Unmanned aerial vehicle deployment method and device, electronic equipment and storage medium

Abstract

The invention relates to an unmanned aerial vehicle deployment method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring digital elevation model data of a target drainage basin; according to the digital elevation model data, performing catchment unit division on the target drainage basin to obtain a plurality of catchment units; taking the geographic center of each catchment unit as a monitoring demand point of the unmanned aerial vehicle; obtaining an ecological environment field observation station in the target drainage basin; taking an ecological environment field observation station as a candidate facility point of the unmanned aerial vehicle; establishing a position set coverage model; and inputting the monitoring demand points and the candidate facility points into the position set coverage model, and obtaining the position coordinates of each target facility point, thereby optimizing the deployment position of the unmanned aerial vehicle, ensuring that the unmanned aerial vehicle covers all the monitoring demand points in a complex three-dimensional environment of the watershed, and improving the comprehensiveness and effectiveness of watershed monitoring.

Description

Technical Field

[0001] The present application relates to the field of drone technology, and in particular to a drone deployment method, device, electronic device, and storage medium. Background Art

[0002] With the rapid development of drone technology, its application in environmental monitoring, disaster warning and ecological protection is becoming more and more extensive. With its flexibility and wide coverage, drones have become an important monitoring tool. For example, establishing a drone remote sensing monitoring network within the basin can quickly and real-time obtain high-precision water ecological environment status information, which is of great significance to the monitoring of the basin's water ecological environment.

[0003] In the related technology, after the drone is deployed, the theoretical coverage range of the drone does not match the actual coverage range, and there are certain monitoring blind spots, which affects the monitoring effect. Summary of the invention

[0004] Based on this, the purpose of this application is to provide a drone deployment method, device, electronic device and storage medium, which can optimize the deployment location of drones, ensure that drones cover all monitoring demand points in the complex three-dimensional environment of the watershed, and improve the comprehensiveness and effectiveness of watershed monitoring.

[0005] According to a first aspect of an embodiment of the present application, a method for deploying a drone is provided, comprising the following steps: Obtain digital elevation model data of the target watershed; According to the digital elevation model data, the target watershed is divided into water catchment units to obtain a number of water catchment units; the geographical center of each water catchment unit is used as the monitoring demand point of the drone; Obtain the ecological environment field observation stations in the target watershed; use the ecological environment field observation stations as candidate facility points for UAVs; Establishing a location set coverage model; the location set coverage model includes a constraint condition, which is used to indicate that when a facility point covers a monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range; Input the monitoring demand points and candidate facility points into the location set coverage model to obtain the location coordinates of each target facility point; The drones are deployed according to the location coordinates of each target facility point.

[0006] According to a second aspect of an embodiment of the present application, a drone deployment device is provided, comprising: A data acquisition module is used to obtain digital elevation model data of the target watershed; The monitoring demand point acquisition module is used to divide the target watershed into water catchment units according to the digital elevation model data, and obtain a number of water catchment units; the geographic center of each water catchment unit is used as the monitoring demand point of the drone; The candidate facility point acquisition module is used to obtain the ecological environment field observation stations in the target watershed; the ecological environment field observation stations are used as candidate facility points for UAVs; A model building module is used to build a location set coverage model; the location set coverage model includes a constraint condition, and the constraint condition is used to indicate that when a facility point covers a monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range; The location coordinate acquisition module is used to input the monitoring demand points and candidate facility points into the location set coverage model to obtain the location coordinates of each target facility point; The drone deployment module is used to deploy drones according to the location coordinates of each target facility point.

[0007] According to a third aspect of an embodiment of the present application, there is provided an electronic device, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the steps of the method of the first aspect.

[0008] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the method of the first aspect are implemented.

[0009] The embodiment of the present application obtains digital elevation model data of the target watershed; divides the target watershed into water catchment units according to the digital elevation model data to obtain a plurality of water catchment units; uses the geographical center of each water catchment unit as the monitoring demand point of the drone; obtains the ecological environment field observation station in the target watershed; uses the ecological environment field observation station as the candidate facility point of the drone; establishes a location set coverage model; the location set coverage model includes constraint conditions, and the constraint conditions are used to indicate that when the facility point covers the monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range; the monitoring demand point and the candidate facility point are input into the location set coverage model to obtain the location coordinates of each target facility point; and the drone is deployed according to the location coordinates of each target facility point. This application constrains the horizontal distance between the facility point and the monitoring demand point, and the vertical distance between the facility point and the monitoring demand point, and selects the target facility point from the candidate facility points to deploy the drone, thereby avoiding the monitoring blind spots caused by the horizontal distance difference and the height difference exceeding the flight capacity of the drone, optimizing the deployment position of the drone, ensuring that the drone covers all monitoring demand points in the complex three-dimensional environment of the watershed, and improving the comprehensiveness and effectiveness of watershed monitoring.

[0010] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application.

[0011] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flowchart of a method for deploying a drone provided in one embodiment of the present application; Figure 2 A structural block diagram of a drone deployment device provided in one embodiment of the present application; Figure 3 A schematic block diagram of the structure of an electronic device provided for one embodiment of the present application. DETAILED DESCRIPTION

[0013] In order to make the objectives, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0014] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0015] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0016] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0017] In addition, in the description of this application, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0018] See also Figure 1 , which is a flow chart of a drone deployment method provided by an embodiment of the present application. The drone deployment method provided by an embodiment of the present application comprises the following steps: S10: Acquire digital elevation model data of the target watershed.

[0019] Among them, the target basin is the basin where water ecological environment monitoring is to be carried out.

[0020] Among them, Digital Elevation Model (DEM) data, DEM data is a digital simulation of landforms through limited terrain elevation data.

[0021] In an embodiment of the present application, digital elevation model data of the target watershed may be downloaded from a geospatial data cloud.

[0022] S20: Divide the target watershed into water catchment units according to the digital elevation model data to obtain a number of water catchment units; and use the geographic center of each water catchment unit as the monitoring demand point of the drone.

[0023] Among them, the catchment unit refers to the closed surface area through which surface runoff flows when it converges to a common outlet.

[0024] In the embodiment of the present application, hydrological analysis software can be used to process and analyze DEM data, divide the target watershed into water catchment units, and obtain multiple water catchment units. After obtaining the water catchment units, the geographic center point of the water catchment unit can be extracted and used as the monitoring demand point of the drone.

[0025] S30: Acquire the ecological environment field observation stations in the target watershed; and use the ecological environment field observation stations as candidate facility points for UAVs.

[0026] Among them, the ecological environment field observation station has become an ideal choice for drone deployment due to its complete infrastructure and convenient transportation conditions. Its superior geographical location and existing support facilities can not only significantly improve the operational efficiency of drones, but also effectively reduce the construction cost of drone deployment.

[0027] In an embodiment of the present application, the ecological environment field observation stations in the target watershed can be obtained based on the spatial distribution data of existing ecological environment field observation stations in the country.

[0028] S40: Establish a location set coverage model; the location set coverage model includes constraint conditions, which are used to indicate that when a facility point covers a monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range.

[0029] Among them, the location set coverage model is a site selection optimization model, whose goal is to select the least number of facilities or to complete the layout of facilities at the lowest cost while ensuring that all demand points are covered.

[0030] The first preset distance range and the second preset distance range can be manually set according to actual needs.

[0031] In the embodiment of the present application, the terrain inside the target watershed is complex and the altitude difference is large. When deploying drones, it is necessary to consider the vertical distance between the facility point and the monitoring demand point to avoid monitoring blind spots caused by altitude differences exceeding the flight capability of the drone, thereby affecting the monitoring effect.

[0032] Specifically, when establishing a location set coverage model, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range as constraints that need to be met for the facility point to cover the monitoring demand point.

[0033] S50: Input the monitoring demand points and candidate facility points into the location set coverage model to obtain the location coordinates of each target facility point.

[0034] In an embodiment of the present application, the location set coverage model selects target facility points that meet the constraints from the candidate facility points based on the location coordinates of the monitoring demand points and the candidate facility points and the constraints.

[0035] S60: Deploy the UAVs according to the location coordinates of each target facility point.

[0036] In an embodiment of the present application, the drone is deployed to the location coordinates of each target facility point.

[0037] In the embodiment of the present application, digital elevation model data of the target watershed is obtained; according to the digital elevation model data, the target watershed is divided into water catchment units to obtain a plurality of water catchment units; the geographic center of each water catchment unit is used as the monitoring demand point of the UAV; the ecological environment field observation station in the target watershed is obtained; the ecological environment field observation station is used as the candidate facility point of the UAV; a location set coverage model is established; the location set coverage model includes constraint conditions, and the constraint conditions are used to indicate that when the facility point covers the monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range; the monitoring demand point and the candidate facility point are input into the location set coverage model to obtain the location coordinates of each target facility point; and the UAV is deployed according to the location coordinates of each target facility point. This application constrains the horizontal distance between the facility point and the monitoring demand point, and the vertical distance between the facility point and the monitoring demand point, and selects the target facility point from the candidate facility points to deploy the drone, thereby avoiding the monitoring blind spots caused by the horizontal distance difference and the height difference exceeding the flight capacity of the drone, optimizing the deployment position of the drone, ensuring that the drone covers all monitoring demand points in the complex three-dimensional environment of the watershed, and improving the comprehensiveness and effectiveness of watershed monitoring.

[0038] In one embodiment, the constraint conditions include that each monitoring demand point is covered by at least one facility point. When the horizontal distance between the monitoring demand point and the facility point is less than or equal to the operating radius of the drone, and the vertical distance between the monitoring demand point and the facility point is less than or equal to the flight altitude of the drone, the facility point covers the monitoring demand point.

[0039] In the embodiment of the present application, the constraint condition can be expressed as:

[0040]

[0041] in, Indicates whether facility point j can cover monitoring demand point i. If facility point j can cover monitoring demand point i, then ,otherwise . represents the horizontal distance between monitoring demand point i and facility point j, It represents the vertical distance between the monitoring demand point i and the facility point j, R represents the operating radius of the drone, and H represents the flight altitude of the drone.

[0042] The embodiment of the present application limits the horizontal distance between the monitoring demand point and the facility point to be less than or equal to the operating radius of the drone, and the vertical distance between the monitoring demand point and the facility point to be less than or equal to the flight altitude of the drone. This avoids monitoring blind spots caused by horizontal distance differences and altitude differences exceeding the flight capacity of the drone, optimizes the deployment position of the drone, ensures that the drone covers all monitoring demand points in the complex three-dimensional environment of the watershed, and improves the comprehensiveness and effectiveness of watershed monitoring.

[0043] In one embodiment, the location set coverage model includes an objective function, which takes the minimum number of facility points when all monitored demand points are covered by the facility points as a target.

[0044] In the embodiment of the present application, the objective function can be expressed as:

[0045] in, Indicates whether facility point j is selected as the target facility point. If facility point j is selected as the target facility point, then ,otherwise, , M represents the total number of facilities.

[0046] The embodiment of the present application requires that a minimum number of facility points be selected under the premise that all monitoring demand points are covered. Since the number of facility points is minimized, the efficiency of drone deployment can be improved and the cost of drone deployment can be reduced.

[0047] In one embodiment, in step S20, the target watershed is divided into water catchment units according to the digital elevation model data to obtain a plurality of water catchment units, including steps S201 to S206, which are specifically as follows: S201: Use the depression-filling tool of the hydrological analysis software to perform depression-filling processing on the digital elevation model data to obtain digital elevation model data without depressions.

[0048] In the embodiment of the present application, due to the terrain, there will be depressed areas in the DEM data. In the depressed areas, unreasonable or erroneous water flow direction data will be obtained. Therefore, before calculating the water flow direction data, the DEM data must be filled to obtain DEM data without depressions.

[0049] S202: Using the flow direction tool of the hydrological analysis software and the maximum slope method on the digital elevation model data without depressions, obtain the water flow direction data of each grid of the digital elevation model data without depressions.

[0050] Among them, the maximum slope method is a terrain analysis method used to calculate the water flow accumulation matrix. The water flow accumulation matrix refers to the cumulative value of water flowing from different locations into a specific point in an area. By calculating the water flow accumulation matrix, information such as the path of the water flow, the convergence area of ​​the water flow, and the direction of the water flow can be determined.

[0051] In the embodiment of the present application, the elevation difference of each grid is obtained through DEM data. The slope is determined according to the elevation difference. The flow direction of the water flow is determined according to the magnitude of the slope. In the maximum slope drop method, the basic principle of calculating the flow direction data of the water flow is that water flows to a lower place, and the flow direction is limited to flowing along the direction of the maximum slope, that is, the greater the slope, the easier it is for the water flow to flow to a lower place.

[0052] S203: Based on the water flow direction data of each grid, the flow tool of the hydrological analysis software is used to calculate the cumulative flow of the digital elevation model data without depressions.

[0053] Among them, in the process of surface runoff simulation, the runoff accumulation is calculated based on the water flow direction data. Specifically, there is a unit of water at each point in the digital ground elevation model represented by a grid. According to the natural law that water flows from high to low, the water flow value flowing at each point is calculated based on the water flow direction data of the regional terrain to obtain the runoff accumulation of the area.

[0054] In the embodiment of the present application, the water flow direction data of each grid is input into the flow tool of the hydrological analysis software to obtain the cumulative flow of the digital elevation model data without depressions.

[0055] S204: Based on the preset minimum cumulative runoff, the grid calculator of the hydrological analysis software is used to extract the target river network grid data from the grids whose runoff accumulation is greater than the preset minimum cumulative runoff.

[0056] Among them, the minimum cumulative runoff determines the scope of the target watershed watershed unit division.

[0057] In the embodiment of the present application, the cumulative runoff of each grid is compared with the preset minimum cumulative runoff to determine the grid whose cumulative runoff is greater than the preset minimum cumulative runoff. The grid calculator of the hydrological analysis software is used to calculate these grids to obtain the target river network grid data.

[0058] S205: Use the river linking tool of the hydrological analysis software to link the target river network raster data into a target river network.

[0059] The density of the target river network increases as the minimum cumulative runoff decreases, and the range of the target watershed catchment unit decreases as the density of the target river network increases.

[0060] In an embodiment of the present application, the target river network grid data is input into the river linking tool of the hydrological analysis software to obtain the target river network.

[0061] S206: Use the watershed tool of the hydrological analysis software to divide the target river network into watershed units to obtain a number of watershed units.

[0062] In an embodiment of the present application, the target river network is input into the watershed tool of the hydrological analysis software to obtain a number of water catchment units.

[0063] By using the fill tool, flow direction tool, flow tool, raster calculator, river link tool and watershed tool of the hydrological analysis software, the target watershed can be automatically and quickly divided into several watershed units.

[0064] In one embodiment, before the step of using the geographical center of each water catchment unit as the monitoring demand point of the drone in step S20, the following steps are included: S200: Use the feature conversion tool of the hydrological analysis software to extract the geographic center of all watershed units in the target basin.

[0065] Among them, the Feature to Point tool can convert input features (such as multipoints, lines, or areas) into point features. For area features (such as watershed units), the tool can extract their center points or internal points as output point features.

[0066] In the embodiment of the present application, each water catchment unit in the target watershed is input into the element conversion tool of the hydrological analysis software to obtain the geographic center of each water catchment unit.

[0067] By using the Feature to Point tool, you can automatically and quickly obtain the geographic centers of all watershed units in the target watershed.

[0068] The following is an embodiment of the device of the present application, which can be used to execute the content of the method in the embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the content of the method in the embodiment of the present application.

[0069] See also Figure 2 , which shows a schematic diagram of the structure of the drone deployment device provided in the embodiment of the present application. The drone deployment device 7 provided in the embodiment of the present application includes: A data acquisition module 71 is used to acquire digital elevation model data of a target watershed; The monitoring demand point acquisition module 72 is used to divide the target watershed into water catchment units according to the digital elevation model data, and obtain a number of water catchment units; the geographical center of each water catchment unit is used as the monitoring demand point of the drone; The candidate facility point acquisition module 73 is used to obtain the ecological environment field observation station in the target watershed; the ecological environment field observation station is used as the candidate facility point of the UAV; A model building module 74 is used to build a location set coverage model; the location set coverage model includes a constraint condition, and the constraint condition is used to indicate that when the facility point covers the monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range; The location coordinate acquisition module 75 is used to input the monitoring demand points and the candidate facility points into the location set coverage model to obtain the location coordinates of each target facility point; The drone deployment module 76 is used to deploy drones according to the location coordinates of each target facility point.

[0070] It should be noted that the drone deployment device provided in the above embodiment only uses the division of the above functional modules as an example when executing the drone deployment method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the drone deployment device and the drone deployment method provided in the above embodiment belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0071] The following is an embodiment of the device of the present application, which can be used to execute the content of the method in the embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the content of the method in the embodiment of the present application.

[0072] See also Figure 3 The present application also provides an electronic device 300, which may be a computer, a mobile phone, a tablet computer, etc. In an exemplary embodiment of the present application, the electronic device 300 is a computer, which may include: at least one processor 301, at least one memory 302, at least one display, at least one network interface 303, a user interface 304, and at least one communication bus 305.

[0073] The user interface 304 is mainly used to provide an input interface for the user and obtain data input by the user. Optionally, the user interface may also include a standard wired interface or a wireless interface.

[0074] The network interface 303 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0075] The communication bus 305 is used to realize the connection and communication between these components.

[0076] Among them, the processor 301 may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. Optionally, the processor can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed by the display layer; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor, but implemented separately through a chip.

[0077] Among them, the memory 302 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory includes a non-transitory computer-readable storage medium. The memory can be used to store instructions, programs, codes, code sets or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory may also be optionally at least one storage device located away from the aforementioned processor. As Figure 3 , as a computer storage medium, the memory may include an operating system, a network communication module, a user interface module, and an operating application program.

[0078] The processor can be used to call the application of the drone deployment method stored in the memory, and specifically execute the method steps of the above-mentioned embodiment. The specific execution process can be referred to the specific description shown in the embodiment, which will not be repeated here.

[0079] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0080] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for deploying a drone, characterized in that: The steps include: Obtain digital elevation model data of the target watershed; According to the digital elevation model data, the target watershed is divided into water catchment units to obtain a plurality of water catchment units; the geographical center of each water catchment unit is used as a monitoring demand point of the drone; Obtaining ecological environment field observation stations within the target watershed; Taking the ecological environment field observation station as a candidate facility point for the UAV; Establishing a location set coverage model; the location set coverage model includes a constraint condition, wherein the constraint condition is used to indicate that when a facility point covers a monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range; Input the monitoring demand points and the candidate facility points into the location set coverage model to obtain the location coordinates of each target facility point; The drone is deployed according to the location coordinates of each of the target facility points.

2. The method for deploying a drone according to claim 1, characterized in that: The constraint conditions include that each of the monitoring demand points is covered by at least one of the facility points, and when the horizontal distance between the monitoring demand point and the facility point is less than or equal to the operating radius of the drone, and the vertical distance between the monitoring demand point and the facility point is less than or equal to the flight altitude of the drone, the facility point covers the monitoring demand point.

3. The method for deploying a drone according to claim 1, characterized in that: The location set coverage model includes an objective function, which takes the minimum number of facility points when all monitored demand points are covered by the facility points as a target.

4. The method for deploying a drone according to any one of claims 1 to 3, characterized in that: The step of dividing the target watershed into water catchment units according to the digital elevation model data to obtain a plurality of water catchment units comprises: Using a depression-filling tool of a hydrological analysis software to perform depression-filling processing on the digital elevation model data to obtain digital elevation model data without depressions; Using the flow direction tool of the hydrological analysis software to obtain the water flow direction data of each grid of the digital elevation model data without depressions by using the maximum slope drop method on the digital elevation model data without depressions; According to the water flow direction data of each grid, the flow accumulation of the digital elevation model data without depressions is calculated using the flow tool of the hydrological analysis software; Based on a preset minimum cumulative runoff, using a grid calculator of the hydrological analysis software, extracting target river network grid data from grids whose confluence accumulation is greater than the preset minimum cumulative runoff; Use the river linking tool of the hydrological analysis software to link the target river network grid data into a target river network; The watershed tool of the hydrological analysis software is used to divide the target river network into watershed units to obtain a plurality of watershed units.

5. The method for deploying a drone according to any one of claims 1 to 3, characterized in that: Before the step of using the geographical center of each water catchment unit as the monitoring demand point of the drone, the method includes: The feature conversion tool of the hydrological analysis software was used to extract the geographic centers of all water catchment units in the target watershed.

6. A drone deployment device, characterized in that: include: A data acquisition module is used to obtain digital elevation model data of the target watershed; A monitoring demand point acquisition module is used to divide the target watershed into water catchment units according to the digital elevation model data to obtain a plurality of water catchment units; and the geographical center of each water catchment unit is used as the monitoring demand point of the drone; A candidate facility point acquisition module is used to obtain an ecological environment field observation station in the target watershed; Taking the ecological environment field observation station as a candidate facility point for the UAV; A model building module, used to build a location set coverage model; the location set coverage model includes a constraint condition, the constraint condition is used to indicate that when a facility point covers a monitoring demand point, the horizontal distance between the facility point and the monitoring demand point is within a first preset distance range, and the vertical distance between the facility point and the monitoring demand point is within a second preset distance range; A location coordinate acquisition module, used to input the monitoring demand point and the candidate facility point into the location set coverage model to obtain the location coordinates of each target facility point; The drone deployment module is used to deploy the drone according to the location coordinates of each target facility point.

7. An electronic device, characterized in that: include: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the steps of the drone deployment method as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the drone deployment method as described in any one of claims 1 to 5 are implemented.

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