A method and system for calculating urban green space vegetation carbon sequestration based on point cloud technology

Abstract

The invention discloses a method and system for calculating the carbon sink of urban green space vegetation based on point cloud technology, which belongs to the field of urban green space carbon sink calculation. The calculation method comprises: S1 using a three-dimensional laser radar scanner to collect point cloud data of the measured green space, using Trimble Real Works software to classify and process the point cloud data of the measured green space, and obtaining canopy point cloud data and ground cover point cloud data of evergreen and deciduous trees and shrubs; S2 performing voxel modeling on the canopy point cloud data of evergreen and deciduous trees and shrubs, and counting the canopy volumes of evergreen and deciduous trees and shrubs; S3 performing grid modeling on the ground cover point cloud data, and counting the three-dimensional surface area of ​​the ground cover; S4 calculating the carbon sink of evergreen and deciduous trees and shrubs according to the canopy volumes of evergreen and deciduous trees and shrubs using a tree and shrub carbon sink calculation formula; then calculating the ground cover carbon sink according to the three-dimensional surface area of ​​the ground cover using a ground cover carbon sink calculation formula; and adding the two together to obtain the total carbon sink of the measured green space vegetation.

Description

Technical Field

[0001] The present invention belongs to the field of urban green space carbon sink calculation, and specifically relates to a method and system for calculating urban green space vegetation carbon sink based on point cloud technology. Background Art

[0002] In recent years, industrialization and rapid urban expansion have led to a rapid increase in atmospheric levels of greenhouse gases such as carbon dioxide, contributing to global warming, frequent extreme weather events, rising sea levels, and a sharp decline in biodiversity. Green spaces, as a crucial component of urban ecosystems, play a key role in neutralizing urban carbon emissions through their vegetation, soil, and other components, which can reduce, absorb, and store carbon dioxide from the air. The carbon sequestration benefits of urban green spaces have become a key area of ​​research, and calculating carbon sequestration is a crucial method for evaluating these benefits.

[0003] Existing methods for calculating carbon sequestration in urban green space vegetation include plot inventory, assimilation, micrometeorological methods, and remote sensing estimation. These methods are often based on manual measurements or satellite remote sensing data, resulting in large and complex computational workloads, low efficiency, and inaccurate results. This is because manual measurement data cannot accurately describe complex forms such as plants, while remote sensing data cannot capture information on the vertical structure of the understory, making it difficult to accurately reflect the spatial characteristics of urban green space vegetation. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a method and system for calculating the carbon sequestration of urban green space vegetation based on point cloud technology, which solves the technical problems in the background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for calculating carbon sequestration of urban green space vegetation based on point cloud technology includes the following steps:

[0007] S1, using a 3D LiDAR scanner to collect point cloud data of the green space under test, and using Trimble RealWorks software to classify and process the point cloud data of the green space under test, to obtain the canopy point cloud data and ground cover point cloud data of evergreen and deciduous trees and shrubs;

[0008] S2, perform voxel modeling on the canopy point cloud data of evergreen and deciduous trees and shrubs obtained in S1, and calculate the canopy volume of evergreen and deciduous trees and shrubs based on the modeling results;

[0009] S3, gridding the ground cover point cloud data obtained in S1 and calculating the three-dimensional surface area of ​​the ground cover according to the modeling results;

[0010] S4: Based on the canopy volume of evergreen and deciduous trees and shrubs obtained in S2, the carbon sink of evergreen and deciduous trees and shrubs is calculated using the tree and shrub carbon sink calculation formula; then, based on the three-dimensional surface area of ​​the ground cover obtained in S3, the ground cover carbon sink is calculated using the ground cover carbon sink calculation formula; finally, the two are added together to obtain the total carbon sink of the green vegetation under test.

[0011] Furthermore, in S1, the classification processing step of the point cloud data includes:

[0012] S11. Use Trimble RealWorks software to classify the point cloud data of the surveyed area into four categories: surface, trees and shrubs, buildings, and others.

[0013] S12, based on the classified point cloud data obtained in S11, use the point cloud segmentation function of Trimble RealWorks software to first remove the hard ground point cloud data from the surface point cloud data to obtain the ground cover point cloud data; secondly, divide the tree and shrub point cloud data into tree point cloud data and shrub point cloud data; then remove the building and other point cloud data;

[0014] S13, using the point cloud segmentation function of Trimble RealWorks software, the shrub point cloud data obtained in S12 is divided into evergreen shrub point cloud data and deciduous shrub point cloud data;

[0015] S14, using the watershed algorithm in the LIDAR360 software to segment the tree point cloud data obtained in S12 into individual trees, and obtain the point cloud data of evergreen trees and deciduous trees;

[0016] S15, removing data other than the canopy from the evergreen and deciduous shrub point cloud data obtained in S13 and the evergreen and deciduous tree point cloud data obtained in S14, to obtain the canopy point cloud data of the evergreen and deciduous trees and shrubs.

[0017] Furthermore, in S14, the step of segmenting a single tree to obtain point cloud data of evergreen trees and deciduous trees includes:

[0018] S141, using the surface point cloud data and the tree point cloud data, generate a digital elevation model and a digital surface model through irregular triangulation interpolation and inverse distance weighted interpolation methods, and subtract the two models to obtain a canopy height model;

[0019] S142: Perform tree segmentation based on the canopy height model. Use the watershed algorithm to obtain initial tree data and seed points. Then, use the ALS seed point editing tool in the LIDAR360 software to check and correct the tree segmentation results. Add or delete seed points with segmentation errors and perform tree segmentation again to obtain the tree point cloud data.

[0020] S143, referring to the current vegetation distribution map of the site, the tree species are identified and classified based on the segmentation results to obtain point cloud data of evergreen trees and deciduous trees.

[0021] Furthermore, in S2, the specific steps of obtaining the canopy volume of evergreen and deciduous trees and shrubs include:

[0022] S21, using the Rhino software platform and the Tarsier plug-in in Grasshopper software to build a voxel modeled battery pack;

[0023] S22, based on the voxel modeling battery group obtained in S21 and the functional relationship between the voxel side length and the plant modeling volume, a voxel side length test battery group was constructed using the Rhino software platform with the help of the Anemone plug-in in the Grasshopper software;

[0024] S23, determining the voxel side length of the voxelized modeling of trees and shrubs according to the voxel side length test battery set constructed in S22;

[0025] S24, importing the canopy point cloud data of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs and the voxel side lengths obtained in S23 into the voxel modeling battery pack, completing the voxel modeling of the canopy point cloud data of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs, and obtaining the corresponding canopy volumes.

[0026] Furthermore, in S22, the functional relationship between the voxel side length and the plant modeling volume is as follows:

[0027] X=1 / k

[0028] Y=V k

[0029] Where k is the side length of the voxel; V k Model the volume of the plant corresponding to the k-voxel edge length setting.

[0030] Furthermore, in S23, the specific steps of determining the voxel side length of the voxelized modeling of trees and shrubs include:

[0031] S231, randomly select single tree samples obtained by single tree segmentation in S14 to perform voxel side length k value test, and select multiple single trees of different tree species and multiple single trees of the same tree species as samples;

[0032] S232: Input the sample data into the voxel side length test battery pack, output the X and Y values ​​obtained in each cycle, visualize the function curve image using Matlab software, compare the function curve images of multiple samples, analyze the Y value change trend, and determine the corresponding X value interval based on the interval where the Y value change slows down, thereby obtaining the k value interval;

[0033] S233 , by comparing the voxel modeling effect within the k value range with the actual plant morphology, the k value with the modeling effect closest to the actual morphology is selected as the voxel side length of the voxel modeling.

[0034] Furthermore, in S3, the process of obtaining the three-dimensional surface area of ​​the ground cover includes:

[0035] S31, import the ground cover point cloud data into Rhino software and use the Patch tool to generate the surface mesh;

[0036] S32, projecting the ground cover boundary onto the curved surface, removing the grids outside the ground cover area, and obtaining a gridded model of the ground cover;

[0037] S33, use the area statistics tool to obtain the three-dimensional surface area of ​​the ground cover.

[0038] Furthermore, the tree and shrub carbon sequestration calculation formula is:

[0039] C ts =S ts ×V ts

[0040] Where C ts is the average annual carbon sequestration of trees and shrubs, S ts is the average annual carbon dioxide absorption by trees and shrubs, V ts is the canopy volume of trees and shrubs.

[0041] Furthermore, the calculation formula for the ground cover carbon sequestration is as follows:

[0042] C g =S g ×A g

[0043] Where C g is the annual average carbon sequestration of ground cover, S g is the annual average ground cover carbon sequestration rate, A g is the three-dimensional surface area of ​​the ground cover.

[0044] A system for calculating urban green space vegetation carbon sequestration based on point cloud technology, including:

[0045] Data acquisition and processing unit: A 3D lidar scanner is used to collect point cloud data of the green space being measured. Trimble RealWorks software is used to classify and process the point cloud data of the green space being measured, obtaining canopy point cloud data and ground cover point cloud data of evergreen and deciduous trees and shrubs.

[0046] Tree and shrub canopy volume calculation unit: voxel modeling is performed on the canopy point cloud data of evergreen and deciduous trees and shrubs classified by the data acquisition and processing unit, and the canopy volumes of evergreen and deciduous trees and shrubs are calculated based on the modeling results;

[0047] Ground cover three-dimensional surface area calculation unit: grid modeling is performed on the ground cover point cloud data obtained by the data acquisition and processing unit, and the three-dimensional surface area of ​​the ground cover is calculated based on the modeling results;

[0048] Carbon sink calculation unit: The carbon sink of evergreen and deciduous trees and shrubs is calculated based on the canopy volume of evergreen and deciduous trees and shrubs obtained by the tree and shrub canopy volume calculation unit using the tree and shrub carbon sink calculation formula; the ground cover three-dimensional surface area is then calculated based on the ground cover three-dimensional surface area calculation unit using the ground cover carbon sink calculation formula to obtain the ground cover carbon sink; finally, the two are added together to obtain the total carbon sink of the green vegetation under test.

[0049] Beneficial effects of the present invention:

[0050] The present invention achieves precise calculation of carbon sinks in urban green spaces. In the calculation of carbon sinks for trees and shrubs, the voxelized modeling method based on point cloud data proposed by the present invention not only overcomes the limitation of inaccurate crown shape simulation in plant modeling, but also effectively solves the problem of plant volume errors caused by gaps between tree leaves and branches, enabling precise modeling of trees and shrubs, thereby making carbon sink calculations more accurate. In the calculation of ground cover carbon sinks, compared with the previous method of directly using the projected area of ​​the ground cover, the present invention constructs a three-dimensional surface model based on point cloud data and obtains the three-dimensional surface area of ​​the ground cover based on this model. This method can take into account the influence of terrain undulation factors in actual applications, thereby improving the accuracy of ground cover carbon sink calculations.

[0051] Furthermore, the method is easy to use and highly efficient. Using Rhino+Grasshopper software to build the battery pack, rapid voxel modeling and volume calculations were achieved for a variety of tree species. The method is easy to use and highly efficient, significantly saving manpower and resources. It eliminates the need for lengthy field data collection and the tedious data processing required. Furthermore, data processing and calculations can be performed by a single professional. Compared to carbon sequestration calculations for urban green spaces of the same scale, this method significantly reduces operational time. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0053] Figure 1 is a flow chart of the carbon sequestration calculation method of the present invention;

[0054] Figure 2 This is the specific point cloud data classification process of the implementation case of the present invention;

[0055] Figure 3 The voxel-modeled battery pack constructed by the present invention;

[0056] Figure 4 It is a voxel side length test battery pack constructed by the present invention;

[0057] Figure 5 This is a test curve diagram of the voxel side length k value of an embodiment of the present invention, where a is a test curve of samples of different tree species, and b is a test curve of multiple samples of the same tree species;

[0058] Figure 6 This is the modeling effect corresponding to different voxel side length k values ​​(k = 0.04-0.08) of the embodiment of the present invention;

[0059] Figure 7 This is a voxelized model of trees and shrubs based on point cloud data in an embodiment of the present invention;

[0060] Figure 8 It is a ground cover gridding model based on point cloud data in an implementation case of the present invention. DETAILED DESCRIPTION

[0061] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0062] like Figure 1 As shown in FIG, a method for calculating carbon sequestration of urban green space vegetation based on point cloud technology includes the following specific steps:

[0063] S1: Select an urban green space with a tree-shrub-grass composite plant community and use a 3D LiDAR scanner to collect point cloud data. Based on the automatic classification and point cloud segmentation functions of Trimble RealWorks software and the watershed algorithm of LIDAR360 software, classify and process the point cloud data of the measured green space to obtain the canopy point cloud data and ground cover point cloud data of evergreen and deciduous trees and shrubs; Figure 2 As shown, the specific steps are:

[0064] S11, using Trimble Realworks software to automatically classify the point cloud data of the surveyed area into four categories: surface, trees and shrubs, buildings, and others.

[0065] S12, based on the classified point cloud data obtained in S11, uses the point cloud segmentation function of Trimble RealWorks software to first remove the hard ground point cloud data from the surface point cloud data to obtain the ground cover point cloud data; secondly, the tree and shrub point cloud data are divided into tree point cloud data and shrub point cloud data; and finally, the building and other point cloud data are eliminated.

[0066] S13, based on the shrub point cloud data obtained in S12, uses the point cloud segmentation function of Trimble RealWorks software to further divide it into evergreen shrub and deciduous shrub point cloud data.

[0067] S14, using the watershed algorithm in the LIDAR360 software to segment the tree point cloud data obtained in S12 into individual trees, and obtain the point cloud data of evergreen trees and deciduous trees; the specific process is as follows:

[0068] S141, using surface point cloud data and tree point cloud data, generate a digital elevation model (DEM) and a digital surface model (DSM) through irregular triangulation (TIN) and inverse distance weighted interpolation (IDW) methods, and subtract the two to obtain a canopy height model (CHM);

[0069] S142: Perform tree segmentation based on the canopy height model (CHM). Initial tree data and seed points are obtained using the watershed algorithm. The ALS seed point editing tool in the LIDAR360 software is then used to check and correct the tree segmentation results. Seed points with segmentation errors are added or deleted, and the tree segmentation is performed again to obtain the tree point cloud data.

[0070] S143, referring to the current vegetation distribution map of the site, the tree species are identified and classified based on the segmentation results to obtain point cloud data of evergreen trees and deciduous trees.

[0071] S15, removing data other than the canopy from the evergreen and deciduous shrub point cloud data obtained in S13 and the evergreen and deciduous tree point cloud data obtained in S14, to obtain the canopy point cloud data of the evergreen and deciduous trees and shrubs.

[0072] S2, perform voxel modeling on the evergreen and deciduous tree and shrub canopy point cloud data obtained in S1, and calculate the canopy volume of evergreen and deciduous trees and shrubs based on the modeling results. The specific process is as follows:

[0073] S21, using the Rhino software platform and the Tarsier plug-in in Grasshopper software to construct a voxel modeling battery pack; Figure 3 As shown, the battery pack is divided into two parts: plant modeling and volume calculation;

[0074] The plant modeling part starts with Point Cloud (input point cloud data); its output is connected to BoundingBox to frame the point cloud within the box and Voxellize Point Cloud; the input of VoxellizePoint Cloud is connected to Cell Size, Decay Ray, Maximum Value (the maximum number of point clouds that can be accommodated in a single voxel), and Lower Threshold, and the output is connected to Deconstruct Point Cloud to generate the center point of the voxel; the output of DeconstructPoint Cloud is connected to Centre Box to create a cube with the voxel center point; Division is added between Cell Size and Centre Box, with the input A (dividend) of Division connected to Cell Size and the input B (divisor) set to 2, which is the distance from the voxel center point to the x-, y-, and z-facades - half the size of a single voxel.

[0075] The volume calculation part first connects Volume to the output of Centre Box to calculate the volume of a single voxel, then connects MassAddition to the output of Volume to calculate the sum of the volumes of the voxels, and finally displays the total volume of the voxelized model by connecting to Panel.

[0076] S22, based on the functional relationship between voxel side length and plant modeling volume and the voxel modeling battery pack constructed in S21, the voxel side length test battery pack was constructed using the Rhino software platform with the help of the Anemone plug-in in the Grasshopper software, as shown in Figure 4 As shown;

[0077] The functional relationship between the voxel side length and the plant modeling volume is as follows:

[0078] X=1 / k

[0079] Y=V k

[0080] Where k is the side length of the voxel, in m; V k The plant modeling volume corresponding to the k-voxel side length setting, unit m 3 ;

[0081] The starting cell of the voxel edge length test battery pack is Loop Start, and its input is connected to Repeat (number of loops), Button (loop switch) and Data (initial value); the output is connected to Addition (addition operation), and the initial value is superimposed correspondingly each loop to generate and output the k voxel edge length value of each loop; the output of Addition is connected to the voxel modeling battery pack, and voxel modeling and plant volume calculation of the k value input in each loop are performed. The final volume output of the voxel modeling battery pack is connected to the Data Recorder (data recording) battery to record the volume calculated in each loop; in addition, the output of Addition is connected to the data input of Loop End (to form a closed loop), and the data output of Loop End is connected to Division (division operation) to perform 1 / k numerical calculation in each loop. The output of Division is connected to Panel (panel) to record the 1 / k value output during each loop. The complete process of the loop is as follows: at the initial end, the starting voxel edge length k = 0.01m is input, and the operation X = 1 / k, voxel modeling and volume Y = V are performed. k After the automatic statistics are completed, the loop will automatically re-enter the initial end. At this time, the voxel side length k will automatically accumulate 0.01m. Each time the loop is repeated, the voxel side length will automatically accumulate 0.01m, and the calculation, modeling and volume statistics steps will be repeated until the set value is reached and the loop ends.

[0082] S23, determining the voxel side length of the tree and shrub voxel modeling based on the voxel side length test battery set constructed in S22; the specific steps include:

[0083] Randomly select single tree samples obtained by single tree segmentation in S14 for voxel side length k value test, and select multiple single trees of different tree species and multiple single trees of the same tree species as samples. Input the sample data into the voxel side length test battery pack, output the X and Y values ​​obtained in each cycle, and visualize the function curve image through Matlab software, as shown in the figure below: Figure 5 As shown in the figure, compare the function curve images of multiple samples, analyze the Y value change trend, determine the corresponding X value interval based on the interval where the Y value change slows down, and then obtain the k value interval; as shown in the figure, Figure 6 As shown in FIG, by comparing the voxel modeling effect within the k value range with the actual plant morphology, the k value with the modeling effect closest to the actual morphology is selected as the voxel side length of the voxel modeling.

[0084] S24, import the canopy point cloud data of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs and the voxel edge length k value obtained in S23 into the voxel modeling battery pack, complete the voxel modeling of the canopy point cloud data of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs, and obtain the corresponding canopy volume, such as Figure 7shown.

[0085] S3, grid modeling is performed on the ground cover point cloud data obtained in S1, and the three-dimensional surface area of ​​the ground cover is calculated based on the modeling results. The specific process is as follows:

[0086] S31, import the ground cover point cloud data into Rhino software and use the Patch tool to generate the surface mesh;

[0087] S32, projecting the ground cover boundary onto the surface, removing the grid outside the ground cover area, and obtaining a gridded model of the ground cover, such as Figure 8 As shown;

[0088] S33, use the area statistics tool to obtain the three-dimensional surface area of ​​the ground cover.

[0089] S4, based on the canopy volume of evergreen and deciduous trees and shrubs obtained in S2, the carbon sinks of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs are calculated using the tree and shrub carbon sink calculation formula; based on the three-dimensional surface area of ​​ground cover obtained in S3, the ground cover carbon sink is calculated using the ground cover carbon sink calculation formula; the two are added together to obtain the total carbon sink of the green space vegetation under test, as shown in Table 1:

[0090]

[0091] The specific steps include:

[0092] S41, based on the canopy volume of evergreen and deciduous trees and shrubs obtained in S2, calculate the total carbon sink of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs using the tree and shrub carbon sink calculation formula; the tree and shrub carbon sink calculation formula is:

[0093] C ts =S ts ×V ts

[0094] Where C ts is the annual average carbon sequestration of trees and shrubs, unit: kg; S ts V is the average annual carbon dioxide absorption by trees and shrubs, unit: kg / (㎡·a); ts is the canopy volume of trees and shrubs, unit: m2;

[0095] In this embodiment, as shown in Table 1, the calculated annual average carbon sequestration of evergreen trees is 893.27 kg, the carbon sequestration of deciduous trees is 1045.30 kg, the carbon sequestration of evergreen shrubs is 10.57 kg, and the carbon sequestration of deciduous shrubs is 170.69 kg.

[0096] S42, based on the three-dimensional ground cover surface area obtained in S3, calculate the ground cover carbon sink using the ground cover carbon sink calculation formula; the ground cover carbon sink calculation formula is as follows:

[0097] Cg =S g ×A g

[0098] Where C g is the annual average carbon sequestration of ground cover, unit: kg; S g is the annual average ground cover carbon sequestration rate, unit: kg / (㎡·a); A g It is the three-dimensional surface area of ​​the ground cover, unit is m2.

[0099] In this embodiment, as shown in Table 1, the calculated annual average carbon sequestration of ground cover is 1223.02 kg.

[0100] S43, adding the carbon sequestration of trees and shrubs to that of ground cover, we get the total annual average carbon sequestration of urban green vegetation to be 3342.86 kg.

[0101] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0102] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention, and such changes and modifications fall within the scope of the invention as claimed.

Claims

1. A method for calculating urban green space vegetation carbon sequestration based on point cloud technology, characterized in that: The following steps are involved: S1, using a 3D LiDAR scanner to collect point cloud data of the green space under test, and using Trimble RealWorks software to classify and process the point cloud data of the green space under test, to obtain the canopy point cloud data and ground cover point cloud data of evergreen and deciduous trees and shrubs; S2, perform voxel modeling on the canopy point cloud data of evergreen and deciduous trees and shrubs obtained in S1, and calculate the canopy volume of evergreen and deciduous trees and shrubs based on the modeling results; S3, gridding the ground cover point cloud data obtained in S1 and calculating the three-dimensional surface area of ​​the ground cover according to the modeling results; S4, based on the canopy volume of evergreen and deciduous trees and shrubs obtained in S2, calculate the carbon sink of evergreen and deciduous trees and shrubs using the tree and shrub carbon sink calculation formula; then, based on the three-dimensional surface area of ​​ground cover obtained in S3, calculate the ground cover carbon sink using the ground cover carbon sink calculation formula; Finally, the two are added together to obtain the total carbon sequestration of the green vegetation under test; In S1, the classification processing step of the point cloud data includes: S11, using Trimble Realworks software, the point cloud data of the surveyed area were divided into four categories: surface, trees and shrubs, buildings, and others; S12, based on the classified point cloud data obtained in S11, use the point cloud segmentation function of Trimble RealWorks software to first remove the hard ground point cloud data from the surface point cloud data to obtain the ground cover point cloud data; secondly, divide the tree and shrub point cloud data into tree point cloud data and shrub point cloud data; then remove the building and other point cloud data; S13, using the point cloud segmentation function of Trimble RealWorks software, the shrub point cloud data obtained in S12 is divided into evergreen shrub point cloud data and deciduous shrub point cloud data; S14, using the watershed algorithm in the LIDAR360 software to segment the tree point cloud data obtained in S12 into individual trees, and obtain the point cloud data of evergreen trees and deciduous trees; S15, removing data other than the canopy from the evergreen and deciduous shrub point cloud data obtained in S13 and the evergreen and deciduous tree point cloud data obtained in S14, to obtain the canopy point cloud data of the evergreen and deciduous trees and shrubs.

2. The method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to claim 1 is characterized in that: In S14, the steps of segmenting a single tree to obtain point cloud data of evergreen trees and deciduous trees include: S141, using the surface point cloud data and the tree point cloud data, generate a digital elevation model and a digital surface model through irregular triangulation interpolation and inverse distance weighted interpolation methods, and subtract the two models to obtain a canopy height model; S142: Perform tree segmentation based on the canopy height model. Use the watershed algorithm to obtain initial tree data and seed points. Then, use the ALS seed point editing tool in the LIDAR360 software to check and correct the tree segmentation results. Add or delete seed points with segmentation errors and perform tree segmentation again to obtain the tree point cloud data. S143, referring to the current vegetation distribution map of the site, the tree species are identified and classified based on the segmentation results to obtain point cloud data of evergreen trees and deciduous trees.

3. The method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to claim 2 is characterized in that: In S2, the specific steps for obtaining the canopy volume of evergreen and deciduous trees and shrubs include: S21, using the Rhino software platform and the Tarsier plug-in in Grasshopper software to build a voxel modeled battery pack; S22, based on the voxel modeling battery group obtained in S21 and the functional relationship between the voxel side length and the plant modeling volume, a voxel side length test battery group was constructed using the Rhino software platform with the help of the Anemone plug-in in the Grasshopper software; S23, determining the voxel side length of the voxelized modeling of trees and shrubs according to the voxel side length test battery set constructed in S22; S24, importing the canopy point cloud data of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs and the voxel side lengths obtained in S23 into the voxel modeling battery pack, completing the voxel modeling of the canopy point cloud data of evergreen trees, deciduous trees, evergreen shrubs, and deciduous shrubs, and obtaining the corresponding canopy volumes.

4. The method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to claim 3 is characterized in that: In S22, the functional relationship between the voxel side length and the plant modeling volume is as follows: X=1 / k Y=V k Where k is the side length of the voxel; V k Model the volume of the plant corresponding to the k-voxel edge length setting.

5. The method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to claim 3 is characterized in that: In S23, the specific steps of determining the voxel side length of the tree and shrub voxel modeling include: S231, randomly select single tree samples obtained by single tree segmentation in S14 to perform voxel side length k value test, and select multiple single trees of different tree species and multiple single trees of the same tree species as samples; S232: Input the sample data into the voxel side length test battery pack, output the X and Y values ​​obtained in each cycle, visualize the function curve image using Matlab software, compare the function curve images of multiple samples, analyze the Y value change trend, and determine the corresponding X value interval based on the interval where the Y value change slows down, thereby obtaining the k value interval; S233 , by comparing the voxel modeling effect within the k value range with the actual plant morphology, the k value with the modeling effect closest to the actual morphology is selected as the voxel side length of the voxel modeling.

6. The method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to claim 1 is characterized in that: In S3, the process of calculating the three-dimensional surface area of ​​the ground cover includes: S31, import the ground cover point cloud data into Rhino software and use the Patch tool to generate the surface mesh; S32, projecting the ground cover boundary onto the curved surface, removing the grids outside the ground cover area, and obtaining a gridded model of the ground cover; S33, use the area statistics tool to obtain the three-dimensional surface area of ​​the ground cover.

7. The method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to claim 1 is characterized in that: The calculation formula for the carbon sequestration of trees and shrubs is: C ts =S ts ×V ts Where C ts is the average annual carbon sequestration of trees and shrubs, S ts is the average annual carbon dioxide absorption by trees and shrubs, V ts is the canopy volume of trees and shrubs.

8. The method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to claim 1 is characterized in that: The calculation formula for ground cover carbon sequestration is as follows: C g =S g ×A g Where C g is the annual average carbon sequestration of ground cover, S g is the annual average ground cover carbon sequestration rate, A g is the three-dimensional surface area of ​​the ground cover.

9. A system for calculating carbon sequestration of urban green space vegetation based on point cloud technology, which executes the method for calculating carbon sequestration of urban green space vegetation based on point cloud technology according to any one of claims 1 to 8, characterized in that: include: Data acquisition and processing unit: A 3D lidar scanner is used to collect point cloud data of the green space being measured. Trimble RealWorks software is used to classify and process the point cloud data of the green space being measured to obtain canopy point cloud data and ground cover point cloud data of evergreen and deciduous trees and shrubs. Tree and shrub canopy volume calculation unit: voxel modeling is performed on the canopy point cloud data of evergreen and deciduous trees and shrubs classified by the data acquisition and processing unit, and the canopy volumes of evergreen and deciduous trees and shrubs are calculated based on the modeling results; Ground cover three-dimensional surface area calculation unit: grid modeling is performed on the ground cover point cloud data obtained by the data acquisition and processing unit, and the three-dimensional surface area of ​​the ground cover is calculated based on the modeling results; Carbon sink calculation unit: The carbon sink of evergreen and deciduous trees and shrubs is calculated using the tree and shrub carbon sink calculation formula based on the canopy volume of evergreen and deciduous trees and shrubs obtained in the tree and shrub canopy volume calculation unit. Then, based on the three-dimensional surface area of ​​the ground cover obtained by the ground cover three-dimensional surface area calculation unit, the ground cover carbon sink amount is calculated using the ground cover carbon sink calculation formula; Finally, the two are added together to obtain the total carbon sequestration of the measured green vegetation.

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