A fine regional vegetation carbon sink visualization method and system

Abstract

This invention relates to the field of ecological environment management technology, specifically disclosing a refined method and system for visualizing regional vegetation carbon sequestration. The method includes: extracting land use types of a target area based on remote sensing data of land use types and biomass; determining forest areas based on land use types and establishing growth curves for the forest areas based on preset fitting curves; calculating the carbon sequestration amount of the forest areas based on the growth curves and determining the carbon sequestration ratio of different forest areas; allocating the total carbon sequestration amount to different sub-regions of the target area based on the carbon sequestration ratios, and visually converting the allocated target areas. This invention first selects a target area, calculates the carbon sequestration amount based on the forest areas within the target area, then redistributes the carbon sequestration to different areas according to land use types, and visualizes the redistribution results, facilitating the management of the area.

Description

Technical Field

[0001] This invention relates to the field of ecological environment management technology, specifically a method and system for visualizing regional vegetation carbon sequestration. Background Technology

[0002] A thorough understanding of spatial differences in forest carbon sequestration can guide national and regional forestry departments in proposing reasonable ecosystem protection and carbon sequestration enhancement measures, and provide a reference for optimizing the spatial development and protection pattern of terrestrial ecosystems, improving ecological functional zones, and enhancing the carbon sequestration function of forests.

[0003] Achieving spatialization of forest carbon sinks relies heavily on high-resolution remote sensing data and ecosystem model simulations. While the development of remote sensing technology provides robust data support for ecosystem research and management, high-resolution satellite remote sensing imagery is difficult to acquire, has poor timeliness, and is easily affected by external environmental factors. Especially for small areas, higher spatial resolution is required; limitations in spatial resolution prevent the spatial visualization of forest carbon sinks in small areas, making it difficult to distinguish differences in carbon sink levels within the region. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for visualizing carbon sequestration in a refined area of ​​vegetation, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for visualizing carbon sequestration in a refined area of ​​vegetation, the method comprising:

[0007] Select a target area, obtain historical ecosystem data for that area, and determine the total carbon sink of vegetation in that area;

[0008] Remote sensing data on land use types and biomass of the target area are acquired, and land use types of the target area are extracted based on the land use type and biomass remote sensing data; wherein, the land use types include forest, grassland and farmland;

[0009] Forest areas are determined based on land use type, and growth curves of forest areas are established based on preset fitting curves; the growth curves are the curve relationship between vegetation biomass and forest age.

[0010] The carbon sequestration of the forest area is calculated based on the growth curve, and the carbon sequestration ratio of different forest areas is determined.

[0011] Based on the carbon sequestration ratio, the total carbon sequestration is allocated to different sub-regions of the target area, and the allocated target areas are then visualized.

[0012] As a further aspect of the present invention: the step of determining the total carbon sink of the vegetation in the area includes:

[0013] The carbon sink of different types of vegetation in all spatial grids of the target area is obtained based on the trained dynamic vegetation model.

[0014] Then, the total carbon sink of the target area is calculated based on the area of ​​each vegetation type.

[0015] As a further aspect of the present invention: the step of determining the total carbon sink of the vegetation in the area includes:

[0016] Obtain forest resource statistics data, input the forest resource statistics data into a preset calculation formula, and obtain the total carbon sequestration;

[0017] The calculation formula is as follows:

[0018] Carbon_sink=C_stock×ρ_wood×k_convert×R_carbon×44 / 12;

[0019] Wherein, Carbon_sink represents forest carbon sink; C_stock represents the change in standing timber volume over two consecutive years; ρ_wood represents the average timber density of standing timber; k_convert represents the biomass conversion coefficient; R_carbon represents the carbon content of biomass; and 44 / 12 refers to the CO2 / C ratio.

[0020] As a further aspect of the present invention: the fitting curve is:

[0021] BM = BM_eq × (1 - e^((-age / τ)))

[0022] Wherein, BM represents vegetation biomass; BM_eq represents the equilibrium vegetation biomass density; age represents the stand age; and τ represents the recovery time of the equilibrium vegetation biomass density.

[0023] As a further aspect of the present invention: the step of calculating the carbon sink of the forest area based on the growth curve includes:

[0024] Obtain the annual vegetation biomass bm1 for each forest grid from the vegetation biomass data of the target area;

[0025] The tree age (age1) is determined based on the growth curve.

[0026] Calculate the biomass bm0 corresponding to the tree age 0 of the previous year based on the growth curve;

[0027] Calculate the difference between bm1 and bm0 to estimate the annual forest carbon sink for each forest grid.

[0028] The present invention also provides a fine-grained regional vegetation carbon sequestration visualization system, the system comprising:

[0029] The total carbon sink module is used to select a target area, obtain historical ecosystem data for that area, and determine the total carbon sink of the vegetation in that area.

[0030] The type determination module is used to acquire land use type remote sensing data and biomass remote sensing data of the target area, and extract the land use type of the target area based on the land use type remote sensing data and biomass remote sensing data; wherein, the land use type includes forest, grassland and farmland;

[0031] The curve generation module is used to determine forest areas based on land use type and to establish growth curves for forest areas based on preset fitting curves; the growth curves are the curve relationships between vegetation biomass and forest age.

[0032] The sub-region calculation module is used to calculate the carbon sink of a forest region based on the growth curve and to determine the carbon sink ratio of different forest regions.

[0033] The allocation and display module is used to allocate the total carbon sequestration amount to different sub-regions of the target area based on the carbon sequestration ratio, and to perform a visual transformation of the allocated target area.

[0034] As a further aspect of the present invention: the sub-region calculation module includes:

[0035] The first acquisition unit is used to acquire the annual vegetation biomass bm1 of each forest grid from the vegetation biomass data of the target area.

[0036] The first calculation unit is used to determine the tree age (age1) based on the growth curve.

[0037] The second calculation unit is used to calculate the biomass bm0 corresponding to the tree age 0 of the previous year based on the growth curve.

[0038] The difference calculation unit is used to calculate the difference between bm1 and bm0 to estimate the annual forest carbon sink of each forest grid.

[0039] Compared with the prior art, the beneficial effects of the present invention are: the present invention first selects the target area, calculates the carbon sink based on the forest area in the target area, and then redistributes the carbon sink in different areas according to the land use type, and visualizes the redistribution results, which facilitates the staff's control over the area. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0041] Figure 1 A flowchart for a method to visualize carbon sequestration in fine-grained regional vegetation.

[0042] Figure 2 This is a high-resolution vegetation biomass map of a certain area in 2010.

[0043] Figure 3 This is a high-resolution land use type map of a certain region in 2020.

[0044] Figure 4 This is a curve showing the relationship between forest biomass and forest age in a certain region.

[0045] Figure 5 This is a spatial distribution map of forest carbon sinks in a certain region in 2017.

[0046] Figure 6 This is a spatial distribution map of forest carbon sinks in a certain region in 2018. Detailed Implementation

[0047] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0048] Example 1

[0049] Figure 1 The flowchart illustrates a method for visualizing carbon sequestration in a refined area of ​​vegetation. In this embodiment of the invention, a method for visualizing carbon sequestration in a refined area of ​​vegetation includes:

[0050] Step S100: Select the target area, obtain historical ecosystem data for the area, and determine the total carbon sink of the vegetation in the area;

[0051] Step S200: Obtain remote sensing data of land use type and biomass of the target area, and extract the land use type of the target area based on the remote sensing data of land use type and biomass; wherein, the land use type includes forest, grassland and farmland;

[0052] Step S300: Determine the forest area based on land use type, and establish the forest area growth curve based on the preset fitting curve; the growth curve is the curve relationship between vegetation biomass and forest age.

[0053] Step S400: Calculate the carbon sequestration of the forest area based on the growth curve, and determine the carbon sequestration ratio of different forest areas;

[0054] Step S500: Based on the carbon sink ratio, allocate the total carbon sink amount to different sub-regions of the target area, and perform a visual transformation on the allocated target areas.

[0055] In one example of the technical solution of this invention:

[0056] Step 1: Select a specific small area and calculate the total carbon sink of the vegetation in that area by combining the ecosystem data of that area over several consecutive years.

[0057] In this embodiment of the application, the target area is a county or city in East China, with an area of ​​approximately 590 square kilometers, which is about one-quarter of a 50-kilometer resolution grid.

[0058] In this embodiment of the application, based on Method 2 in the invention, the forest carbon sink in the region from 2016 to 2019 is calculated according to data such as the standing timber volume and forest area of ​​the region, as shown in Table 1.

[0059] Table 1. Forest carbon sequestration capacity of a certain region

[0060]

[0061] Step 2: Obtain high-resolution remote sensing data on land use types and biomass for the region.

[0062] In this embodiment, forest biomass remote sensing data with a resolution of 100 meters from 2010 was selected (see...). Figure 2 ) and the 2020 10-meter resolution land use type map (see Figure 3 These are sufficient to vividly depict the terrain features of the area.

[0063] To differentiate biomass data corresponding to different types of vegetation, forest biomass maps and land cover maps need to be overlaid. However, due to the inconsistency in resolution between the two, the forest biomass map is resampled from its nearest neighbors to obtain a map with the same resolution as the land cover map. Biomass data is then extracted from all forest grids.

[0064] Step 3: Establish tree growth curves for the area.

[0065] In this embodiment, by running the dynamic vegetation model to a steady state, the vegetation carbon density data for the four forest types and over the past 100 years for the grid in which the region is located are obtained. Table 2 shows the vegetation carbon density data for the four forest types at seven time points. The total vegetation carbon density of all forest types each year is converted into biomass using a coefficient of 0.45. Then, forest biomass and forest age data are used to fit the parameters according to the above formula. The formula for fitting the growth curve is as follows, and the growth curve is shown in [reference needed]. Figure 4 .

[0066] AGB=115.81×(1-e^((-age / 35.33)));

[0067] Table 2 Carbon density of forest at different growth stages in a certain region

[0068]

[0069] Step 4: Calculate the carbon sink of all grid forests in a certain area.

[0070] After unifying high-resolution biomass data and land use type data to a 10-meter resolution, the coordinates of each grid, including forest, farmland, and grassland, were determined based on land cover type. Since growth curves are only applicable to forest trees, the age of the forest corresponding to the forest biomass in each grid was deduced using the vegetation growth curve. Then, the forest biomass of the previous year was calculated, and the forest carbon sink of each grid was estimated using the difference between the two years of forest biomass.

[0071] Step 5: Carbon sink spatialization.

[0072] In this embodiment, the total carbon sequestration of the region in 2017 and 2018 is allocated to each grid according to the grid forest carbon sequestration ratio calculated in step 4, thus spatializing the forest carbon sequestration. For grid points without vegetation, such as construction land and bare land, the carbon sequestration is set to zero. The spatial maps of forest carbon sequestration in this region in 2018 and 2019 are shown below. Figure 5 , Figure 6 .

[0073] In a preferred embodiment of the technical solution of the present invention, the step of determining the total carbon sink of the vegetation in the area includes:

[0074] The carbon sink of different types of vegetation in all spatial grids of the target area is obtained based on the trained dynamic vegetation model.

[0075] Then, the total carbon sink of the target area is calculated based on the area of ​​each vegetation type.

[0076] In a preferred embodiment of the technical solution of the present invention, the step of determining the total carbon sink of the vegetation in the area includes:

[0077] Obtain forest resource statistics data, input the forest resource statistics data into a preset calculation formula, and obtain the total carbon sequestration;

[0078] The calculation formula is as follows:

[0079] Carbon_sink=C_stock×ρ_wood×k_convert×R_carbon×44 / 12;

[0080] Wherein, Carbon_sink represents forest carbon sink; C_stock represents the change in standing timber volume over two consecutive years; ρ_wood represents the average timber density of standing timber; k_convert represents the biomass conversion coefficient; R_carbon represents the carbon content of biomass; and 44 / 12 refers to the CO2 / C ratio.

[0081] The above content provides methods for calculating the total carbon sink of vegetation in the target area. There are two methods in total:

[0082] Method 1: Dynamic vegetation model simulation can obtain the carbon sink of different types of vegetation in all spatial grids of the target area. Then, the total carbon sink of each type of vegetation in the target area is calculated based on its area, and then the total carbon sink of the target area is calculated.

[0083] Method 2: Calculate the total carbon sink of the target area's forests using forest resource statistics, such as standing timber volume, according to the following formula.

[0084] As a preferred embodiment of the technical solution of the present invention, the fitting curve is:

[0085] BM=BM_eq×(1-e^((-age / τ)));

[0086] Wherein, BM represents vegetation biomass; BM_eq represents the equilibrium vegetation biomass density; age represents the stand age; and τ represents the recovery time of the equilibrium vegetation biomass density.

[0087] As a preferred embodiment of the technical solution of the present invention, the step of calculating the carbon sink of the forest area based on the growth curve includes:

[0088] Obtain the annual vegetation biomass bm1 for each forest grid from the vegetation biomass data of the target area;

[0089] The tree age (age1) is determined based on the growth curve.

[0090] Calculate the biomass bm0 corresponding to the tree age 0 of the previous year based on the growth curve;

[0091] Calculate the difference between bm1 and bm0 to estimate the annual forest carbon sink for each forest grid.

[0092] It is worth mentioning that for step S500 above, namely the spatial visualization process of vegetation carbon sequestration:

[0093] Forests typically act as carbon sinks each year. Carbon sink spatialization allocates the total carbon sink amount of a target area to forest grids based on the carbon sink proportion in each spatial grid. However, in some areas, forests may become carbon sources due to factors such as deforestation and natural disasters. In such cases, the total carbon emissions are allocated to each forest grid point based on the vegetation biomass proportion in each grid. For farmland and grassland, their total carbon sink / carbon source amounts are allocated proportionally to the corresponding spatial grids. For built-up areas and bare land, the carbon sink amount is set to zero, thus achieving carbon sink visualization for the target area.

[0094] Example 2

[0095] In an embodiment of the present invention, a fine-grained regional vegetation carbon sequestration visualization system is provided, the system comprising:

[0096] The total carbon sink module is used to select a target area, obtain historical ecosystem data for that area, and determine the total carbon sink of the vegetation in that area.

[0097] The type determination module is used to acquire land use type remote sensing data and biomass remote sensing data of the target area, and extract the land use type of the target area based on the land use type remote sensing data and biomass remote sensing data; wherein, the land use type includes forest, grassland and farmland;

[0098] The curve generation module is used to determine forest areas based on land use type and to establish growth curves for forest areas based on preset fitting curves; the growth curves are the curve relationships between vegetation biomass and forest age.

[0099] The sub-region calculation module is used to calculate the carbon sink of a forest region based on the growth curve and to determine the carbon sink ratio of different forest regions.

[0100] The allocation and display module is used to allocate the total carbon sequestration amount to different sub-regions of the target area based on the carbon sequestration ratio, and to perform a visual transformation of the allocated target area.

[0101] Furthermore, the sub-region calculation module includes:

[0102] The first acquisition unit is used to acquire the annual vegetation biomass bm1 of each forest grid from the vegetation biomass data of the target area.

[0103] The first calculation unit is used to determine the tree age (age1) based on the growth curve.

[0104] The second calculation unit is used to calculate the biomass bm0 corresponding to the tree age 0 of the previous year based on the growth curve.

[0105] The difference calculation unit is used to calculate the difference between bm1 and bm0 to estimate the annual forest carbon sink of each forest grid.

[0106] All functions of the fine-grained regional vegetation carbon sequestration visualization method are performed by computer equipment, which includes one or more processors and one or more memories. The one or more memories store at least one piece of program code, which is loaded and executed by the one or more processors to realize the functions of the fine-grained regional vegetation carbon sequestration visualization method.

[0107] The processor fetches instructions from memory one by one, analyzes the instructions, and then performs the corresponding operations according to the instructions, generating a series of control commands to enable the various parts of the computer to act automatically, continuously, and in a coordinated manner, forming an organic whole. This enables the input of programs and data, as well as the calculation and output of results. The arithmetic or logical operations generated in this process are all performed by the arithmetic unit. The memory includes a read-only memory (ROM), which is used to store computer programs. The memory is equipped with external protection devices.

[0108] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0109] Those skilled in the art will understand that the above description of the service equipment is merely an example and does not constitute a limitation on the terminal equipment. It may include more or fewer components than described above, or a combination of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0110] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the terminal device, connecting various parts of the user terminal via various interfaces and lines.

[0111] The aforementioned memory can be used to store computer programs and / or modules. The aforementioned processor implements various functions of the aforementioned terminal device by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as information collection template display function, product information publishing function, etc.); the data storage area may store data created based on the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that different product providers need to publish, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0112] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the modules / units in the systems of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the functions of the various system embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0113] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0114] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for visualizing carbon sequestration in refined regional vegetation, characterized in that, The method includes: Select a target area, obtain historical ecosystem data for that area, and determine the total carbon sink of vegetation in that area; Remote sensing data on land use types and biomass of the target area are acquired, and land use types of the target area are extracted based on the land use type and biomass remote sensing data; wherein, the land use types include forest, grassland and farmland; Forest areas are determined based on land use type, and growth curves of forest areas are established based on preset fitting curves; the growth curves are the curve relationship between vegetation biomass and forest age. The carbon sequestration of the forest area is calculated based on the growth curve, and the carbon sequestration ratio of different forest areas is determined. Based on the carbon sequestration ratio, the total carbon sequestration is allocated to different sub-regions of the target area, and the allocated target areas are then visualized.

2. The method for visualizing detailed regional vegetation carbon sequestration according to claim 1, characterized in that, The steps for determining the total carbon sink of the vegetation in the area include: The carbon sink of different types of vegetation in all spatial grids of the target area is obtained based on the trained dynamic vegetation model. Then, the total carbon sink of the target area is calculated based on the area of ​​each vegetation type.

3. The method for visualizing detailed regional vegetation carbon sequestration according to claim 1, characterized in that, The steps for determining the total carbon sink of the vegetation in the area include: Obtain forest resource statistics data, input the forest resource statistics data into a preset calculation formula, and obtain the total carbon sequestration; The calculation formula is as follows: Carbon_sink=C_stock×ρ_wood×k_convert×R_carbon×44 / 12; Wherein, Carbon_sink represents forest carbon sink; C_stock represents the change in standing timber volume over two consecutive years; ρ_wood represents the average timber density of standing timber; k_convert represents the biomass conversion coefficient; R_carbon represents the carbon content of biomass; and 44 / 12 refers to the CO2 / C ratio.

4. The method for visualizing detailed regional vegetation carbon sequestration according to claim 2 or 3, characterized in that, The fitted curve is: BM = BM_eq × (1 - e^((-age / τ))) Wherein, BM represents vegetation biomass; BM_eq represents the equilibrium vegetation biomass density; age represents the stand age; and τ represents the recovery time of the equilibrium vegetation biomass density.

5. The method for visualizing detailed regional vegetation carbon sequestration according to claim 1, characterized in that, The step of calculating the carbon sink of the forest area based on the growth curve includes: Obtain the annual vegetation biomass bm1 for each forest grid from the vegetation biomass data of the target area; The tree age (age1) is determined based on the growth curve. Calculate the biomass bm0 corresponding to the tree age 0 of the previous year based on the growth curve; Calculate the difference between bm1 and bm0 to estimate the annual forest carbon sink for each forest grid.

6. A refined regional vegetation carbon sequestration visualization system, characterized in that, The system includes: The total carbon sink module is used to select a target area, obtain historical ecosystem data for that area, and determine the total carbon sink of the vegetation in that area. The type determination module is used to acquire land use type remote sensing data and biomass remote sensing data of the target area, and extract the land use type of the target area based on the land use type remote sensing data and biomass remote sensing data; wherein, the land use type includes forest, grassland and farmland; The curve generation module is used to determine forest areas based on land use type and to establish growth curves for forest areas based on preset fitting curves; the growth curves are the curve relationships between vegetation biomass and forest age. The sub-region calculation module is used to calculate the carbon sink of a forest region based on the growth curve and to determine the carbon sink ratio of different forest regions. The allocation and display module is used to allocate the total carbon sequestration amount to different sub-regions of the target area based on the carbon sequestration ratio, and to perform a visual transformation of the allocated target area.

7. The fine-grained regional vegetation carbon sequestration visualization system according to claim 6, characterized in that, The sub-region calculation module includes: The first acquisition unit is used to acquire the annual vegetation biomass bm1 of each forest grid from the vegetation biomass data of the target area. The first calculation unit is used to determine the tree age (age1) based on the growth curve. The second calculation unit is used to calculate the biomass bm0 corresponding to the tree age 0 of the previous year based on the growth curve. The difference calculation unit is used to calculate the difference between bm1 and bm0 to estimate the annual forest carbon sink of each forest grid.

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