CN118857278A - A method and system for surveying and mapping geographic information - Google Patents

Abstract

The application relates to a geographic information mapping method and a geographic information mapping system, which relate to the technical field of geographic information mapping, and the method comprises the following steps: formulating a flight path of the unmanned aerial vehicle platform based on the mapping task so that the total flight path of the unmanned aerial vehicle covers a target area of the mapping task; when the unmanned aerial vehicle flies and acquires image data based on the corresponding flight path, feedback adjustment is performed by detecting self-positioning information and gesture information, so that the quality of image acquisition is maintained when the unmanned aerial vehicle flies; and the mapping information processing device receives the image data returned by the unmanned aerial vehicle in real time to perform point cloud fusion, and recognizes the feature of the ground object to construct a geographical mapping model.

Description

A method and system for surveying and mapping geographic information

Technical Field

The present application relates to the technical field of geographic information surveying and mapping, and in particular to a geographic information surveying and mapping method and system.

Background Art

In the existing technology, geographic information mapping mainly relies on ground measurement, satellite remote sensing and manned aircraft aerial photography. These methods have the following shortcomings: ground measurement has a limited operating range and is difficult to cover complex terrain; satellite remote sensing has the advantage of large-area coverage, but its resolution and update frequency are limited; and manned aircraft aerial photography is expensive and has greater operating risks. With the popularity of drones, how to use drones to map geographic information is a technical problem that technicians in this field need to overcome.

Summary of the invention

In order to at least partially solve the above technical problems, the present application provides a geographic information surveying and mapping method and system.

In a first aspect, a geographic information surveying and mapping method provided in this application adopts the following technical solution.

A geographic information surveying and mapping method is applied to a surveying and mapping system, wherein the surveying and mapping system includes an unmanned aerial vehicle platform and a surveying and mapping information processing device; the geographic information surveying and mapping method includes:

Formulate a flight path of a drone of the drone platform based on the surveying and mapping task so that the total flight path of the drone covers the target area of the surveying and mapping task;

When the UAV flies based on the corresponding flight path and collects image data, it detects its own positioning information and attitude information to make feedback adjustments so that the UAV maintains the quality of image collection during flight;

The surveying and mapping information processing device receives the image data sent back by the drone in real time, performs point cloud fusion, identifies the features of the ground objects and constructs a geographic surveying and mapping model;

Among them, the drone makes feedback adjustments by detecting its own positioning information and attitude information, including:

Obtain the current attitude angle data from the inertial navigation unit and obtain the self-positioning information from the GIS system;

Calculate a first error value based on the expected attitude angle and the actual attitude angle, and calculate a second error value based on the expected positioning information and the actual positioning information;

Based on the first error value and the second error value, a total control output is obtained by using a PID control algorithm;

A first execution action is obtained based on the total control output; the first execution action includes adjusting the motor speed of the drone and changing the rudder angle.

Optionally, obtaining a total control output based on the first error value and the second error value through a PID control algorithm respectively includes:

For attitude control, set the first PID parameters; the first PID parameters include: pitch axis PID parameters, roll axis PID parameters and yaw axis PID parameters; the PID parameters include proportional, integral and differential parameters;

For position control, a second PID parameter is set; the second PID parameter includes a longitude PID parameter, a latitude PID parameter and an altitude PID parameter;

Calculate the integral, proportional and differential terms in the PID algorithm;

The integral term, proportional term and differential term of the pitch axis, roll axis and yaw axis are added to obtain the total output of attitude control;

The integral term, proportional term and differential term of longitude, latitude and altitude are added to obtain the total output of position control;

The total control output is obtained based on the total output of the attitude control and the total output of the position control.

Optionally, the flight path of the UAV is formulated based on the surveying and mapping task, including:

Conduct preliminary analysis of target areas with heavy surveying and mapping tasks through satellite images to clarify regional boundaries, terrain features and obstacle distribution;

Dividing the target area into a plurality of sub-areas according to the size, terrain characteristics and obstacle distribution of the target area;

Match several preliminary flight paths for the UAV based on sub-area division and obstacle distribution;

The preliminary flight path is optimized based on a particle swarm optimization algorithm to formulate a flight path for the UAV.

Optionally, optimizing the preliminary flight path based on a particle swarm optimization algorithm to formulate a flight path for the UAV includes:

A plurality of preliminary flight paths are represented by a plurality of particles; each particle represents a preliminary flight path;

The fitness f of each particle is evaluated based on the preset evaluation function; fitness f = w1*flight distance + w2*flight time - w3*coverage; w1, w2 and w3 are weight factors;

For each particle, if the fitness f is not less than the fitness f1 of the historical optimal solution, the particle with mass f is updated to the personal optimal solution;

Check the fitness of all particles and find the current global optimal solution as the flight path of the drone.

Optionally, the surveying and mapping information processing device receives the image data sent back by the drone in real time to perform point cloud fusion, identify the features of the ground objects and construct a geographic surveying and mapping model, including:

An image preprocessing algorithm is deployed in the UAV using edge computing technology to perform image preprocessing and send the preprocessed image to a surveying and mapping information processing device; the image preprocessing algorithm includes image denoising, brightness and color correction;

Surveying and mapping information processing device: extract feature points from each frame of image;

Match and triangulate feature points at different perspectives to obtain point cloud data;

Segmenting the point cloud data to distinguish different ground features; the ground features include buildings, vegetation, roads and water areas;

Extracting further features from the identified features of the ground object; the further features include: shape, texture and height information;

Constructing a three-dimensional geographic information model based on the point cloud data, ground features and three-dimensional modeling software;

The three-dimensional geographic information model is integrated with the attribute data of the GIS system to obtain a geographic mapping model.

In the second aspect, a geographic information surveying and mapping method provided in this application adopts the following technical solution.

A geographic information surveying and mapping system, characterized in that it comprises: an unmanned aerial vehicle platform and a surveying and mapping information processing device; wherein:

Formulate a flight path of a drone of the drone platform based on the surveying and mapping task so that the total flight path of the drone covers the target area of the surveying and mapping task;

When the UAV flies based on the corresponding flight path and collects image data, it detects its own positioning information and attitude information to make feedback adjustments so that the UAV maintains the quality of image collection during flight;

The surveying and mapping information processing device receives the image data sent back by the drone in real time, performs point cloud fusion, identifies the features of the ground objects and constructs a geographic surveying and mapping model;

Among them, the drone makes feedback adjustments by detecting its own positioning information and attitude information, including:

Obtain current attitude angle data from the inertial navigation unit and obtain self-positioning information from the GIS system;

Calculate a first error value based on the expected attitude angle and the actual attitude angle, and calculate a second error value based on the expected positioning information and the actual positioning information;

Based on the first error value and the second error value, a total control output is obtained by respectively using a PID control algorithm;

Based on the total control output, a first execution action is obtained; the first execution action includes adjusting the motor speed of the drone and changing the rudder angle,

Optionally, obtaining a total control output based on the first error value and the second error value through a PID control algorithm respectively includes:

For attitude control, the first PID parameters are set; the first PID parameters include: pitch axis PID parameters, roll axis PID parameters and yaw axis PID parameters; the PID parameters include proportional, integral and differential parameters;

For position control, second PID parameters are set; the second PID parameters include longitude PID parameters, latitude PID parameters and altitude PID parameters;

Calculate the integral term, proportional term and differential term in the PID algorithm;

The integral term, proportional term and differential term of the pitch axis, roll axis and yaw axis are added to obtain the total output of attitude control;

The integral term, proportional term and differential term of longitude, latitude and altitude are added to obtain the total output of position control;

The total control output is obtained based on the total output of the attitude control and the total output of the position control.

Optionally, the flight path of the UAV is formulated based on the surveying and mapping task, including:

Conduct preliminary analysis of target areas with heavy surveying and mapping tasks through satellite images to clarify regional boundaries, terrain features and obstacle distribution;

Dividing the target area into a plurality of sub-areas according to the size, terrain characteristics and obstacle distribution of the target area;

Match several preliminary flight paths for the UAV based on sub-area division and obstacle distribution;

The preliminary flight path is optimized based on a particle swarm optimization algorithm to formulate a flight path for the UAV.

In a third aspect, the present application discloses an electronic device, comprising a memory and a processor, wherein the memory stores a computer program that is loaded by the processor and executes any of the above methods.

In a fourth aspect, the present application discloses a computer-readable storage medium storing a computer program that can be loaded by a processor and execute any of the above methods.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a geographic information surveying and mapping method according to an embodiment of the present application;

FIG2 is a block diagram of a geographic information surveying and mapping system according to an embodiment of the present application;

In the figure, 201 is an unmanned aerial vehicle platform; 202 is a surveying and mapping information processing device.

DETAILED DESCRIPTION

The present application is further described below in conjunction with Figures 1-2 and specific embodiments:

First of all, it should be noted that in the description of this application, if the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside" and other directional words appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the drawings, which is only for the convenience of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of this application; in addition, if the terms "first", "second", "third" and other numerical quantifiers appear, they are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in this application, unless otherwise clearly specified and limited, if the terms "installed", "connected", and "connected" appear, they should be understood in a broad sense, for example, it can be a fixed connection, or a detachable connection, a limited connection such as an interference fit, a transition fit, or an integral connection; it can be directly connected or indirectly connected through an intermediate medium; therefore, for ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific circumstances.

The embodiment of the present application discloses a geographic information surveying and mapping method. Referring to FIG1 , as an implementation of a geographic information surveying and mapping method, the method is applied to a surveying and mapping system, wherein the surveying and mapping system includes an unmanned aerial vehicle platform and a surveying and mapping information processing device; the geographic information surveying and mapping method includes the following steps:

Step 101: formulate a flight path of a drone of the drone platform based on a surveying and mapping task so that the total flight path of the drone covers a target area of the surveying and mapping task.

Step 102: When the UAV flies based on the corresponding flight path and collects image data, feedback adjustment is performed by detecting its own positioning information and attitude information so that the UAV maintains the quality of image collection during flight.

Step 103: The surveying and mapping information processing device receives the image data sent back by the drone in real time, performs point cloud fusion, identifies the features of the ground objects, and constructs a geographic surveying and mapping model.

Among them, the drone makes feedback adjustments by detecting its own positioning information and attitude information, including:

Obtain the current attitude angle data from the inertial navigation unit and obtain the self-positioning information from the GIS system;

Calculate a first error value based on the expected attitude angle and the actual attitude angle, and calculate a second error value based on the expected positioning information and the actual positioning information;

Based on the first error value and the second error value, a total control output is obtained by using a PID control algorithm;

A first execution action is obtained based on the total control output; the first execution action includes adjusting the motor speed of the drone and changing the rudder angle.

Specifically, the UAV platform refers to an unmanned aerial vehicle system that is used to carry various sensors and navigation equipment. The UAV can fly autonomously according to the real-time set route, perform aerial flight missions and collect image data. The surveying and mapping information processing device is a ground station device that is responsible for receiving the image data sent back by the UAV, processing and analyzing it, and finally forming a useful geographic information surveying and mapping product. Point cloud fusion refers to matching the feature points in multiple images taken by the UAV, converting them into a set of points in three-dimensional space, and then integrating these point clouds through algorithms to construct a three-dimensional terrain surface model. PID control algorithm: that is, proportional-integral-differential control algorithm, which can automatically adjust the control output according to the difference between the set target value and the actual measurement value, so that the UAV can fly more smoothly. By setting the flight path of the UAV to ensure full coverage of the target area, the surveying and mapping efficiency is greatly improved compared with traditional manual or fixed point observation. During the flight, the UAV constantly compares the difference between the expected posture and the actual posture, the expected position and the actual position, and uses the PID algorithm to quickly make adjustments, so that the UAV can fly stably and the captured image data is more stable.

As a specific implementation of a geographic information surveying and mapping method, a total control output is obtained through a PID control algorithm based on the first error value and the second error value, including:

For attitude control, set the first PID parameters; the first PID parameters include: pitch axis PID parameters, roll axis PID parameters and yaw axis PID parameters; the PID parameters include proportional, integral and differential parameters;

For position control, a second PID parameter is set; the second PID parameter includes a longitude PID parameter, a latitude PID parameter and an altitude PID parameter;

Calculate the integral, proportional and differential terms in the PID algorithm;

The integral term, proportional term and differential term of the pitch axis, roll axis and yaw axis are added to obtain the total output of attitude control;

The integral term, proportional term and differential term of longitude, latitude and altitude are added to obtain the total output of position control;

The total control output is obtained based on the total output of the attitude control and the total output of the position control.

Specifically, for the three axes (pitch, roll, and yaw) of the drone, the proportional (P), integral (I), and differential (D) parameters are set respectively. For each axis, the proportional term (error value multiplied by the proportional coefficient), the integral term (accumulated past errors multiplied by time multiplied by the integral coefficient), and the differential term (error change rate multiplied by the differential coefficient) are calculated. The three terms of each axis are summed to obtain the total output of attitude control. Similarly, independent PID parameters are set for longitude, latitude, and altitude. According to the difference between the current position and the target position, the PID terms of longitude, latitude, and altitude are calculated. The control quantities of these three dimensions are added together to obtain the total output of position control, which guides the drone to move to the correct position or maintain the current position. Through the rapid response of attitude control, the attitude of the drone can be quickly adjusted even in the case of wind interference or operational errors, to avoid severe shaking and maintain the quality of image acquisition. Position control ensures that the drone can fly accurately along the preset path, and even in the face of complex terrain and environmental changes, the accuracy of the route can be maintained through continuous adjustment. By combining the total output of attitude control and position control, the UAV can cope with attitude deviation and position deviation at the same time, achieving a smoother and more stable flight trajectory, which is crucial for high-quality geographic information mapping, ensuring the continuity and integrity of image data, and thus obtaining good image quality.

As a specific implementation of a geographic information surveying and mapping method, the flight path of the drone is formulated based on a surveying and mapping task, including:

Conduct preliminary analysis of target areas with heavy surveying and mapping tasks through satellite images to clarify regional boundaries, terrain features and obstacle distribution;

Dividing the target area into a plurality of sub-areas according to the size, terrain characteristics and obstacle distribution of the target area;

Match several preliminary flight paths for the UAV based on sub-area division and obstacle distribution;

The preliminary flight path is optimized based on a particle swarm optimization algorithm to formulate a flight path for the UAV.

Specifically, high-resolution satellite images are used to identify the boundaries of the target area; based on the analysis results, the entire target area is subdivided into multiple sub-areas. The principle of division usually considers the manageability of the sub-areas, the similarity of the terrain, and avoiding dense obstacle areas, so that the UAV can complete the mapping task efficiently and safely. The size and shape of each sub-area will be flexibly adjusted according to the actual terrain complexity and obstacle distribution. For each sub-area, a preliminary flight path is designed based on its boundaries and internal obstacle layout to ensure that the UAV can effectively cover each sub-area. The particle swarm optimization algorithm is introduced to further optimize the preliminary designed flight path. The PSO algorithm simulates the foraging behavior of bird flocks in nature and searches for the optimal path in the solution space through a large number of "particles". Each particle represents a possible flight path. They continuously update the flight direction and speed according to their own historical best position and the global best position of the group, and gradually approach the global optimal solution. After multiple rounds of iterations, the particle swarm gradually converges and finds the path solution that maximizes the fitness function, which is the final flight path of the UAV. Through particle swarm optimization, the flight path can avoid obstacles to the greatest extent, reduce unnecessary detours and repeated coverage, shorten the overall flight time and reduce energy consumption.

As a specific implementation of a geographic information surveying and mapping method, a surveying and mapping information processing device receives image data sent back by the drone in real time to perform point cloud fusion, identify features of land objects and construct a geographic surveying and mapping model, including:

An image preprocessing algorithm is deployed in the UAV using edge computing technology to perform image preprocessing and send the preprocessed image to a surveying and mapping information processing device; the image preprocessing algorithm includes image denoising, brightness and color correction;

Surveying and mapping information processing device: extract feature points from each frame of image;

Match and triangulate feature points at different perspectives to obtain point cloud data;

Segmenting the point cloud data to distinguish different ground features; the ground features include buildings, vegetation, roads and water areas;

Extracting further features from the identified features of the ground object; the further features include: shape, texture and height information;

Constructing a three-dimensional geographic information model based on the point cloud data, ground features and three-dimensional modeling software;

The three-dimensional geographic information model is integrated with the attribute data of the GIS system to obtain a geographic mapping model.

Specifically, by deploying edge computing technology on drones for image preprocessing, such as denoising and brightness and color correction, the timeliness and bandwidth efficiency of data processing are significantly improved. The burden on the back-end server is reduced, ensuring high-quality image data transmission in low-bandwidth or high-latency communication environments. The surveying and mapping information processing device extracts feature points from each frame of the image, and matches and triangulates the feature points at different viewing angles. Through the intelligent segmentation of point cloud data, the system can effectively distinguish different land features such as buildings, vegetation, roads, and waters, and further extract their shape, texture, and height information. Combining point cloud data, fine land features, and advanced 3D modeling software, the system can construct an information-rich 3D geographic information model. The 3D model is integrated with the attribute data of the GIS system, so that the model has an accurate correspondence with the geographic location and can also associate various types of attribute information.

The present application also provides a geographic information surveying and mapping system, including: an unmanned aerial vehicle platform and a surveying and mapping information processing device; wherein,

Formulate a flight path of a drone of the drone platform based on the surveying and mapping task so that the total flight path of the drone covers the target area of the surveying and mapping task;

When the UAV flies based on the corresponding flight path and collects image data, it detects its own positioning information and attitude information to make feedback adjustments so that the UAV maintains the quality of image collection during flight;

The surveying and mapping information processing device receives the image data sent back by the drone in real time, performs point cloud fusion, identifies the features of the ground objects and constructs a geographic surveying and mapping model;

Among them, the drone makes feedback adjustments by detecting its own positioning information and attitude information, including:

Obtain the current attitude angle data from the inertial navigation unit and obtain the self-positioning information from the GIS system;

Calculate a first error value based on the expected attitude angle and the actual attitude angle, and calculate a second error value based on the expected positioning information and the actual positioning information;

Based on the first error value and the second error value, a total control output is obtained by using a PID control algorithm;

A first execution action is obtained based on the total control output; the first execution action includes adjusting the motor speed of the drone and changing the rudder angle.

As one implementation of a geographic information surveying and mapping method, a total control output is obtained by using a PID control algorithm based on the first error value and the second error value, including:

For attitude control, set the first PID parameters; the first PID parameters include: pitch axis PID parameters, roll axis PID parameters and yaw axis PID parameters; the PID parameters include proportional, integral and differential parameters;

For position control, a second PID parameter is set; the second PID parameter includes a longitude PID parameter, a latitude PID parameter and an altitude PID parameter;

Calculate the integral, proportional and differential terms in the PID algorithm;

The integral term, proportional term and differential term of the pitch axis, roll axis and yaw axis are added to obtain the total output of attitude control;

The integral term, proportional term and differential term of longitude, latitude and altitude are added to obtain the total output of position control;

The total control output is obtained based on the total output of the attitude control and the total output of the position control.

As one implementation of a geographic information surveying and mapping method, the flight path of the drone is formulated based on a surveying and mapping task, including:

Conduct preliminary analysis of target areas with heavy surveying and mapping tasks through satellite images to clarify regional boundaries, terrain features and obstacle distribution;

Dividing the target area into a plurality of sub-areas according to the size, terrain characteristics and obstacle distribution of the target area;

Match several preliminary flight paths for the UAV based on sub-area division and obstacle distribution;

The preliminary flight path is optimized based on a particle swarm optimization algorithm to formulate a flight path for the UAV.

The embodiment of the present application also discloses an electronic device.

Specifically, the device includes a memory and a processor, and the memory stores a computer program that can be loaded by the processor and execute any of the above-mentioned geographic information surveying and mapping methods.

The embodiment of the present application also discloses a computer-readable storage medium. Specifically, the computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned geographic information surveying and mapping methods, and the computer-readable storage medium includes, for example, a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

It should be noted that the above embodiments are only used to illustrate the present application and are not intended to limit the technical solutions described in the present application. Although the present application has been described in detail in this specification with reference to the above embodiments, a person of ordinary skill in the art should understand that a person of ordinary skill in the art can still modify or make equivalent substitutions to the present application, and all technical solutions and improvements thereof that do not depart from the spirit and scope of the present application should be included in the scope of the claims of the present application.

Claims (10)

1. A geographic information surveying and mapping method, characterized in that it is applied to a surveying and mapping system, wherein the surveying and mapping system includes an unmanned aerial vehicle platform and a surveying and mapping information processing device; the geographic information surveying and mapping method includes: Formulate a flight path of a drone of the drone platform based on the surveying and mapping task so that the total flight path of the drone covers the target area of the surveying and mapping task; When the UAV flies based on the corresponding flight path and collects image data, it detects its own positioning information and attitude information to make feedback adjustments so that the UAV maintains the quality of image collection during flight; The surveying and mapping information processing device receives the image data sent back by the drone in real time, performs point cloud fusion, identifies the features of the ground objects and constructs a geographic surveying and mapping model; Among them, the drone makes feedback adjustments by detecting its own positioning information and attitude information, including: Obtain current attitude angle data from the inertial navigation unit and obtain self-positioning information from the GIS system; Calculate a first error value based on the expected attitude angle and the actual attitude angle, and calculate a second error value based on the expected positioning information and the actual positioning information; Based on the first error value and the second error value, a total control output is obtained by respectively using a PID control algorithm; A first execution action is obtained based on the total control output; the first execution action includes adjusting the motor speed of the drone and changing the rudder angle. 2. A geographic information surveying and mapping method according to claim 1, characterized in that, based on the first error value and the second error value, a total control output is obtained by respectively using a PID control algorithm, comprising: For attitude control, the first PID parameters are set; the first PID parameters include: pitch axis PID parameters, roll axis PID parameters and yaw axis PID parameters; the PID parameters include proportional, integral and differential parameters; For position control, second PID parameters are set; the second PID parameters include longitude PID parameters, latitude PID parameters and altitude PID parameters; Calculate the integral term, proportional term and differential term in the PID algorithm; The integral term, proportional term and differential term of the pitch axis, roll axis and yaw axis are added to obtain the total output of attitude control; The integral term, proportional term and differential term of longitude, latitude and altitude are added to obtain the total output of position control; The total control output is obtained based on the total output of the attitude control and the total output of the position control. 3. A geographic information surveying and mapping method according to claim 2, characterized in that the flight path of the drone is formulated based on the surveying and mapping task, comprising: Conduct preliminary analysis of target areas with heavy surveying and mapping tasks through satellite images to clarify regional boundaries, terrain features and obstacle distribution; Dividing the target area into a plurality of sub-areas according to the size, terrain characteristics and obstacle distribution of the target area; Match several preliminary flight paths for the UAV based on sub-area division and obstacle distribution; The preliminary flight path is optimized based on a particle swarm optimization algorithm to formulate a flight path for the UAV. 4. A geographic information surveying and mapping method according to claim 3, characterized in that the preliminary flight path is optimized based on a particle swarm optimization algorithm to formulate the flight path of the UAV, comprising: A plurality of preliminary flight paths are represented by a plurality of particles; each particle represents a preliminary flight path; The fitness f of each particle is evaluated based on the preset evaluation function; fitness f = w1*flight distance + w2*flight time - w3*coverage; w1, w2 and w3 are weight factors; For each particle, if the fitness f is not less than the fitness f1 of the historical optimal solution, the particle with mass f is updated to the personal optimal solution; Check the fitness of all particles and find the current global optimal solution as the flight path of the drone. 5. A geographic information surveying and mapping method according to claim 4, characterized in that the surveying and mapping information processing device receives the image data sent back by the drone in real time to perform point cloud fusion, identify the features of the ground objects and construct a geographic surveying and mapping model, comprising: An image preprocessing algorithm is deployed in the UAV using edge computing technology to perform image preprocessing and send the preprocessed image to a surveying and mapping information processing device; the image preprocessing algorithm includes image denoising, brightness and color correction; Surveying and mapping information processing device: extract feature points from each frame of image; Match and triangulate feature points at different perspectives to obtain point cloud data; Segmenting the point cloud data to distinguish different ground features; the ground features include buildings, vegetation, roads and water areas; Extracting further features from the identified features of the ground object; the further features include: shape, texture and height information; Constructing a three-dimensional geographic information model based on the point cloud data, ground features and three-dimensional modeling software; The three-dimensional geographic information model is integrated with the attribute data of the GIS system to obtain a geographic mapping model. 6. A geographic information surveying and mapping system, characterized by comprising: an unmanned aerial vehicle platform and a surveying and mapping information processing device; wherein: Formulate a flight path of a drone of the drone platform based on the surveying and mapping task so that the total flight path of the drone covers the target area of the surveying and mapping task; When the UAV flies based on the corresponding flight path and collects image data, it detects its own positioning information and attitude information to make feedback adjustments so that the UAV maintains the quality of image collection during flight; The surveying and mapping information processing device receives the image data sent back by the drone in real time, performs point cloud fusion, identifies the features of the ground objects and constructs a geographic surveying and mapping model; Among them, the drone makes feedback adjustments by detecting its own positioning information and attitude information, including: Obtain current attitude angle data from the inertial navigation unit and obtain self-positioning information from the GIS system; Calculate a first error value based on the expected attitude angle and the actual attitude angle, and calculate a second error value based on the expected positioning information and the actual positioning information; Based on the first error value and the second error value, a total control output is obtained by respectively using a PID control algorithm; A first execution action is obtained based on the total control output; the first execution action includes adjusting the motor speed of the drone and changing the rudder angle. 7. A geographic information mapping system according to claim 6, characterized in that the overall control output is obtained by using a PID control algorithm based on the first error value and the second error value, respectively, comprising: For attitude control, the first PID parameters are set; the first PID parameters include: pitch axis PID parameters, roll axis PID parameters and yaw axis PID parameters; the PID parameters include proportional, integral and differential parameters; For position control, second PID parameters are set; the second PID parameters include longitude PID parameters, latitude PID parameters and altitude PID parameters; Calculate the integral term, proportional term and differential term in the PID algorithm; The integral term, proportional term and differential term of the pitch axis, roll axis and yaw axis are added to obtain the total output of attitude control; The integral term, proportional term and differential term of longitude, latitude and altitude are added to obtain the total output of position control; The total control output is obtained based on the total output of the attitude control and the total output of the position control. 8. A geographic information surveying and mapping system according to claim 7, characterized in that the flight path of the drone is formulated based on the surveying and mapping task, comprising: Conduct preliminary analysis of target areas with heavy surveying and mapping tasks through satellite images to clarify regional boundaries, terrain features and obstacle distribution; Dividing the target area into a plurality of sub-areas according to the size, terrain characteristics and obstacle distribution of the target area; Match several preliminary flight paths for the UAV based on sub-area division and obstacle distribution; The preliminary flight path is optimized based on a particle swarm optimization algorithm to formulate a flight path for the UAV. 9. An electronic device, characterized in that it comprises a memory and a processor, wherein the memory stores a computer program according to any one of the methods of claims 1 to 5 which is loaded and executed by the processor. 10. A computer-readable storage medium, characterized in that it stores a computer program that can be loaded by a processor and executes the method according to any one of claims 1 to 5.