such as checking whether there are isolated points, lines, and surfaces. If there are isolated points, lines, and surfaces, output the location information of the isolated points, lines, and surfaces, and regenerate the 3D real scene model of the target area after field remeasurement of the location information. Use measurement tools (such as measuring rulers, angle measuring instruments, etc.) to measure specific objects (i.e. Figure 3 The size, angle, etc. of the checkpoints in the image are compared with the actual data or reference data to analyze the differences and determine whether the differences meet the model accuracy requirements. If they meet the requirements, the 3D real scene model of the target geographic area is output. If they do not meet the accuracy requirements, the data is collected again or the model is corrected to obtain the final 3D real scene model.

[0088] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0089] The embodiment of the present application also provides a geographic information mapping device. It should be noted that the geographic information mapping device of the embodiment of the present application can be used to execute the method for geographic information mapping provided by the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions thereof will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0090] The following is an introduction to the geographic information surveying and mapping device provided in the embodiments of the present application.

[0091] Figure 5 is a structural block diagram of a geographic information surveying and mapping device according to an embodiment of the present application. Figure 5 As shown, the device comprises:

[0092] The acquisition unit 10 is used to acquire geographic data, which includes image data, laser data and drone trajectory data.

[0093] Specifically, Figure 3 As shown, the camera carried by the drone is used to obtain low-altitude high-resolution image data, the lidar obtains low-altitude laser data, the GPS module and inertial measurement unit inside the drone obtain the drone POS data, and the signal receiving device inside the drone obtains the base station data. The base station data and POS data are fused and processed to generate the drone trajectory data to obtain the above-mentioned geographic data.

[0094] The first generating unit 20 is used to generate a digital orthophoto map according to the above image data.

[0095] Specifically, Figure 3 As shown, the data preprocessing stage uses Figure 4 The image data processing module in the image data extracts feature points from the image data, establishes the corresponding relationship between the image data, performs adjustment calculation based on the feature point matching results and the drone trajectory data, splices the image data according to the position relationship obtained by the adjustment calculation, and generates a continuous digital orthophoto map, which also corresponds to Figure 3 DOM in . DOM, or Digital Orthophoto Map, is a high-resolution image data taken by drones, which is processed through a series of processes to generate an image map with precise geographic coordinates and scale.

[0096] The input unit 30 is used to input the above-mentioned UAV trajectory data into the flight track adjustment model to obtain the flight track parameter value, and the above-mentioned flight track parameter value is the attitude parameter of the above-mentioned UAV during the flight process.

[0097] Specifically, the flight strip adjustment model can be a model such as the "twelve parameter model". The UAV trajectory data is imported into the flight strip adjustment model. Based on the conjugate points or ground control points in the flight strip overlapping area, the observation equation is established, and the observation equation is solved using mathematical methods such as the least squares method to obtain the parameter values ​​of the flight strip adjustment model.

[0098] The first correction unit 40 is used to perform error correction on the laser data according to the flight path parameter value to obtain laser point cloud data.

[0099] Specifically, the point cloud coordinates are corrected for each flight strip according to the flight strip parameter values, that is, the error of the laser data is corrected, and the laser data after flight strip adjustment is output as the laser point cloud data.

[0100] The filtering unit 50 is used to perform point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data.

[0101] Specifically, Figure 3 As shown, the CoProcess2.0 software is used to perform point cloud filtering on the laser point cloud data to separate ground points and non-ground points, thereby obtaining ground point cloud data and non-ground point cloud data.

[0102] The second generating unit 60 is used to generate digital elevation model data according to the ground point cloud data, and extract ground feature according to the digital orthophoto and the non-ground point cloud data to obtain ground feature data.

[0103] Specifically, using Figure 4 The ground data analysis module in the software separates the ground points by repeatedly building a triangulated surface network model, and repeatedly adds new laser points to expand the model, ensuring that each added laser point makes the model closer to the ground surface, so as to finally obtain an approximate ground surface, build the ground point cloud data into a TIN model, and further generate DEM data in a regular grid format. DEM is the abbreviation of "Digital Elevation Model". It is a mathematical model used to describe the elevation information of the earth's surface. DEM represents the elevation values ​​of different locations on the surface in the form of grid points and is used to build a terrain model. DEM realizes the digital simulation of the ground terrain through limited terrain elevation data, that is, the digital expression of the terrain surface morphology. It is also a physical ground model that represents the ground elevation in the form of a set of ordered numerical arrays. It is a branch of the digital terrain model, and various other terrain feature values ​​can be derived from it. The image information of the above-mentioned digital orthophoto map and the height information of the non-ground point cloud data are used to extract and identify the ground feature to obtain the ground feature data. Figure 4The ground data analysis module in the system filters the laser point cloud to separate ground points and non-ground points, and constructs DEM data from the ground point cloud data. The non-ground data analysis module aligns the non-ground point cloud data with the digital orthophoto map, and uses the image information of the digital orthophoto map and the height information of the non-ground point cloud data to extract and identify the ground object features and obtain the ground object data.

[0104] It should be noted that by dividing point cloud data into ground points and non-ground points, different processing methods and optimization strategies can be used for different types of point cloud data. The fusion of non-ground point cloud data and image data (i.e., digital orthophotos) can make full use of the texture information of the image and the geometric information of the point cloud to generate a more detailed ground model that can accurately reflect the shape, texture and position of the ground object. The ground point cloud data only needs to process the geometric information, which can not only improve the efficiency of data processing, but also reduce unnecessary calculations and resource consumption.

[0105] The third generating unit 70 is used to superimpose the terrain data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying based on the three-dimensional real scene model. The contour data is the data generated when the digital elevation model data is imported into the predetermined mapping software to generate contour lines.

[0106] Specifically, Figure 4 As shown, the model generation module is used to import the digital elevation model data into the predetermined mapping software to generate contour data, and the object data and the contour data are superimposed in the same spatial reference system to construct a three-dimensional real-scene model of the target area. Superimposing the object data and the contour data in the same spatial reference system can ensure that the relative position relationship between the terrain and the objects is accurate.

[0107] It should be noted that the predetermined mapping software can be commonly used mapping software, as long as the mapping software can be based on basic surveying and mapping results and applied to the vector collection and editing of aerial survey data in industries such as land, electricity, water conservancy, and transportation. The predetermined mapping software uses a computer-assisted interactive guidance mode, with plane DOM, various aerial triangulation stereo pairs, real-scene models, etc. as input data sources, to achieve rapid collection and editing, batch processing, linkage update, operation inspection, results storage and mapping of elements such as land features, landforms, and monomer models.

[0108] In this embodiment, an acquisition unit is used to acquire geographic data, and the above-mentioned geographic data includes image data, laser data and drone trajectory data; a first generation unit is used to generate a digital orthophoto map based on the above-mentioned image data; an input unit is used to input the above-mentioned drone trajectory data into a flight strip adjustment model to obtain flight strip parameter values, and the above-mentioned flight strip parameter values ​​are attitude parameters of the above-mentioned drone during flight; a first correction unit is used to perform error correction on the above-mentioned laser data according to the above-mentioned flight strip parameter values ​​to obtain laser point cloud data; a filtering unit is used to perform point cloud filtering on the above-mentioned laser point cloud data to obtain ground point cloud data and non-ground point cloud data; a second generation unit is used to generate digital elevation model data based on the above-mentioned ground point cloud data, and extract ground feature features based on the above-mentioned digital orthophoto map and the above-mentioned non-ground point cloud data to obtain ground feature data; a third generation unit is used to superimpose the ground feature data and contour line data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying and mapping based on the above-mentioned three-dimensional real scene model, and the above-mentioned contour line data is the data when the above-mentioned digital elevation model data is imported into a predetermined mapping software to generate contour lines. This application uses drones to obtain image data, laser data, POS data and base station data, and fuses the base station data and POS data to generate drone trajectory data; establishes a corresponding relationship between image data, generates a continuous digital orthophoto map, and performs error correction on the original laser data to output a laser point cloud; performs point cloud filtering on the laser point cloud to separate ground points and non-ground points, constructs digital elevation model data from the ground point cloud data, aligns the non-ground point laser point cloud with the digital orthophoto map, and outputs the extracted ground object information; superimposes the ground object data and contour line data in the same spatial reference system to construct a three-dimensional real scene model of the target area. It can accurately reflect the shape, texture and position of the ground object, and can also reduce unnecessary calculations and resource consumption. This application solves the problem that geographic information surveying and mapping in the prior art only relies on spatial coordinate points to distinguish different objects or scenes, making surveying and mapping more difficult.

[0109] In order to improve the positioning accuracy and reliability of the drone, in an optional implementation, the acquisition unit includes:

[0110] A first acquisition module, using a camera mounted on the drone to acquire the above image data;

[0111] A second acquisition module acquires the above laser data through a laser radar;

[0112] A third acquisition module, using the drone to acquire base station data and POS data, the base station data includes the signal strength and distance information of the drone, and the POS data includes the location data, attitude data and flight data of the drone;

[0113] An alignment module performs preliminary alignment on the base station data and the POS data according to the timestamps to obtain time series data;

[0114] The first fusion module utilizes a fusion algorithm to fuse the base station data and the POS data in the time series data to generate the UAV trajectory data.

[0115] In the above embodiment, the drone is equipped with an orthographic camera and an oblique camera to obtain low-altitude high-resolution image data, a laser radar is equipped to obtain low-altitude laser data, the GPS module and inertial measurement unit (IMU) inside the drone obtain the drone POS data, and the signal receiving device inside the drone obtains the base station data. POS (Position and Orientation System) data, that is, position and attitude system data, is the key information recorded by the drone during flight, including the three-dimensional coordinates (longitude, latitude, altitude), speed, acceleration and attitude information (heading angle, pitch angle, roll angle) of the drone. The base station data and POS data are preliminarily aligned according to the timestamp to form a time series data containing two data sources, and the base station data and POS data are fused using a fusion algorithm (such as Kalman filtering and particle filtering) to generate drone trajectory data.

[0116] In order to eliminate image distortion caused by terrain undulations and camera posture changes, in an optional implementation manner, the first generating unit includes:

[0117] A first extraction module extracts feature points from the image data, wherein the feature points at least include corner points and edge points in the image;

[0118] A matching module performs feature point matching between the above-mentioned image data, obtains feature point matching results and establishes image correspondence, wherein the above-mentioned image correspondence is a correspondence between any two images;

[0119] A calculation module performs adjustment calculation based on the feature point matching results and the UAV trajectory data to obtain the internal and external orientation elements of the camera carried by the UAV, wherein the internal and external orientation elements include the position and posture of the camera and the relative position relationship between the images;

[0120] A correction module uses a digital elevation model to perform tilt correction and projection error correction on the above image data to obtain an orthophoto;

[0121] The stitching module stitches the orthophotos according to the relative position relationship and the image correspondence relationship to obtain the digital orthophoto map.

[0122] In the above embodiment, feature points, such as corner points, edge points, etc., are automatically extracted from the pre-processed image data, and feature point matching is performed between different images to establish a corresponding relationship between images (the corresponding relationship is used to splice images); using the aerial triangulation encryption software, adjustment calculation is performed based on the feature point matching results and the drone trajectory data to solve the internal and external orientation elements of the camera, that is, the position and posture of the camera and the relative position relationship between the images. The image is orthorectified using the digital elevation model (that is, using the RPC (Rational Polynomial Coefficients) parameters and digital elevation model data of the image itself to correct the tilt and projection difference of the image, thereby obtaining an orthophoto.) to eliminate the image distortion caused by the undulating terrain and the change of the camera posture, and the corrected image is spliced ​​according to the relative position relationship obtained by the adjustment calculation and the corresponding relationship between the images to generate the above-mentioned continuous digital orthophoto map, which not only has a high spatial resolution, but also can accurately reflect the real morphology and texture information of the surface.

[0123] Adjustment is an optimization technique used to minimize the difference between observations (such as feature point matches) and model predictions. In photogrammetry, this is usually done by minimizing the reprojection error.

[0124] In order to improve the accuracy and reliability of laser point cloud data, in an optional implementation manner, the first correction unit includes:

[0125] A transformation module transforms the laser data from an original coordinate system to a target coordinate system according to the flight path parameter value to obtain accurate laser data, wherein the target coordinate system is a coordinate system more accurate than the original coordinate system;

[0126] The correction module uses the above-mentioned UAV trajectory data and system calibration data to solve and correct the above-mentioned precise laser data using a point cloud solution method to obtain the above-mentioned laser point cloud data. The above-mentioned system calibration data is used to correct the system error and flight path deviation of the above-mentioned UAV during the flight process. The above-mentioned flight path deviation is the error in the above-mentioned laser data obtained due to the trajectory deviation of the above-mentioned UAV during the surveying and mapping process. The above-mentioned system error is the elevation difference caused by the discontinuous data elevation of multiple flight paths. The above-mentioned flight path is obtained by dividing the above-mentioned target geographical area into multiple strips.

[0127] In the above embodiment, the laser data is corrected according to the solved parameter values, and the laser data is transformed from the original coordinate system to a more accurate geographic coordinate system according to the solved parameter values, and the original laser data is error corrected by combining the above-mentioned UAV trajectory data and system calibration data, and the laser data after flight zone adjustment is output as laser point cloud data. The accuracy and reliability of the laser point cloud data can be improved by error correction of the initial laser data. The laser point cloud data is stored in LAS format.

[0128] In order to accurately correct the point cloud data, in an optional implementation, the correction module includes:

[0129] The acquisition submodule obtains the mean error of the plane position and the mean error of the elevation of the above-mentioned precise laser data. The mean error of the plane position is the mean error between the ground control point and the theoretical value in the plane position of the above-mentioned precise laser data between each flight strip, and the mean error of the elevation is the mean error between the elevation value in the above-mentioned precise laser data between each flight strip and the true elevation value on the ground;

[0130] The correction submodule, when the error judgment conditions are met, corrects the system error by deploying ground control points until the above error judgment conditions are no longer met, and splices all the above flight strips to obtain the above laser point cloud data. The above error judgment conditions are that the above plane position error is greater than the average point cloud spacing, the above elevation error is greater than the elevation point cloud accuracy, and the above system error exists.

[0131] In the above embodiment, when the flight strips are spliced, the flight strips are automatically spliced ​​in the airborne LiDAR data post-processing software. The mean error of the plane position of the same-name points in the point cloud data between different flight strips (including the same flight and different flights) should be less than the average point cloud spacing, and the mean error of the elevation should be less than the point cloud elevation accuracy requirement specified in the technical requirements. If the mean error exceeds the limit and there is a system error, the system error is corrected by laying out ground control points until the system error is less than the error, and then the flight strips are spliced ​​to obtain the above laser point cloud data.

[0132] In order to accurately reflect the shape, texture and position of the ground object, in an optional implementation manner, the second generating unit includes:

[0133] A registration module is used to register the digital orthophoto image and the non-ground point cloud data, so that the digital orthophoto image and the non-ground point cloud data are located in the same spatial reference coordinates, thereby obtaining the registered digital orthophoto image and the registered non-ground point cloud data;

[0134] The second extraction module uses texture analysis technology to extract texture information and color information in the digital orthophoto image after registration, and uses edge detection method to extract shape feature information of objects in the digital orthophoto image after registration;

[0135] A third extraction module extracts height information from the registered non-ground point cloud data;

[0136] The second fusion module obtains the above-mentioned ground object data by fusing the above-mentioned texture information, the above-mentioned color information, the above-mentioned ground object shape feature information and the above-mentioned height information.

[0137] In the above embodiment, the digital orthophoto image is registered with the non-ground point laser point cloud data based on the ground control point (GCP) or other feature points by using GIS software, the texture and color information in the digital orthophoto image is extracted by using texture analysis technology (such as gray level co-occurrence matrix, local binary pattern, etc.), the shape features of the objects in the digital orthophoto image are extracted by edge detection, region segmentation, etc., and the image information of the digital orthophoto image and the height information of the non-ground point laser point cloud are extracted to extract and identify the features of the objects, and the extracted texture, color, shape and height information of the objects are output. Among them, the digital orthophoto image provides the texture, color and shape information of the objects, while the non-ground point laser point cloud provides accurate height and three-dimensional morphological information, which can make full use of the texture information of the image and the geometric information of the point cloud to generate a more sophisticated object model, which can accurately reflect the shape, texture and position of the objects.

[0138] In order to improve the accuracy of the three-dimensional real scene model generated for the target geographical area, in an optional implementation manner, the device further includes:

[0139] A measuring unit, used to measure the object information of the object to be measured on the three-dimensional real scene model of the target geographical area by using a measuring tool, wherein the measuring tool at least includes a measuring ruler and an angle measuring device, and the object information at least includes the size and angle of the object to be measured;

[0140] A comparison unit is used to compare and analyze the above-mentioned ground feature information with reference ground feature data to obtain data differences;

[0141] A judging unit, used to judge whether the data difference meets the accuracy requirement of the three-dimensional real scene model;

[0142] The second correction unit is used to correct the three-dimensional real scene model when it is determined that the data difference does not meet the accuracy requirement of the three-dimensional real scene model.

[0143] In the above embodiment, if Figure 3As shown, use automated tools or scripts to check the integrity of the 3D real scene model of the target geographic area, such as checking whether there are isolated points, lines, and surfaces. If there are isolated points, lines, and surfaces, output the location information of the isolated points, lines, and surfaces, and regenerate the 3D real scene model of the target area after field remeasurement of the location information. Use measurement tools (such as measuring rulers, angle measuring instruments, etc.) to measure specific objects (i.e. Figure 3 The size, angle, etc. of the checkpoints in the image are compared with the actual data or reference data to analyze the differences and determine whether the differences meet the model accuracy requirements. If they meet the requirements, the 3D real scene model of the target geographic area is output. If they do not meet the accuracy requirements, the data is collected again or the model is corrected to obtain the final 3D real scene model.

[0144] The geographic information surveying and mapping device includes a processor and a memory. The acquisition unit, the first generation unit, the input unit, etc. are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0145] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to solve the problem that geographic information mapping in the prior art only relies on spatial coordinate points to distinguish different objects or scenes, making mapping more difficult.

[0146] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0147] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the geographic information surveying and mapping method.

[0148] Specifically, geographic information surveying and mapping methods include:

[0149] Step S201, obtaining geographic data, the geographic data including image data, laser data and drone trajectory data;

[0150] Step S202, generating a digital orthophoto map according to the above image data;

[0151] Step S203, inputting the above-mentioned UAV trajectory data into a flight zone adjustment model to obtain flight zone parameter values, where the above-mentioned flight zone parameter values ​​are attitude parameters of the above-mentioned UAV during flight;

[0152] Step S204, performing error correction on the laser data according to the flight path parameter value to obtain laser point cloud data;

[0153] Step S205, performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data;

[0154] Step S206, generating digital elevation model data according to the ground point cloud data, and extracting ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data;

[0155] Step S207, superimpose the feature data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying based on the three-dimensional real scene model. The contour data is the data generated when the digital elevation model data is imported into a predetermined mapping software to generate contour lines.

[0156] An embodiment of the present invention provides a processor, and the processor is used to run a program, wherein the geographic information surveying and mapping method is executed when the program is run.

[0157] Specifically, geographic information surveying and mapping methods include:

[0158] Step S201, obtaining geographic data, the geographic data including image data, laser data and drone trajectory data;

[0159] Step S202, generating a digital orthophoto map according to the above image data;

[0160] Step S203, inputting the above-mentioned UAV trajectory data into a flight zone adjustment model to obtain flight zone parameter values, where the above-mentioned flight zone parameter values ​​are attitude parameters of the above-mentioned UAV during flight;

[0161] Step S204, performing error correction on the laser data according to the flight path parameter value to obtain laser point cloud data;

[0162] Step S205, performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data;

[0163] Step S206, generating digital elevation model data according to the ground point cloud data, and extracting ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data;

[0164] Step S207, superimpose the feature data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying based on the three-dimensional real scene model. The contour data is the data generated when the digital elevation model data is imported into a predetermined mapping software to generate contour lines.

[0165] An embodiment of the present invention provides a geographic information surveying and mapping system, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, at least the following steps are implemented:

[0166] Step S201, obtaining geographic data, the geographic data including image data, laser data and drone trajectory data;

[0167] Step S202, generating a digital orthophoto map according to the above image data;

[0168] Step S203, inputting the above-mentioned UAV trajectory data into a flight zone adjustment model to obtain flight zone parameter values, where the above-mentioned flight zone parameter values ​​are attitude parameters of the above-mentioned UAV during flight;

[0169] Step S204, performing error correction on the laser data according to the flight path parameter value to obtain laser point cloud data;

[0170] Step S205, performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data;

[0171] Step S206, generating digital elevation model data according to the ground point cloud data, and extracting ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data;

[0172] Step S207, superimpose the feature data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying based on the three-dimensional real scene model. The contour data is the data generated when the digital elevation model data is imported into a predetermined mapping software to generate contour lines.

[0173] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps:

[0174] Step S201, obtaining geographic data, the geographic data including image data, laser data and drone trajectory data;

[0175] Step S202, generating a digital orthophoto map according to the above image data;

[0176] Step S203, inputting the above-mentioned UAV trajectory data into a flight zone adjustment model to obtain flight zone parameter values, where the above-mentioned flight zone parameter values ​​are attitude parameters of the above-mentioned UAV during flight;

[0177] Step S204, performing error correction on the laser data according to the flight path parameter value to obtain laser point cloud data;

[0178] Step S205, performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data;

[0179] Step S206, generating digital elevation model data according to the ground point cloud data, and extracting ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data;

[0180] Step S207, superimpose the feature data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying based on the three-dimensional real scene model. The contour data is the data generated when the digital elevation model data is imported into a predetermined mapping software to generate contour lines.

[0181] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0182] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0183] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0184] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0185] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0186] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0187] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0188] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0189] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0190] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0191] 1) The geographic information surveying and mapping method of the present application, first, obtains geographic data, the above-mentioned geographic data includes image data, laser data and drone trajectory data; then, generates a digital orthophoto map according to the above-mentioned image data; then, inputs the above-mentioned drone trajectory data into the flight strip adjustment model to obtain the flight strip parameter value, and the above-mentioned flight strip parameter value is the attitude parameter of the above-mentioned drone during flight; then, according to the above-mentioned flight strip parameter value, the above-mentioned laser data is error corrected to obtain laser point cloud data; then, the above-mentioned laser point cloud data is point cloud filtered to obtain ground point cloud data and non-ground point cloud data; then, digital elevation model data is generated according to the above-mentioned ground point cloud data, and the ground feature is extracted according to the above-mentioned digital orthophoto map and the above-mentioned non-ground point cloud data to obtain ground object data; finally, the ground object data and contour line data are superimposed under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying and mapping according to the above-mentioned three-dimensional real scene model, and the above-mentioned contour line data is the data when the above-mentioned digital elevation model data is imported into the predetermined mapping software to generate contour lines. This application uses drones to obtain image data, laser data, POS data and base station data, and fuses the base station data and POS data to generate drone trajectory data; establishes a corresponding relationship between image data, generates a continuous digital orthophoto map, and performs error correction on the original laser data to output a laser point cloud; performs point cloud filtering on the laser point cloud to separate ground points and non-ground points, constructs digital elevation model data from the ground point cloud data, aligns the non-ground point laser point cloud with the digital orthophoto map, and outputs the extracted ground object information; superimposes the ground object data and contour line data in the same spatial reference system to construct a three-dimensional real scene model of the target area. It can accurately reflect the shape, texture and position of the ground object, and can also reduce unnecessary calculations and resource consumption. This application solves the problem that geographic information surveying and mapping in the prior art only relies on spatial coordinate points to distinguish different objects or scenes, making surveying and mapping more difficult.

[0192] 2) The geographic information surveying and mapping device of the present application comprises an acquisition unit for acquiring geographic data, wherein the geographic data comprises image data, laser data and drone trajectory data; a first generation unit for generating a digital orthophoto map according to the image data; an input unit for inputting the drone trajectory data into a flight path adjustment model to obtain flight path parameter values, wherein the flight path parameter values ​​are attitude parameters of the drone during flight; a first correction unit for performing error correction on the laser data according to the flight path parameter values ​​to obtain laser point cloud data; and a filtering unit for filtering the laser point cloud. The data is point cloud filtered to obtain ground point cloud data and non-ground point cloud data; the second generating unit is used to generate digital elevation model data according to the above ground point cloud data, and extract ground feature according to the above digital orthophoto map and the above non-ground point cloud data to obtain ground object data; the third generating unit is used to superimpose the ground object data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying and mapping according to the above three-dimensional real scene model, and the above contour line data is the data when the above digital elevation model data is imported into the predetermined mapping software to generate contour lines. This application uses drones to obtain image data, laser data, POS data and base station data, and fuses the base station data and POS data to generate drone trajectory data; establishes a corresponding relationship between image data, generates a continuous digital orthophoto map, and performs error correction on the original laser data to output a laser point cloud; performs point cloud filtering on the laser point cloud to separate ground points and non-ground points, constructs digital elevation model data from the ground point cloud data, aligns the non-ground point laser point cloud with the digital orthophoto map, and outputs the extracted ground object information; superimposes the ground object data and contour line data in the same spatial reference system to construct a three-dimensional real scene model of the target area. It can accurately reflect the shape, texture and position of the ground object, and can also reduce unnecessary calculations and resource consumption. This application solves the problem that geographic information surveying and mapping in the prior art only relies on spatial coordinate points to distinguish different objects or scenes, making surveying and mapping more difficult.

[0193] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A geographic information surveying and mapping method, characterized in that: include: Acquiring geographic data, wherein the geographic data includes image data, laser data, and drone trajectory data; Generate a digital orthophoto map based on the image data; Inputting the UAV trajectory data into a flight strip adjustment model to obtain flight strip parameter values, wherein the flight strip parameter values ​​are attitude parameters of the UAV during flight; Performing error correction on the laser data according to the flight path parameter value to obtain laser point cloud data; Performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data; Generate digital elevation model data according to the ground point cloud data, and extract ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data; The feature data and contour line data are superimposed under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying based on the three-dimensional real scene model. The contour line data is the data generated when the digital elevation model data is imported into the predetermined mapping software to generate contour lines.

2. The method according to claim 1, characterized in that Get geographic data, including: Acquiring the image data using a camera carried by the drone; Acquiring the laser data through a laser radar; Using the drone to obtain base station data and POS data, the base station data includes the signal strength and distance information of the drone, and the POS data includes the position data, attitude data and flight data of the drone; Preliminarily aligning the base station data and the POS data according to timestamps to obtain time series data; The base station data and the POS data in the time series data are fused using a fusion algorithm to generate the drone trajectory data.

3. The method according to claim 1, characterized in that Generating a digital orthophoto map according to the image data includes: Extracting feature points from the image data, wherein the feature points include at least corner points and edge points in the image; Performing feature point matching between different image data to obtain feature point matching results and establish image correspondence, wherein the image correspondence is a correspondence between any two images; Perform adjustment calculation based on the feature point matching result and the drone trajectory data to obtain the internal and external orientation elements of the camera carried by the drone, wherein the internal and external orientation elements include the position and posture of the camera and the relative position relationship between the images; Using a digital elevation model to perform tilt correction and projection error correction on the image data to obtain an orthophoto; The orthophotos are spliced ​​according to the relative position relationship and the image correspondence relationship to obtain the digital orthophoto map.

4. The method according to claim 1, characterized in that: The laser data is error corrected according to the flight path parameter value to obtain laser point cloud data, including: According to the flight path parameter value, the laser data is transformed from the original coordinate system to the target coordinate system to obtain accurate laser data, wherein the target coordinate system is a coordinate system that is more accurate than the original coordinate system; The precise laser data is solved and corrected by a point cloud solution method using the UAV trajectory data and system calibration data to obtain the laser point cloud data. The system calibration data is used to correct the system error and flight strip deviation of the UAV during flight. The flight strip deviation is the error in the laser data obtained due to the trajectory deviation of the UAV during the surveying and mapping process. The system error is the elevation difference caused by the discontinuous data elevation of multiple flight strips. The flight strip is obtained by dividing the target geographical area into multiple strips.

5. The method according to claim 4, characterized in that The precise laser data is solved and corrected by using a point cloud solution method to obtain the laser point cloud data, including: Obtaining the mean error of the plane position and the mean error of the elevation of the precise laser data, wherein the mean error of the plane position is the mean error of the plane position of the precise laser data between each flight strip at the same measuring point, and the mean error of the elevation is the mean error between the elevation value in the precise laser data between each flight strip and the true elevation value on the ground; When the error judgment conditions are met, the system error is corrected by deploying ground control points until the error judgment conditions are no longer met. All the flight strips are spliced ​​to obtain the laser point cloud data. The error judgment conditions are that the plane position error is greater than the average point cloud spacing, the elevation error is greater than the elevation point cloud accuracy, and the system error exists.

6. The method according to claim 1, characterized in that Extracting ground feature features according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data includes: Aligning the digital orthophoto image and the non-ground point cloud data so that the digital orthophoto image and the non-ground point cloud data are located in the same spatial reference coordinates, thereby obtaining the aligned digital orthophoto image and the aligned non-ground point cloud data; Extracting texture information and color information from the digital orthophoto image after registration using texture analysis technology, and extracting shape feature information of objects from the digital orthophoto image after registration using edge detection method; Extracting height information from the registered non-ground point cloud data; The ground object data is obtained by fusing the texture information, the color information, the ground object shape feature information and the height information.

7. The method according to claim 1, characterized in that After the object data and the contour line data are superimposed under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, the method further includes: Measuring the object information of the object to be measured on the three-dimensional real scene model of the target geographical area by using a measuring tool, wherein the measuring tool at least includes a measuring ruler and an angle measuring device, and the object information at least includes the size and angle of the object to be measured; Comparing and analyzing the ground feature information with reference ground feature data to obtain data differences; Determining whether the data difference meets the accuracy requirement of the three-dimensional real scene model; When it is determined that the data difference does not meet the accuracy requirement of the three-dimensional real scene model, the three-dimensional real scene model is corrected.

8. A geographic information surveying and mapping device, characterized in that: The device comprises: An acquisition unit, used to acquire geographic data, wherein the geographic data includes image data, laser data, and drone trajectory data; A first generating unit, used for generating a digital orthophoto map according to the image data; An input unit, used for inputting the UAV trajectory data into a flight strip adjustment model to obtain a flight strip parameter value, wherein the flight strip parameter value is an attitude parameter of the UAV during flight; A first correction unit, used for performing error correction on the laser data according to the flight path parameter value to obtain laser point cloud data; A filtering unit, used for performing point cloud filtering on the laser point cloud data to obtain ground point cloud data and non-ground point cloud data; A second generating unit is used to generate digital elevation model data according to the ground point cloud data, and extract ground feature according to the digital orthophoto map and the non-ground point cloud data to obtain ground feature data; The third generating unit is used to superimpose the terrain data and the contour data under the same spatial reference to generate a three-dimensional real scene model of the target geographical area, so as to perform field surveying and mapping according to the three-dimensional real scene model. The contour data is the data when the digital elevation model data is imported into the predetermined mapping software to generate contour lines.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A geographic information surveying and mapping system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 7.

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