Bursaphelenchus xylophilus withered tree remote sensing coordinate information acquisition and conversion method

Abstract

The invention discloses a pine wood nematode disease withered tree remote sensing coordinate information acquisition and conversion method, and belongs to the technical field of information conversion. The method comprises the following steps: step 1, accessing a pine forest data management database; 2, recognizing the dead standing tree based on the remote sensing image; step 3, coordinate matching; step 4, performing visual marking; and 5, coordinate information conversion: converting the remote sensing coordinate information into prevention and control task information according to the coordinate information and the pine forest data management database. According to the method, through the steps of recognizing the dead trees based on the remote sensing images and converting the coordinate information, the dead trees infected with the pine wood nematode disease are accurately positioned and recognized, then efficient and comprehensive dead tree information collection is achieved, and the problems that in the prior art, manual inspection efficiency is low, and omission is prone to occurring are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of information conversion, and particularly to a method for collecting and converting remote sensing coordinate information of standing dead trees affected by pine wilt disease. Background Art

[0002] Pine wilt disease is a devastating disease of pine forests. In traditional forest pest monitoring and control work, the positioning and information collection of standing dead trees affected by pine wilt disease often rely on manual inspections. Forestry workers need to shuttle through pine forest areas on foot, and rely on experience to check the health status of pine trees one by one and record information such as coordinates.

[0003] This method not only consumes a large amount of human, material and time costs, but also is prone to omissions during inspections when facing large areas of pine forests, resulting in some standing dead trees infected with pine wilt disease not being discovered in time, thus delaying the best control opportunity. Summary of the Invention

[0004] The embodiments of the present application solve the problems of low efficiency and easy omission in manual inspections in the prior art by providing a method for collecting and converting remote sensing coordinate information of standing dead trees affected by pine wilt disease, and achieve efficient and comprehensive collection of standing dead tree information.

[0005] The embodiments of the present application provide a method for collecting and converting remote sensing coordinate information of standing dead trees affected by pine wilt disease, including the following steps: Step 1, access the pine forest data management database; Step 2, identify standing dead trees based on remote sensing images: obtain the remote sensing spectral image of the target pine forest area, identify and locate the standing dead trees and dying trees infected with pine wilt disease from the remote sensing spectral image, and obtain the remote sensing coordinate information corresponding to the standing dead trees and dying trees; Step 3, coordinate matching: perform spatial matching and registration of all remote sensing coordinate information with the geographic base map to obtain the drawn remote sensing scan map; Step 4, visual marking: visually mark the standing dead trees and dying trees on the remote sensing scan map; Step 5, coordinate information conversion: according to the coordinate information and the pine forest data management database, convert the remote sensing coordinate information into prevention and control task information, including triggering spraying prevention and control tasks by using the remaining coordinates of other pine trees except the coordinates of standing dead trees and dying trees as the points to be sprayed; The steps of the spraying prevention and control task include: Step A1: aggregate the points to be sprayed into several operation blocks with the elevation deviation less than the first threshold and the planar distance less than the second threshold as constraints; Step A2: solve the shortest connected path for all the points to be sprayed within each operation block; Step A3: Taking the centroid coordinates of the operation block as nodes, use the ant colony algorithm to generate a block operation sequence with the global minimum time cost; Step A4: Output the block operation sequence as a set of waypoint instructions executable by the drone.

[0006] Furthermore, the pine forest data management database includes pine tree numbers, pine tree locations, and historical inspection information; The pine tree location refers to the longitude and latitude information of the current pine tree and the felled pine tree; The historical inspection information refers to the results of the staff's inspection of the pine trees, including health, injury type, and treatment history.

[0007] Furthermore, the identification method of the standing dead trees is as follows: Calculate the normalized difference vegetation index and excess green index based on the multispectral image, generate a binary mask image according to the double-threshold condition, and screen out low-activity pixels; Perform morphological closing operations on continuous low-activity pixel clusters to fill holes, and extract the minimum bounding rectangles of each cluster; Take the center point of the rectangle as the initial pixel coordinates of the standing dead tree, and generate a set of longitude and latitude coordinates through geographic projection conversion.

[0008] Furthermore, the identification method of the dying trees is as follows: Analyze the vegetation index and red-edge position offset based on the multispectral image, obtain the vegetation index threshold range and red-edge offset threshold, and screen out suspected targets with the vegetation index in the degradation interval and the red-edge offset exceeding the limit; Extract the texture features of the suspected targets, including the entropy of the gray-level co-occurrence matrix and the fractal dimension, obtain the texture entropy threshold and fractal dimension threshold, and retain the target pine trees that meet both spectral and texture anomalies; Convert the pixel coordinates of the screened target pine trees into longitude and latitude coordinates in the geographic coordinate system through affine transformation; Using the longitude and latitude coordinates as the index key, query the pine forest data management database to obtain the historical injury dataset of the target pine trees, including injury type coding, injury severity, and cumulative treatment duration; Obtain the infection risk value, and mark the target pine trees with the infection risk value not less than the infection risk threshold as dying trees, and output their longitude and latitude coordinates and infection risk values.

[0009] Furthermore, the infection risk value formula is: ; where R is the infection risk value, is the weight value, , is the historical injury severity, is the cumulative treatment duration after time-dependent attenuation processing, is the time decay factor, is the planar distance from the target pine tree to the nearest diseased tree.

[0010] Furthermore, the specific steps for spatially matching and registering all remote sensing coordinate information with the geographic base map to obtain the drawn remote sensing scan map are as follows: Use the forest digital elevation model and the vector small class boundary map as the geographic base map; Convert the remote sensing coordinate information set of standing dead trees and dying trees into the coordinates of the geographic base map: , is the rotation and scaling matrix, is the translation vector, and are the longitude and latitude of the coordinates in the geographic map, and are the longitude and latitude in the remote sensing coordinate information; Optimize the matrix parameters through the measured coordinates of the ground control points; Fuse the coordinates on the optimized geographic map with the forest digital elevation model to generate a three-dimensional remote sensing scan map.

[0011] Furthermore, the visualization marking of standing dead trees and dying trees on the remote sensing scan map specifically refers to: Mark the coordinate points of standing dead trees on the remote sensing scan map with a colored circular frame. The diameter of the circular frame is proportional to the crown size, and mark the coordinate values of the standing dead trees on the remote sensing scan map; Mark the coordinate points of dying trees on the remote sensing scan map with a colored double-layer circular frame. The outer diameter of the double-layer circular frame is a fixed number of pixels, and the inner ring is filled with transparency that is positively correlated with the infection risk value. Mark the coordinate values and infection risk values of the dying trees on the remote sensing scan map.

[0012] Furthermore, the conversion of remote sensing coordinate information into prevention and control task information also includes: Generate task work orders according to the coordinate point types and attributes of the visualization markings: The coordinates of standing dead trees trigger the felling task. The standing dead tree task work order includes: positioning coordinates, stump treatment requirements, associated small class numbers; The coordinates of dying trees trigger the injection task. The dying tree task work order includes: positioning coordinates, injection requirements.

[0013] Furthermore, the formula for obtaining the shortest connected path is: ; Among them, is the operation block number, is the total number of points to be sprayed within the operation block, and are the numbers of points to be sprayed within the operation block, A binary decision variable for path decision-making, , is the time cost of wind direction.

[0014] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By the step of identifying standing dead trees based on remote sensing images and converting coordinate information, the standing dead trees infected with pine wilt disease can be accurately located and identified, thereby achieving efficient and comprehensive collection of standing dead tree information, effectively solving the problems of low efficiency and easy omission in manual inspection in the prior art.

[0015] 2. By using technologies such as calculating the normalized difference vegetation index and the excess green index from multispectral images to identify standing dead trees, the accuracy and objectivity of standing dead tree identification are improved. By deeply analyzing features such as the vegetation index and the offset of the red edge position to screen for dying trees, the scope and degree of diseased pine trees can be determined more accurately.

[0016] 3. By spatially matching and registering the remote sensing coordinate information with the geographic base map and visualizing the markings, the distribution of standing dead trees and dying trees infected with pine wilt disease in the pine forest can be intuitively displayed, and by converting the coordinate information into prevention and control task information, targeted prevention and control task allocation can be achieved. Description of the Drawings

[0017] Figure 1 is a flow chart of the method for collecting and converting remote sensing coordinate information of standing dead trees infected with pine wilt disease provided by the embodiments of the present application. Detailed Embodiments

[0018] The embodiments of the present application provide a method for collecting and converting remote sensing coordinate information of standing dead trees infected with pine wilt disease, which solves the problems of low efficiency and easy omission in manual inspection in the prior art. By the step of identifying standing dead trees based on remote sensing images and converting coordinate information, the standing dead trees infected with pine wilt disease can be accurately located and identified, thereby achieving efficient and comprehensive collection of standing dead tree information.

[0019] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the drawings of the specification and specific embodiments.

[0020] As Figure 1 shown, the embodiments of the present application provide a method for collecting and converting remote sensing coordinate information of standing dead trees infected with pine wilt disease. The method includes the following steps: Step 1, accessing the pine forest data management database; Step 2, identifying standing dead trees based on remote sensing images: obtaining the remote sensing spectral image of the target pine forest area, identifying and locating the standing dead trees and dying trees infected with pine wilt disease from the remote sensing spectral image, and obtaining the remote sensing coordinate information corresponding to the standing dead trees and dying trees; Step 3, Coordinate matching: Spatially match and register all remote sensing coordinate information with the geographic base map to obtain the drawn remote sensing scan map; Step 4, Visual marking: Visually mark the standing dead trees and dying trees on the remote sensing scan map; Step 5, Coordinate information conversion: According to the coordinate information and the pine forest data management database, convert the remote sensing coordinate information into prevention and control task information, including using the remaining pine tree coordinates other than the standing dead tree coordinates and dying tree coordinates as the points to be sprayed to trigger the spraying prevention and control task; The steps of the spraying prevention and control task include: Step A1: Aggregate the points to be sprayed into several operation blocks with the constraint that the elevation deviation is less than the first threshold and the planar distance is less than the second threshold; Step A2: Solve the shortest connected path for all the points to be sprayed within each operation block; Step A3: Use the ant colony algorithm to generate a global minimum time-cost block operation sequence with the centroid coordinates of the operation block as nodes; Step A4: Output the block operation sequence as a waypoint instruction set executable by the drone, including three-dimensional coordinates and spraying parameters.

[0021] Further, the pine forest data management database includes pine tree numbers, pine tree locations, and historical inspection information; The pine tree location refers to the longitude and latitude information of the current pine tree and the felled pine tree; The historical inspection information refers to the results of the staff's inspection of the pine trees, including health, injury types, and treatment history.

[0022] Further, the identification method of the standing dead trees is: Calculate the normalized difference vegetation index and excess green index based on the multispectral image, generate a binary mask image according to the double-threshold condition, and screen out the low-activity pixels; Perform morphological closing operation on the continuous low-activity pixel clusters to fill the holes, and extract the minimum bounding rectangles of each cluster; The steps of performing morphological closing operation on the continuous low-activity pixel clusters to fill the holes include: Step 1: Construct a circular structuring element , whose diameter satisfies , 、 are the pixel mapping values of the minimum and maximum crown diameters of the pine trees; Step 2: Traverse the mask image with the structuring element , and perform on the target pixel ; Expand the boundary of the pixel cluster outward to fill the internal hole gaps; Step 3: Use the same structuring element for the dilated image Perform ; Contract the expanded boundary to the original cluster geometric contour; Step 4: Extract the connected regions after closing operation and filter out the noise points with an area smaller than the minimum projected area of a single pine tree; Take the center point of the rectangle as the initial pixel coordinates of the standing dead tree, and generate a set of longitude and latitude coordinates through geographic projection transformation.

[0023] For the identification technology of standing dead trees, in the early stage, it mainly relied on simple visual interpretation of remote sensing images. Staff judged whether it was a standing dead tree by observing the spectral feature changes of pine trees on the remote sensing images with the naked eye. However, this method is highly subjective and greatly affected by the technical level and experience differences of personnel, and it is difficult to guarantee the identification accuracy. Moreover, relying solely on spectral information, it is very difficult to accurately distinguish standing dead trees in the face of complex forest environments and diverse vegetation types, and it is easy to misjudge other normal pine trees or vegetation with similar spectral features as standing dead trees, making the subsequent prevention and control work lack pertinence.

[0024] By using technologies such as calculating the normalized difference vegetation index and the excess green index from multi-spectral images to identify standing dead trees, the accuracy and objectivity of standing dead tree identification have been improved. By deeply analyzing features such as vegetation index and red-edge position offset to screen out dying trees, the scope and degree of diseased pine trees can be determined more accurately, effectively solving the problems of low identification accuracy of standing dead trees and dying trees and being easily interfered by subjective factors in the existing technology.

[0025] Furthermore, the method for identifying dying trees is as follows: Based on multi-spectral image analysis of vegetation index and red-edge position offset, obtain the vegetation index threshold range and red-edge offset threshold, and screen out the suspected targets with the vegetation index in the degradation interval and the red-edge offset exceeding the limit; Extract the texture features of the suspected targets, including gray-level co-occurrence matrix entropy and fractal dimension, obtain the texture entropy threshold and fractal dimension threshold, and retain the target pine trees that simultaneously meet the spectral and texture anomalies; Convert the pixel coordinates of the screened target pine trees into longitude and latitude coordinates in the geographic coordinate system through affine transformation; Using this longitude and latitude coordinate as the index key, query the pine forest data management database to obtain the historical injury datasets of the target pine trees, including injury type codes, injury severity, and cumulative treatment duration; Obtain the infection risk value, and mark the target pine trees with the infection risk value not less than the infection risk threshold as dying trees, and output their longitude and latitude coordinates and infection risk values.

[0026] Furthermore, the formula for the infection risk value is: ; Among them, R is the infection risk value, is the weight value, , is the historical injury severity, is the cumulative treatment duration after time decay processing, is the time decay factor, is the planar distance from the target pine tree to the nearest diseased tree.

[0027] Calculate the historical injury severity : ; Among them, is the injury type weight, , is the th number of days of injury persistence, m is the total number of injuries, is the maximum effective statistical period; Perform time decay processing on the cumulative treatment duration to obtain : ; Among them, is the treatment time decay coefficient, e is the natural constant; Retrieve the positions and felling times of the felled diseased trees within the coordinate radius , calculate the planar distance from the target pine tree to the nearest diseased tree, and the time decay factor , is the number of months since the felling of the nearest diseased tree.

[0028] Furthermore, the specific steps for spatially matching and registering all remote sensing coordinate information with the geographic base map to obtain the drawn remote sensing scan map are as follows: Use the forest digital elevation model and the vector small class boundary map as the geographic base map; Convert the remote sensing coordinate information set of standing dead and dying trees into the coordinates of the geographic base map: , is the rotation and scaling matrix, is the translation vector, and are the longitude and latitude of the coordinates in the geographic map, and are the longitude and latitude in the remote sensing coordinate information; Optimize the matrix parameters through the measured coordinates of the ground control points; Fuse the coordinates on the optimized geographic map with the forest digital elevation model to generate a three-dimensional remote sensing scan map.

[0029] Further, the visual marking of standing dead trees and dying trees on the remote sensing scan map specifically refers to: Marking the coordinate points of standing dead trees on the remote sensing scan map with color circular frames, where the diameter of the circular frame is proportional to the crown size, and marking the coordinate values of the standing dead trees on the remote sensing scan map; Marking the coordinate points of dying trees on the remote sensing scan map with color double-layer circular frames, where the outer diameter of the double-layer circular frame is a fixed number of pixels, and the inner ring is filled with a transparency that is positively correlated with the infection risk value, and the transparency , and marking the coordinate values and infection risk values of the dying trees on the remote sensing scan map.

[0030] Further, the conversion of remote sensing coordinate information into prevention and control task information specifically includes: Generating task work orders according to the coordinate point types and attributes of the visual marking: The coordinate of the standing dead tree triggers a felling task, and the standing dead tree task work order includes: positioning coordinates, requirements for stump treatment, and associated sub-compartment numbers; The coordinate of the dying tree triggers an injection task, and the dying tree task work order includes: positioning coordinates, injection requirements , is the average injection requirement, is the infection risk value.

[0031] In the link of converting coordinate information into prevention and control task information, the traditional method lacks a systematic and intelligent processing process. Usually, manually based on a small amount of coordinate information collected, combined with experience, roughly plan the prevention and control task areas and measures. This approach cannot fully consider factors such as the overall distribution of pine forests, the specific disease conditions of individual pine trees, and the geographical environment, resulting in unreasonable allocation of prevention and control tasks. For example, the prevention and control efforts in some severely diseased areas are insufficient, while there may be over-prevention in relatively healthy areas, wasting prevention and control resources and affecting the prevention and control effect.

[0032] By spatially matching and registering the remote sensing coordinate information with the geographical base map and visually marking, thereby intuitively showing the distribution of standing dead trees and dying trees caused by pine wilt disease in the pine forest, and by converting the coordinate information into prevention and control task information, thus realizing targeted allocation of prevention and control tasks, effectively solving the problem in the prior art that the conversion of coordinate information into prevention and control tasks is unreasonable and cannot fully consider various factors.

[0033] Further, the formula for obtaining the shortest connected path is: ; where is the operation block number, is the total number of points to be sprayed within the operation block, and are the numbers of points to be sprayed within the operation block, is a binary decision variable for path decision-making, , indicating that each point to be sprayed has exactly one entrance, indicating that each point to be sprayed has exactly one exit, is the wind direction time cost, , is the weight, , is the surface distance from the point to be sprayed to , is the elevation cost from the point to be sprayed to , is the wind direction time cost from the point to be sprayed to , , is the angle between the flight direction and the wind direction, is the wind resistance coefficient, is the calibrated speed of the UAV.

[0034] In summary, the embodiments of the present application identify standing dead trees based on remote sensing images and perform coordinate information conversion, thereby accurately locating and identifying standing dead trees infected with pine wilt disease, and further realizing efficient and comprehensive collection of standing dead tree information.

[0035] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0036] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementing in the process Figure 1 one process or multiple processes and / or blocks Figure 1means for the functions specified in one or more blocks.

[0037] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction means which implements the functions specified in one Figure 1 or more processes and / or blocks Figure 1 or more blocks.

[0038] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one Figure 1 or more processes and / or blocks Figure 1 or more blocks.

[0039] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to cover the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0040] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. Remote sensing coordinate information acquisition and conversion method for standing dead trees infected with Bursaphelenchus xylophilus, characterized in that It includes the following steps: Step 1, access the pine forest data management database; Step 2, identify dead standing trees based on remote sensing images: Obtain the remote sensing spectral images of the target pine forest area, identify and locate the dead standing trees and dying trees infected with pine wood nematode disease from the remote sensing spectral images, and obtain the remote sensing coordinate information corresponding to the dead standing trees and dying trees; Step 3, coordinate matching: Perform spatial matching and registration of all remote sensing coordinate information with the geographic base map to obtain the drawn remote sensing scan map; Step 4, visual marking: Visually mark the dead standing trees and dying trees on the remote sensing scan map; Step 5, coordinate information conversion: According to the coordinate information and the pine forest data management database, convert the remote sensing coordinate information into prevention and control task information, including using the remaining pine tree coordinates other than the dead standing tree coordinates and dying tree coordinates as the points to be sprayed to trigger the spraying prevention and control task; The steps of the said spraying prevention and control task include: Step A1: Aggregate the points to be sprayed into several operation blocks with the constraint that the elevation deviation is less than the first threshold and the planar distance is less than the second threshold; Step A2: Solve the shortest connected path for all the points to be sprayed within each operation block; Step A3: Use the ant colony algorithm to generate a block operation sequence with the minimum global time cost with the center coordinates of the operation block as nodes; Step A4: Output the block operation sequence as a waypoint instruction set executable by the drone.

2. The method for collecting and converting remote sensing coordinate information of dead standing trees infected with Bursaphelenchus xylophilus according to claim 1, wherein, The said pine forest data management database includes pine tree numbers, pine tree locations, and historical inspection information; The said pine tree location refers to the longitude and latitude information of the current pine tree and the felled pine tree; The said historical inspection information refers to the results of the staff's inspection of the pine trees, including health, injury types, and treatment history.

3. The method for collecting and converting remote sensing coordinate information of standing dead trees infected with Bursaphelenchus xylophilus according to claim 1, characterized in that, The identification method of the said dead standing trees is: Calculate the normalized difference vegetation index and excess green index based on the multispectral image, generate a binary mask image according to the double-threshold condition and screen out the low-activity pixels; Perform morphological closing operation on the continuous low-activity pixel clusters to fill the holes and extract the minimum bounding rectangles of each cluster; Take the center point of the rectangle as the initial pixel coordinates of the dead standing tree, and generate a longitude and latitude coordinate set through geographic projection conversion.

4. The method for collecting and converting remote sensing coordinate information of dead standing trees infected with Bursaphelenchus xylophilus according to claim 3, wherein, The identification method of the said dying trees is: Analyze the vegetation index and red edge position offset based on the multispectral image, obtain the vegetation index threshold range and red edge offset threshold, and screen out the suspected targets with the vegetation index in the degradation interval and the red edge offset exceeding the limit; Extract the texture features of the suspected targets, including gray-level co-occurrence matrix entropy and fractal dimension, obtain the texture entropy threshold and fractal dimension threshold, and retain the target pine trees that simultaneously meet the spectral and texture anomalies; Convert the pixel coordinates of the screened target pine trees into longitude and latitude coordinates in the geographic coordinate system through affine transformation; Use the longitude and latitude coordinates as the index key to query the pine forest data management database to obtain the historical injury dataset of the target pine trees, including injury type codes, injury severity, and cumulative treatment duration; Obtain the infection risk value, and mark the target pine trees with the infection risk value not less than the infection risk threshold as dying trees, and output their longitude and latitude coordinates and infection risk values.

5. The method for collecting and converting remote sensing coordinate information of dead standing trees infected with Bursaphelenchus xylophilus as described in claim 4, wherein The infection risk value formula is as follows: ; where R is the infection risk value, is the weight value, , is the severity of historical injuries, is the cumulative treatment duration after time decay processing, is the time decay factor, is the planar distance from the target pine tree to the nearest diseased tree.

6. The method for collecting and converting remote sensing coordinate information of dead standing trees infected with Bursaphelenchus xylophilus according to claim 1, wherein The specific steps of performing spatial matching and registration of all remote sensing coordinate information with the geographic base map to obtain the drawn remote sensing scan map are: Use the digital elevation model of the forest area and the vector small-class boundary map as the geographic base map; Convert the remote sensing coordinate information set of standing dead trees and dying trees into the coordinates of the geographic base map: , is the rotation and scaling matrix, is the translation vector, and are the longitude and latitude of the coordinates in the geographic map, and are the longitude and latitude in the remote sensing coordinate information; Optimize the matrix parameters through the measured coordinates of the ground control points; Fuse the coordinates on the optimized geographic map with the digital elevation model of the forest area to generate a three-dimensional remote sensing scan map.

7. The method for collecting and converting remote sensing coordinate information of dead standing trees infected with Bursaphelenchus xylophilus according to claim 1, wherein The visualization marking of standing dead trees and dying trees on the remote sensing scan map specifically refers to: Mark the coordinate points of standing dead trees on the remote sensing scan map with a colored circular frame, the diameter of the circular frame is proportional to the crown size, and mark the coordinate values of the standing dead trees on the remote sensing scan map; Mark the coordinate points of dying trees on the remote sensing scan map with a double-layer colored circular frame, the outer diameter of the double-layer circular frame is a fixed pixel, the inner ring is filled with transparency positively correlated with the infection risk value, and mark the coordinate values and infection risk values of the dying trees on the remote sensing scan map.

8. The method for collecting and converting remote sensing coordinate information of dead standing trees infected with Bursaphelenchus xylophilus according to claim 7, characterized in that, The conversion of the remote sensing coordinate information into prevention and control task information also includes: Generate a task work order according to the type and attributes of the coordinate points of the visualization marking: The coordinate of the standing dead tree triggers the felling task, and the standing dead tree task work order includes: positioning coordinates, stump treatment requirements, associated small-class numbers; The coordinate of the dying tree triggers the injection task, and the dying tree task work order includes: positioning coordinates, injection requirements.

9. The method for collecting and converting remote sensing coordinate information of dead standing trees infected with Bursaphelenchus xylophilus according to claim 8, characterized in that, The acquisition formula for the shortest connected path is: ； Among them, is the operation block number, is the total number of spraying points to be sprayed within the operation block, and are the numbers of spraying points to be sprayed within the operation block, is the binary decision variable for path decision-making, , is the wind direction time cost.

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