Method and device for calculating mangrove carbon storage based on airborne lidar point cloud

Abstract

The application relates to a mangrove carbon storage calculation method and device based on an airborne laser radar point cloud, wherein the method comprises the following steps: extracting single-tree height and crown width parameters by using unmanned aerial vehicle laser radar point cloud data, calculating single-tree carbon storage by using corresponding tree species allometric growth equations, and establishing a function relationship between mangrove single-tree carbon density and single-tree height; filtering the laser radar point cloud data to obtain a crown height model, and substituting the crown height model into a mangrove carbon density equation between the single-tree carbon density and the single-tree height to obtain a mangrove region carbon storage. Therefore, the problems that the current mangrove carbon storage estimation precision is difficult to evaluate and the results lack theoretical explanation are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of forest ecology and remote sensing surveying, and particularly relates to a mangrove carbon storage calculation method and device based on airborne laser radar point cloud. BACKGROUND

[0002] "Blue carbon" refers to carbon absorbed and stored by marine and coastal ecosystems, and coastal wetlands such as salt marshes and mangroves are the main components of blue carbon ecosystems. The area of coastal wetlands accounts for less than 0.5% of the seabed, and the plant biomass accounts for 0.05% of the terrestrial plants, but the carbon storage of the coastal wetlands contributes more than 15% of the global terrestrial carbon storage and more than 50% of the marine carbon storage. As a typical representative, mangroves have a particularly significant impact on global carbon cycle.

[0003] However, the reliability of existing mangrove carbon storage estimation is poor, and it is difficult to achieve high-resolution and high-timeliness monitoring of large-scale mangrove carbon sinks, which needs to be solved urgently. SUMMARY

[0004] The present application provides a mangrove carbon storage calculation method and device based on airborne laser radar point cloud to solve the problems that the accuracy of current mangrove carbon storage estimation is difficult to evaluate and the results lack theoretical explanation.

[0005] The first aspect embodiment of the present application provides a mangrove carbon storage calculation method based on airborne laser radar point cloud, comprising the following steps: acquiring laser radar point cloud data of a target mangrove forest area, collecting a plurality of target single tree point clouds through the laser radar point cloud data, and extracting single tree height and crown width parameters corresponding to each target single tree point cloud in the plurality of target single tree point clouds, to calculate single tree carbon density corresponding to each target single tree point cloud based on the single tree height, the crown width parameters and a preset allometric equation of tree species; establishing a functional relationship between the single tree height and the single tree carbon density, determining a plurality of target fitting functions corresponding to the functional relationship, and performing model fitting on the plurality of target fitting functions to obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and establishing a mangrove carbon density equation corresponding to the target mangrove forest area according to the correlation coefficient; acquiring ground point data and non-ground point data corresponding to the laser radar point cloud data, and constructing a digital elevation model and a digital surface model according to the ground point data and the non-ground point data respectively, to calculate the carbon storage of the target mangrove forest area through the digital elevation model, the digital surface model and the mangrove carbon density equation.

[0006] Optionally, in an embodiment of the present application, the extracting the tree height and crown width parameters corresponding to each of the plurality of target single tree point clouds comprises: calculating the tree height corresponding to each of the plurality of target single tree point clouds by using the lowest point and the highest point of the target single tree corresponding to each of the plurality of target single tree point clouds; and calculating the crown width parameters corresponding to each of the plurality of target single tree point clouds by using the longest crown width and the shortest crown width of the target single tree corresponding to each of the plurality of target single tree point clouds.

[0007] Optionally, in an embodiment of the present application, the determining the plurality of target functions corresponding to the function relationship and performing model fitting on the plurality of target functions to obtain a correlation coefficient corresponding to each of the plurality of target functions, and establishing the red mangrove carbon density equation corresponding to the target red mangrove region according to the correlation coefficient comprises: obtaining a scatter plot between the single tree carbon density and the single tree height, and determining the plurality of target functions corresponding to the function relationship according to the scatter plot, wherein the plurality of target functions comprises a linear function, a polynomial function, a power function and an exponential function; performing model fitting on the plurality of target functions to obtain the correlation coefficient corresponding to each of the plurality of target functions, and comparing the correlation coefficients of the plurality of target functions to obtain a maximum correlation coefficient; obtaining a target function corresponding to the maximum correlation coefficient, and determining the red mangrove carbon density equation according to the target function corresponding to the maximum correlation coefficient.

[0008] Optionally, in an embodiment of the present application, the obtaining ground point data and non-ground point data corresponding to the laser radar point cloud data, and constructing a digital elevation model and a digital surface model according to the ground point data and the non-ground point data respectively, to calculate the carbon storage of the target mangrove forest region through the digital elevation model, the digital surface model and the mangrove carbon density equation, comprises: filtering the laser radar point cloud data to obtain the ground point data and the non-ground point data, and constructing the digital elevation model through the ground point data, and establishing the digital surface model using the non-ground point data; determining a canopy height model according to the digital elevation model and the digital surface model, and substituting the canopy height model into the mangrove carbon density equation to calculate the carbon storage of the target mangrove forest region.

[0009] The second aspect embodiment of the present application provides a mangrove carbon storage calculation device based on airborne laser radar point cloud, comprising: an extraction module configured to obtain laser radar point cloud data of a target mangrove forest region, and acquire a plurality of target single tree point clouds through the laser radar point cloud data, and extract single tree height and crown width parameters corresponding to each target single tree point cloud in the plurality of target single tree point clouds, to calculate single tree carbon density corresponding to each target single tree point cloud based on the single tree height, the crown width parameters and a preset allometric equation of tree species; a fitting module configured to establish a functional relationship between the single tree height and the single tree carbon density, and determine a plurality of target fitting functions corresponding to the functional relationship, and perform model fitting on the plurality of target fitting functions to obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and establish a mangrove carbon density equation corresponding to the target mangrove forest region according to the correlation coefficient; a construction module configured to obtain ground point data and non-ground point data corresponding to the laser radar point cloud data, and construct a digital elevation model and a digital surface model according to the ground point data and the non-ground point data respectively, to calculate the carbon storage of the target mangrove forest region through the digital elevation model, the digital surface model and the mangrove carbon density equation.

[0010] Optionally, in an embodiment of the present application, the extraction module comprises: a statistics unit configured to count a plurality of characteristic values of the target individual tree corresponding to each target individual tree point cloud, wherein the plurality of characteristic values comprise individual tree lowest point, individual tree highest point, individual tree longest crown width and individual tree shortest crown width; a first calculation unit configured to calculate the individual tree height by using the individual tree lowest point and the individual tree highest point, and calculate the crown width parameter by using the individual tree longest crown width and the individual tree shortest crown width; a substitution unit configured to substitute the individual tree height and the crown width parameter into the allometric equation of tree species to calculate the individual tree biomass, and calculate the individual tree carbon storage corresponding to the target individual tree according to the individual tree biomass and a preset red forest carbon content coefficient; and a second calculation unit configured to calculate the individual tree crown area corresponding to the target individual tree based on the crown width parameter, and calculate the individual tree carbon density according to the individual tree crown area and the individual tree carbon storage.

[0011] Optionally, in an embodiment of the present application, the fitting module comprises: an acquisition unit configured to acquire a scatter plot between the individual tree carbon density and the individual tree height, and determine a plurality of target functions to be fitted corresponding to the functional relationship according to the scatter plot, wherein the plurality of target functions to be fitted comprise linear function, polynomial function, power function and exponential function; a comparison unit configured to perform model fitting on the plurality of target functions to be fitted to obtain a correlation coefficient corresponding to each target function to be fitted, and compare the correlation coefficients of the plurality of target functions to be fitted to obtain a maximum correlation coefficient; and a determination unit configured to acquire a target function to be fitted corresponding to the maximum correlation coefficient, and determine the mangrove carbon density equation according to the target function to be fitted corresponding to the maximum correlation coefficient.

[0012] Optionally, in an embodiment of the present application, the construction module comprises: a filtering unit configured to filter the laser radar point cloud data to obtain the ground point data and the non-ground point data, and construct the digital elevation model by using the ground point data, and establish the digital surface model by using the non-ground point data; and a third calculation unit configured to determine a canopy height model according to the digital elevation model and the digital surface model, and substitute the canopy height model into the mangrove carbon density equation to calculate the carbon storage of the target red forest region.

[0013] The third aspect embodiment of the present application provides an electronic device, comprising: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for calculating the carbon storage of mangrove based on airborne laser radar point cloud as described in the above embodiments.

[0014] The fourth aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program. The program is executed by a processor to implement the method for calculating the mangrove carbon storage based on the airborne laser radar point cloud.

[0015] The fifth aspect of the embodiment of the present application provides a computer program product, which includes a computer program. The computer program is executed to implement the method for calculating the mangrove carbon storage based on the airborne laser radar point cloud.

[0016] Therefore, the embodiment of the present application has the following beneficial effects:

[0017] The embodiment of the present application can obtain the laser radar point cloud data of the target mangrove forest area, collect a plurality of target single tree point clouds through the laser radar point cloud data, extract the single tree height and crown width parameters corresponding to each target single tree point cloud in the plurality of target single tree point clouds, calculate the single tree carbon density corresponding to each target single tree point cloud based on the single tree height, the crown width parameters and the preset allometric equation of tree species, establish a functional relationship between the single tree height and the single tree carbon density, determine a plurality of target fitting functions corresponding to the functional relationship, perform model fitting on the plurality of target fitting functions, obtain the correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and establish a mangrove carbon density equation corresponding to the target mangrove forest area according to the correlation coefficient. The ground point data and the non-ground point data corresponding to the laser radar point cloud data are obtained, and a digital elevation model and a digital surface model are constructed according to the ground point data and the non-ground point data respectively. The carbon storage of the target mangrove forest area is calculated through the digital elevation model, the digital surface model and the mangrove carbon density equation. The present application uses unmanned aerial vehicle remote sensing technology to help realize high-resolution and high-timeliness monitoring of large-scale mangrove carbon sinks, thereby providing technical support for the national carbon neutralization target. Thus, the problems that the estimation accuracy of the mangrove carbon storage is difficult to evaluate and the results lack theoretical explanation are solved.

[0018] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0019] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the following drawings, in which:

[0020] Figure 1 A flowchart of a method for calculating the mangrove carbon storage based on the airborne laser radar point cloud according to the embodiment of the present application is shown.

[0021] Figure 2An execution logic diagram of a mangrove carbon storage calculation method based on airborne laser radar point cloud provided for an embodiment of the present application;

[0022] Figure 3 A mangrove unmanned aerial vehicle laser radar data diagram provided for an embodiment of the present application;

[0023] Figure 4 A mangrove single tree point cloud data, single tree height and crown width parameter diagram provided for an embodiment of the present application;

[0024] Figure 5 A mangrove single tree carbon density and tree height parameter different function fitting diagram provided for an embodiment of the present application;

[0025] Figure 6 A mangrove regional canopy height model diagram provided for an embodiment of the present application;

[0026] Figure 7 A mangrove regional carbon storage diagram provided for an embodiment of the present application;

[0027] Figure 8 An example diagram of a mangrove carbon storage calculation device based on airborne laser radar point cloud according to an embodiment of the present application;

[0028] Figure 9 A structure diagram of an electronic device provided for an embodiment of the present application.

[0029] Among them, 10 is a mangrove carbon storage calculation device based on airborne laser radar point cloud; 100 is an extraction module, 200 is a fitting module, 300 is a construction module; 901 is a memory, 902 is a processor, 903 is a communication interface. DETAILED DESCRIPTION

[0030] The embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0031] A method and device for calculating mangrove carbon storage based on airborne laser radar point cloud are described below with reference to the accompanying drawings. In view of the problems mentioned in the background art, the present application provides a method for calculating mangrove carbon storage based on airborne laser radar point cloud. In this method, laser radar point cloud data of a target mangrove forest area is obtained, and a plurality of target tree point clouds are collected from the laser radar point cloud data. The tree height and crown width parameters corresponding to each target tree point cloud in the plurality of target tree point clouds are extracted. Based on the tree height, crown width parameters, and a pre-set allometric equation for the tree species, the carbon density of each target tree point cloud is calculated. A functional relationship between the tree height and the carbon density of the tree is established, and a plurality of target fitting functions corresponding to the functional relationship are determined. The plurality of target fitting functions are model fitted to obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions. A mangrove carbon density equation corresponding to the target mangrove forest area is established according to the correlation coefficient. Ground point data and non-ground point data corresponding to the laser radar point cloud data are obtained, and a digital elevation model and a digital surface model are constructed according to the ground point data and the non-ground point data, respectively. The carbon storage of the target mangrove forest area is calculated by the digital elevation model, the digital surface model, and the mangrove carbon density equation. The present application uses unmanned aerial vehicle remote sensing technology to help achieve high-resolution and high-timeliness monitoring of large-scale mangrove carbon sinks, thereby providing technical support for the national carbon neutralization target. Thus, the problems of difficult evaluation of the current mangrove carbon storage estimation accuracy and lack of theoretical explanation of the results are solved.

[0032] Specifically, Figure 1 A flowchart of a method for calculating mangrove carbon storage based on airborne laser radar point cloud is provided in an embodiment of the present application.

[0033] As Figure 1 shown, the method for calculating mangrove carbon storage based on airborne laser radar point cloud includes the following steps:

[0034] In step S101, laser radar point cloud data of a target mangrove forest area is obtained, and a plurality of target tree point clouds are collected from the laser radar point cloud data. The tree height and crown width parameters corresponding to each target tree point cloud in the plurality of target tree point clouds are extracted. Based on the tree height, crown width parameters, and a pre-set allometric equation for the tree species, the carbon density of each target tree point cloud is calculated.

[0035] In an embodiment of the present application, the laser radar point cloud data of the target mangrove forest area is first obtained, and 50 tree point clouds with uniform height distribution (i.e., a plurality of target tree point clouds) are selected from the laser radar point cloud data. The tree height and crown width parameters are extracted, and the tree height and crown width parameters are substituted into the allometric equation for the corresponding tree species. The carbon storage of the tree is calculated in combination with the carbon content coefficient, as shown in Figure 2As shown, the single tree carbon stock is then divided by the single tree crown area to obtain the single tree carbon density.

[0036] Optionally, in one embodiment of the present application, the tree height and crown width parameters corresponding to each target tree point cloud in multiple target tree point clouds are extracted to calculate the tree carbon density corresponding to each target tree point cloud based on the tree height, crown width parameters and a preset tree species allometric growth equation, including: counting multiple characteristic values ​​of the target tree corresponding to each target tree point cloud, wherein the multiple characteristic values ​​include the lowest point of the tree, the highest point of the tree, the longest crown width of the tree and the shortest crown width of the tree; calculating the tree height by the lowest point and the highest point of the tree, and calculating the crown width parameters using the longest crown width and the shortest crown width of the tree; substituting the tree height and crown width parameters into the tree species allometric growth equation to calculate the tree biomass, and calculating the tree carbon storage corresponding to the target tree based on the tree biomass and a preset red forest carbon content coefficient; calculating the tree crown area corresponding to the target tree based on the crown width parameters, and calculating the tree carbon density based on the tree crown area and the tree carbon storage.

[0037] As a possible implementation method, the embodiment of the present application is as follows Figure 3 Fifty single tree point clouds with uniform height distribution were selected from the mangrove UAV lidar data shown, and the tree height and crown width parameters were extracted from them.

[0038] Specifically, the embodiment of the present application calculates the lowest point H of each tree low , highest point H high 、Longest crown width W long , shortest crown width W short etc., and H high and H low Calculate the tree height parameter H = H high -H low , by W long With W short The average crown width parameter W = (W long +W short ) / 2, the height H and crown width parameters W of the separated single trees are as follows Figure 4 shown.

[0039] Secondly, the embodiment of the present application can substitute the tree height and crown width parameters into the allometric growth equation of the corresponding mangrove species to calculate the tree biomass B, and multiply it by the carbon content coefficient CF of the corresponding mangrove to obtain the single tree carbon storage C = CF·B; then, the embodiment of the present application can divide the single tree carbon storage C by the single tree crown area S = π·(W / 2) 2 Calculate the carbon density of a single tree: C′ = C / S. Common mangrove allometric growth equations and carbon content coefficients are shown in the following table:

[0040] Table 1

[0041]

[0042] Therefore, the embodiment of the present application extracts the mangrove tree height and crown width parameters through the laser radar point cloud data, establishes the mangrove single tree structure equation, and further calculates the carbon density of the mangrove at different heights, which is not only simple and easy to implement, but also can save a lot of manpower and material resources.

[0043] In step S102, a function relationship between the single tree height and the single tree carbon density is established, a plurality of target fitting functions corresponding to the function relationship are determined, and model fitting is performed on the plurality of target fitting functions to obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and a mangrove carbon density equation corresponding to the target red forest region is established according to the correlation coefficient.

[0044] Further, the embodiment of the present application also needs to establish a function relationship between the mangrove single tree carbon density and the single tree height, and model fitting is performed on the plurality of polynomial functions (i.e. the plurality of target fitting functions) such as power function and exponential function according to the scatter plot distribution of the single tree height and the single tree carbon density to obtain a correlation coefficient corresponding to each target fitting function, and the function with the highest correlation coefficient is selected as the mangrove carbon density equation.

[0045] Optionally, in an embodiment of the present application, the plurality of target fitting functions corresponding to the function relationship are determined, and model fitting is performed on the plurality of target fitting functions to obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and a mangrove carbon density equation corresponding to the target red forest region is established according to the correlation coefficient, including: obtaining a scatter plot between the single tree carbon density and the single tree height, and determining a plurality of target fitting functions corresponding to the function relationship according to the scatter plot, wherein the plurality of target fitting functions include linear function, polynomial function, power function and exponential function; model fitting is performed on the plurality of target fitting functions to obtain a correlation coefficient corresponding to each target fitting function, and the correlation coefficients of the plurality of target fitting functions are compared to obtain a maximum correlation coefficient; the target fitting function corresponding to the maximum correlation coefficient is obtained, and the mangrove carbon density equation is determined according to the target fitting function corresponding to the maximum correlation coefficient.

[0046] It should be noted that the embodiment of the present application establishes a function relationship C' = f(H) between the mangrove single tree carbon density C' and the single tree height data H, and obtains a scatter plot between the single tree carbon density and the single tree height, so as to select a suitable function (i.e. target fitting function) such as linear function, polynomial function, power function and exponential function according to the scatter plot of the mangrove single tree carbon density and the tree height to perform model fitting, so as to obtain a correlation coefficient corresponding to the target fitting function, wherein the fitting function of the mangrove single tree carbon density and the single tree height is shown in the following table:

[0047] Table 2

[0048]

[0049] It should be noted that the embodiment of the present application requires that the tree height distribution be relatively uniform, the number of single trees be no less than 50, and the model fitting correlation coefficient be greater than 0.8.

[0050] Subsequently, the embodiment of the present application can select the function with the optimal fitting effect to establish the relationship between the mangrove carbon density and the height, as shown in formula (1), and select the function with the highest fitting degree for subsequent calculation. Figure 5

[0051] In step S103, ground point data and non-ground point data corresponding to the laser radar point cloud data are obtained, and a digital elevation model and a digital surface model are constructed according to the ground point data and the non-ground point data, respectively, to calculate the carbon storage of the target mangrove forest region through the digital elevation model, the digital surface model, and the mangrove carbon density equation.

[0052] Further, the embodiment of the present application obtains ground points and non-ground points by filtering the point cloud data (i.e., the laser radar point cloud data) of the mangrove forest region, generates a digital elevation model DEM from the ground points, generates a digital surface model DSM from the non-ground points, and calculates a canopy height model CHM = DSM-DEM, so as to calculate the carbon storage of the region by substituting CHM into the mangrove carbon density equation.

[0053] Alternatively, in an embodiment of the present application, ground point data and non-ground point data corresponding to the laser radar point cloud data are obtained, and a digital elevation model and a digital surface model are constructed according to the ground point data and the non-ground point data, respectively, to calculate the carbon storage of the target mangrove forest region through the digital elevation model, the digital surface model, and the mangrove carbon density equation, including: filtering the laser radar point cloud data to obtain the ground point data and the non-ground point data, and constructing a digital elevation model through the ground point data and establishing a digital surface model using the non-ground point data; determining a canopy height model according to the digital elevation model and the digital surface model, and substituting the canopy height model into the mangrove carbon density equation to calculate the carbon storage of the target mangrove forest region.

[0054] It should be noted that the embodiment of the present application filters the laser radar point cloud data to obtain ground points G and non-ground points N, and generates a digital elevation model DEM from the ground points G and generates a digital surface model DSM from the non-ground points N, wherein the spatial resolution of DEM and DSM is P.

[0055] Secondly, the embodiment of the present application can calculate a canopy height model CHM through the digital elevation model DEM and the digital surface model DSM, and the canopy height model CHM of the target mangrove forest region is as shown in formula (2). Figure 6 ​As shown, the mathematical expression thereof is as shown in the following formula:

[0056] CHM = DSM - DEM

[0057] Afterwards, the embodiment of the present application can substitute the tree height in the CHM into the mangrove carbon density equation to calculate the mangrove carbon storage C i,j = P 2 · f(H i,j ), the mangrove carbon storage being as shown in the following formula: Figure 7

[0058]

[0059] wherein m, n represent the number of rows and columns of the CHM; i, j represent the i-th row and the j-th column; C i,j represents the carbon storage of the i-th row j-th column pixel.

[0060] Therefore, the embodiment of the present application helps to realize high-resolution and high-time-efficiency monitoring of large-scale mangrove carbon sinks through accurate calculation of regional mangrove aboveground carbon storage based on laser radar point cloud data, and provides reliable technical support for the national carbon neutralization target.

[0061] According to the method for calculating mangrove carbon storage based on airborne laser radar point cloud provided by the embodiment of the present application, laser radar point cloud data of a target mangrove forest region is obtained, and a plurality of target single tree point clouds are collected through the laser radar point cloud data, and the single tree height and crown width parameters corresponding to each target single tree point cloud in the plurality of target single tree point clouds are extracted, so as to calculate the single tree carbon density corresponding to each target single tree point cloud based on the single tree height, the crown width parameters and a preset allometric equation of tree species; a functional relationship between the single tree height and the single tree carbon density is established, and a plurality of target fitting functions corresponding to the functional relationship are determined, and model fitting is performed on the plurality of target fitting functions, so as to obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and a mangrove carbon density equation corresponding to the target mangrove forest region is established according to the correlation coefficient; ground point data and non-ground point data corresponding to the laser radar point cloud data are obtained, and a digital elevation model and a digital surface model are constructed according to the ground point data and the non-ground point data respectively, so as to calculate the carbon storage of the target mangrove forest region through the digital elevation model, the digital surface model and the mangrove carbon density equation. The present application helps to realize high-resolution and high-time-efficiency monitoring of large-scale mangrove carbon sinks through unmanned aerial vehicle remote sensing technology, thereby providing technical support for the national carbon neutralization target.

[0062] Secondly, the device for calculating mangrove carbon storage based on airborne laser radar point cloud according to the embodiment of the present application is described with reference to the accompanying drawings.

[0063] Figure 8 ​is a block schematic diagram of a mangrove carbon storage calculation device based on airborne laser radar point cloud of an embodiment of the present application.

[0064] As shown in the figure, the mangrove carbon storage calculation device 10 based on airborne laser radar point cloud includes an extraction module 100, a fitting module 200, and a construction module 300. Figure 8

[0065] The extraction module 100 is configured to acquire laser radar point cloud data of a target mangrove forest area, collect a plurality of target single tree point clouds from the laser radar point cloud data, extract single tree height and crown width parameters corresponding to each target single tree point cloud in the plurality of target single tree point clouds, and calculate single tree carbon density corresponding to each target single tree point cloud based on the single tree height, the crown width parameters, and a preset allometric equation of tree species.

[0066] The fitting module 200 is configured to establish a functional relationship between the single tree height and the single tree carbon density, determine a plurality of target fitting functions corresponding to the functional relationship, perform model fitting on the plurality of target fitting functions, obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and establish a mangrove carbon density equation corresponding to the target mangrove forest area according to the correlation coefficient.

[0067] The construction module 300 is configured to acquire ground point data and non-ground point data corresponding to the laser radar point cloud data, construct a digital elevation model and a digital surface model according to the ground point data and the non-ground point data respectively, and calculate carbon storage of the target mangrove forest area by using the digital elevation model, the digital surface model, and the mangrove carbon density equation.

[0068] Optionally, in an embodiment of the present application, the extraction module includes a statistical unit, a first calculation unit, a substitution unit, and a second calculation unit.

[0069] The statistical unit is configured to count a plurality of characteristic values of a target single tree corresponding to each target single tree point cloud, wherein the plurality of characteristic values include a single tree lowest point, a single tree highest point, a single tree longest crown width, and a single tree shortest crown width.

[0070] The first calculation unit is configured to calculate the single tree height by using the single tree lowest point and the single tree highest point, and calculate the crown width parameters by using the single tree longest crown width and the single tree shortest crown width.

[0071] The substitution unit is configured to substitute the single tree height and the crown width parameters into the allometric equation of tree species to calculate single tree biomass, and calculate single tree carbon storage corresponding to the target single tree according to the single tree biomass and a preset carbon content coefficient of mangrove forest.

[0072] The second calculation unit is configured to calculate single tree crown width area corresponding to the target single tree based on the crown width parameters, and calculate the single tree carbon density according to the single tree crown width area and the single tree carbon storage.​

[0073] Optionally, in an embodiment of the present application, the fitting module 200 comprises an acquisition unit, a comparison unit and a determination unit.

[0074] The acquisition unit is configured to acquire a scatter plot between the single tree carbon density and the single tree height, and determine a plurality of target functions to be fitted corresponding to a functional relationship according to the scatter plot, wherein the plurality of target functions to be fitted comprises a linear function, a polynomial function, a power function and an exponential function.

[0075] The comparison unit is configured to perform model fitting on the plurality of target functions to be fitted to obtain a correlation coefficient corresponding to each target function to be fitted, and compare the correlation coefficients of the plurality of target functions to be fitted to obtain a maximum correlation coefficient.

[0076] The determination unit is configured to acquire a target function to be fitted corresponding to the maximum correlation coefficient, and determine a mangrove carbon density equation according to the target function to be fitted corresponding to the maximum correlation coefficient.

[0077] Optionally, in an embodiment of the present application, the construction module 300 comprises a filtering unit and a third calculation unit.

[0078] The filtering unit is configured to filter the laser radar point cloud data to obtain ground point data and non-ground point data, and construct a digital elevation model by using the ground point data, and establish a digital surface model by using the non-ground point data.

[0079] The third calculation unit is configured to determine a canopy height model according to the digital elevation model and the digital surface model, and substitute the canopy height model into the mangrove carbon density equation to calculate the carbon storage of the target mangrove forest region.

[0080] It should be noted that the foregoing explanation and description of the embodiment of the method for calculating the carbon storage of the mangrove forest based on the airborne laser radar point cloud also applies to the embodiment of the device for calculating the carbon storage of the mangrove forest based on the airborne laser radar point cloud, which will not be described here.

[0081] The mangrove carbon storage calculation device based on the airborne laser radar point cloud according to the embodiment of the application comprises an extraction module, which is used to acquire laser radar point cloud data of a target mangrove forest region, and collect a plurality of target single tree point clouds through the laser radar point cloud data, and extract single tree height and crown width parameters corresponding to each target single tree point cloud in the plurality of target single tree point clouds, so as to calculate single tree carbon density corresponding to each target single tree point cloud based on the single tree height, the crown width parameters and a preset tree species allometric growth equation; a fitting module is used to establish a functional relationship between the single tree height and the single tree carbon density, and determine a plurality of target fitting functions corresponding to the functional relationship, and perform model fitting on the plurality of target fitting functions, so as to obtain a correlation coefficient corresponding to each target fitting function in the plurality of target fitting functions, and establish a mangrove carbon density equation corresponding to the target mangrove forest region according to the correlation coefficient; a construction module is used to acquire ground point data and non-ground point data corresponding to the laser radar point cloud data, and construct a digital elevation model and a digital surface model according to the ground point data and the non-ground point data respectively, so as to calculate the carbon storage of the target mangrove forest region through the digital elevation model, the digital surface model and the mangrove carbon density equation. The unmanned aerial vehicle remote sensing technology of the application is helpful to realize high-resolution and high-timeliness monitoring of a large range of mangrove carbon sinks, so as to provide technical support for the carbon neutralization target of the whole country.

[0082] Figure 9 The structure schematic diagram of the electronic device provided by the embodiment of the application is provided. The electronic device can comprise:

[0083] The memory 901, the processor 902 and the computer program stored in the memory 901 and executable on the processor 902.

[0084] The processor 902 implements the mangrove carbon storage calculation method based on the airborne laser radar point cloud provided in the above embodiment when executing the program.

[0085] Further, the electronic device further comprises:

[0086] The communication interface 903 is used for communication between the memory 901 and the processor 902.

[0087] The memory 901 is used to store the computer program executable on the processor 902.

[0088] The memory 901 can contain a high-speed RAM memory, and can also include a non-volatile memory, for example, at least one disk memory.

[0089] If the memory 901, the processor 902 and the communication interface 903 are implemented independently, the communication interface 903, the memory 901 and the processor 902 can be connected with each other through a bus and complete communication between each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Figure 9 Only one thick line is used in the figure to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0090] Optionally, in a specific implementation, if the memory 901, the processor 902 and the communication interface 903 are integrated on a chip, the memory 901, the processor 902 and the communication interface 903 can complete communication between each other through an internal interface.

[0091] The processor 902 can be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement one or more embodiments of the present application.

[0092] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the method for calculating mangrove carbon storage based on airborne laser radar point cloud.

[0093] The embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program is executed to implement the method for calculating mangrove carbon storage based on airborne laser radar point cloud.

[0094] In the description of the application, reference to "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" means that a particular feature, structure, material, or characteristic being described is included in at least one embodiment or example of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment or example. Furthermore, the described specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples. In addition, the usage of "N" means at least two, for example, two, three or the like, unless explicitly stated otherwise.

[0095] Furthermore, the terms "first", "second", or the like, are used merely as a designation of certain elements or features, and do not imply or connote relative importance or a specific order of categorization thereof. Accordingly, features described as "first" or "second" can be explicitly or implicitly included in at least one of the features. In the description of the application, the meaning of "N" is at least two, for example, two, three, etc., unless explicitly specified otherwise.

[0096] Any process or method descriptions or blocks in flow charts or otherwise described herein represent embodiments which can be managed as one or more modules, segments, or portions of code which include one or more executable instructions for implementing specific logic functions or steps, and alternate implementations are possible. In some embodiments, the processes and methods described can be executed by one or more apparatuses or devices, either directly or after conversion to another language. Alternate implementations are possible.

[0097] The logic and / or steps represented in the flowcharts and / or described herein, for example, can be considered as a sequence of executable instructions stored in a computer readable medium, which can be executed by an instruction execution system, apparatus or device, such as a computer-based system, a processor-based system, or other system that can fetch the instructions from the instruction execution system, apparatus or device and execute the instructions, or a combination of the above. For the purposes of this specification, a "computer readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus or device. The computer readable medium can be a computer readable storage medium or a computer readable signal medium. The computer readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a propagation medium. The computer readable signal medium can include, but is not limited to, a computer readable medium that facilitates transfer of the program from one place to another. A specific example of a computer readable medium is a non-transitory computer-readable storage medium. A specific example of a computer readable signal medium is a source or destination of the computer readable medium. Another specific example of a computer readable signal medium is a computer readable signal travelling through space. Thus, a computer readable medium can take many forms of hardware to carry out the program for use by or in connection with the instruction execution system, apparatus or device.

[0098] It should be understood that aspects of the application can be implemented in hardware, software, firmware or a combination thereof. In the above embodiments, the N steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware and in another embodiment, the hardware can be implemented with any or a combination of the following technologies, which are all well known in the art: a discrete logic circuit(s) having logic gates for implementing logic functions upon an application of data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array(s) (PGA), a field programmable gate array (FPGA), etc.

[0099] Those of skill in the art would understand that the steps carried out in the above-mentioned embodiments can be implemented by a program instructing the relevant hardware to complete all or part of the steps, and the program can be stored in a computer readable storage medium. When the program is executed, it includes one of the steps of the method embodiments or a combination thereof.

[0100] In addition, each of the functional units in the various embodiments of the present application can be integrated in one processing module, or each of the units can be physically present separately, or two or more units can be integrated in one module. The integrated module can be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0101] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A method for calculating mangrove carbon storage based on airborne lidar point cloud, characterized in that: The following steps are involved: Obtaining laser radar point cloud data of a target red forest area, collecting multiple target tree point clouds using the laser radar point cloud data, and extracting tree height and crown width parameters corresponding to each target tree point cloud in the multiple target tree point clouds, so as to calculate the individual tree carbon density corresponding to each target tree point cloud based on the individual tree height, the crown width parameters, and a preset tree species allometric growth equation; Establishing a functional relationship between the individual tree height and the individual tree carbon density, determining multiple target functions to be fitted corresponding to the functional relationship, performing model fitting on the multiple target functions to be fitted to obtain a correlation coefficient corresponding to each target function to be fitted in the multiple target functions to be fitted, and establishing a mangrove carbon density equation corresponding to the target mangrove forest area based on the correlation coefficient; Obtain ground point data and non-ground point data corresponding to the lidar point cloud data, and construct a digital elevation model and a digital surface model based on the ground point data and the non-ground point data, respectively, so as to calculate the carbon storage of the target mangrove forest area through the digital elevation model, the digital surface model and the mangrove carbon density equation.

2. The method according to claim 1, characterized in that The step of extracting the tree height and crown width parameters corresponding to each target tree point cloud from the plurality of target tree point clouds, and calculating the tree carbon density corresponding to each target tree point cloud based on the tree height, the crown width parameters, and a preset tree species allometric growth equation, includes: Counting multiple characteristic values ​​of the target tree corresponding to each target tree point cloud, wherein the multiple characteristic values ​​include the lowest point of the single tree, the highest point of the single tree, the longest crown width of the single tree, and the shortest crown width of the single tree; Calculating the height of the single tree by the lowest point of the single tree and the highest point of the single tree, and calculating the crown width parameter by using the longest crown width of the single tree and the shortest crown width of the single tree; Substituting the tree height and crown width parameters into the tree species allometric growth equation to calculate the tree biomass, and calculating the tree carbon storage corresponding to the target tree based on the tree biomass and a preset red forest carbon content coefficient; Based on the crown width parameter, the crown width area of ​​the target tree is calculated, and the carbon density of the target tree is calculated according to the crown width area and the carbon storage of the target tree.

3. The method according to claim 2, characterized in that The determining of multiple target functions to be fitted corresponding to the functional relationship, performing model fitting on the multiple target functions to be fitted to obtain correlation coefficients corresponding to each target function to be fitted in the multiple target functions to be fitted, and establishing a mangrove carbon density equation corresponding to the target mangrove forest area based on the correlation coefficients, including: Obtaining a scatter plot between the single tree carbon density and the single tree height, and determining, based on the scatter plot, multiple target functions to be fitted corresponding to the functional relationship, wherein the multiple target functions to be fitted include linear functions, polynomial functions, power functions, and exponential functions; Performing model fitting on the multiple types of target functions to be fitted to obtain a correlation coefficient corresponding to each type of target function to be fitted, and comparing the correlation coefficients of the multiple types of target functions to be fitted to obtain a maximum correlation coefficient; A target function to be fitted corresponding to the maximum correlation coefficient is obtained, and the mangrove carbon density equation is determined according to the target function to be fitted corresponding to the maximum correlation coefficient.

4. The method according to claim 3, characterized in that The acquiring of ground point data and non-ground point data corresponding to the lidar point cloud data, and constructing a digital elevation model and a digital surface model based on the ground point data and the non-ground point data, respectively, to calculate the carbon storage of the target mangrove forest area by using the digital elevation model, the digital surface model and the mangrove carbon density equation, includes: Filtering the laser radar point cloud data to obtain the ground point data and the non-ground point data, constructing the digital elevation model using the ground point data, and establishing the digital surface model using the non-ground point data; A canopy height model is determined based on the digital elevation model and the digital surface model, and the canopy height model is substituted into the mangrove carbon density equation to calculate the carbon storage of the target mangrove forest area.

5. A mangrove carbon storage calculation device based on airborne laser radar point cloud, characterized in that: include: an extraction module for acquiring laser radar point cloud data of a target red forest area, collecting a plurality of target single tree point clouds using the laser radar point cloud data, and extracting the tree height and crown width parameters corresponding to each of the plurality of target single tree point clouds, so as to calculate the single tree carbon density corresponding to each target single tree point cloud based on the tree height, the crown width parameters, and a preset tree species allometric growth equation; a fitting module, configured to establish a functional relationship between the individual tree height and the individual tree carbon density, determine multiple target functions to be fitted corresponding to the functional relationship, perform model fitting on the multiple target functions to be fitted to obtain a correlation coefficient corresponding to each target function to be fitted in the multiple target functions to be fitted, and establish a mangrove carbon density equation corresponding to the target mangrove forest area based on the correlation coefficient; A construction module is used to obtain ground point data and non-ground point data corresponding to the lidar point cloud data, and to construct a digital elevation model and a digital surface model based on the ground point data and the non-ground point data, respectively, so as to calculate the carbon storage of the target mangrove forest area through the digital elevation model, the digital surface model and the mangrove carbon density equation.

6. The device according to claim 5, characterized in that The extraction module includes: a statistical unit, configured to count a plurality of characteristic values ​​of the target tree corresponding to each target tree point cloud, wherein the plurality of characteristic values ​​include the lowest point of the tree, the highest point of the tree, the longest crown width of the tree, and the shortest crown width of the tree; A first calculation unit is configured to calculate the height of the single tree by using the lowest point and the highest point of the single tree, and calculate the crown width parameter by using the longest crown width and the shortest crown width of the single tree; A substitution unit is used to substitute the tree height and the crown width parameters into the tree species allometric growth equation to calculate the tree biomass, and calculate the single tree carbon storage corresponding to the target tree based on the single tree biomass and a preset red forest carbon content coefficient; The second calculation unit is configured to calculate the crown area of ​​the target tree based on the crown parameter, and calculate the carbon density of the target tree according to the crown area and the carbon storage of the target tree.

7. The device according to claim 6, characterized in that The fitting module includes: an acquisition unit, configured to acquire a scatter plot between the single tree carbon density and the single tree height, and determine, based on the scatter plot, multiple target functions to be fitted corresponding to the functional relationship, wherein the multiple target functions to be fitted include linear functions, polynomial functions, power functions, and exponential functions; a comparing unit, configured to perform model fitting on the multiple types of target functions to be fitted to obtain a correlation coefficient corresponding to each type of target function to be fitted, and compare the correlation coefficients of the multiple types of target functions to be fitted to obtain a maximum correlation coefficient; A determination unit is configured to obtain a target function to be fitted corresponding to the maximum correlation coefficient, and determine the mangrove carbon density equation according to the target function to be fitted corresponding to the maximum correlation coefficient.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for calculating mangrove carbon storage based on airborne lidar point cloud as described in any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the mangrove carbon storage calculation method based on airborne lidar point cloud as described in any one of claims 1 to 4.

10. A computer program product comprising a computer program, characterized in that The computer program is executed to implement the mangrove carbon storage calculation method based on airborne lidar point cloud according to any one of claims 1 to 4.

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