Geographic information land surveying and mapping system based on dynamic unmanned aerial vehicle remote sensing surveying and mapping

Abstract

The invention discloses a geographic information land surveying and mapping system based on dynamic unmanned aerial vehicle remote sensing surveying and mapping, and belongs to the technical field. The geographic information land surveying and mapping system based on dynamic unmanned aerial vehicle remote sensing surveying and mapping comprises a route planning module, a surveying and mapping module and a model generation module. According to the invention, the problem that the measurement result has a large error due to the fact that the signal is easily shielded when the obstacle exists in the measurement environment in the prior art is solved, the error of the measurement result due to the fact that the signal is shielded by the obstacle is avoided, dynamic monitoring is realized, the accuracy and precision of the image are improved, and the readability and practicability of the image are enhanced; according to the method, the system and the device, the working efficiency is improved, the cost is reduced, image deformation caused by systematic and non-systematic factors can be eliminated or reduced, and the image is enabled to better conform to actual geographic space parameters, so that the reliability and the accuracy of surveying and mapping data are improved, and the generated three-dimensional model is enabled to be more accurate and better in surveying and mapping effect.

Description

Technical Field

[0001] The present invention relates to the technical field of land surveying and mapping, and specifically to a geographic information land surveying and mapping system based on dynamic UAV remote sensing surveying and mapping. Background Technique

[0002] Geographic information refers to information related to spatial geographical distribution, which represents the general term of numbers, texts, graphics, images, etc. of the inherent data, quality, distribution characteristics, connections and laws of surface objects and the environment. In urban and rural construction, land resource utilization, environmental protection and other work, land measurement and mapping of various maps must be carried out for planning and management. In geological exploration, mineral development, water conservancy, transportation and other construction, control surveying, mine surveying, route surveying and topographic map drawing must be carried out for geological general survey and the design and construction of various buildings.

[0003] A Chinese patent with the publication number CN117554979A discloses a geographic information surveying and mapping system and its method, including: a laser emission module, a signal processing module, a laser reception module, a scanning module, and a power supply module. The functions of the laser emission module and the laser reception module are to emit collimated laser beams and receive the returned laser beams. The function of the scanning module is to synchronously scan the emission beam and the receiving field direction. The function of the signal processing module is to calculate the regional distance image based on the obtained information. The function of the power supply module is to provide power supply for the hardware of other blocks; through the direct pulse laser ranging method in the digital situation, detection is carried out through the cooperation of the laser emission module, the laser reception module, and the scanning module, and object space opto-mechanical scanning is used for scanning imaging, and a rotating mirror is used for laser scanning, which improves the ranging accuracy and does not affect the accuracy of its angle measurement at the same time.

[0004] In the actual use process of the surveying and mapping system of the above patent, when measuring topographic data through laser beams, when there are obstacles in the measurement environment, the signal is easily blocked, resulting in a large error in the measurement result. Therefore, it does not meet the existing requirements, and for this reason, we propose a geographic information land surveying and mapping system based on dynamic UAV remote sensing surveying and mapping. Summary of the Invention

[0005] The purpose of the present invention is to provide a geographic information land surveying and mapping system based on dynamic UAV remote sensing surveying and mapping, which increases the observation range, avoids signal occlusion by obstacles, resulting in errors in measurement results, realizes dynamic monitoring, improves the accuracy and precision of images, enhances the readability and practicality of images, as well as improves work efficiency and reduces costs. By correcting the surveying and mapping images, image deformation caused by systematic and non-systematic factors can be eliminated or reduced, making it more in line with actual geographical space parameters, thereby improving the reliability and accuracy of surveying and mapping data, making the generated three-dimensional model more accurate, and the surveying and mapping effect better, and solving the problems raised in the above background technique.

[0006] To achieve the above object, the present invention provides the following technical solutions: A geographic information land surveying and mapping system based on dynamic UAV remote sensing surveying and mapping, comprising:

[0007] A route planning module, configured to obtain the topography and meteorology of the target area, and combine the topography and meteorology of the target area to plan a flight route;

[0008] A surveying and mapping module, configured to photograph the target area according to the optimized surveying and mapping route, and generate multi-view remote sensing images with overlap and tilt angles.

[0009] A model generation module, configured to integrate the remote sensing images taken along the surveying and mapping route, obtain and utilize the surveying and mapping images, correct the obtained surveying and mapping images using a deviation correction module, and generate a three-dimensional model with geographic coordinates and elevation information.

[0010] Preferably, the route planning module includes:

[0011] A data collection module, configured to collect topographic data of the target area and historical meteorological data of the target area;

[0012] A route generation module, configured to generate a UAV flight route using the spider wasp optimization algorithm according to the topographic data of the target area combined with meteorological data.

[0013] Preferably, the route generation module specifically includes:

[0014] Construct and optimize a deep learning model, input the collected historical meteorological data of the target area into the deep learning model for weather prediction, and obtain weather data during surveying and mapping;

[0015] Obtain the surveying and mapping map of the target area, determine the starting point and ending point of the UAV flight route, and generate the UAV flight route using the spider wasp optimization algorithm.

[0016] Preferably, the surveying and mapping module includes:

[0017] A route optimization module, configured to optimize the surveying and mapping section according to the flight path of the UAV and the current UAV position;

[0018] A data acquisition module, configured to control the UAV to collect remote sensing images of the target area according to the optimized flight route and preprocess the collected remote sensing images;

[0019] Preferably, the data acquisition module includes:

[0020] A data collection module, configured to control the UAV to collect remote sensing images of the target area according to the optimized flight route;

[0021] A data processing module for preprocessing the collected remote sensing images. The preprocessing includes: atmospheric correction, geometric correction, radiometric correction, and image registration. By preprocessing the remote sensing images, the accuracy and consistency of the image data can be ensured, and errors can be reduced.

[0022] Preferably, the deviation correction module includes:

[0023] A comparison module for comparing the mapping image with the remote sensing image of the target area captured by the UAV to obtain the correction deviation;

[0024] A data correction module for correcting the mapping image using the geometric correction model according to the correction deviation.

[0025] Preferably, the route optimization module specifically includes:

[0026] A section annotation module for obtaining the flight path of the UAV and the current UAV position, dividing the mapping area into several blocks according to the coverage boundary during UAV mapping, and respectively annotating the completed mapping blocks and the uncompleted mapping blocks on the mapping area map;

[0027] A section overlap module for counting the number of overlapping blocks in each section, normalizing the number of overlapping blocks, the total overlapping area, and the area covered during section mapping to obtain the overlap value of each section. When the overlap value is greater than or equal to the set overlap threshold, it is a repeated section;

[0028] A section replacement module for selecting the section with the minimum optimization value as the target section for section replacement when the overlap values of the alternative sections are all greater than or equal to the set overlap threshold.

[0029] Preferably, the optimization process of the route optimization module specifically includes:

[0030] Obtaining the flight path of the UAV and the current UAV position, dividing the mapping area into several blocks according to the coverage boundary during UAV mapping, and respectively annotating the completed mapping blocks and the uncompleted mapping blocks on the mapping area map;

[0031] Dividing the flight path into several sections, separately performing spatial overlay of each section with the blocks in the mapping map to obtain the overlapping blocks of each section and the overlapping area of each overlapping block;

[0032] Counting the number of overlapping blocks in each section, and summing up the overlapping areas of each overlapping block to obtain the total overlapping area;

[0033] Calculate the area covered during the surveying and mapping of each road section, normalize the number of overlapping blocks, the total overlapping area, and the area covered during the surveying and mapping of the road section, analyze the values obtained after the normalization process, and obtain the overlapping value of each road section;

[0034] When the overlapping value is greater than or equal to the set overlapping threshold, mark this road section as a duplicate road section;

[0035] Select the starting point and ending point of the flight for the duplicate road section, and use the genetic algorithm to generate several alternative road sections, thereby obtaining the alternative road sections for each duplicate road section;

[0036] Select any one of the duplicate road sections and analyze the overlapping value of its corresponding alternative road section. When there is an overlapping value less than the set overlapping threshold among the overlapping values of each alternative road section, select the alternative road section with the smallest overlapping value as the target road section, and replace the corresponding duplicate road section with the target road section;

[0037] When the overlapping values of each alternative road section are all greater than or equal to the set overlapping threshold, obtain the lengths of the duplicate road section and each alternative road section, and perform weighted calculation with their corresponding overlapping values to obtain the optimization value;

[0038] Select the road section with the smallest optimization value as the target road section, and replace the corresponding duplicate road section with the target road section. After replacement, the target road section is the optimized path, and control the drone to fly and survey according to its optimized path.

[0039] Preferably, the integration of the remote sensing images taken along the surveying route specifically includes:

[0040] Perform aerial triangulation on the remote sensing images to obtain the coordinate information of the primary remote sensing images, and splice each preprocessed primary remote sensing image according to the obtained coordinate information to obtain the spliced primary regional image;

[0041] Perform aerial triangulation on the preprocessed secondary remote sensing images to obtain the coordinate information of the secondary remote sensing images, and splice each preprocessed secondary remote sensing image according to the obtained coordinate information to obtain the spliced secondary regional image;

[0042] Perform fusion processing based on the primary regional image and the secondary regional image to obtain the remote sensing image of the target area;

[0043] Convert each pixel point in the primary regional image and the secondary regional image to the standard coordinate system for representation, where each coordinate point corresponds to a pixel point in the regional image;

[0044] Perform fusion processing according to the corresponding same coordinate points in the primary regional image and the secondary regional image to obtain the remote sensing image of the target area.

[0045] Preferably, the generation of the three-dimensional model with geographic coordinates and elevation information specifically includes:

[0046] Obtain the integrated remote sensing image of the target area, and analyze the obtained remote sensing image of the target area through the data processing center, and extract the boundaries, control points and ground object features of the remote sensing image of the target area;

[0047] Generate three-dimensional point cloud data of surface features from the remote sensing images of the target area from different perspectives through stereo matching;

[0048] Use the point cloud data combined with the coordinate points in the remote sensing image to generate a three-dimensional model with geographic coordinates and elevation information through inverse distance weighted interpolation method.

[0049] Compared with the prior art, the beneficial effects of the present invention are:

[0050] The present invention uses an unmanned aerial vehicle to take remote sensing images of the target area and uses the remote sensing images for surveying and mapping, increasing the observation range, avoiding signal occlusion by obstacles, causing errors in the measurement results, realizing dynamic monitoring, and making up for each other's advantages. It not only retains the spatial details of high-spatial-resolution remote sensing images, but also contains the rich spectral information of multi-spectral remote sensing images, so as to obtain an image with enhanced spatial resolution and spectral resolution at the same time, improving the accuracy and precision of the image, enhancing the readability and practicability of the image, as well as improving work efficiency and reducing costs. By correcting the surveying and mapping images, the image deformation caused by systematic and non-systematic factors can be eliminated or reduced, making it more in line with the actual geospatial parameters, thereby improving the reliability and accuracy of the surveying and mapping data, making the generated three-dimensional model more accurate and the surveying and mapping effect better. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a module schematic diagram of the geographic information land surveying and mapping system based on dynamic unmanned aerial vehicle remote sensing surveying and mapping of the present invention;

[0052] Figure 2 It is a flowchart of the geographic information land surveying and mapping system based on dynamic unmanned aerial vehicle remote sensing surveying and mapping of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0053] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0054] In order to solve the problem that in the existing actual use process, when measuring topographic data through a laser beam, when there are obstacles in the measurement environment, the signal is easily blocked, resulting in a large error in the measurement result, please refer to Figure 1 - Figure 2 , the following technical solutions are provided in this embodiment:

[0055] A geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping, including:

[0056] A route planning module, configured to obtain the topographic features and meteorology of a target area, and combine the topographic features and meteorology of the target area to plan a flight route;

[0057] A surveying and mapping module, configured to photograph the target area according to the optimized surveying and mapping route, and generate multi-view remote sensing images with overlap and tilt angles.

[0058] A model generation module, configured to integrate the remote sensing images taken by the surveying and mapping route, obtain a surveying and mapping image and use it, correct it using a deviation correction module, and generate a three-dimensional model with geographic coordinates and elevation information.

[0059] The route planning module includes:

[0060] A data collection module, configured to collect topographic feature data of the target area and historical meteorological data of the target area;

[0061] A route generation module, configured to generate a UAV flight route using the spider wasp optimization algorithm according to the topographic feature data of the target area combined with meteorological data.

[0062] The route generation module specifically includes:

[0063] Construct and optimize a deep learning model, input the historical meteorological data of the collected target area into the deep learning model for weather prediction, and obtain the weather data during surveying and mapping;

[0064] Obtain the surveying and mapping map of the target area, determine the starting point and ending point of the UAV flight route, and generate the UAV flight route using the spider wasp optimization algorithm.

[0065] The surveying and mapping module includes:

[0066] A route optimization module, configured to optimize the surveying and mapping section according to the flight path of the UAV and the current UAV position;

[0067] A data acquisition module, configured to control the UAV to collect remote sensing images of the target area according to the optimized flight route and preprocess the collected remote sensing images;

[0068] The data acquisition module includes:

[0069] A data acquisition module, which is used to control the drone to collect remote sensing images of the target area according to the optimized flight route;

[0070] A data processing module, which is used to preprocess the collected remote sensing images. The preprocessing includes: atmospheric correction, geometric correction, radiometric correction and image registration. By preprocessing the remote sensing images, the accuracy and consistency of the image data can be ensured, and errors can be reduced.

[0071] A deviation correction module, including:

[0072] A comparison module, which is used to compare the surveying and mapping images with the remote sensing images of the target area captured by the drone to obtain the correction deviation;

[0073] A data correction module, which is used to correct the surveying and mapping images according to the correction deviation by using the geometric correction model.

[0074] A route optimization module, specifically including:

[0075] A section annotation module, which is used to obtain the flight path of the drone and the current position of the drone, divide the surveying and mapping area into several blocks according to the coverage boundary during drone surveying and mapping, and mark the completed and uncompleted blocks on the surveying and mapping area map respectively;

[0076] A section overlap module, which is used to count the number of overlapping blocks in each section, normalize the number of overlapping blocks, the total overlapping area and the area covered during section surveying and mapping to obtain the overlap value of each section. When the overlap value is greater than or equal to the set overlap threshold, it is a repeated section;

[0077] A section replacement module, which is used to select the section with the smallest optimization value as the target section for section replacement when the overlap values of the alternative sections are all greater than or equal to the set overlap threshold.

[0078] The optimization process of the route optimization module specifically includes:

[0079] Obtain the flight path of the drone and the current position of the drone, divide the surveying and mapping area into several blocks according to the coverage boundary during drone surveying and mapping, and mark the completed and uncompleted blocks on the surveying and mapping area map respectively;

[0080] Divide the flight path into several sections, perform spatial overlay of each section with the blocks in the surveying and mapping map separately to obtain the overlapping blocks of each section and the overlapping area of each overlapping block;

[0081] Count the number of overlapping blocks in each section, and sum up the overlapping areas of each overlapping block to obtain the total overlapping area;

[0082] Calculate the area covered during the surveying and mapping of each road section, normalize the number of overlapping blocks, the total overlapping area, and the area covered during the surveying and mapping of the road section, analyze the values obtained after the normalization process, and obtain the overlapping value of each road section;

[0083] When the overlapping value is greater than or equal to the set overlapping threshold, mark this road section as a duplicate road section;

[0084] Select the starting point and ending point of the flight for the duplicate road section, and use the genetic algorithm to generate several alternative road sections, thereby obtaining the alternative road sections for each duplicate road section;

[0085] Select any one of the duplicate road sections and analyze the overlapping value of its corresponding alternative road section. When there is an overlapping value less than the set overlapping threshold among the overlapping values of each alternative road section, select the alternative road section with the smallest overlapping value as the target road section, and replace the corresponding duplicate road section with the target road section;

[0086] When the overlapping values of each alternative road section are all greater than or equal to the set overlapping threshold, obtain the lengths of the duplicate road section and each alternative road section, and perform weighted calculation with their corresponding overlapping values to obtain the optimization value;

[0087] Select the road section with the smallest optimization value as the target road section, and replace the corresponding duplicate road section with the target road section. After replacement, the target road section is the optimized path, and control the drone to fly and survey according to its optimized path.

[0088] Integrate the remote sensing images taken along the surveying route, specifically including:

[0089] Perform aerial triangulation on the remote sensing images to obtain the coordinate information of the primary remote sensing images, and perform stitching processing on each preprocessed primary remote sensing image according to the obtained coordinate information to obtain the stitched primary regional image;

[0090] Perform aerial triangulation on the preprocessed secondary remote sensing images to obtain the coordinate information of the secondary remote sensing images, and perform stitching processing on each preprocessed secondary remote sensing image according to the obtained coordinate information to obtain the stitched secondary regional image;

[0091] Perform fusion processing based on the primary regional image and the secondary regional image to obtain the remote sensing image of the target area;

[0092] Convert each pixel point in the primary regional image and the secondary regional image to the standard coordinate system for representation, where each coordinate point corresponds to a pixel point in the regional image;

[0093] Perform fusion processing according to the corresponding same coordinate points in the primary regional image and the secondary regional image to obtain the remote sensing image of the target area.

[0094] Generate a 3D model with geographic coordinates and elevation information, specifically including:

[0095] Obtain the integrated remote sensing image of the target area, and analyze the obtained remote sensing image of the target area through the data processing center, and extract the boundaries, control points, and ground object features of the remote sensing image of the target area;

[0096] Generate 3D point cloud data of the surface features from the remote sensing images of the target area from different perspectives through stereo matching;

[0097] Use the point cloud data combined with the coordinate points in the remote sensing image to generate a 3D model with geographic coordinates and elevation information through the inverse distance weighted interpolation method.

[0098] Working principle: When using the geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping of the present invention, according to Figure 1 and Figure 2 , it includes the following steps:

[0099] Step 1: Collect the topographic and geomorphic data of the target area and the historical meteorological data of the target area, and generate the UAV flight route by using the spider wasp optimization algorithm according to the topographic and geomorphic data of the target area combined with the meteorological data;

[0100] Step 2: Optimize the surveying and mapping section according to the flight path of the UAV and the current UAV position, and control the UAV to collect remote sensing images of the target area according to the optimized flight route and preprocess the collected remote sensing images;

[0101] Step 3: Integrate the remote sensing images taken along the surveying and mapping route to obtain the surveying and mapping image of the target area. By integrating the remote sensing images, the spatial resolution and spectral resolution of the image can be improved, the visual quality of the image can be enhanced, the macroscopic observation ability can be enhanced, dynamic monitoring can be realized, diversified detection means can be provided, and the data volume is large. Complementary advantages can be achieved, retaining both the spatial details of the high-spatial-resolution remote sensing image and the rich spectral information of the multi-spectral remote sensing image, so as to obtain an image with enhanced spatial resolution and spectral resolution at the same time;

[0102] Step 4: Compare the surveying and mapping image with the remote sensing image of the target area taken by the UAV to obtain the correction deviation, and correct the surveying and mapping image according to the correction deviation by using the geometric correction model. By correcting the surveying and mapping image, the accuracy and precision of the image can be improved, the readability and practicability of the image can be enhanced, and the work efficiency can be improved and the cost can be reduced. By correcting the surveying and mapping image, the image deformation caused by systematic and non-systematic factors can be eliminated or reduced, making it more in line with the actual geographical space parameters, thereby improving the reliability and accuracy of the surveying and mapping data, making the generated 3D model more accurate, and the surveying and mapping effect better;

[0103] Step 5: After the correction is completed, a three-dimensional model with geographical coordinates and elevation information is generated using the surveyed image, a surveyed graph is generated using the remote sensing image, and a three-dimensional model is generated using the surveyed graph, which can accurately describe the geographical information of the target area.

[0104] In summary, for the geographical information land surveying and mapping system based on dynamic UAV remote sensing surveying and mapping of the present invention, the remote sensing image of the target area is captured by the UAV and used for surveying and mapping, which increases the observation range and avoids signal occlusion by obstacles, resulting in errors in the measurement results. By integrating the remote sensing images, the spatial resolution and spectral resolution of the images are improved, dynamic monitoring is realized, diverse detection means are provided, and the data volume is large, so that advantages can be taken to make up for deficiencies. It not only retains the spatial details of the high-spatial-resolution remote sensing images but also includes the rich spectral information of the multi-spectral remote sensing images, thereby obtaining an image with enhanced spatial resolution and spectral resolution at the same time. By correcting the surveyed image, the accuracy and precision of the image are improved, the readability and practicability of the image are enhanced, and the work efficiency is increased and the cost is reduced. By correcting the surveyed image, the image distortion caused by systematic and non-systematic factors can be eliminated or reduced, making it more in line with the actual geographical space parameters, thereby improving the reliability and accuracy of the surveying and mapping data and making the generated three-dimensional model more accurate and the surveying and mapping effect better.

[0105] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "including:", "comprising" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0106] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made in these embodiments without departing from the principles and spirit of the present invention.

Claims

1. Geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping, characterized by: include: The route planning module is used to obtain the topography and weather of the target area, and plan the flight route based on the topography and weather of the target area; The surveying and mapping module is used to photograph the target area according to the optimized surveying and mapping route to generate multi-view remote sensing images with overlapping degrees and tilt angles; The model generation module is used to integrate the remote sensing images taken along the surveying route, obtain the surveying image and use it, obtain the surveying image and use the deviation correction module to correct it, and generate a three-dimensional model with geographic coordinates and elevation information.

2. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 1 is characterized by: The route planning module comprises: A data collection module is used to collect topographic data of the target area and historical meteorological data of the target area; The route generation module is used to generate the UAV flight route based on the topographic data of the target area combined with the meteorological data using the spider bee optimization algorithm.

3. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 1 is characterized by: The route generation module specifically includes: Build and optimize a deep learning model, input the collected historical meteorological data of the target area into the deep learning model for weather forecasting, and obtain the weather data during surveying and mapping; Obtain a survey map of the target area, determine the starting and ending points of the drone's flight route, and use the spider bee optimization algorithm to generate the drone's flight route.

4. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 1 is characterized by: The surveying and mapping module comprises: Route optimization module, used to optimize the surveying route according to the flight path of the drone and the current position of the drone; The data acquisition module is used to control the UAV to collect remote sensing images of the target area according to the optimized flight route and pre-process the collected remote sensing images.

5. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 4 is characterized by: The data acquisition module comprises: The data acquisition module is used to control the UAV to collect remote sensing images of the target area according to the optimized flight route; The data processing module is used to preprocess the collected remote sensing images. The preprocessing includes atmospheric correction, geometric correction, radiation correction and image registration. By preprocessing the remote sensing images, the accuracy and consistency of the image data can be ensured.

6. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 1 is characterized by: The deviation correction module comprises: A comparison module is used to compare the surveying image with the remote sensing image of the target area taken by the drone to obtain the correction deviation; The data correction module is used to correct the surveying and mapping images according to the correction deviation using the geometric correction model.

7. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 4 is characterized by: The route optimization module specifically includes: The road section marking module is used to obtain the flight path and current position of the drone, divide the survey area into several blocks according to the coverage boundary of the drone during surveying, and mark the blocks that have been surveyed and the blocks that have not been surveyed on the map of the survey area respectively; The road section overlap module is used to count the number of overlapping blocks of each road section, normalize the number of overlapping blocks, the total overlapping area and the area covered during the road section mapping to obtain the overlap value of each road section. When the overlap value is greater than or equal to the set overlap threshold, it is a repeated road section; The road section replacement module is used to select the road section with the smallest optimization value as the target road section for road section replacement when the overlap values ​​of the alternative road sections are all greater than or equal to the set overlap threshold.

8. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 7 is characterized by: The optimization process of the route optimization module specifically includes: Obtain the flight path and current position of the drone, divide the survey area into several blocks according to the coverage boundary of the drone survey, and mark the blocks that have been surveyed and the blocks that have not been surveyed on the map of the survey area; The flight path is divided into several sections, and each section is spatially superimposed with the blocks in the surveying map to obtain the overlapping blocks of each section and the overlapping area of ​​each overlapping block; Count the number of overlapping blocks of each road section, and sum up the overlapping areas of each overlapping block to obtain the total overlapping area; Calculate the area covered by each road section during surveying and mapping, normalize the number of overlapping blocks, the total overlapping area, and the area covered by the road section during surveying and mapping, analyze the normalized values, and obtain the overlap value of each road section; When the overlap value is greater than or equal to the set overlap threshold, the road section is recorded as a repeated road section; Select the flight start point and flight end point of the repeated route, and use the genetic algorithm to generate several alternative routes, thereby obtaining alternative routes for each repeated route; Select any one of the repeated sections and analyze the overlap value of the corresponding alternative sections. When the overlap value of the alternative sections is less than the set overlap threshold, select the alternative section with the smallest overlap value as the target section, and replace the corresponding repeated section with the target section. When the overlap values ​​of the alternative sections are greater than or equal to the set overlap threshold, the lengths of the repeated section and the alternative sections are obtained, and weighted calculation is performed on the lengths and the corresponding overlap values ​​to obtain an optimized value; The section with the smallest optimization value is selected as the target section, and the target section replaces the corresponding repeated section. After the replacement, the target section is the optimized path, and the UAV is controlled to perform flight mapping according to its optimized path.

9. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 1 is characterized by: The integration of remote sensing images taken along the surveying route specifically includes: Performing aerial triangulation on the remote sensing image to obtain coordinate information of the primary remote sensing image, and splicing the pre-processed primary remote sensing images according to the obtained coordinate information to obtain a spliced ​​primary regional image; Performing aerial triangulation on the pre-processed secondary remote sensing images to obtain coordinate information of the secondary remote sensing images, and splicing the pre-processed secondary remote sensing images according to the obtained coordinate information to obtain a spliced ​​secondary regional image; Based on the fusion processing of the primary regional image and the secondary regional image, a remote sensing image of the target area is obtained; Each pixel point in the primary regional image and the secondary regional image is converted into a standard coordinate system for representation, wherein each coordinate point corresponds to a pixel point in the regional image; The corresponding fusion processing is performed according to the same coordinate points in the primary regional image and the secondary regional image to obtain the remote sensing image of the target area.

10. The geographic information land surveying and mapping system based on dynamic UAV remote sensing mapping according to claim 1 is characterized by: The generating of the three-dimensional model with geographic coordinates and elevation information specifically includes: Obtain the integrated remote sensing images of the target area, analyze the acquired remote sensing images of the target area through the data processing center, and extract the boundaries, control points and ground features of the remote sensing images of the target area; Generate three-dimensional point cloud data of surface features from remote sensing images of target areas at different viewing angles through stereo matching; The point cloud data is combined with the coordinate points in the remote sensing image to generate a three-dimensional model with geographic coordinates and elevation information through the inverse distance weighted interpolation method.

Images