Method and device for detecting light energy loss of vegetation, electronic equipment and storage medium

Abstract

The application relates to a vegetation light energy loss detection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring point cloud data of a real sample plot; establishing a virtual sample plot according to the point cloud data; simulating light radiation on the virtual sample plot; calculating a first light energy value received by target virtual vegetation in the virtual sample plot when the target virtual vegetation is shaded by adjacent virtual vegetation; removing the adjacent virtual vegetation in the virtual sample plot, and calculating a second light energy value received by the target virtual vegetation; and obtaining a light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value. The application simulates light radiation in the virtual sample plot, respectively calculates light energy values of the target virtual vegetation when the target virtual vegetation is shaded by adjacent virtual vegetation or not, and obtains a light energy loss value, so that the light energy loss caused by the target vegetation due to shading by adjacent vegetation is quantified, a measuring device is not needed, an indirect index is not needed, and the accuracy of the light energy loss value is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vegetation monitoring, in particular to a vegetation light energy loss detection method and device, an electronic device and a storage medium. BACKGROUND

[0002] In a vegetation community, the solar light energy received by a single vegetation will cause light energy loss due to the shadow generated by adjacent vegetation. In some methods, the influence of the shadow is measured by relying on indirect indicators (such as crop yield), and the light energy loss value cannot be quantitatively obtained. In some methods, field observation equipment is used to measure the light energy loss value of the vegetation, but due to the influence of environmental complexity and the limitation of the measurement equipment, the accuracy and comprehensiveness of the data are difficult to guarantee. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a vegetation light energy loss detection method and device, an electronic device and a storage medium, which can quantitatively obtain the light energy loss of the target vegetation caused by the shadow of the adjacent vegetation, and improve the accuracy of the light energy loss value.

[0004] According to a first aspect of an embodiment of the present application, a vegetation light energy loss detection method is provided, comprising the following steps:

[0005] Obtaining point cloud data of a real sample plot; wherein the point cloud data comprises a first point cloud of a target vegetation, a second point cloud of adjacent vegetation located around the target vegetation, and a third point cloud of a topography where the target vegetation and the adjacent vegetation are located;

[0006] Establishing a virtual sample plot according to the point cloud data; wherein the virtual sample plot comprises a target virtual vegetation corresponding to the target vegetation, adjacent virtual vegetation corresponding to the adjacent vegetation, and a virtual topography corresponding to the topography;

[0007] Performing light radiation simulation on the virtual sample plot;

[0008] Calculating a first light energy value received by the target virtual vegetation in the virtual sample plot when the adjacent virtual vegetation is shaded; removing the adjacent virtual vegetation in the virtual sample plot, and calculating a second light energy value received by the target virtual vegetation in the virtual sample plot;

[0009] Obtaining a light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value.

[0010] According to a second aspect of an embodiment of the present application, a vegetation light energy loss detection device is provided, comprising:

[0011] A point cloud data acquisition module is configured to obtain point cloud data of a real sample plot; wherein the point cloud data comprises a first point cloud of a target vegetation, a second point cloud of adjacent vegetation located around the target vegetation, and a third point cloud of a topography where the target vegetation and the adjacent vegetation are located;

[0012] a virtual sample plot establishing module configured to establish a virtual sample plot according to the point cloud data, wherein the virtual sample plot comprises target virtual vegetation corresponding to the target vegetation, adjacent virtual vegetation corresponding to the adjacent vegetation, and virtual terrain corresponding to the terrain;

[0013] a light radiation simulation module configured to simulate light radiation on the virtual sample plot;

[0014] a light energy value calculation module configured to calculate a first light energy value of the target virtual vegetation in the virtual sample plot when the target virtual vegetation is shaded by the adjacent virtual vegetation, and to calculate a second light energy value of the target virtual vegetation in the virtual sample plot after the adjacent virtual vegetation is removed from the virtual sample plot;

[0015] a light energy loss value obtaining module configured to obtain a light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value.

[0016] According to a third aspect of the embodiments of the present application, an electronic device is provided, comprising a processor and a memory, wherein the memory stores a computer program which is adapted to be loaded and executed by the processor to perform the steps of the method of the first aspect.

[0017] According to a fourth aspect of the embodiments of the present application, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method of the first aspect.

[0018] The embodiments of the present application obtain the point cloud data of the real sample plot, establish a virtual sample plot according to the point cloud data, simulate light radiation on the virtual sample plot, calculate a first light energy value of the target virtual vegetation in the virtual sample plot when the target virtual vegetation is shaded by the adjacent virtual vegetation, remove the adjacent virtual vegetation from the virtual sample plot, calculate a second light energy value of the target virtual vegetation in the virtual sample plot, and obtain a light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value. The embodiments of the present application simulate light radiation on the virtual sample plot, calculate the light energy values of the target virtual vegetation when the target virtual vegetation is shaded by the adjacent virtual vegetation and when the target virtual vegetation is not shaded by the adjacent virtual vegetation, and obtain the light energy loss value, thereby quantifying the light energy loss of the target vegetation caused by the shading of the adjacent vegetation, without using measuring equipment and without relying on indirect indicators, and the accuracy of the light energy loss value is improved.

[0019] It should be understood that the general description above and the detailed description below are only exemplary and explanatory, and cannot limit the present application.

[0020] In order to better understand and implement, the present application is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1A flowchart of a method for detecting loss of light energy of vegetation according to an embodiment of the present application is shown in FIG. 1.

[0022] Figure 2 A structural block diagram of a device for detecting loss of light energy of vegetation according to an embodiment of the present application is shown in FIG. 2.

[0023] Figure 3 A structural schematic block diagram of an electronic device according to an embodiment of the present application is shown in FIG. 3. DETAILED DESCRIPTION

[0024] In order to make the objectives, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0025] It should be clear that the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0026] The terms used in the embodiments of the present application are only for the purpose of describing the specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms "a", "an" and "the" used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein means and includes any or all possible combinations of one or more associated listed items.

[0027] The following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments are not intended to represent all implementations consistent with the present application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not necessarily describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0028] In addition, in the description of the present application, "multiple" means two or more, unless otherwise specified. "And / or" describes the association between the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally represents that the associated objects before and after are in an "or" relationship.

[0029] Please refer to Figure 1, which is a flowchart of a vegetation light energy loss detection method provided in an embodiment of the present application. The vegetation light energy loss detection method provided in the embodiment of the present application comprises the following steps:

[0030] S10: Obtain point cloud data of a real plot; wherein the point cloud data comprises first point cloud of target vegetation, second point cloud of adjacent vegetation located around the target vegetation, and third point cloud of a topography where the target vegetation and the adjacent vegetation are located.

[0031] The real plot refers to a typical plot for studying vegetation in ecology, which is usually set in the center of a vegetation community to avoid transition zones.

[0032] The target vegetation is vegetation in the real plot to be detected for light energy loss. The adjacent vegetation is vegetation in a preset area centered on the target vegetation. When sunlight shines, the shadow of the adjacent vegetation will block the target vegetation, forming shade for the target vegetation.

[0033] In the embodiment of the present application, the Terrestrial Laser Scanning (TLS) technology is used to scan the real plot to obtain the point cloud data of the real plot.

[0034] S20: Establish a virtual plot according to the point cloud data; wherein the virtual plot comprises target virtual vegetation corresponding to the target vegetation, adjacent virtual vegetation corresponding to the adjacent vegetation, and virtual topography corresponding to the topography.

[0035] The virtual plot is a virtual model constructed based on real plot data, which is used to reproduce the spatial structure and characteristics of vegetation and its environment in the real plot.

[0036] In the embodiment of the present application, the point cloud data is input into virtual simulation software to establish the virtual plot in a virtual simulation environment.

[0037] S30: Perform light radiation simulation on the virtual plot.

[0038] In the embodiment of the present application, the Digital Terrain Model (DTM) and the solar trajectory algorithm are used to simulate the solar radiation of the virtual plot at different times and seasons.

[0039] S40: Calculate a first light energy value received by the target virtual vegetation in the virtual plot when the adjacent virtual vegetation shades; remove the adjacent virtual vegetation in the virtual plot to calculate a second light energy value received by the target virtual vegetation in the virtual plot.

[0040] In the embodiments of the present application, the solar energy received by the target vegetation with and without the shading of the adjacent vegetation is calculated by using the computational virtual measurement (CVM) technology. The CVM technology is a method of processing raw data by simulating the physical behavior of a measuring instrument in a virtual space, instead of using a traditional mathematical model. This technology avoids the pre-defined model of the measured object (such as vegetation), eliminating the deviation between the real object and the model object. The technology focuses on the objectivity at the algorithm level, measuring the vegetation parameters through physical simulation (such as water level displacement method). It does not need to predefine the shape or calibration and verification procedures, because the measurement is based on the repeated process, rather than relying on a predictive mathematical model.

[0041] S50: Obtain the light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value.

[0042] In the embodiments of the present application, the second light energy value is subtracted from the first light energy value to obtain the light energy loss value of the target virtual vegetation.

[0043] By applying the embodiments of the present application, the point cloud data of the real sample plot is obtained; the virtual sample plot is established according to the point cloud data; the light radiation simulation of the virtual sample plot is performed; the first light energy value received by the target virtual vegetation in the virtual sample plot when the adjacent virtual vegetation is shaded is calculated; the adjacent virtual vegetation in the virtual sample plot is removed, and the second light energy value received by the target virtual vegetation in the virtual sample plot is calculated; and the light energy loss value of the target virtual vegetation is obtained according to the first light energy value and the second light energy value. By performing the light radiation simulation in the virtual sample plot, the light energy values of the target virtual vegetation with and without the shading of the adjacent virtual vegetation are calculated, and the light energy loss value is obtained, so that the light energy loss of the target vegetation caused by the shading of the adjacent vegetation is quantified, without using measuring equipment and without relying on indirect indicators, thereby improving the accuracy of the light energy loss value.

[0044] In one embodiment, step S20 includes steps S21-S23, which are as follows:

[0045] S21: Perform data cleaning on the point cloud data to obtain cleaned point cloud data.

[0046] The data cleaning includes detecting noise points and outlier points, and deleting and correcting these points.

[0047] In the embodiments of the present application, the point cloud data is cleaned by using a point cloud filtering algorithm to obtain cleaned point cloud data. The point cloud filtering algorithm includes but is not limited to radius filtering, mean filtering, moving least squares filtering, and Gaussian filtering algorithm.

[0048] S22: performing terrain recognition and vegetation recognition on the cleaned point cloud data to obtain terrain feature data and morphological feature data of a plurality of vegetation; wherein the plurality of vegetation includes target vegetation and adjacent vegetation.

[0049] The terrain feature data includes, but is not limited to, altitude, slope, and slope direction.

[0050] The morphological feature data includes the contour, structure, height, and width of the vegetation.

[0051] In the embodiments of the present application, the semantic segmentation method is used to perform vegetation recognition and terrain recognition on the cleaned point cloud data to obtain terrain feature data and morphological feature data of a plurality of vegetation.

[0052] S23: establishing a virtual sample plot according to the morphological feature data and the terrain feature data.

[0053] In the embodiments of the present application, the morphological feature data and the terrain feature data are input into virtual simulation software to establish a virtual sample plot.

[0054] Through data cleaning of the point cloud data, the quality of the point cloud data can be improved, thereby improving the accuracy of the virtual sample plot.

[0055] In one embodiment, step S23 includes steps S231-S232, which are specifically as follows:

[0056] S231: using a preset vegetation modeling method to obtain target virtual vegetation and adjacent virtual vegetation according to the morphological feature data.

[0057] The preset vegetation modeling method includes, but is not limited to, a voxel modeling method, a quantitative structure model (QSM) method, and a context capture center (CCC) method.

[0058] In the embodiments of the present application, a preset vegetation modeling method is used to perform three-dimensional modeling on the target vegetation and the adjacent vegetation according to the morphological feature data, to obtain target virtual vegetation corresponding to the target vegetation and adjacent virtual vegetation corresponding to the adjacent vegetation.

[0059] S232: using an irregular triangle mesh method to model the terrain according to the terrain feature data to obtain a virtual terrain.

[0060] Among them, the Triangulated Irregular Network (TIN) method is a method for representing a terrain surface or other irregular spatial data, which approximates the real surface by constructing a triangular network.

[0061] In the embodiment of the present application, the irregular triangular network method is used to perform three-dimensional modeling on the terrain where the target vegetation and the adjacent vegetation are located according to the terrain feature data, and obtain the virtual terrain.

[0062] In one embodiment, step S231 includes step S2311, which is specifically as follows:

[0063] S2311: voxelizing the morphological feature data to model the three-dimensional structure of the target vegetation and the adjacent vegetation, the target virtual vegetation and the adjacent virtual vegetation.

[0064] Among them, voxelization refers to the process of converting a discrete point cloud into a regular 3D grid, and each voxel (cubic unit) contains spatial position and attribute information.

[0065] In the embodiment of the present application, the morphological feature data is input into a point cloud voxelization processing tool to obtain the target virtual vegetation and the adjacent virtual vegetation. The point cloud voxelization processing tool can be an open source software Cloud Compare.

[0066] In one embodiment, step S231 includes steps S2312-S2313, which are specifically as follows:

[0067] S2312: extracting the stems and branches of the target vegetation and the stems and branches of the adjacent vegetation from the morphological feature data;

[0068] S2313: using the least square method to respectively perform cylindrical parameter optimization fitting on the stems and branches of the target vegetation and the stems and branches of the adjacent vegetation to obtain the target virtual vegetation and the adjacent virtual vegetation.

[0069] In the embodiment of the present application, the stems and branches of the target vegetation and the stems and branches of the adjacent vegetation are respectively parameterized as cylinders to obtain the target virtual vegetation and the adjacent virtual vegetation. Specifically, in the cylindrical parameter optimization fitting, the least square method is used to fit the center line, radius and direction of the cylinder, which is realized by constructing a cost function and minimizing it.

[0070] In one embodiment, step S30 includes steps S31-S32, which are specifically as follows:

[0071] S31: obtaining the actual sunlight irradiation direction of the real plot.

[0072] In the embodiment of the present application, the actual sunlight irradiation direction of the real sample plot can be obtained through meteorological station data. The actual sunlight irradiation direction of the real sample plot can also be measured through a sensor.

[0073] S32: adjusting the virtual sunlight irradiation direction of the virtual sample plot to the actual sunlight irradiation direction, and performing light irradiation according to the virtual sunlight irradiation direction within a preset time period.

[0074] The preset time period can be set according to actual needs.

[0075] In the embodiment of the present application, in the light irradiation simulation software, the virtual sunlight irradiation direction of the virtual sample plot is adjusted to the actual sunlight irradiation direction, and the light irradiation duration is set. The light irradiation simulation software can be a full-day irradiation simulation software Sunshine_pro_2022.

[0076] By adjusting the virtual sunlight irradiation direction in the virtual sample plot to be consistent with the real sample plot, the accuracy and reliability of the simulation result are ensured.

[0077] The following is an apparatus embodiment of the present application, which can be used to execute the content of the method in the embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the content of the method in the embodiment of the present application.

[0078] Please refer to Figure 2 which shows a structure schematic diagram of a vegetation light energy loss detection device provided by the embodiment of the present application. The vegetation light energy loss detection device 6 provided by the embodiment of the present application comprises:

[0079] A point cloud data acquisition module 61 is configured to acquire point cloud data of a real sample plot. The point cloud data comprises first point cloud of target vegetation, second point cloud of adjacent vegetation located around the target vegetation, and third point cloud of a topography where the target vegetation and the adjacent vegetation are located.

[0080] A virtual sample plot establishment module 62 is configured to establish a virtual sample plot according to the point cloud data. The virtual sample plot comprises target virtual vegetation corresponding to the target vegetation, adjacent virtual vegetation corresponding to the adjacent vegetation, and virtual topography corresponding to the topography.

[0081] A light irradiation simulation module 63 is configured to perform light irradiation simulation on the virtual sample plot.

[0082] A light energy value calculation module 64 is configured to calculate a first light energy value received by the target virtual vegetation in the virtual sample plot when the adjacent virtual vegetation is shaded, and to calculate a second light energy value received by the target virtual vegetation in the virtual sample plot after the adjacent virtual vegetation is removed.

[0083] The light energy loss value obtaining module 65 is configured to obtain the light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value.

[0084] It should be noted that the vegetation light energy loss detection device provided in the above embodiments is only used as an example to illustrate the division of the above functional modules when the vegetation light energy loss detection method is performed. In actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions. In addition, the vegetation light energy loss detection device and the vegetation light energy loss detection method provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments. Therefore, it will not be repeated here.

[0085] The following is an equipment embodiment of the present application, which can be used to execute the content of the method in the embodiments of the present application. For details not disclosed in the equipment embodiments of the present application, please refer to the content of the method in the embodiments of the present application.

[0086] Please refer to Figure 3 The present application also provides an electronic device 300, which can be a computer, a mobile phone, a tablet computer, etc. In the exemplary embodiments of the present application, the electronic device 300 is a computer, which can include at least one processor 301, at least one memory 302, at least one display, at least one network interface 303, a user interface 304, and at least one communication bus 305.

[0087] The user interface 304 is mainly used to provide an input interface for the user to obtain user input data. Optionally, the user interface can also include a standard wired interface and a wireless interface.

[0088] The network interface 303 can optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0089] The communication bus 305 is used to realize the connection and communication between the components.

[0090] The processor 301 can include one or more processing cores. The processor connects various parts within the entire electronic device by various interfaces and lines, executes various functions of the electronic device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. Alternatively, the processor can be implemented in at least one of a hardware form of a digital signal processing (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA). The processor can be integrated with a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes an operating system, a user interface, and an application program; the GPU is responsible for rendering and drawing the content to be displayed by the display layer; and the modem is used for processing wireless communication. It can be understood that the above-mentioned modem can also not be integrated into the processor, but can be realized by a separate chip.

[0091] The memory 302 can include a random access memory (RAM) and a read-only memory (ROM). Optionally, the memory includes a non-transitory computer-readable storage medium. The memory can be used to store instructions, programs, codes, code sets or instruction sets. The memory can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory can also be at least one storage device located away from the above-mentioned processor. For example, Figure 3 The memory as a computer storage medium can include an operating system, a network communication module, a user interface module, and an operation application.

[0092] The processor can be used to call the application program of the vegetation light energy loss detection method stored in the memory, and specifically execute the method steps of the above-mentioned embodiments. The specific execution process can be referred to the specific description of the embodiments, which will not be repeated here.

[0093] It should also be noted that the terms "comprising", "comprises" or other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0094] The above embodiments are only used to illustrate the present application, but not to limit it. Instead of the above, various modifications and changes can be made to the application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall fall into the scope of the claims of the application.

Claims

1. A method of detecting loss of light energy by vegetation, characterized by, The method comprises the following steps: Obtaining point cloud data of a real sample plot, wherein the point cloud data comprises a first point cloud of target vegetation, a second point cloud of adjacent vegetation located around the target vegetation, and a third point cloud of a terrain where the target vegetation and the adjacent vegetation are located; Performing data cleaning on the point cloud data to obtain cleaned point cloud data; Performing terrain identification and vegetation identification on the cleaned point cloud data to obtain terrain feature data and morphological feature data of a plurality of vegetation, wherein the plurality of vegetation comprises the target vegetation and the adjacent vegetation; Obtaining target virtual vegetation and adjacent virtual vegetation according to the morphological feature data by using a preset vegetation modeling method; Modeling the terrain according to the terrain feature data by using an irregular triangle network method to obtain a virtual sample plot, wherein the virtual sample plot comprises the target virtual vegetation corresponding to the target vegetation, the adjacent virtual vegetation corresponding to the adjacent vegetation, and a virtual terrain corresponding to the terrain; Performing light radiation simulation on the virtual sample plot; Calculating a first light energy value received by the target virtual vegetation in the virtual sample plot when the adjacent virtual vegetation is shaded; removing the adjacent virtual vegetation in the virtual sample plot to calculate a second light energy value received by the target virtual vegetation in the virtual sample plot; Obtaining a light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value.

2. The method according to claim 1, wherein: The step of obtaining the target virtual vegetation and the adjacent virtual vegetation according to the morphological feature data by using the preset vegetation modeling method comprises: Performing voxelization processing on the morphological feature data to model a three-dimensional structure of the target vegetation and the adjacent vegetation, and the target virtual vegetation and the adjacent virtual vegetation.

3. The method according to claim 1, wherein: The step of obtaining the target virtual vegetation and the adjacent virtual vegetation according to the morphological feature data by using the preset vegetation modeling method comprises: Extracting a trunk and branches of the target vegetation and a trunk and branches of the adjacent vegetation from the morphological feature data; Performing cylindrical parameter optimization fitting on the trunk and branches of the target vegetation and the trunk and branches of the adjacent vegetation respectively by using a least square method to obtain the target virtual vegetation and the adjacent virtual vegetation.

4. The method according to any one of claims 1 to 3, wherein: The step of performing light radiation simulation on the virtual sample plot comprises: Obtaining an actual sunlight irradiation direction of the real sample plot; Adjusting a virtual sunlight irradiation direction of the virtual sample plot to the actual sunlight irradiation direction, and performing light radiation according to the virtual sunlight irradiation direction for a preset time period.

5. A device for detecting loss of light energy by vegetation, characterized by Comprise: The point cloud data acquisition module is configured to acquire point cloud data of a real sample plot, wherein the point cloud data comprises first point cloud data of target vegetation, second point cloud data of adjacent vegetation located around the target vegetation, and third point cloud data of a topography where the target vegetation and the adjacent vegetation are located. The virtual sample plot establishment module is configured to perform data cleaning on the point cloud data to obtain cleaned point cloud data, perform topography identification and vegetation identification on the cleaned point cloud data to obtain topography feature data and morphological feature data of a plurality of vegetations, wherein the plurality of vegetations comprise the target vegetation and the adjacent vegetation, and obtain target virtual vegetation and adjacent virtual vegetation according to the morphological feature data by using a preset vegetation modeling method, and model the topography according to the topography feature data by using an irregular triangle network method to obtain the virtual sample plot, wherein the virtual sample plot comprises the target virtual vegetation corresponding to the target vegetation, the adjacent virtual vegetation corresponding to the adjacent vegetation, and virtual topography corresponding to the topography. The light radiation simulation module is configured to perform light radiation simulation on the virtual sample plot. The light energy value calculation module is configured to calculate a first light energy value received by the target virtual vegetation in the virtual sample plot when the adjacent virtual vegetation is shaded, and calculate a second light energy value received by the target virtual vegetation in the virtual sample plot after the adjacent virtual vegetation is removed. The light energy loss value obtaining module is configured to obtain a light energy loss value of the target virtual vegetation according to the first light energy value and the second light energy value.

6. An electronic device, comprising: The computer program is loaded and executed by the processor, and the steps of the vegetation light energy loss detection method according to any one of claims 1 to 4 are implemented. The computer program is loaded and executed by the processor, and the steps of the vegetation light energy loss detection method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium storing a computer program, wherein the computer program comprises the following steps of: receiving a request for a resource from a client; determining whether the client is authorized to access the resource; and if the client is authorized to access the resource, providing the resource to the client. ​

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