CN116625354B

CN116625354B - High-precision topographic map generation method and system based on multi-source mapping data

Info

Publication number: CN116625354B
Application number: CN202310896442.8A
Authority: CN
Inventors: 张秀民; 张秀锦; 胡福祥; 吴兆德
Original assignee: Shandong Provincial Institute of Land Surveying and Mapping
Current assignee: Shandong Provincial Institute of Land Surveying and Mapping
Priority date: 2023-07-21
Filing date: 2023-07-21
Publication date: 2023-09-29
Anticipated expiration: 2043-07-21
Also published as: CN116625354A

Abstract

The invention relates to the technical field of high-precision topographic map generation, in particular to a high-precision topographic map generation method and system based on multi-source mapping data: different precision influence parameters in the mapping process, including satellite images, aerial photographic images and laser radar data precision influence parameters, are acquired, further data analysis processing is carried out, different precision evaluation indexes are generated, and the different precision evaluation indexes are compared with different precision evaluation thresholds to judge whether the acquired different data sources are credible or not: if all the precision evaluation indexes are in the precision evaluation threshold range, all the data sources acquired in the mapping process are credible, and feature extraction, integration and fusion are performed to generate a high-precision topographic map. The method of the invention obviously improves the horizontal precision, the contour precision and the elevation precision of the topographic map, so that the precision of the topographic map is comprehensively improved, the erroneous generation of the topographic map with low precision is avoided, and simultaneously, the real-time debugging and the overhaul of staff are facilitated.

Description

High-precision topographic map generation method and system based on multi-source mapping data

Technical Field

The invention relates to the technical field of high-precision topographic map generation, in particular to a high-precision topographic map generation method and system based on multi-source mapping data.

Background

The topography refers to a projection of the topography and the geographical position, shape on the horizontal plane, in particular, the topography and the topography on the ground are projected on the horizontal plane according to the horizontal projection method (projected on the horizontal plane along the plumb line direction), and the topography is drawn on the drawing according to a certain scale, and the figure is called topography. Because the area range of the drawing is smaller, the topographic map can accurately and detailedly represent natural geographic elements such as land relief hydrology, topography, soil, vegetation and the like, and social and economic elements such as residential points, traffic lines, boundary lines, engineering buildings and the like, is an indispensable tool in economic construction, national defense construction and scientific research, and is also basic data for compiling various small-scale universal maps, thematic maps and atlases. The surface characteristic data of the topographic map usually need to be mapped by means of an aerial camera, a satellite remote sensing system, a laser radar system and the like, so that in the mapping process, the satellite remote sensing image related parameters, the laser radar related measurement data and the aerial photography related measurement data all influence the precision of the topographic map.

In order to continuously optimize the functions of the topographic map or the map, various intelligent topographic map or map generating methods are developed. As an invention patent with application number of CN201910156262.X, a method and a device for generating a high-precision map are disclosed, and picture data is obtained from a camera; acquiring point cloud data from a laser radar; acquiring attitude information from a Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU); processing the picture data to extract visual characteristic information, and carrying out gesture estimation according to the visual characteristic information extracted by the current frame, the integrated gesture information which is fused previously and the map visual characteristic information which is maintained previously to obtain camera gesture estimation; processing the point cloud data to obtain point cloud information, and carrying out attitude estimation according to the point cloud information and other information to obtain radar attitude estimation; fusing the attitude information, the camera attitude estimation and the radar attitude estimation to obtain a more accurate and stable attitude estimation result; and fusing the picture data and the point cloud data according to the more accurate and stable posture estimation result to construct a high-precision map. The invention patent with the application number of CN202210677302.7 discloses a topographic map mapping method, a topographic map mapping device, topographic map mapping equipment and a storage medium, discloses historical geographic data based on a region to be painted, and carries out comparison analysis on the historical geographic data and a preset real-scene three-dimensional model of the region to be painted through a preset checking method to obtain reference geographic data meeting preset precision requirements; determining position information of the terrain elements and the ground feature elements according to the terrain elements and the ground feature elements identified in the live-action three-dimensional model and the reference geographic data, and generating an initial drawing terrain map of the region to be drawn according to the position information of the terrain elements and the ground feature elements; when a ground feature which cannot be identified exists in the live-action three-dimensional model, determining the position information of the ground feature by adopting a multi-piece front intersection algorithm based on images of the ground feature under different visual angles, and performing supplementary drawing on the initial drawing topographic map according to the position information of the ground feature to generate a supplementary drawing topographic map; and extracting elevation data of different positions in the live-action three-dimensional model based on the point cloud data of the region to be drawn, and generating Gao Chengdian and contour lines in the supplementary drawing topographic map according to the extracted elevation data to obtain a target topographic map of the region to be drawn.

However, the above-mentioned topographic map generating method cannot avoid the precision error of the topographic map in the mapping process of the aerial camera, the satellite remote sensing system, the laser radar system, etc.

Disclosure of Invention

In view of the above, the invention aims to provide a high-precision topographic map generation method and system based on multi-source mapping data, so as to overcome precision errors of the prior art on topographic maps in mapping processes of aerial cameras, satellite remote sensing systems, laser radar systems and the like.

Based on the above purposes, the invention provides a high-precision topographic map generating method based on multi-source mapping data, which comprises the steps of acquiring different precision influence parameters in the mapping process, including satellite image precision influence parameters, aerial photography image precision influence parameters and laser radar data precision influence parameters, further analyzing and processing data to generate satellite image precision evaluation indexes, aerial photography precision evaluation indexes and laser radar precision evaluation indexes, and comparing the different precision evaluation indexes with different precision evaluation thresholds to judge whether the acquired satellite image, aerial photography image and laser radar data are credible or not: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and carrying out feature extraction, integration and fusion on different data sources (satellite images, aerial photographic images and laser radar data) to generate a high-precision topographic map based on multi-source mapping data; otherwise, the image and data information acquired in the mapping process are not all credible, and different early warning signals are sent out according to the precision evaluation index which is not in the precision evaluation threshold range.

Further, the high-precision topographic map generating method based on the multi-source mapping data comprises the following steps:

s1: collecting satellite image precision influence parameters: in the satellite remote sensing monitoring process, a resolution stability coefficient REWx of a satellite image and a satellite link bandwidth stability coefficient DKWx are obtained, and the method specifically comprises the following steps:

resolution stability refers to consistency and repeatability of the resolution of the satellite in images taken at different times, and if the resolution of the satellite image is stable at different times, the accuracy of the satellite image is high, so that a high-precision topographic map is obtained. Factors affecting the resolution stability of satellite images mainly include the following:

satellite platform stability: the stability of the satellite platform is critical to image resolution stability. If the satellite is disturbed by excessive vibrations, swings or other instability factors, the image resolution may be affected.

Atmospheric conditions: the atmosphere also has a certain influence on the quality and resolution of satellite images, and the light changes in the transmission process due to the scattering, absorption and refraction of the atmosphere, so that the definition and resolution of the images are reduced. Different atmospheric conditions, such as atmospheric turbulence and temperature, humidity changes in the atmosphere, etc., can affect the resolution stability of the image.

Satellite orbit: the orbit of satellites also has an impact on the stability of the resolution of images, low Earth Orbit (LEO) satellites typically have higher resolution, but their shorter orbit period may result in different observed geometries for images of the same region being observed.

Satellite imaging parameters: the parameter settings of satellite imaging can also have an impact on image resolution stability, e.g., parameters such as exposure time, gain settings, filter selection, etc., can affect image quality and resolution stability.

The effect of the resolution stability of satellite images on the accuracy of the topography includes the following aspects:

consistency of boundaries and lines: if the resolution stability of the satellite image is not high, the same line or boundary may have slight changes in different images, which may cause the boundary lines in the topographic map to be incoherent or blurred, and reduce the accuracy of the topographic map;

object recognition and classification: if the resolution stability is poor, the same object may show differences in different images, so that the identification and classification of the object in the topographic map become difficult, and the accuracy of the topographic map is reduced;

spatial analysis and measurement: resolution stability is very important for spatial analysis and measurement, and if the resolution of satellite images deviates greatly at different time points, basic measurement parameters such as distance, area, direction and the like in the topographic map are affected, so that the spatial analysis result in the topographic map is inaccurate.

Therefore, to generate accurate topography, consistency and consistency in the resolution of the satellite images needs to be maintained.

S11: the resolution stability factor REWx of the satellite image is obtained by the following steps:

s111: acquiring resolution of satellite images at different time periods within T timeT represents the numbers of network transmission rates of different time periods in the T time, and t=1, 2, 3, 4, … … and n are positive integers;

it should be noted that the resolution of the satellite image may be read by image editing software or a dedicated image attribute viewer;

s112: resolution of satellite images through different time periods within T timeThe resolution stability factor REWx of the satellite image is calculated as follows:

satellite link bandwidth stability has a significant impact on the accuracy of satellite images, with some possible effects:

image transfer speed: the bandwidth stability of the satellite link directly influences the speed of image transmission, if the bandwidth is unstable, the transmission process may be influenced by delay or interruption, so that the image transmission is slow or fails, which may result in loss or incompleteness of image data, and the accuracy and quality of the image are reduced;

compression rate and data loss: in order to accommodate the limited bandwidth, satellite images typically require data compression prior to transmission, and variations in bandwidth stability may lead to variations in image data compression rate, such that some important details are lost during transmission, which may lead to reduced image accuracy, particularly in applications requiring high resolution and high quality images;

Image processing and analysis: satellite images often require further processing and analysis to extract useful information, for example, remote sensing images may require analysis for feature classification, object detection, and change detection, and bandwidth stability problems may lead to loss or error of image data during processing and analysis, which may negatively impact the accuracy and reliability of image analysis and application;

real-time application analysis: variations in bandwidth stability may lead to increased data transmission and processing times, thereby reducing the accuracy and efficiency of real-time applications.

Therefore, the bandwidth stability of the satellite link has a critical impact on the accuracy and reliability of the satellite image. The stable bandwidth can ensure smooth image transmission and ensure the integrity and quality of image data, thereby improving the accuracy and applicability of images.

S12: the acquisition mode of the satellite link bandwidth stability coefficient DKWx is as follows:

s121: acquiring satellite link bandwidths of different time periods in T timeT represents the numbers of network transmission rates of different time periods in the T time, and t=1, 2, 3, 4, … … and n are positive integers;

it should be noted that, the bandwidth on the satellite link may be measured by using network performance testing tools, which may evaluate the transmission speed of the link by sending and receiving data packets, and common network performance testing tools include iPerf, speedtest; alternatively, network traffic on the satellite link is captured and analyzed using a network protocol analyzer (e.g., wireshark), and the actual transmission rate and bandwidth utilization on the link is determined by analyzing the traffic;

S122: the satellite link bandwidth stability coefficient DKWx is calculated through satellite link bandwidths DKt of different time periods in the T time, and the calculation formula is as follows:

s2: acquiring aerial photography image precision influence parameters: in the large-range aerial photography process of the unmanned aerial vehicle, the frame rate stability coefficient HZWx and the sharpness stability coefficient HRWx of the aerial camera are obtained, and the method specifically comprises the following steps:

the frame rate refers to the number of images displayed per second, determines the number of images shot by a camera in unit time, and has two main effects on the stability of the frame rate in the generation of aerial topography:

angular deviation: the frame rate unstable camera may have a different degree of viewing angle offset between successive frames, which may cause image distortion, causing errors in the topography at a particular region or angle, and the frame rate stable camera may reduce such angular offset, providing more accurate image data;

and (3) data processing: a low frame rate and unstable camera may lead to challenges in data processing and image stitching, and for aerial images, it is often necessary to stitch successive images to generate a complete topography, and an unstable frame rate may lead to incoherence or distortion in the image stitching process, thereby affecting the accuracy of stitching and the quality of the results.

Therefore, for the accuracy of the topographic map, the stability of the frame rate of the aerial camera is important, and the high stable frame rate can provide more space and time information, so that the spatial resolution, the time sequence resolution and the overall accuracy of the topographic map are improved.

S21: the frame rate stability coefficient HZWx of the aerial camera is obtained by the following steps:

s211: acquiring frame rates of aerial cameras at different time intervals in T timeT represents the number of the frame rate of the aerial camera in different time periods within the T time, and t=1, 2, 3, 4, … … and n are positive integers;

s212: calculating average value of frame rate of aerial camera in different time periods in T timeThe calculation formula is as follows:

s213: average value of frame rate of aerial camera according to different time periods in T timeFrame rate of aerial photography cameraThe frame rate stability factor HZWx is calculated as follows:

the sharpness stability of an aerial camera has an important impact on the topography generated:

details of the topographic map: the sharpness stability of the camera determines the definition and detail richness of the image, if the sharpness stability of the camera is poor, the image can be blurred or distorted, so that the definition and detail level of a topographic map are reduced, operations such as identification, classification and measurement of objects in the topographic map can be influenced, and the accuracy of the topographic map can be reduced;

Feature extraction and matching: in the process of generating a topographic map, feature extraction and matching are usually required to be carried out on the image so as to identify ground objects, register the ground objects and the like, the sharpness stability of a camera directly influences the quality of the feature extraction and matching, if the sharpness stability of the camera is poor, the features in the image can be blurred or unclear, the accuracy of the feature extraction and matching is reduced, and the accuracy of the topographic map is further influenced;

visual reconstruction: the aerial image is generally used for carrying out three-dimensional visual reconstruction, a three-dimensional model or point cloud data of a topographic map is generated, the sharpness stability of a camera is critical to the accuracy and quality of visual reconstruction, if the sharpness stability of the camera is poor, inaccurate image alignment in the visual reconstruction process can be caused, errors or blurring phenomena can exist in a reconstruction result, and the accuracy and the authenticity of the topographic map are affected;

visual measurement: measurement tasks in the topography, such as distance measurement, area measurement, etc., are also affected by the sharpness stability of the camera, a stable image can provide a more accurate measurement result, and blurred or distorted images can cause an increase in measurement errors;

thus, the sharpness stability of the aerial camera is crucial for generating high-precision topography, and stable image quality can provide clear and accurate data, facilitating more accurate topography construction, analysis and application.

S22: the sharpness stabilizing coefficient HRWx of the aerial camera is obtained by the following steps:

s221: obtaining aerial camera sharpness for different time periods within a T timeT represents the T timeNumbers of imaging sharpness in different periods, t=1, 2, 3, 4, … …, n being a positive integer;

s222: calculating average sharpness of aerial camera at different time intervals in T timeThe calculation formula is as follows:

s223: average value of sharpness of aerial camera according to different time periods in T timeSharpness of aerial cameraThe sharpness stabilization factor HRWx is calculated as follows:

s3: collecting laser radar data precision influence parameters: in the process of acquiring data by the laser radar, an angular resolution stability coefficient JFWx and a scanning frequency stability coefficient SPWx of the laser radar are acquired, and the method specifically comprises the following steps:

the stability of the angular resolution of the lidar, which means that the lidar is able to resolve the smallest angular difference between two targets, has an important influence on the accuracy of the topography generated, and the stability of this value, which indicates this angular resolution, is in each case kept relatively consistent and reliable. When the angular resolution stability of the lidar is high, it means that it can more accurately resolve small angular differences between targets, which is important for establishing high-precision topography. If the angular resolution is less stable, this means that the laser radar may have a variation in resolution under different conditions, resulting in a reduced accuracy of the generated topography. The high angular resolution stable lidar can more accurately capture the details and geometry of the target, thereby generating a more accurate topography, e.g., when constructing a three-dimensional topography, the high angular resolution stable lidar can more accurately determine the boundaries and shape of the object. In addition, the angular resolution stability of the lidar also affects its continuity in the time axis, and if the stability is low, the angular resolution may change over time, resulting in discontinuities or inconsistencies in the topography.

Therefore, the stability of the angular resolution of the lidar has an important influence on the precision of the generated topographic map, and the higher-stability angular resolution is helpful to improve the precision, consistency and continuity of the topographic map, which is one of the key factors for obtaining the high-precision topographic map in various applications of the lidar technology.

S31: the obtaining mode of the angle resolution stability coefficient JFWx of the laser radar is as follows:

s311: obtaining angular resolution of lidar for different periods of time within a T-timeT represents the number of the angular resolutions of the lidar at different time periods within the T time, t=1, 2, 3, 4, … …, n being a positive integer;

it should be noted that, the angular resolution measurement of the lidar generally requires instrument calibration and experimental verification, and the following are common measurement methods:

instrument calibration: before the angular resolution measurement can be performed, the lidar first needs to be calibrated to ensure that its internal parameters and settings are accurate. This includes calibration of the laser transmitter, detector and associated electronics;

setting an angle target: selecting an appropriate target (the target can be a reflecting object, a stick or an object with a certain geometric shape) according to the angular resolution range to be measured, and placing the target on a measuring plane of the laser radar;

And (3) collecting measurement data: measuring by using laser radar equipment, adjusting the laser radar to a required scanning mode and an angle range, ensuring that a laser beam can cover a target area, and collecting data returned by the laser radar at required intervals, including target intensity and position information returned by the radar;

and (3) data processing: processing the collected data to obtain angle information of the target position, and signal processing methods such as convolution, fourier transform or correlation analysis can be used to extract the angle information of the target;

angular resolution calculation: calculating the angular resolution of the laser radar system according to the acquired data and the data processing result;

s312: calculating the average value of the laser radar angular resolutions of different time periods in T timeThe calculation formula is as follows:

s313: mean value of laser radar angular resolution according to different time periods in T timeLaser radar angular resolution +.>The angular resolution stability factor JFWx is calculated as follows:

in the lidar, the scanning frequency refers to the number of times of scanning the laser beam per second. The stability of the scanning frequency has an important influence on the accuracy of the generated topography, the following are several aspects of its influence:

Point cloud resolution: the stability of the scanning frequency is directly related to the resolution of the point cloud data acquired by the lidar. The higher scanning frequency can acquire a large amount of point cloud data more quickly, so that finer and precise topographic map detail information is obtained.

Topography registration accuracy: in creating a topography map, the point cloud data of multiple scans need to be registered, i.e. they are spatially aligned. If the scanning frequency is unstable, the time difference between the point cloud data may increase, thereby increasing the error of registration. The stable scanning frequency can reduce time difference and improve registration accuracy of the topographic map.

Motion distortion: lidar is typically mounted on robots or vehicles for topographical construction, and high stability scanning frequencies can reduce the distorting effects of motion. When the scanning frequency is stable, the acquired point cloud data are distributed more uniformly in time, and the geometric structure of the environment can be restored more accurately.

Obstacle detection and tracking: the stable scanning frequency enables the lidar to better detect and track moving obstacles. The continuous and stable scanning can capture the motion trail and change of the obstacle, and has important roles in the applications of robot navigation, obstacle avoidance and the like.

Therefore, the stability of the scanning frequency in the laser radar is directly related to the accuracy and quality of the topographic map construction, and the stable scanning frequency can improve the resolution of point cloud data, reduce registration errors and the influence of motion distortion and is beneficial to the detection and tracking of obstacles.

S32: the acquisition mode of the scanning frequency stability coefficient of the laser radar is as follows:

s321: acquiring scanning frequencies of laser radars in different time periods within T timeT represents the number of the angular resolutions of the lidar at different time periods within the T time, t=1, 2, 3, 4, … …, n being a positive integer;

it should be noted that the scanning frequency can be measured by the following methods:

observation point cloud data: point cloud data is acquired using a lidar, and then the scan frequency is calculated by analyzing the data. The laser radar emits a plurality of laser beams when scanning, and the laser beams are reflected back at different time points to form point cloud data. By analyzing the time stamp information in the point cloud data, a reference point or object is selected, a plurality of positions thereof in the point cloud are observed, the time required for the distance change between the positions is calculated, and then the scanning frequency is calculated by the measured time difference.

Or using external sensors: the scanning frequency of the lidar is measured by using an external sensor. For example, a photoresistor or photosensor may be used to detect the number of passes of the laser beam through the sensor, synchronize the external sensor with the lidar, and record the signal received by the sensor to calculate the scanning frequency.

S322: calculating average value of laser radar scanning frequency of different time periods in T timeThe calculation formula is as follows:

s323: mean value of laser radar scanning frequency according to different time periods in T timeLaser radar scanning frequency->The scan frequency stability factor SPWx is calculated as follows:

s4: and (3) carrying out data analysis processing on the resolution stabilizing coefficient REWx of the acquired satellite image acquired in the step (S1) and the satellite link bandwidth stabilizing coefficient DKWx to generate a satellite image accuracy evaluation index WTJp.

S5: and (3) carrying out data analysis processing on the frame rate stability coefficient HZWx and the sharpness stability coefficient HRWx of the aerial camera acquired in the step (S2) to generate an aerial photographic precision evaluation index HSJp.

S6: and (3) carrying out data analysis processing on the angle resolution stability coefficient JFWx and the scanning frequency stability coefficient SPWx of the laser radar obtained in the step (S3) to generate a laser radar precision evaluation index LDJp.

S7: the satellite image precision evaluation index WTJp, the aerial photography precision evaluation index HSJp and the laser radar precision evaluation index LDJp are respectively compared with a satellite image precision evaluation threshold value YWTJ, an aerial photography precision evaluation threshold value YHSJ and a laser radar precision evaluation threshold value YLDJ, and whether the acquired satellite image, aerial photography image and laser radar data are credible or not is judged: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and carrying out feature extraction, integration and fusion on different data sources (satellite images, aerial photographic images and laser radar data) to generate a high-precision topographic map based on multi-source mapping data; otherwise, the image and data information acquired in the mapping process are not all credible, and different early warning signals are sent out according to the precision evaluation index which is not in the precision evaluation threshold range.

Further, S4: and (3) carrying out data analysis processing on the resolution stabilizing coefficient REWx of the acquired satellite image and the satellite link bandwidth stabilizing coefficient DKWx acquired in the step (S1) to generate a satellite image precision evaluation index WTJp according to the following calculation formula:

It should be noted that, in the above formula, e1 and e2 are respectively the resolution stability coefficient REWx of the satellite image and the preset scaling factor of the satellite link bandwidth stability coefficient DKWx, and＞/>> 0, e1+e2=1.63, C1 is a constant correction coefficient.

Further, S5: and (3) carrying out data analysis processing on the frame rate stability coefficient HZWx and the sharpness stability coefficient HRWx of the aerial camera acquired in the step (S2) to generate an aerial photographic precision evaluation index HSJp according to the following calculation formula:

it should be noted that, in the above formula, f1 and f2 are respectively the frame rate stability coefficient HZWx of the aerial camera and the preset scaling factor of the sharpness stability coefficient HRWx of the aerial camera, and＞/>f1+f2=1.27, and C2 is a constant correction coefficient.

Further, S6: and (3) carrying out data analysis processing on the angle resolution stability coefficient JFWx and the scanning frequency stability coefficient SPWx of the laser radar obtained in the step (S3) to generate a laser radar precision evaluation index LDJp according to the following calculation formula:

in the above formula, g1 and g2 are respectively the angular resolution stability coefficient JFWx of the lidar, the preset scaling factor of the scanning frequency stability coefficient SPWx of the lidar, and g2 is more than 0 and less than or equal to 1.15.

Further, when WTJp is not more than YWTJ and HSJp is not more than YHSJ and YWTJ is not more than YLDJ, it is explained that all the acquired satellite image, aerial photography image and laser radar data are reliable, and feature extraction is further performed on the acquired different data sources: for satellite images, information of different ground object types (such as roads, buildings, vegetation and the like) can be extracted by using a remote sensing image classification algorithm, for aerial photography images, ground object elevation information can be extracted by using an image matching and parallax algorithm, and for laser radar data, ground object three-dimensional coordinates and elevations can be extracted by using point cloud information; integrating and fusing the extracted characteristic information of different data sources of the satellite image, the aerial photography image and the laser radar data: geographic coordinates of different data sources can be converted into a unified reference coordinate system by using a topographic map registration algorithm, and then characteristic information of each data source is overlapped and combined to generate a comprehensive topographic map containing various types of ground features and elevation information; and finally, carrying out edge smoothing processing on the generated comprehensive topographic map, filling a blank area, and removing overlapping information to obtain a high-precision topographic map based on multi-source mapping data.

Further, when WTJp is larger than YWTJ or/and HSJp is larger than YHSJ or/and YWTJ is larger than YLDJ, the obtained satellite image or/and aerial photography image or/and laser radar data are not credible and sent to an early warning module, and satellite image risk signals or/and aerial photography image risk signals or/and laser radar data risk signals are sent out, so that a worker can conveniently debug and overhaul a satellite remote sensing system or/and an aerial camera or/and a laser radar system in real time. For example: when WTJp is larger than YWTJ, HSJp is smaller than or equal to YHSJ and YWTJ is smaller than or equal to YLDJ, the obtained satellite image is not credible, the aerial photography image and the laser radar data are sent to a pre-warning module, and satellite image risk signals are sent, so that a worker can conveniently debug and overhaul a satellite remote sensing system in real time. Also for example: when WTJp is larger than YWTJ and HSJp is larger than YHSJ and YWTJ is larger than YLDJ, the obtained satellite image, aerial photography image and laser radar data are all unreliable, and are sent to the early warning module to send out satellite image risk signals, aerial photography image risk signals and laser radar data risk signals, so that workers can conveniently debug and overhaul the satellite remote sensing system, the aerial photography camera or the laser radar system in real time.

The present invention further provides a high-precision topography generation system based on multi-source mapping data, comprising:

the satellite image precision influence parameter acquisition module is used for acquiring a resolution stabilizing coefficient REWx of a satellite image and a satellite link bandwidth stabilizing coefficient DKWx;

the aerial photography image precision influence parameter acquisition module is used for acquiring a frame rate stability coefficient HZWx and a sharpness stability coefficient HRWx of the aerial photography camera;

the laser radar data precision influence parameter acquisition module is used for acquiring an angular resolution stability coefficient JFWx and a scanning frequency stability coefficient SPWx of the laser radar;

the data analysis processing module comprises a first data analysis processing module, a second data analysis processing module and a third data analysis processing module; the first data analysis processing module performs data analysis processing on the resolution stabilizing coefficient REW of the satellite image and the satellite link bandwidth stabilizing coefficient DKWx acquired by the satellite image precision influence parameter acquisition module to generate a satellite image precision evaluation index WTJp; the second data analysis processing module performs data analysis processing on the frame rate stability coefficient HZWx and the sharpness stability coefficient HRWx of the aerial camera acquired by the aerial photographic image precision influence parameter acquisition module to generate an aerial photographic precision evaluation index HSJp; the third data analysis processing module performs data analysis processing on the angular resolution stability coefficient JFWx and the scanning frequency stability coefficient SPWx of the laser radar acquired by the laser radar data precision influence parameter acquisition module to generate a laser radar precision evaluation index LDJp;

The comprehensive analysis processing module is used for comparing the satellite image precision evaluation index WTJp, the aerial photography precision evaluation index HSJp and the laser radar precision evaluation index LDJp generated by the data analysis processing module with a satellite image precision evaluation threshold YWTJ, an aerial photography precision evaluation threshold YHSJ and a laser radar precision evaluation threshold YLDJ respectively and judging whether the acquired satellite image, aerial photography image and laser radar data are credible or not: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and carrying out feature extraction, integration and fusion on different data sources (satellite images, aerial photographic images and laser radar data) to generate a high-precision topographic map based on multi-source mapping data; otherwise, the image and the data information acquired in the mapping process are not all trusted and are sent to the early warning module;

and the early warning module sends out different early warning signals according to the precision evaluation indexes which are not in the precision evaluation threshold range.

The invention has the beneficial effects that:

according to the method, the resolution stability coefficient and the satellite link bandwidth stability coefficient of a satellite image are obtained in the satellite remote sensing monitoring process for the first time, the frame rate stability coefficient and the sharpness stability coefficient of an aerial camera are obtained in the unmanned aerial vehicle large-scale aerial photography process, the angle resolution stability coefficient and the scanning frequency stability coefficient of a laser radar are obtained in the laser radar data acquisition process, the satellite image precision evaluation index, the aerial photography precision evaluation index and the laser radar precision evaluation index are further generated, the reliability of the satellite image, the aerial photography image and the laser radar data information is determined by comparing different precision evaluation indexes with different precision evaluation thresholds, and when all data sources are all reliable, a topographic map is generated in a summarizing mode, so that the horizontal precision, the outline precision and the elevation precision of the topographic map are remarkably improved, and the precision of the topographic map is improved in an omnibearing mode.

Meanwhile, for an unreliable data source, different risk signals (satellite images or/and aerial photographic images or/and laser radar data risk signals) are sent out, so that error generation of low-precision topographic maps is avoided, meanwhile, a worker can conveniently debug and overhaul a satellite remote sensing system or/and an aerial photographic camera or/and a laser radar system in real time, the reason of precision errors of topographic maps caused in the mapping process is rapidly eliminated, and the precision of subsequent mapping data and the precision of subsequent regenerated topographic maps are improved.

Drawings

In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only of the invention and that other drawings can be obtained from them without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a high-precision topographic map generating method based on multi-source mapping data according to the present invention;

FIG. 2 is a block diagram of a high-precision topography generation system based on multi-source mapping data in accordance with the present invention.

Description of the embodiments

The present invention will be further described in detail with reference to specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.

It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", etc. are used merely to indicate relative positional relationships, which may also be changed when the absolute position of the object to be described is changed.

The invention provides a high-precision topographic map generating method based on multisource mapping data, which is characterized in that different precision influence parameters in the mapping process, including satellite image precision influence parameters, aerial photography image precision influence parameters and laser radar data precision influence parameters, are acquired, further data analysis processing is carried out, satellite image precision evaluation indexes, aerial photography precision evaluation indexes and laser radar precision evaluation indexes are generated, and the acquired satellite image, aerial photography image and laser radar data are judged whether to be reliable or not by comparing the different precision evaluation indexes with different precision evaluation thresholds: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and carrying out feature extraction, integration and fusion on different data sources (satellite images, aerial photographic images and laser radar data) to generate a high-precision topographic map based on multi-source mapping data; otherwise, the image and data information acquired in the mapping process are not all credible, and different early warning signals are sent out according to the precision evaluation index which is not in the precision evaluation threshold range; the method comprises the following steps:

image transfer speed: the bandwidth stability of the satellite link directly affects the speed of image transmission, and if the bandwidth is unstable, the transmission process may be affected by delay or interruption, thereby causing the image transmission to be slow or interrupted

Failure, which may result in loss or incompleteness of image data, degrading the accuracy and quality of the image;

s221: obtaining aerial camera sharpness for different time periods within a T timeT denotes the numbers of the image capturing acuteness of different periods in T time, t=1, 2, 3, 4, … …, nIs a positive integer;

s311: obtaining angular resolution of lidar for different periods of time within a T-timeT represents the number of the angular resolutions of the lidar at different time periods within the T time, t=1, 2, 3, 4, … …, n being a positive integer; />

s4: and (3) carrying out data analysis processing on the resolution stabilizing coefficient REWx of the acquired satellite image and the satellite link bandwidth stabilizing coefficient DKWx acquired in the step (S1) to generate a satellite image precision evaluation index WTJp according to the following calculation formula:

in the above formula, e1 and e2 are satellite images respectivelyA resolution stabilizing coefficient REWx, a preset proportional coefficient of a satellite link bandwidth stabilizing coefficient DKWx, and＞/>> 0, e1+e2=1.63, C1 is a constant correction coefficient.

S5: and (3) carrying out data analysis processing on the frame rate stability coefficient HZWx and the sharpness stability coefficient HRWx of the aerial camera acquired in the step (S2) to generate an aerial photographic precision evaluation index HSJp according to the following calculation formula:

S6: and (3) carrying out data analysis processing on the angle resolution stability coefficient JFWx and the scanning frequency stability coefficient SPWx of the laser radar obtained in the step (S3) to generate a laser radar precision evaluation index LDJp according to the following calculation formula:

/>

S7: the satellite image precision evaluation index WTJp, the aerial photography precision evaluation index HSJp and the laser radar precision evaluation index LDJp are respectively compared with a satellite image precision evaluation threshold value YWTJ, an aerial photography precision evaluation threshold value YHSJ and a laser radar precision evaluation threshold value YLDJ, and whether the acquired satellite image, aerial photography image and laser radar data are credible or not is judged: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and carrying out feature extraction, integration and fusion on different data sources (satellite images, aerial photographic images and laser radar data) to generate a high-precision topographic map based on multi-source mapping data; otherwise, the image and data information acquired in the mapping process are not all credible, and different early warning signals are sent out according to the precision evaluation index which is not in the precision evaluation threshold range; specifically:

When WTJp is smaller than or equal to YWTJ, HSJp is smaller than or equal to YHSJ, and YWTJ is smaller than or equal to YLDJ, the obtained satellite image, aerial photography image and laser radar data are all trusted, and feature extraction is further carried out on different obtained data sources: for satellite images, information of different ground object types (such as roads, buildings, vegetation and the like) can be extracted by using a remote sensing image classification algorithm, for aerial photography images, ground object elevation information can be extracted by using an image matching and parallax algorithm, and for laser radar data, ground object three-dimensional coordinates and elevations can be extracted by using point cloud information; integrating and fusing the extracted characteristic information of different data sources of the satellite image, the aerial photography image and the laser radar data: geographic coordinates of different data sources can be converted into a unified reference coordinate system by using a topographic map registration algorithm, and then characteristic information of each data source is overlapped and combined to generate a comprehensive topographic map containing various types of ground features and elevation information; and finally, carrying out edge smoothing processing on the generated comprehensive topographic map, filling a blank area, and removing overlapping information to obtain a high-precision topographic map based on multi-source mapping data.

When WTJp is larger than YWTJ or/and HSJp is larger than YHSJ or/and YWTJ is larger than YLDJ, the obtained satellite image or/and aerial photographic image or/and laser radar data are not credible and are sent to an early warning module, and satellite image risk signals or/and aerial photographic image risk signals or/and laser radar data risk signals are sent out, so that a worker can conveniently debug and overhaul a satellite remote sensing system or/and an aerial camera or/and a laser radar system in real time. For example: when WTJp is larger than YWTJ, HSJp is smaller than or equal to YHSJ and YWTJ is smaller than or equal to YLDJ, the obtained satellite image is not credible, the aerial photography image and the laser radar data are sent to a pre-warning module, and satellite image risk signals are sent, so that a worker can conveniently debug and overhaul a satellite remote sensing system in real time. Also for example: when WTJp is larger than YWTJ and HSJp is larger than YHSJ and YWTJ is larger than YLDJ, the obtained satellite image, aerial photography image and laser radar data are all unreliable, and are sent to the early warning module to send out satellite image risk signals, aerial photography image risk signals and laser radar data risk signals, so that workers can conveniently debug and overhaul the satellite remote sensing system, the aerial photography camera or the laser radar system in real time.

The present invention also provides a high-precision topography map generation system based on multi-source mapping data of another embodiment, comprising:

The comprehensive analysis processing module is used for comparing the satellite image precision evaluation index WTJp, the aerial photography precision evaluation index HSJp and the laser radar precision evaluation index LDJp generated by the data analysis processing module with a satellite image precision evaluation threshold YWTJ, an aerial photography precision evaluation threshold YHSJ and a laser radar precision evaluation threshold YLDJ respectively and judging whether the acquired satellite image, aerial photography image and laser radar data are credible or not: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and carrying out feature extraction, integration and fusion on different data sources (satellite images, aerial photographic images and laser radar data) to generate a high-precision topographic map based on multi-source mapping data; specifically:

when WTJp is smaller than or equal to YWTJ, HSJp is smaller than or equal to YHSJ, and YWTJ is smaller than or equal to YLDJ, the obtained satellite image, aerial photography image and laser radar data are all trusted, and feature extraction is further carried out on different obtained data sources: for satellite images, information of different ground object types (such as roads, buildings, vegetation and the like) can be extracted by using a remote sensing image classification algorithm, for aerial photography images, ground object elevation information can be extracted by using an image matching and parallax algorithm, and for laser radar data, ground object three-dimensional coordinates and elevations can be extracted by using point cloud information; integrating and fusing the extracted characteristic information of different data sources of the satellite image, the aerial photography image and the laser radar data: geographic coordinates of different data sources can be converted into a unified reference coordinate system by using a topographic map registration algorithm, and then characteristic information of each data source is overlapped and combined to generate a comprehensive topographic map containing various types of ground features and elevation information; finally, carrying out edge smoothing on the generated comprehensive topographic map, filling a blank area, and removing overlapping information to obtain a high-precision topographic map based on multi-source mapping data;

Otherwise, the image and the data information acquired in the mapping process are not all trusted and are sent to the early warning module; specifically:

when WTJp is larger than YWTJ or/and HSJp is larger than YHSJ or/and YWTJ is larger than YLDJ, the obtained satellite image or/and aerial photographic image or/and laser radar data are not credible, and the satellite image or/and aerial photographic image or/and laser radar data are sent to an early warning module;

the early warning module sends out different early warning signals according to the precision evaluation indexes which are not in the precision evaluation threshold range; specifically:

when WTJp is larger than YWTJ or/and HSJp is larger than YHSJ or/and YWTJ is larger than YLDJ, the early warning module sends out satellite image risk signals or/and aerial photography image risk signals or/and laser radar data risk signals, so that a worker can conveniently debug and overhaul a satellite remote sensing system or/and an aerial camera or/and a laser radar system in real time.

The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is merely a channel underwater topography change analysis system and method logic function division, and other divisions may be implemented in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application, but to enable any modification, equivalent or improvement to be made without departing from the spirit and principles of the application.

Claims

1. A high-precision topographic map generating method based on multisource mapping data is characterized by comprising the following steps of: different precision influence parameters in the mapping process are acquired, wherein the satellite image precision influence parameters comprise a resolution stability coefficient of a satellite image and a satellite link bandwidth stability coefficient, the aerial photography image precision influence parameters comprise a frame rate stability coefficient and a sharpness stability coefficient of an aerial camera, the laser radar data precision influence parameters comprise an angular resolution stability coefficient and a scanning frequency stability coefficient of a laser radar, the data analysis processing is further carried out, satellite images, aerial photography and laser radar precision evaluation indexes are generated, and the acquired satellite images, aerial photography images and laser radar data are judged whether to be reliable or not by comparing the different precision evaluation indexes with different precision evaluation thresholds: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and performing feature extraction, integration and fusion to generate a high-precision topographic map based on multi-source mapping data; the method comprises the following steps:

S1: collecting satellite image precision influence parameters: in the satellite remote sensing monitoring process, obtaining a resolution stabilizing coefficient REWx of a satellite image and a satellite link bandwidth stabilizing coefficient DKWx;

s2: acquiring aerial photography image precision influence parameters: in the process of large-scale aerial photography of the unmanned aerial vehicle, acquiring a frame rate stability coefficient HZWx and a sharpness stability coefficient HRWx of the aerial camera;

s3: collecting laser radar data precision influence parameters: acquiring an angular resolution stability coefficient JFWx and a scanning frequency stability coefficient SPWx of the laser radar in the process of acquiring data by the laser radar;

s4: performing data analysis processing on the resolution stabilizing coefficient REWx of the acquired satellite image acquired in the S1 and the satellite link bandwidth stabilizing coefficient DKWx to generate a satellite image accuracy evaluation index WTJp;

s5: performing data analysis processing on the frame rate stabilizing coefficient HZWx and the sharpness stabilizing coefficient HRWx of the aerial camera acquired in the step S2 to generate an aerial photographic precision evaluation index HSJp;

s6: performing data analysis processing on the angle resolution stability coefficient JFWx and the scanning frequency stability coefficient SPWx of the laser radar obtained in the step S3 to generate a laser radar precision evaluation index LDJp;

s7: the satellite image precision evaluation index WTJp, the aerial photography precision evaluation index HSJp and the laser radar precision evaluation index LDJp are respectively compared with a satellite image precision evaluation threshold value YWTJ, an aerial photography precision evaluation threshold value YHSJ and a laser radar precision evaluation threshold value YLDJ, and whether the acquired satellite image, aerial photography image and laser radar data are credible or not is judged: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and carrying out feature extraction, integration and fusion on different data sources of satellite images, aerial photographic images and laser radar data to generate a high-precision topographic map based on multi-source mapping data; otherwise, the image and data information acquired in the mapping process are not all credible, and different early warning signals are sent out according to the precision evaluation index which is not in the precision evaluation threshold range.

2. The high-precision topographic map generating method based on multisource mapping data according to claim 1, wherein S1: collecting satellite image precision influence parameters: in the satellite remote sensing monitoring process, a resolution stability coefficient REWx of a satellite image and a satellite link bandwidth stability coefficient DKWx are obtained, specifically:

；

s122: satellite link bandwidth through different time periods within T timeThe satellite link bandwidth stability coefficient DKWx is calculated according to the following calculation formula:

3. The high-precision topographic map generating method based on multisource mapping data according to claim 1, wherein S2: acquiring aerial photography image precision influence parameters: in the unmanned aerial vehicle large-scale aerial photography process, the frame rate stability coefficient HZWx and the sharpness stability coefficient HRWx of the aerial camera are obtained, and the method specifically comprises the following steps:

S212：calculating average value of frame rate of aerial camera in different time periods in T timeThe calculation formula is as follows:

；

s213: average value of frame rate of aerial camera according to different time periods in T timeFrame rate of aerial photography camera head +.>The frame rate stability factor HZWx is calculated as follows:

；

s221: obtaining aerial camera sharpness for different time periods within a T timeT represents the numbers of the imaging sharpness of different periods in the T time, t=1, 2, 3, 4, … …, n being a positive integer;

s222: calculating average sharpness of aerial camera at different time intervals in T time The calculation formula is as follows:

；

s223: average value of sharpness of aerial camera according to different time periods in T timeSharpness of aerial camera>The sharpness stabilization factor HRWx is calculated as follows:

4. the high-precision topographic map generating method based on multisource mapping data according to claim 1, wherein S3: collecting laser radar data precision influence parameters: in the process of acquiring data by the laser radar, acquiring an angular resolution stability coefficient JFWx and a scanning frequency stability coefficient SPWx of the laser radar, wherein the method specifically comprises the following steps:

；

s313: mean value of laser radar angular resolution according to different time periods in T timeAngular resolution of lidarThe angular resolution stability factor JFWx is calculated as follows:

；

s323: mean value of laser radar scanning frequency according to different time periods in T timeLaser radar scanning frequencyThe scan frequency stability factor SPWx is calculated as follows:

5. the high-precision topographic map generating method based on multisource mapping data according to claim 1, wherein S4: and (3) carrying out data analysis processing on the resolution stabilizing coefficient REWx of the acquired satellite image and the satellite link bandwidth stabilizing coefficient DKWx acquired in the step (S1) to generate a satellite image precision evaluation index WTJp according to the following calculation formula:

；

in the above, e1 and e2 are respectively the resolution stability coefficient REWx of the satellite image and the preset proportionality coefficient DKWx of the satellite link bandwidth stability coefficient, and＞/>> 0, e1+e2=1.63, C1 is a constant correction coefficient.

6. The high-precision topographic map generating method based on multisource mapping data according to claim 1, wherein S5: and (3) carrying out data analysis processing on the frame rate stability coefficient HZWx and the sharpness stability coefficient HRWx of the aerial camera acquired in the step (S2) to generate an aerial photographic precision evaluation index HSJp according to the following calculation formula:

；

In the above, f1 and f2 are respectively the frame rate stability coefficient HZWx of the aerial camera and the preset scaling factor of the sharpness stability coefficient HRWx of the aerial camera, and＞/>f1+f2=1.27, and C2 is a constant correction coefficient.

7. The high-precision topographic map generating method based on multisource mapping data according to claim 1, wherein S6: and (3) carrying out data analysis processing on the angle resolution stability coefficient JFWx and the scanning frequency stability coefficient SPWx of the laser radar obtained in the step (S3) to generate a laser radar precision evaluation index LDJp according to the following calculation formula:

；

in the above formula, g1 and g2 are respectively the angular resolution stability coefficient JFWx of the laser radar and the preset proportionality coefficient SPWx of the scanning frequency stability coefficient of the laser radar, and g2 is more than 0 and less than or equal to 1.15.

8. The method for generating the high-precision topographic map based on the multi-source mapping data according to claim 1, wherein if all precision evaluation indexes are within a precision evaluation threshold range, the method indicates that all the acquired images and data information in the mapping process are reliable, and performs feature extraction, integration and fusion on different data sources of satellite images, aerial photographic images and laser radar data to generate the high-precision topographic map based on the multi-source mapping data; otherwise, the image and data information acquired in the mapping process are not all credible, and different early warning signals are sent according to the precision evaluation index which is not in the precision evaluation threshold range, specifically:

When WTJp is less than or equal to YWTJ, HSJp is less than or equal to YHSJ and YWTJ is less than or equal to YLDJ, the obtained satellite image, aerial photography image and laser radar data are all trusted, feature extraction is further carried out on different data sources of the obtained satellite image, aerial photography image and laser radar data, geographic coordinates of the different data sources are converted into a unified reference coordinate system by using a topographic map registration algorithm, then feature information of each data source is overlapped and combined, edge smoothing is carried out, blank areas are filled, overlapping information is removed, and a high-precision topographic map based on multi-source mapping data is generated;

when WTJp is larger than YWTJ or/and HSJp is larger than YHSJ or/and YWTJ is larger than YLDJ, the obtained satellite image or/and aerial photography image or/and laser radar data are not credible, the satellite image or/and aerial photography image or/and laser radar data are sent to an early warning module, and a satellite image risk signal or/and aerial photography image risk signal or/and laser radar data risk signal is sent.

9. A generation method according to any one of claims 1-8 applied to a high-precision topography generation system based on multi-source mapping data, comprising:

The comprehensive analysis processing module is used for comparing the satellite image precision evaluation index WTJp, the aerial photography precision evaluation index HSJp and the laser radar precision evaluation index LDJp generated by the data analysis processing module with a satellite image precision evaluation threshold YWTJ, an aerial photography precision evaluation threshold YHSJ and a laser radar precision evaluation threshold YLDJ respectively and judging whether the acquired satellite image, aerial photography image and laser radar data are credible or not: if all the precision evaluation indexes are in the precision evaluation threshold range, representing that all the acquired images and data information in the mapping process are reliable, and performing feature extraction, integration and fusion to generate a high-precision topographic map based on multi-source mapping data; otherwise, the image and the data information acquired in the mapping process are not all trusted and are sent to the early warning module;