Water and soil loss monitoring method and device, medium and unmanned aerial vehicle

Abstract

The invention discloses a water and soil loss monitoring method and device, a medium and an unmanned aerial vehicle, and the method comprises the steps: obtaining a plurality of aerial images in a target region during patrol flight in the target region; determining a real-time change rate corresponding to each real-time water and soil loss parameter in the target area according to the plurality of aerial images in the target area and a preset water and soil model of the target area; determining the real-time water and soil loss change rate of the target area according to the real-time change rate corresponding to each real-time water and soil loss parameter in the target area; determining a water and soil loss risk grade of the target area according to the real-time water and soil loss change rate of the target area; and when the water and soil loss risk level of the target area is greater than a preset level, sending an alarm signal to the target client. The invention belongs to the field of disaster monitoring. The automation degree of water and soil loss monitoring can be improved.

Description

Technical Field

[0001] The present invention relates to the field of disaster monitoring, and in particular to a method, equipment, medium and unmanned aerial vehicle for monitoring soil and water loss. Background Art

[0002] Land loss or land subsidence is the decline or reduction of the land surface due to natural or human factors. Land loss or land subsidence may be caused by many reasons, such as geological activities, groundwater extraction, land development, earthquakes, natural erosion or human activities. In geography and environmental science, land loss is often regarded as an environmental problem because it may lead to ecosystem degradation, land impoverishment and loss of biodiversity. Land loss is a complex geographical and environmental issue that requires comprehensive consideration of the impact of natural factors and human activities in order to take effective management and protection measures.

[0003] Methods for monitoring land subsidence include: benchmark measurement, GPS monitoring, laser scanning measurement, and remote sensing technology. However, the above methods all require a lot of manpower, and the need to monitor the land usually means that land loss or land subsidence may occur, which means that when the relevant personnel conduct field measurements, the life safety of the relevant personnel may be threatened. Therefore, how to improve the automation of soil and water loss monitoring and ensure the safety of relevant personnel is an urgent problem to be solved. Summary of the invention

[0004] The embodiments of the present application solve the technical problem of low automation in soil and water loss monitoring in the prior art by providing a soil and water loss monitoring method, equipment, medium and drone, and achieve the technical effect of improving the automation level of soil and water loss monitoring.

[0005] In a first aspect, the present application provides a method for monitoring soil erosion, the method comprising:

[0006] When patrolling in the target area, obtain several aerial images of the target area;

[0007] Determine the real-time change rate corresponding to each real-time soil and water loss parameter in the target area according to a number of aerial images in the target area and a preset soil and water model of the target area;

[0008] Determine the real-time soil and water loss change rate of the target area according to the real-time change rate corresponding to each real-time soil and water loss parameter in the target area;

[0009] Determine the soil and water loss risk level of the target area based on the real-time soil and water loss change rate of the target area;

[0010] When the soil erosion risk level in the target area is greater than the preset level, an alarm signal is sent to the target client.

[0011] Furthermore, according to a plurality of aerial images in the target area and a preset soil and water model of the target area, the real-time change rate corresponding to each real-time soil and water loss parameter in the target area is determined, including:

[0012] Based on several aerial images, a real-time soil and water model of the target area is constructed;

[0013] According to the difference between the real-time soil and water model of the target area and the preset soil and water model of the target area, the real-time change rate corresponding to each real-time soil and water loss parameter in the target area is determined.

[0014] Furthermore, real-time soil erosion parameters include:

[0015] Vegetation cover, soil exposure, terrain slope, land height and maximum catchment area.

[0016] Further, according to the difference between the real-time soil and water model of the target area and the preset soil and water model of the target area, the real-time change rate corresponding to each real-time soil and water loss parameter in the target area is determined, including:

[0017] Determine the real-time change rate of vegetation coverage in the target area according to the vegetation coverage of the real-time soil and water model and the vegetation coverage of the preset soil and water model in the target area;

[0018] Determine the real-time change rate of soil exposure in the target area according to the soil exposure of the real-time soil and water model and the soil exposure of the preset soil and water model in the target area;

[0019] Determine the real-time change rate of the terrain slope of the target area based on the terrain slope of each point in the real-time soil and water model and the corresponding terrain slope in the preset soil and water model of the target area;

[0020] Determine the real-time change rate of the land height of the target area according to the land height of each point in the real-time soil and water model and the corresponding land height in the preset soil and water model of the target area;

[0021] Determine the real-time change rate of the maximum catchment area of ​​the target area according to the maximum catchment area of ​​the real-time soil and water model and the maximum catchment area of ​​the preset soil and water model of the target area;

[0022] Further, according to the real-time change rate corresponding to each real-time soil and water loss parameter in the target area, the real-time soil and water loss change rate of the target area is determined, including:

[0023] The real-time change rate of soil and water loss in the target area is determined based on the real-time change rate of vegetation coverage, the real-time change rate of soil exposure, the real-time change rate of terrain slope, the real-time change rate of maximum catchment area and the real-time change rate of land height.

[0024] Furthermore, a real-time soil and water model of the target area is constructed based on several aerial images, including:

[0025] Preprocessing several aerial images of the target area, the preprocessing steps include image correction, image denoising and image edge enhancement;

[0026] Perform feature extraction on several pre-processed aerial images to obtain water and soil model data of the target area. The feature extraction includes at least vegetation coverage extraction, soil exposure extraction, terrain slope extraction, water body distribution extraction and terrain height extraction;

[0027] Based on the soil and water model data of the target area, a real-time soil and water model of the target area is constructed.

[0028] Furthermore, the real-time change rate of soil erosion in the target area is determined based on the real-time change rate of vegetation coverage, the real-time change rate of soil exposure, the real-time change rate of terrain slope, the real-time change rate of maximum catchment area and the real-time change rate of land height, including:

[0029] The real-time change rate of soil and water loss in the target area is determined based on the real-time change rate of vegetation coverage, the real-time change rate of soil exposure, the real-time change rate of terrain slope, the real-time change rate of maximum watershed area, the real-time change rate of land height, the preset weight of vegetation coverage change, the preset weight of soil exposure change, the preset weight of land height change, the preset weight of maximum watershed area change and the preset weight of terrain slope.

[0030] In the second aspect, the present application provides a drone, which is equipped with several cameras and AI boxes, including:

[0031] Based on several cameras of the drone, obtain aerial image data of the target area;

[0032] The camera transmits the aerial image data to the AI ​​box;

[0033] The AI ​​box receives aerial image data and determines whether to send an alarm signal to the target client indicating the risk of soil erosion in the target area.

[0034] In a third aspect, the present application provides an electronic device, including:

[0035] processor;

[0036] a memory for storing processor-executable instructions;

[0037] The processor is configured to execute to implement a soil and water loss monitoring method as provided in the first aspect.

[0038] In a fourth aspect, the present application provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement a soil and water loss monitoring method as provided in the first aspect.

[0039] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0040] The present application provides a soil erosion monitoring method, the method comprising: when patrolling in a target area, obtaining several aerial images in the target area; determining the real-time change rate corresponding to each real-time soil erosion parameter in the target area according to the several aerial images in the target area and the preset soil and water model of the target area; determining the real-time soil erosion change rate of the target area according to the real-time change rate corresponding to each real-time soil erosion parameter in the target area; determining the soil erosion risk level of the target area according to the real-time soil erosion change rate of the target area; when the soil erosion risk level of the target area is greater than the preset level, sending an alarm signal to the target client. The present application can improve the automation of soil erosion monitoring by obtaining aerial images, automatically judging the soil erosion risk level of the target area, and automatically judging whether to send an alarm signal to the target client according to the soil erosion risk level. The present application can accurately determine the real-time change rate corresponding to each real-time soil erosion parameter by obtaining aerial images. After determining the real-time soil erosion change rate of the target area, the soil erosion risk level can be accurately judged, providing a reference for landslide and collapse risks for relevant staff to avoid causing greater losses of personnel and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 A schematic diagram of a process of soil and water loss monitoring method provided for this application;

[0043] Figure 2 A schematic diagram of the structure of an electronic device provided in this application. DETAILED DESCRIPTION

[0044] The embodiment of the present application solves the technical problem of low automation level in soil and water loss monitoring in the prior art by providing a soil and water loss monitoring method.

[0045] The technical solution of the embodiment of the present application is to solve the above technical problems, and the overall idea is as follows:

[0046] A soil and water loss monitoring method comprises: when patrolling a target area, obtaining a plurality of aerial images in the target area; determining the real-time change rate corresponding to each real-time soil and water loss parameter in the target area according to the plurality of aerial images in the target area and a preset soil and water model of the target area; determining the real-time soil and water loss change rate of the target area according to the real-time change rate corresponding to each real-time soil and water loss parameter in the target area; determining the soil and water loss risk level of the target area according to the real-time soil and water loss change rate of the target area; and sending an alarm signal to a target client when the soil and water loss risk level of the target area is greater than the preset level.

[0047] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0048] First of all, the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0049] This application provides Figure 1 A soil and water loss monitoring method is shown, comprising steps S11-S15:

[0050] Step S11, when patrolling in the target area, obtaining a number of aerial images in the target area.

[0051] Step S12, determining the real-time change rate corresponding to each real-time soil and water loss parameter in the target area according to a plurality of aerial images in the target area and a preset soil and water model of the target area.

[0052] Step S13, determining the real-time soil and water loss change rate of the target area according to the real-time change rate corresponding to each real-time soil and water loss parameter in the target area.

[0053] Step S14, determining the soil erosion risk level of the target area according to the real-time soil erosion change rate of the target area;

[0054] Step S15: When the soil erosion risk level of the target area is greater than a preset level, an alarm signal is sent to the target client.

[0055] Regarding step S11, when patrolling the target area, a number of aerial images in the target area are acquired.

[0056] The method provided in this application can be implemented based on a drone provided below. Please refer to the following description for details. When the drone is in the target area, several aerial images of the target area can be obtained. The target area refers to the area where soil erosion (sedimentation) needs to be monitored.

[0057] Regarding step S12, the real-time change rate corresponding to each real-time soil and water loss parameter in the target area is determined according to a plurality of aerial images in the target area and a preset soil and water model of the target area.

[0058] The preset soil and water model of the target area refers to a three-dimensional model of the preset area before soil erosion (sedimentation) occurs. The preset model includes vegetation coverage, soil exposure, terrain slope, water body distribution, terrain height, etc. when soil erosion does not occur in the preset area.

[0059] Determining the real-time change rate corresponding to each real-time soil and water loss parameter in the target area may include: constructing a real-time soil and water model of the target area based on a number of aerial images; and determining the real-time change rate corresponding to each real-time soil and water loss parameter in the target area based on the difference between the real-time soil and water model of the target area and a preset soil and water model of the target area. The real-time soil and water loss parameters include: vegetation coverage, soil exposure, terrain slope, land height, and maximum catchment area.

[0060] Among them, building a real-time soil and water model of the target area includes: preprocessing a number of aerial images of the target area, the preprocessing steps including image correction, image denoising and image edge enhancement; extracting features from the preprocessed aerial images to obtain soil and water model data of the target area, the feature extraction at least including vegetation coverage extraction, soil exposure extraction, terrain slope extraction, water body distribution extraction and terrain height extraction; and building a real-time soil and water model of the target area according to the soil and water model data of the target area.

[0061] Image correction aims to eliminate geometric distortion caused by factors such as flight platform attitude, terrain undulations or sensor characteristics, including: using ground control points or GPS data to correct the position and attitude of the image. In combination with geographic information system data, the image pixels are mapped to the real-world geographic coordinate system.

[0062] Image denoising aims to eliminate interference caused by sensor noise, atmospheric interference or artifacts introduced during the transmission process, including: smoothing filter, wavelet transform and statistical model denoising.

[0063] Image edge enhancement aims to highlight the edge information of objects and features in the image to facilitate subsequent feature extraction and analysis, including: detecting edges in the image with the Sobel operator or the Prewitt operator, identifying edge positions by calculating the gradient of pixel gray values, or detecting edges using gradient amplitude and non-maximum suppression techniques to provide clear edge images or using gradient images or other gradient-related features to enhance edges in the image.

[0064] Feature extraction specifically includes:

[0065] Vegetation coverage can be achieved by analyzing the vegetation index in the image. Common indices include the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Vegetation Index (NDWI). Use remote sensing images to extract pixel values ​​of the red band and the near-infrared band. Calculate the vegetation index, such as NDVI = (NIR-Red) / (NIR+Red), where NIR is the near-infrared band and Red is the red band. According to the threshold of the NDVI value, the area with high NDVI value is identified as the vegetation coverage area.

[0066] Soil exposure can be achieved by analyzing the spectral characteristics in the image, which is usually the opposite of the vegetation index, that is, the area not covered by vegetation. Using the vegetation index image, the bare surface areas are found through threshold segmentation or mathematical morphological operations. These areas are usually areas with low NDVI values.

[0067] The terrain slope can be calculated by digital elevation model (DEM) or digital surface model (DSM). Generate an elevation model or surface model based on the preprocessed image. Calculate the elevation change around each pixel to calculate the slope at the pixel. Common methods include using slope algorithms such as Slope algorithm to calculate the slope.

[0068] Water body distribution can be achieved through image classification and threshold segmentation. The preprocessed image can be classified into water bodies and non-water bodies, and water body indices such as the Normalized Difference Water Index (NDWI) can be used. Based on the classification results and thresholds, the water body distribution area in the image can be extracted.

[0069] Terrain height is usually obtained directly from a digital elevation model (DEM) or digital surface model (DSM). Using DEM or DSM data, the elevation value of each pixel is directly extracted. The data can be extracted from LiDAR scans or optical images.

[0070] A real-time soil and water model of the target area can be constructed based on the soil and water model data of the target area extracted above.

[0071] According to the difference between the real-time soil and water model of the target area and the preset soil and water model of the target area, the real-time change rate corresponding to each real-time soil and water loss parameter in the target area is determined, including: according to the difference between the vegetation coverage of the real-time soil and water model and the vegetation coverage of the preset soil and water model of the target area, the real-time change rate of the vegetation coverage of the target area is determined; according to the difference between the soil exposure of the real-time soil and water model and the soil exposure of the preset soil and water model of the target area, the real-time change rate of the soil exposure of the target area is determined; according to the difference between the terrain slope of each point in the real-time soil and water model and the corresponding terrain slope in the preset soil and water model of the target area, the real-time change rate of the terrain slope of the target area is determined; according to the difference between the land height of each point in the real-time soil and water model and the corresponding land height in the preset soil and water model of the target area, the real-time change rate of the land height of the target area is determined; according to the difference between the maximum catchment area of ​​the real-time soil and water model and the maximum catchment area of ​​the preset soil and water model of the target area, the real-time change rate of the maximum catchment area of ​​the target area is determined.

[0072] Take vegetation coverage as an example: based on the difference between the vegetation coverage of the real-time soil and water model and the vegetation coverage of the preset soil and water model of the target area, the real-time change rate of the vegetation coverage of the target area is determined. The vegetation coverage of the real-time soil and water model is 28%. Assuming that the vegetation coverage of the soil and water model is 52%, the real-time change rate of the vegetation coverage of the target area is 52%-28%=24%.

[0073] It should be emphasized that for both land height and terrain slope, the overall change needs to be determined based on the average value of the change at each corresponding point in the preset soil and water model and the real-time soil and water model.

[0074] Take terrain slope as an example:

[0075] Points A, B and C in the real-time soil and water model correspond to points a, b and c in the preset soil and water model. The difference between point A and point a is 10%, the difference between point B and point b is 7%, and the difference between point C and point c is 5%. The real-time change rate of the terrain slope is (12% + 7% + 5%) / 3 = 8%.

[0076] Regarding step S13, the real-time soil and water loss change rate of the target area is determined according to the real-time change rate corresponding to each real-time soil and water loss parameter in the target area.

[0077] Specifically, it includes: determining the real-time change rate of soil erosion in the target area based on the real-time change rate of vegetation coverage, the real-time change rate of soil exposure, the real-time change rate of terrain slope, the real-time change rate of maximum catchment area and the real-time change rate of land height.

[0078] Specifically, the real-time change rate of soil and water loss in the target area can be determined based on the real-time change rate of vegetation coverage, the real-time change rate of soil exposure, the real-time change rate of terrain slope, the real-time change rate of maximum watershed area, the real-time change rate of land height, the preset weight of vegetation coverage change, the preset weight of soil exposure change, the preset weight of land height change, the preset weight of maximum watershed area change and the preset weight of terrain slope.

[0079] The preset weights of vegetation coverage change, soil exposure change, land height change, maximum catchment area change, and terrain slope change can be determined according to actual conditions, and this application provides a possible allocation method. Preset weight of vegetation coverage change: preset weight of soil exposure change: preset weight of land height change: preset weight of maximum catchment area change: preset weight of terrain slope = 0.2: 0.4: 0.15: 0.15: 0.1. The sum of the weights is 1.

[0080] Regarding step S14, the soil erosion risk level of the target area is determined according to the real-time soil erosion change rate of the target area.

[0081] It is understandable that the greater the real-time soil erosion change rate is, the more serious the soil erosion (sedimentation) in the target area is, and the more likely it is to cause secondary disasters such as landslides and collapses.

[0082] The classification of soil and water loss risk levels can be found in Table 1:

[0083] Table 1

[0084]

[0085] Regarding step S15, when the soil erosion risk level of the target area is greater than a preset level, an alarm signal is sent to the target client.

[0086] After determining the soil erosion risk level of the target area, it can be determined whether it is necessary to send an alarm signal to the target client. When the soil erosion risk level of the target area is greater than the preset level, an alarm signal is sent to the target client. The preset risk level can be determined according to the actual situation, for example, medium risk is used as the preset level.

[0087] In summary, the present application provides a method for monitoring soil erosion, the method comprising: when patrolling in a target area, obtaining several aerial images in the target area; determining the real-time change rate corresponding to each real-time soil erosion parameter in the target area according to the several aerial images in the target area and the preset soil and water model of the target area; determining the real-time soil erosion change rate of the target area according to the real-time change rate corresponding to each real-time soil erosion parameter in the target area; determining the soil erosion risk level of the target area according to the real-time soil erosion change rate of the target area; when the soil erosion risk level of the target area is greater than the preset level, sending an alarm signal to the target client. The present application can improve the automation of soil erosion monitoring by obtaining aerial images, automatically judging the soil erosion risk level of the target area, and automatically judging whether to send an alarm signal to the target client according to the soil erosion risk level. The present application can accurately determine the real-time change rate corresponding to each real-time soil erosion parameter by obtaining aerial images. After determining the real-time soil erosion change rate of the target area, the soil erosion risk level can be accurately judged, providing a reference for landslide and collapse risks for relevant staff to avoid causing greater losses of personnel and property.

[0088] Based on the same inventive concept, the present application provides a drone, which is provided with a plurality of cameras and an AI box, including:

[0089] Based on several cameras of the drone, aerial image data of the target area is obtained; the camera transmits the aerial image data to the AI ​​box; the AI ​​box receives the aerial image data and can execute the method in steps S12-S15 provided above.

[0090] Compared with the existing technology, which needs to return aerial image data to the data center for processing, this application can directly issue an early warning by enabling the drone to be equipped with an AI box and having the AI ​​box execute the above-provided method, thereby reducing the data processing process, saving time, and speeding up the early warning process.

[0091] Based on the same inventive concept, the present application also provides Figure 2 An electronic device as shown includes:

[0092] Processor 21;

[0093] A memory 22 for storing instructions executable by the processor 21;

[0094] The processor 21 is configured to execute to implement a soil and water loss monitoring method as provided above.

[0095] Based on the same inventive concept, the present application also provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor 21 of the electronic device, the electronic device can execute a soil and water loss monitoring method as provided above.

[0096] Since the electronic device introduced in this embodiment is an electronic device used to implement the information processing method in the embodiment of the present application, based on the information processing method introduced in the embodiment of the present application, a person skilled in the art can understand the specific implementation of the electronic device of the present embodiment and its various variations, so how the electronic device implements the method in the embodiment of the present application is not described in detail here. As long as a person skilled in the art implements the electronic device used by the information processing method in the embodiment of the present application, it belongs to the scope of protection of this application.

[0097] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may 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.

[0098] The present invention is described with reference to 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 process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0099] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0100] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0101] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0102] 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 equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A soil and water loss monitoring method, characterized in that: The method comprises: When patrolling in a target area, obtaining a number of aerial images in the target area; Determine the real-time change rate corresponding to each real-time soil and water loss parameter in the target area according to a plurality of aerial images in the target area and a preset soil and water model of the target area; Determine the real-time soil and water loss change rate of the target area according to the real-time change rate corresponding to each real-time soil and water loss parameter in the target area; Determining the soil and water loss risk level of the target area according to the real-time soil and water loss change rate of the target area; When the soil erosion risk level of the target area is greater than a preset level, an alarm signal is sent to the target client.

2. A soil and water loss monitoring method as claimed in claim 1, characterized in that: Determining the real-time change rate corresponding to each real-time soil and water loss parameter in the target area according to a plurality of aerial images in the target area and a preset soil and water model of the target area includes: Constructing a real-time soil and water model of the target area based on a number of aerial images; According to the difference between the real-time soil and water model of the target area and the preset soil and water model of the target area, the real-time change rate corresponding to each real-time soil and water loss parameter in the target area is determined.

3. A soil and water loss monitoring method as claimed in claim 2, characterized in that: Real-time soil erosion parameters, including: Vegetation cover, soil exposure, terrain slope, land height and maximum catchment area.

4. A soil and water loss monitoring method as claimed in claim 3, characterized in that: Determining the real-time change rate corresponding to each real-time soil and water loss parameter in the target area according to the difference between the real-time soil and water model of the target area and the preset soil and water model of the target area includes: Determining a real-time change rate of vegetation coverage of the target area according to the vegetation coverage of the real-time soil and water model and the vegetation coverage of a preset soil and water model of the target area; Determining a real-time change rate of soil exposure in the target area according to the soil exposure of the real-time soil and water model and the soil exposure of the preset soil and water model in the target area; Determine the real-time change rate of the terrain slope of the target area according to the terrain slope of each point in the real-time soil and water model and the terrain slope corresponding to the preset soil and water model of the target area; Determine the real-time change rate of the land height of the target area according to the land height of each point in the real-time soil and water model and the corresponding land height in the preset soil and water model of the target area; The real-time change rate of the maximum catchment area of ​​the target area is determined according to the maximum catchment area of ​​the real-time soil and water model and the maximum catchment area of ​​the preset soil and water model of the target area.

5. A soil and water loss monitoring method as claimed in claim 4, characterized in that: Determining the real-time soil and water loss change rate of the target area according to the real-time change rate corresponding to each real-time soil and water loss parameter in the target area includes: The real-time change rate of soil and water loss in the target area is determined based on the real-time change rate of the vegetation coverage, the real-time change rate of the soil exposure, the real-time change rate of the terrain slope, the real-time change rate of the maximum catchment area and the real-time change rate of the land height.

6. A soil and water loss monitoring method as claimed in claim 2, characterized in that: Based on several aerial images, a real-time soil and water model of the target area is constructed, including: Preprocessing a plurality of aerial images of the target area, wherein the preprocessing steps include image correction, image denoising and image edge enhancement; Performing feature extraction on the preprocessed aerial images to obtain water and soil model data of the target area, wherein the feature extraction at least includes vegetation coverage extraction, soil exposure extraction, terrain slope extraction, water body distribution extraction, and terrain height extraction; A real-time soil and water model of the target area is constructed according to the soil and water model data of the target area.

7. A soil and water loss monitoring method as claimed in claim 5, characterized in that: Determining the real-time soil and water loss change rate of the target area according to the real-time change rate of the vegetation coverage, the real-time change rate of the soil exposure, the real-time change rate of the terrain slope, the real-time change rate of the maximum catchment area and the real-time change rate of the land height includes: The real-time change rate of soil and water loss in the target area is determined based on the real-time change rate of the vegetation coverage, the real-time change rate of the soil exposure, the real-time change rate of the terrain slope, the real-time change rate of the maximum watershed area, the real-time change rate of the land height, the preset weight of the vegetation coverage change, the preset weight of the soil exposure change, the preset weight of the land height change, the preset weight of the maximum watershed area change and the preset weight of the terrain slope.

8. A drone, characterized in that: A method for monitoring soil and water loss according to any one of claims 1 to 7 is applied, wherein a plurality of cameras and an AI box are provided on the drone, including: Based on several cameras of the drone, obtain aerial image data of the target area; The camera transmits the aerial image data to the AI ​​box; The AI ​​box receives the aerial image data and determines whether to send an alarm signal to the target client indicating that there is a risk of soil erosion in the target area.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; Wherein, the processor is configured to execute to implement a soil and water loss monitoring method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement a soil and water loss monitoring method as described in any one of claims 1 to 7.

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