Method and device for monitoring soil under photovoltaic panel, electronic equipment and storage medium

Abstract

The application discloses a kind of photovoltaic panel under soil monitoring method, device, electronic equipment and storage medium.The method comprises: based on the first point cloud data of obtained target area, a plurality of target photovoltaic panels are obtained by photovoltaic panel identification;First point cloud data is mapped based on the spatial arrangement features of target photovoltaic panel to determine the target soil point under target photovoltaic panel;Based on the target spectral information corresponding to each target soil point obtained, the echo intensity corresponding to target soil point is normalized, to determine the target echo intensity corresponding to target soil point;Based on the target echo intensity corresponding to target soil point, the target feature vector of the soil under target photovoltaic panel is constructed;At least two soil inversion models are obtained, and the target soil parameters are determined based on soil inversion model and the target feature vector, and the spatial distribution map of target area is generated based on all target soil parameters.The application realizes the observability and stability of soil data under shading condition.

Description

Technical Field

[0001] This invention relates to the field of new energy ecological environment monitoring and active remote sensing technology, and in particular to a method, device, electronic equipment and storage medium for monitoring soil under photovoltaic panels. Background Technology

[0002] In large-scale photovoltaic power plants in deserts, semi-arid regions, and agro-pastoral transition zones, photovoltaic panel arrays alter the surface radiation budget and rainfall redistribution processes, directly impacting dust risk, vegetation restoration, and ecological restoration effectiveness. This, in turn, affects operation and maintenance (such as dust migration and vegetation management). Therefore, it is necessary to conduct repeatable and comparable routine monitoring of the soil conditions beneath the photovoltaic panels.

[0003] Current methods for detecting soil conditions under photovoltaic panels generally involve ground sampling and underground sensor sampling, followed by data processing to obtain the soil condition. However, this method has limited coverage, high cost, and difficulty in frequently and repeatedly collecting and analyzing data, which may affect the accuracy of soil condition data. Summary of the Invention

[0004] This invention provides a method, device, electronic equipment, and storage medium for soil monitoring under photovoltaic panels to achieve the observability and stability of soil data under shading conditions.

[0005] According to one aspect of the present invention, a method for monitoring soil under a photovoltaic panel is provided, the method comprising: The first point cloud data of the target area is acquired, and photovoltaic panel identification is performed based on the first point cloud data to obtain multiple target photovoltaic panels; the first point cloud data is three-dimensional point cloud data with spectral information; the target area is deployed with a photovoltaic panel array. Based on the spatial arrangement characteristics of the target photovoltaic panel, the first point cloud data is mapped to determine the target soil points under the target photovoltaic panel, and the target spectral information corresponding to each target soil point is obtained; the target spectral information is extracted from the first point cloud data; the target spectral information includes echo intensity and reflectivity; Based on the target spectral information, the echo intensity corresponding to the target soil point is normalized to determine the target echo intensity corresponding to the target soil point. Based on the target echo intensity corresponding to the target soil point, a target feature vector of the soil under the target photovoltaic panel is constructed; the target feature vector includes at least one of the echo intensity of the target soil point, the normalization degree between the echo intensities of each target soil point, the brightness variation between the echo intensities of each target soil point, and the spectral variation degree between the echo intensities of each target soil point. At least two soil inversion models are acquired. Based on the soil inversion models and the target feature vectors, target soil parameters are determined. A spatial distribution map of the target area is generated based on all the target soil parameters. The soil inversion models are used to describe the mapping relationship between the feature vectors and the soil parameters. The soil parameters are used to reflect the physicochemical properties of the soil.

[0006] According to another aspect of the present invention, a soil monitoring device under a photovoltaic panel is provided, the device comprising: The identification module is used to acquire first point cloud data of the target area, and to identify photovoltaic panels based on the first point cloud data to obtain multiple target photovoltaic panels; the first point cloud data is three-dimensional point cloud data with spectral information; the target area is equipped with a photovoltaic panel array. The soil point determination module is used to map the first point cloud data based on the spatial arrangement characteristics of the target photovoltaic panel to determine the target soil points under the target photovoltaic panel, and to obtain the target spectral information corresponding to each target soil point; the target spectral information is extracted from the first point cloud data; the target spectral information includes echo intensity and reflectivity; The normalization processing module is used to normalize the echo intensity corresponding to the target soil point based on the target spectral information, and determine the target echo intensity corresponding to the target soil point. The feature determination module is used to construct a target feature vector of the soil under the target photovoltaic panel based on the target echo intensity corresponding to the target soil point; the target feature vector includes at least one of the echo intensity of the target soil point, the normalization degree between the echo intensities of each target soil point, the brightness variation between the echo intensities of each target soil point, and the spectral variation degree between the echo intensities of each target soil point. The soil parameter determination module is used to acquire at least two soil inversion models, determine target soil parameters based on the soil inversion models and the target feature vectors, and generate a spatial distribution map of the target area based on all the target soil parameters; the soil inversion models are used to describe the mapping relationship between the feature vectors and the soil parameters; the soil parameters are used to reflect the physicochemical properties of the soil.

[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the soil monitoring method under the photovoltaic panel according to any embodiment of the present invention.

[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the soil monitoring method under a photovoltaic panel according to any embodiment of the present invention.

[0009] The technical solution of this invention involves acquiring first point cloud data of a target area where a photovoltaic panel array is deployed, and then identifying multiple target photovoltaic panels based on the first point cloud data. The first point cloud data is three-dimensional point cloud data with spectral information, which can be used for subsequent inversion of multi-band echo intensity under the photovoltaic panels, significantly improving the availability of data in the area under the panels. Based on the spatial arrangement characteristics of the target photovoltaic panels, the first point cloud data is mapped to determine the target soil points under the photovoltaic panels, achieving accurate extraction of soil points under the photovoltaic panels. Simultaneously, target spectral information corresponding to each target soil point is extracted from the first point cloud data for subsequent normalization processing of multi-band echo intensity. This normalization processing of the echo intensity corresponding to the target soil point based on the target spectral information accurately determines the target echo intensity corresponding to the target soil point, thereby reducing brightness fluctuations caused by different scanning distances, platform postures, and local slopes. Furthermore, based on the target echo intensity corresponding to the target soil point, a target feature vector of the soil under the target photovoltaic panel is constructed. Since the target feature vector includes at least one of the following: echo intensity of the target soil point, normalization degree between the echo intensities of each target soil point, brightness variation between the echo intensities of each target soil point, and spectral variation degree between the echo intensities of each target soil point, it is convenient to use a rich combination of target feature vectors and combine at least two soil inversion models to accurately determine the target soil parameters reflecting the physicochemical properties of the soil. Finally, a spatial distribution map of the target area is generated based on all target soil parameters, realizing an effective quantitative assessment of the physicochemical properties of the soil under the photovoltaic panel, thereby achieving the observability and stability of soil data under shading conditions.

[0010] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1This is a flowchart of a method for monitoring soil under a photovoltaic panel according to an embodiment of the present invention; Figure 2 This is a flowchart of another method for monitoring soil under photovoltaic panels according to an embodiment of the present invention; Figure 3 This is an example diagram of the area division of the under-plate mask according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a soil monitoring device under a photovoltaic panel according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device for implementing the soil monitoring method under a photovoltaic panel according to an embodiment of the present invention. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0014] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0015] Example 1 Figure 1 This is a flowchart illustrating a method for monitoring soil under a photovoltaic panel according to an embodiment of the present invention. This embodiment is applicable to monitoring soil under photovoltaic panels. The method can be executed by a soil monitoring device under the photovoltaic panel, which can be implemented in hardware and / or software. This device can be configured in any electronic device with network communication capabilities. Figure 1 As shown, the soil monitoring method under photovoltaic panels of the present invention may include: S110. Obtain the first point cloud data of the target area, identify photovoltaic panels based on the first point cloud data, and obtain multiple target photovoltaic panels; the first point cloud data is three-dimensional point cloud data with spectral information; a photovoltaic panel array is deployed in the target area.

[0016] Specifically, the first point cloud data can be acquired using a mobile platform equipped with a multispectral lidar or hyperspectral lidar, thus enabling the obtained three-dimensional point cloud data to have spectral information. This eliminates the need to repeatedly perform multispectral scanning on the soil under the photovoltaic panels in the target area, greatly improving the data acquisition efficiency.

[0017] For example, the mobile platform could be a drone, equipped with a multispectral or hyperspectral lidar, which scans the target area along a preset scanning route. Simultaneously, it receives spectral information such as echo intensity, reflectivity, and wavelength bands reflected from different objects within the target area, as well as three-dimensional point cloud data to describe location information, thus forming the first point cloud data. Objects can include soil, vegetation, photovoltaic panels, and other objects covered by the target area.

[0018] Furthermore, after acquiring the first point cloud data of the target area and before identifying photovoltaic panels based on the first point cloud data, the method may further include: performing quality screening on the first point cloud data to obtain updated first point cloud data; wherein, the quality screening includes, but is not limited to, removing points with excessively low signal-to-noise ratio, echo saturation, or abnormal multi-band intensity.

[0019] Accordingly, photovoltaic panel identification based on the first point cloud data to obtain multiple target photovoltaic panels may include: performing Random Sampling Consensus Algorithm (RANSAC) plane fitting / region growing segmentation on the first point cloud data to obtain multiple planar segments. Based on the first point cloud data corresponding to each planar segment, the planar parameters of each planar segment are determined; wherein, the planar parameters include the planar area, the planar residual, multiple local planar normal vectors, and multiple local planar tilt angles. Then, the planar segments whose planar parameters meet preset conditions are determined as target photovoltaic panels. The preset conditions include the planar area being greater than a preset area, the planar residual being less than a preset residual, the concentration of local planar normal vectors meeting a preset concentration, and the similarity between the direction of the local planar tilt angle and the main direction of the array meeting a preset similarity. The principle of region growing segmentation can be understood as: achieving point cloud segmentation based on a region growing strategy, using normal vector consistency or spectral feature similarity as the growth criterion, gradually merging neighboring connected points from the seed point to generate independent segmented regions with spatial consistency and attribute consistency.

[0020] Optionally, to avoid mixing in flat surfaces such as rooftops, constraints such as "array periodic arrangement" and / or "support height range" can be used to update and check the target photovoltaic panels, ensuring the accuracy of the final multiple target photovoltaic panels.

[0021] S120. Based on the spatial arrangement characteristics of the target photovoltaic panel, the first point cloud data is mapped to determine the target soil points under the target photovoltaic panel, and the target spectral information corresponding to each target soil point is obtained; the target spectral information is extracted from the first point cloud data; the target spectral information includes echo intensity and reflectivity.

[0022] Among them, spatial arrangement characteristics can be understood as the photovoltaic panel's structural information, such as the size and area of ​​the photovoltaic panel, installation height, and tilt angle.

[0023] Specifically, the target photovoltaic panels are mapped onto the target ground plane according to their spatial arrangement characteristics. Then, the first point cloud data corresponding to the target ground plane is used as the target soil point under the target photovoltaic panel, and the target spectral information corresponding to each target soil point is obtained from the first point cloud data corresponding to the target ground plane.

[0024] S130. Based on the target spectral information, the echo intensity corresponding to the target soil point is normalized to determine the target echo intensity corresponding to the target soil point.

[0025] Specifically, there is a preset correlation between different echo intensities and reflectivities and the normalization coefficient. Based on the preset correlation and the target spectral information, the target normalization coefficient is determined. Based on the target normalization coefficient, the echo intensity corresponding to the target soil point is normalized to determine the target echo intensity corresponding to the target soil point.

[0026] In an embodiment of the present invention, optionally, normalizing the echo intensity corresponding to the target soil point based on the target spectral information to determine the target echo intensity corresponding to the target soil point may include steps A1-A2: Step A1: Determine the reflection intensity of the target soil point based on the reflectance in the target spectral information.

[0027] Specifically, the incident wave intensity corresponding to the target soil point is obtained, and the reflection intensity corresponding to the target soil point is determined based on the incident wave intensity and reflectivity; for example, the reflection intensity corresponding to the target soil point is the product of the incident wave intensity and the reflectivity.

[0028] The reflectance in the target spectral information can be divided into a first reflectance or a second reflectance. The first reflectance can be understood as the reflectance of the target soil point when a reflector is installed; the second reflectance can be understood as the reflectance of the target soil point when no reflector is installed.

[0029] Step A2: Determine the target echo intensity corresponding to the target soil point based on the reflection intensity corresponding to the target soil point and the echo intensity in the target spectral information corresponding to the target soil point.

[0030] Specifically, the echo intensity in the target spectral information corresponding to the target soil point. Reflection intensity corresponding to the target soil point The ratio of the two values ​​is determined as the target echo intensity corresponding to the target soil point. It can be expressed by the following formula: .

[0031] In this embodiment of the invention, the reflectance of the target soil point is determined based on the reflectance in the target spectral information corresponding to the target soil point. The echo intensity in the target spectral information corresponding to the target soil point is normalized based on the reflectance of the target soil point, thereby reducing the brightness fluctuations caused by differences in distance, attitude and local slope, ensuring the accuracy of the target echo intensity corresponding to the target soil point after normalization, and making the target echo intensity more statistically comparable.

[0032] Optionally, after determining the target echo intensity corresponding to the target soil point, the method further includes: determining the point mapped from the target soil point onto the target photovoltaic panel as a reference point, and determining the local normal vector at the reference point; determining the light incidence angle based on the local normal vector, updating the target echo intensity based on the light incidence angle, and determining the updated target echo intensity.

[0033] Specifically, based on the angle of incidence of light θ Determine the correction factor, and define the ratio of the target echo intensity to the correction factor as the updated target echo intensity; the updated target echo intensity This can be expressed using the following formula: .

[0034] In this embodiment of the invention, after determining the target echo intensity corresponding to the target soil point, the target echo intensity is updated based on the incident angle of the light, and the updated target echo intensity is determined to reduce the influence of ground slope on the target echo intensity.

[0035] Optionally, before normalizing the echo intensity corresponding to the target soil point based on the target spectral information to determine the target echo intensity corresponding to the target soil point, the method further includes: updating the target soil point based on the target height information, normal vector, and local roughness of the target point on the target photovoltaic panel corresponding to the location of the target soil point, thereby obtaining the updated target soil point and eliminating non-soil points such as supports, cables, and vegetation points. Further, a quantile regression strategy or outlier removal strategy is used to analyze the bands of the target soil point to obtain the updated target soil point, thereby eliminating outlier target soil points.

[0036] S140. Based on the target echo intensity corresponding to the target soil point, construct the target feature vector of the soil under the target photovoltaic panel; the target feature vector includes at least one of the following: echo intensity of the target soil point, normalization degree between the echo intensities of each target soil point, brightness variation between the echo intensities of each target soil point, and spectral variation degree between the echo intensities of each target soil point.

[0037] Specifically, the echo intensity of the target soil point can be the echo intensity of the target soil point corresponding to the preset sensitive band.

[0038] The normalization degree between the echo intensities of each target soil point can be expressed by the following formula: .

[0039] The brightness variation of the echo intensity between different target soil points can be expressed by the following formula: .

[0040] The degree of spectral variation in echo intensity between different target soil points can be expressed by the following formula: .

[0041] S150. Obtain at least two soil inversion models. Based on the soil inversion models and target feature vectors, determine the target soil parameters. Generate a spatial distribution map of the target area based on all target soil parameters. The soil inversion models are used to describe the mapping relationship between feature vectors and soil parameters. The soil parameters are used to reflect the physical and chemical properties of the soil.

[0042] The soil inversion model can be a ridge regression model, a partial least squares regression model (PLSR), a random forest model (RF), or a gradient boosting decision tree model (GBDT). The spatial distribution map includes the distribution of the target soil parameters for all target soil points corresponding to each target photovoltaic panel; that is, the spatial distribution map can reflect both the distribution of the physicochemical properties of the soil under each target photovoltaic panel and the distribution of the physicochemical properties of the soil in the entire target area.

[0043] Specifically, determining the target soil parameters based on the soil inversion model and the target feature vector may include: determining the first soil parameter corresponding to each soil inversion model based on each soil inversion model and the target feature vector; and determining the target soil parameter corresponding to each target feature vector based on all the first soil parameters corresponding to each target feature vector.

[0044] Accordingly, determining the target soil parameter corresponding to each target feature vector based on all the first soil parameters corresponding to each target feature vector may include: determining the target soil parameter corresponding to each target feature vector by taking the mean or weighted average of all the first soil parameters corresponding to each target feature vector.

[0045] The technical solution of this invention involves acquiring first point cloud data of a target area where a photovoltaic panel array is deployed, and then identifying multiple target photovoltaic panels based on the first point cloud data. The first point cloud data is three-dimensional point cloud data with spectral information, which can be used for subsequent inversion of multi-band echo intensity under the photovoltaic panels, significantly improving the availability of data in the area under the panels. Based on the spatial arrangement characteristics of the target photovoltaic panels, the first point cloud data is mapped to determine the target soil points under the photovoltaic panels, achieving accurate extraction of soil points under the photovoltaic panels. Simultaneously, target spectral information corresponding to each target soil point is extracted from the first point cloud data for subsequent normalization processing of multi-band echo intensity. This normalization processing of the echo intensity corresponding to the target soil point based on the target spectral information accurately determines the target echo intensity corresponding to the target soil point, thereby reducing brightness fluctuations caused by different scanning distances, platform postures, and local slopes. Furthermore, based on the target echo intensity corresponding to the target soil point, a target feature vector of the soil under the target photovoltaic panel is constructed. Since the target feature vector includes at least one of the following: echo intensity of the target soil point, normalization degree between the echo intensities of each target soil point, brightness variation between the echo intensities of each target soil point, and spectral variation degree between the echo intensities of each target soil point, it is convenient to use a rich combination of target feature vectors and combine at least two soil inversion models to accurately determine the target soil parameters reflecting the physicochemical properties of the soil. Finally, a spatial distribution map of the target area is generated based on all target soil parameters, realizing an effective quantitative assessment of the physicochemical properties of the soil under the photovoltaic panel, thereby achieving the observability and stability of soil data under shading conditions.

[0046] Example 2 Figure 2 This is a flowchart of another method for monitoring soil under photovoltaic panels provided by an embodiment of the present invention. The technical solution of this embodiment further optimizes the process of the method for monitoring soil under photovoltaic panels based on the above embodiments. This embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2 As shown, the soil monitoring method under photovoltaic panels of the present invention may include: S210. Obtain the first point cloud data of the target area, identify photovoltaic panels based on the first point cloud data, and obtain multiple target photovoltaic panels; the first point cloud data is three-dimensional point cloud data with spectral information; a photovoltaic panel array is deployed in the target area.

[0047] S220. Based on the spatial arrangement characteristics of the target photovoltaic panel, project the target photovoltaic panel to determine the mask under the target photovoltaic panel; according to the position information of the mask under the panel, extract the second point cloud data from the first point cloud data; map the second point cloud data onto the mask under the panel to obtain the target soil points under the target photovoltaic panel, and obtain the target spectral information corresponding to each target soil point; the target spectral information is extracted from the first point cloud data; the target spectral information includes echo intensity and reflectivity.

[0048] Optionally, projecting the target photovoltaic panel based on its spatial arrangement characteristics to determine the undermask of the target photovoltaic panel may include: projecting the target photovoltaic panel based on its spatial arrangement characteristics to generate a ground projection area; and expanding the projection area outward by a preset distance to determine the undermask of the target photovoltaic panel.

[0049] The preset distance can be set according to actual needs; for example, the preset distance can be selected between 0.2 and 2 meters. The preset distance can also be determined based on the height information and tilt angle of the target photovoltaic panel.

[0050] Optionally, after determining the under-mask of the target photovoltaic panel, the method further includes: dividing the under-mask into a droplet zone, a transition zone, and a center zone based on the distance from the edge of the under-mask; the droplet zone is the region from the edge of the under-mask to a first position; the transition zone is the region from the first position to a second position; the center zone is the region from the second position to the center of the under-mask; a first distance separates the first position from the edge of the under-mask; a second distance separates the second position from the edge of the under-mask; the first distance is less than the second distance. For example, such as... Figure 3 The diagram shows an example of the droplet zone, transition zone, and center zone of the mask under the plate.

[0051] S230. Based on the target spectral information, the echo intensity corresponding to the target soil point is normalized to determine the target echo intensity corresponding to the target soil point.

[0052] S240. Based on the target echo intensity corresponding to the target soil point, construct the target feature vector of the soil under the target photovoltaic panel; the target feature vector includes at least one of the following: echo intensity of the target soil point, normalization degree between the echo intensities of each target soil point, brightness variation between the echo intensities of each target soil point, and spectral variation degree between the echo intensities of each target soil point.

[0053] S250. Obtain at least two soil inversion models. Based on the soil inversion models and target feature vectors, determine the target soil parameters. Generate a spatial distribution map of the target area based on all target soil parameters. The soil inversion models are used to describe the mapping relationship between feature vectors and soil parameters. The soil parameters are used to reflect the physical and chemical properties of the soil.

[0054] Among them, the physical and chemical properties of soil can be soil volumetric water content (VWC), salinity / electric conductivity (EC) and organic matter (OM / SOC) and other physical and chemical characteristics.

[0055] In an embodiment of the present invention, optionally, generating a spatial distribution map of the target area based on all target soil parameters may include steps B1-B5: Step B1: Divide the under-panel mask of the target photovoltaic panel into a preset number of target grids, and determine the grid soil parameters corresponding to the target grids based on all the target soil parameters within the target grids.

[0056] Specifically, the median, mean, or weighted average of all target soil parameters within the target grid is determined as the corresponding grid soil parameter.

[0057] Step B2: Based on all grid soil parameters, determine the first spatial distribution map corresponding to the target photovoltaic panel.

[0058] Specifically, based on the spatial location information corresponding to the grid soil parameters, the first spatial distribution map corresponding to the target photovoltaic panel is determined.

[0059] Step B3: Based on the target soil parameters corresponding to the target photovoltaic panel, determine the soil difference parameters between the target soil parameters corresponding to each pair of the drip zone, transition zone and central zone of the mask under the target photovoltaic panel.

[0060] Specifically, the differences between the target soil parameters of the dripping zone of the mask under the target photovoltaic panel and the target soil parameters of the transition zone are determined as multiple first soil difference parameters between the dripping zone and the transition zone of the mask under the target photovoltaic panel; the position of the first soil difference parameter corresponds to the position of the target soil parameter of the dripping zone. The differences between the target soil parameters of the dripping zone of the mask under the target photovoltaic panel and the target soil parameters of the central zone are determined as multiple second soil difference parameters between the dripping zone and the central zone of the mask under the target photovoltaic panel; the position of the second soil difference parameter corresponds to the position of the target soil parameter of the dripping zone. The differences between the target soil parameters in the central zone and the target soil parameters in the transition zone of the mask under the target photovoltaic panel are determined as multiple third soil difference parameters between the central zone and the transition zone of the mask under the target photovoltaic panel; the position of the third soil difference parameter corresponds to the position of the target soil parameter in the central zone. The differences between the target soil parameters of the transition zone of the mask under the target photovoltaic panel and the target soil parameters of the drip zone are determined as multiple fourth soil difference parameters between the drip zone and the transition zone of the mask under the target photovoltaic panel; the position of the fourth soil difference parameter corresponds to the position of the target soil parameter of the transition zone. The differences between the target soil parameters in the central zone of the mask under the target photovoltaic panel and the target soil parameters in the drip zone are determined as multiple fifth soil difference parameters between the drip zone and the central zone of the mask under the target photovoltaic panel; the position of the fifth soil difference parameter corresponds to the position of the target soil parameter in the central zone. The differences between the target soil parameters of the transition zone and the target soil parameters of the mask under the target photovoltaic panel are determined as multiple sixth soil difference parameters between the center zone and the transition zone of the mask under the target photovoltaic panel; the position of the sixth soil difference parameter corresponds to the position of the target soil parameter in the transition zone. Furthermore, all first soil difference parameters, all second soil difference parameters, all third soil difference parameters, all fourth soil difference parameters, all fifth soil difference parameters, and all sixth soil difference parameters are identified as all soil difference parameters of the target photovoltaic panel.

[0061] Step B4: Based on soil difference parameters, determine the second spatial distribution map corresponding to the target photovoltaic panel.

[0062] Specifically, the second spatial distribution map corresponding to the target photovoltaic panel is determined based on the location information of soil difference parameters.

[0063] Step B5: Based on the first and second spatial distribution maps corresponding to all target photovoltaic panels in the target area, construct a spatial distribution map of the target area.

[0064] Specifically, the first and second spatial distribution maps corresponding to the target photovoltaic panels are merged and filled according to the location information to obtain the spatial distribution map of the target photovoltaic panels. Then, the spatial distribution maps of all the target photovoltaic panels in the target area are combined to determine the spatial distribution map of the target area.

[0065] In this embodiment of the invention, the undermask of a target photovoltaic panel is divided into a predetermined number of target grids. Based on all target soil parameters within each grid, the corresponding grid soil parameters are determined. A first spatial distribution map corresponding to the target photovoltaic panel is then determined based on all grid soil parameters, thereby accurately locating the distribution of individual soil parameters. Based on the target soil parameters corresponding to the target photovoltaic panel, soil difference parameters are determined between each pair of target soil parameters in the drip zone, transition zone, and central zone of the undermask. Based on these soil difference parameters, a second spatial distribution map corresponding to the target photovoltaic panel is determined, thereby accurately locating the changes in soil parameters at different locations. Furthermore, based on the first and second spatial distribution maps corresponding to all target photovoltaic panels in the target area, a spatial distribution map of the target area is constructed. This integrates the distribution of individual soil parameters with the changes in soil parameters at different locations, allowing for a clear and intuitive reflection of various changes within a single spatial distribution map. This provides a more readily applicable quantitative basis for subsequent inspection, early warning, and refined operation and maintenance.

[0066] Optionally, in this embodiment of the invention, after determining the target soil parameters based on the soil inversion model and the target feature vector, the method may further include: acquiring soil parameter pairs at the same location in the target area at different time periods; the soil parameter pair includes a second soil parameter and a third soil parameter; the second soil parameter is the soil parameter of the first time period; the third soil parameter is the soil parameter of the first time period; both the second and third soil parameters can be obtained using the photovoltaic panel under-soil monitoring method of the present invention. The second and third soil parameters are differentially analyzed to determine the parameter change of the soil parameter pair; a parameter change curve for the target area is constructed based on the parameter change; the parameter change curve represents the change of soil parameters fluctuating over time, enabling comparison of soil parameters across time phases to support operation and maintenance inspections, risk warnings, and remediation assessments at different time periods.

[0067] The technical solution of this invention involves acquiring first point cloud data of a target area where a photovoltaic panel array is deployed, and identifying multiple target photovoltaic panels based on the first point cloud data. The first point cloud data is three-dimensional point cloud data with spectral information, which can be used for subsequent inversion of multi-band echo intensity under the photovoltaic panel, significantly improving the availability of data in the area under the panel. Based on the spatial arrangement characteristics of the target photovoltaic panels, the target photovoltaic panels are projected to determine the mask under the target photovoltaic panels. According to the position information of the mask under the panels, second point cloud data is extracted from the first point cloud data. The second point cloud data is mapped onto the mask under the panels to obtain target soil points under the target photovoltaic panels. This achieves accurate extraction of soil points under the photovoltaic panels by combining the interference of strong reflections consistent with the structure of the photovoltaic panels. At the same time, target spectral information corresponding to each target soil point is extracted from the first point cloud data to facilitate subsequent normalization processing of multi-band echo intensity. This achieves normalization processing of the echo intensity corresponding to the target soil point based on the target spectral information, thereby accurately determining the target echo intensity corresponding to the target soil point, and reducing brightness fluctuations caused by different scanning distances, platform postures, and local slopes. Furthermore, based on the target echo intensity corresponding to the target soil point, a target feature vector of the soil under the target photovoltaic panel is constructed. Since the target feature vector includes at least one of the following: echo intensity of the target soil point, normalization degree between the echo intensities of each target soil point, brightness variation between the echo intensities of each target soil point, and spectral variation degree between the echo intensities of each target soil point, it is convenient to use a rich combination of target feature vectors and combine at least two soil inversion models to accurately determine the target soil parameters reflecting the physicochemical properties of the soil. Finally, a spatial distribution map of the target area is generated based on all target soil parameters, realizing an effective quantitative assessment of the physicochemical properties of the soil under the photovoltaic panel. That is, this invention can obtain a stable multi-band echo response in the long-term shadow area under the photovoltaic panel without relying on changes in solar irradiance and atmospheric transmittance, significantly improving the data availability and cross-temporal consistency of the area under the panel, that is, realizing the observability and stability of soil data under shading conditions.

[0068] Example 3 Figure 4 This is a schematic diagram of a soil monitoring device under a photovoltaic panel provided in an embodiment of the present invention. This embodiment is applicable to monitoring the soil under a photovoltaic panel. The soil monitoring device can be implemented in hardware and / or software, and can be configured in any electronic device with network communication capabilities. Figure 4 As shown, the soil monitoring device under the photovoltaic panel of the present invention may include: The identification module 310 is used to acquire first point cloud data of the target area, identify photovoltaic panels based on the first point cloud data, and obtain multiple target photovoltaic panels; the first point cloud data is three-dimensional point cloud data with spectral information; the target area is equipped with a photovoltaic panel array; The soil point determination module 320 is used to map the first point cloud data based on the spatial arrangement characteristics of the target photovoltaic panel to determine the target soil points under the target photovoltaic panel, and to obtain the target spectral information corresponding to each target soil point; the target spectral information is extracted from the first point cloud data; the target spectral information includes echo intensity and reflectivity; The normalization processing module 330 is used to normalize the echo intensity corresponding to the target soil point based on the target spectral information, and determine the target echo intensity corresponding to the target soil point. The feature determination module 340 is used to construct a target feature vector of the soil under the target photovoltaic panel based on the target echo intensity corresponding to the target soil point; the target feature vector includes at least one of the echo intensity of the target soil point, the normalization degree between the echo intensities of each target soil point, the brightness variation between the echo intensities of each target soil point, and the spectral variation degree between the echo intensities of each target soil point. The soil parameter determination module 350 is used to acquire at least two soil inversion models, determine target soil parameters based on the soil inversion models and the target feature vectors, and generate a spatial distribution map of the target area based on all the target soil parameters; the soil inversion models are used to describe the mapping relationship between the feature vectors and the soil parameters; the soil parameters are used to reflect the physicochemical properties of the soil.

[0069] Based on the above embodiments, optionally, the soil point determination module includes a projection unit, a data extraction unit, and a data mapping unit. The projection unit is used to project the target photovoltaic panel based on the spatial arrangement characteristics of the target photovoltaic panel to determine the under-panel mask of the target photovoltaic panel. The data extraction unit is used to extract second point cloud data from the first point cloud data according to the position information of the under-panel mask. The data mapping unit is used to map the second point cloud data onto the under-panel mask to obtain the target soil points under the target photovoltaic panel.

[0070] Based on the above embodiments, optionally, the projection unit is used to: project the target photovoltaic panel based on the spatial arrangement characteristics of the target photovoltaic panel to generate a ground projection area; and expand the projection area outward by a preset distance to determine the under-panel mask of the target photovoltaic panel.

[0071] Optionally, based on the above embodiments, the preset distance is determined according to the height information and tilt angle of the target photovoltaic panel.

[0072] Based on the above embodiments, optionally, the normalization processing module is used to determine the reflection intensity corresponding to the target soil point based on the reflectance in the target spectral information corresponding to the target soil point; and to determine the target echo intensity corresponding to the target soil point based on the reflection intensity corresponding to the target soil point and the echo intensity in the target spectral information corresponding to the target soil point.

[0073] Optionally, based on the above embodiments, the device further includes an update module, which is used to determine, after determining the target echo intensity corresponding to the target soil point, the point mapped by the target soil point on the target photovoltaic panel as a reference point, and determine the local normal vector at the reference point; determine the light incident angle based on the local normal vector, update the target echo intensity based on the light incident angle, and determine the updated target echo intensity.

[0074] Based on the above embodiments, optionally, the soil parameter determination module is used to determine the first soil parameter corresponding to each soil inversion model based on each soil inversion model and the target feature vector; and to determine the target soil parameter corresponding to each target feature vector based on all the first soil parameters corresponding to each target feature vector.

[0075] Optionally, based on the above embodiments, the device further includes an under-mask division module. This module, after determining the under-mask of the target photovoltaic panel, divides the under-mask into a droplet zone, a transition zone, and a center zone based on the distance from the edge of the under-mask. The droplet zone is the area from the edge of the under-mask to a first position; the transition zone is the area from the first position to a second position; and the center zone is the area from the second position to the center of the under-mask. A first distance separates the first position from the edge of the under-mask; a second distance separates the second position from the edge of the under-mask; and the first distance is less than the second distance.

[0076] Based on the above embodiments, optionally, the soil parameter determination module includes a distribution map determination unit. The distribution map determination unit is used to divide the undermask of the target photovoltaic panel into a preset number of target grids; determine the grid soil parameters corresponding to the target grids based on all target soil parameters within the target grids; determine a first spatial distribution map corresponding to the target photovoltaic panel based on all the grid soil parameters; determine soil difference parameters between the corresponding target soil parameters of the drip zone, transition zone, and central zone of the undermask of the target photovoltaic panel based on the target soil parameters; determine a second spatial distribution map corresponding to the target photovoltaic panel based on the soil difference parameters; and construct a spatial distribution map of the target area based on the first spatial distribution map and the second spatial distribution map corresponding to all the target photovoltaic panels in the target area.

[0077] Optionally, based on the above embodiments, the device further includes a parameter variation curve determination module. This module is used to obtain soil parameter pairs located at the same position in the target area at different time periods after determining the target soil parameters based on the soil inversion model and the target feature vector. The soil parameter pairs include a second soil parameter and a third soil parameter. The second soil parameter and the third soil parameter are differentiated to determine the parameter variation of the soil parameter pair. Based on the parameter variation, a parameter variation curve for the target area is constructed. The parameter variation curve represents the change of soil parameters over time.

[0078] The soil monitoring device under the photovoltaic panel provided in this embodiment of the invention can execute the soil monitoring method under the photovoltaic panel provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0079] Example 4 According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0080] Figure 5 A schematic diagram of an electronic device that can be used to implement the soil monitoring method under photovoltaic panels according to embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0081] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0082] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0083] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the soil monitoring method under photovoltaic panels.

[0084] In some embodiments, the soil monitoring method under a photovoltaic panel can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via read-only memory (ROM) 12 and / or communication unit 19. When the computer program is loaded into random access memory (RAM) 13 and executed by processor 11, one or more steps of the soil monitoring method under a photovoltaic panel described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the soil monitoring method under a photovoltaic panel by any other suitable means (e.g., by means of firmware).

[0085] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0086] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0087] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0088] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0089] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0090] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0091] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0092] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for monitoring soil under photovoltaic panels, characterized in that, The method includes: The first point cloud data of the target area is acquired, and photovoltaic panel identification is performed based on the first point cloud data to obtain multiple target photovoltaic panels; the first point cloud data is three-dimensional point cloud data with spectral information; the target area is deployed with a photovoltaic panel array. Based on the spatial arrangement characteristics of the target photovoltaic panel, the first point cloud data is mapped to determine the target soil points under the target photovoltaic panel, and the target spectral information corresponding to each target soil point is obtained; the target spectral information is extracted from the first point cloud data; the target spectral information includes echo intensity and reflectivity; Based on the target spectral information, the echo intensity corresponding to the target soil point is normalized to determine the target echo intensity corresponding to the target soil point. Based on the target echo intensity corresponding to the target soil point, a target feature vector of the soil under the target photovoltaic panel is constructed; the target feature vector includes at least one of the echo intensity of the target soil point, the normalization degree between the echo intensities of each target soil point, the brightness variation between the echo intensities of each target soil point, and the spectral variation degree between the echo intensities of each target soil point. At least two soil inversion models are acquired. Based on the soil inversion models and the target feature vectors, target soil parameters are determined. A spatial distribution map of the target area is generated based on all the target soil parameters. The soil inversion models are used to describe the mapping relationship between the feature vectors and the soil parameters. The soil parameters are used to reflect the physicochemical properties of the soil.

2. The method according to claim 1, characterized in that, Based on the spatial arrangement characteristics of the target photovoltaic panel, the first point cloud data is mapped to determine the target soil points under the target photovoltaic panel, including: Based on the spatial arrangement characteristics of the target photovoltaic panel, the target photovoltaic panel is projected to determine the under-panel mask of the target photovoltaic panel; Based on the position information of the under-plate mask, extract the second point cloud data from the first point cloud data; The second point cloud data is mapped onto the mask under the panel to obtain the target soil point under the target photovoltaic panel.

3. The method according to claim 2, characterized in that, Based on the spatial arrangement characteristics of the target photovoltaic panel, the target photovoltaic panel is projected to determine the under-panel mask of the target photovoltaic panel, including: Based on the spatial arrangement characteristics of the target photovoltaic panel, the target photovoltaic panel is projected to generate a ground projection area; The projection area is expanded outward by a preset distance to determine the underside mask of the target photovoltaic panel.

4. The method according to claim 3, characterized in that, The preset distance is determined based on the height information and tilt angle of the target photovoltaic panel.

5. The method according to claim 1, characterized in that, Based on the target spectral information, the echo intensity corresponding to the target soil point is normalized to determine the target echo intensity corresponding to the target soil point, including: The reflection intensity corresponding to the target soil point is determined based on the reflectance in the target spectral information corresponding to the target soil point. The target echo intensity corresponding to the target soil point is determined based on the reflection intensity corresponding to the target soil point and the echo intensity in the target spectral information corresponding to the target soil point.

6. The method according to claim 1 or 5, characterized in that, After determining the target echo intensity corresponding to the target soil point, the method further includes: The point on the target photovoltaic panel mapped from the target soil point is determined as the reference point, and the local normal vector at the reference point is determined. The incident angle of the light ray is determined based on the local normal vector, and the target echo intensity is updated based on the incident angle of the light ray to determine the updated target echo intensity.

7. The method according to claim 1, characterized in that, Obtain at least two soil inversion models, and determine the target soil parameters based on the soil inversion models and the target feature vector, including: Based on each soil inversion model and the target feature vector, determine the first soil parameter corresponding to each soil inversion model; Based on all the first soil parameters corresponding to each target feature vector, the target soil parameters corresponding to each target feature vector are determined.

8. The method according to claim 3, characterized in that, After determining the under-panel mask of the target photovoltaic panel, the method further includes: Based on the distance from the edge of the under-plate mask, the under-plate mask is divided into a drop zone, a transition zone, and a center zone; the drop zone is the area from the edge of the under-plate mask to a first position; the transition zone is the area from the first position to a second position; the center zone is the area from the second position to the center of the under-plate mask; the first position is spaced apart from the edge of the under-plate mask by a first distance; the second position is spaced apart from the edge of the under-plate mask by a second distance; the first distance is less than the second distance.

9. The method according to claim 8, characterized in that, A spatial distribution map of the target area is generated based on all the aforementioned target soil parameters, including: The mask under the target photovoltaic panel is divided into a preset number of target grids, and the grid soil parameters corresponding to the target grids are determined based on all the target soil parameters within the target grids. Based on all the grid soil parameters, a first spatial distribution map corresponding to the target photovoltaic panel is determined; Based on the target soil parameters corresponding to the target photovoltaic panel, determine the soil difference parameters between the target soil parameters corresponding to each pair of the dripping zone, transition zone and central zone of the mask under the target photovoltaic panel; Based on the soil difference parameters, a second spatial distribution map corresponding to the target photovoltaic panel is determined; Based on the first spatial distribution map and the second spatial distribution map corresponding to all the target photovoltaic panels in the target area, a spatial distribution map of the target area is constructed.

10. The method according to claim 1, characterized in that, After determining the target soil parameters based on the soil inversion model and the target feature vector, the method further includes: Obtain soil parameter pairs at the same location in the target area at different time periods; the soil parameter pairs include a second soil parameter and a third soil parameter; The second soil parameter and the third soil parameter are differentially analyzed to determine the parameter change of the soil parameter pair; Based on the parameter changes, a parameter change curve for the target area is constructed; the parameter change curve represents the changes in soil parameters over time.

11. A soil monitoring device under a photovoltaic panel, characterized in that, The device includes: The identification module is used to acquire first point cloud data of the target area, and to identify photovoltaic panels based on the first point cloud data to obtain multiple target photovoltaic panels; the first point cloud data is three-dimensional point cloud data with spectral information; the target area is equipped with a photovoltaic panel array. The soil point determination module is used to map the first point cloud data based on the spatial arrangement characteristics of the target photovoltaic panel to determine the target soil points under the target photovoltaic panel, and to obtain the target spectral information corresponding to each target soil point; the target spectral information is extracted from the first point cloud data; the target spectral information includes echo intensity and reflectivity; The normalization processing module is used to normalize the echo intensity corresponding to the target soil point based on the target spectral information, and determine the target echo intensity corresponding to the target soil point. The feature determination module is used to construct a target feature vector of the soil under the target photovoltaic panel based on the target echo intensity corresponding to the target soil point; the target feature vector includes at least one of the echo intensity of the target soil point, the normalization degree between the echo intensities of each target soil point, the brightness variation between the echo intensities of each target soil point, and the spectral variation degree between the echo intensities of each target soil point. The soil parameter determination module is used to acquire at least two soil inversion models, determine target soil parameters based on the soil inversion models and the target feature vectors, and generate a spatial distribution map of the target area based on all the target soil parameters; the soil inversion models are used to describe the mapping relationship between the feature vectors and the soil parameters; the soil parameters are used to reflect the physicochemical properties of the soil.

12. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the soil monitoring method under the photovoltaic panel according to any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for monitoring soil under a photovoltaic panel as described in any one of claims 1-10.

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