Carbon sequestration service flow feature identification method based on supply-demand relationship

Abstract

The invention discloses a carbon sequestration service flow feature identification method based on a supply-demand relationship, and belongs to the technical field of ecological system services. Based on an InVEST model and a carbon emission coefficient method, various energy sources and carbon generated in the using process of the energy sources serve as main carbon emission sources, and by means of land utilization types, population density and the like, refined evaluation of the supply quantity and the demand quantity of the carbon sequestration service is achieved; carbon sequestration service supply and demand surplus or deficit relation analysis is realized based on the supply and demand ratio; and quantizing the carbon sequestration service flow intensity based on the breaking point and the field intensity model, and finally realizing feature identification of the carbon sequestration service space flow rate, the path number, the path direction and the like, so as to optimize and explore how to quantify the balance relationship and the flow feature of the carbon sequestration service in the key area.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecosystem services, in particular to a carbon sequestration service flow feature identification method based on supply and demand relationship. BACKGROUND

[0002] Ecosystem carbon sequestration service refers to the fixation and storage of CO2 in the atmosphere by an ecosystem to offset part of the carbon emissions generated by human activities, and is an important part of ecosystem regulation services.

[0003] In the prior art, carbon sequestration service research focuses on single-dimensional supply or demand evaluation, and static quantitative analysis is carried out by using CASA, InVEST, carbon emission coefficient and other models. Although existing research has begun to focus on the supply and demand relationship and spatial flow characteristics of carbon sequestration service, the current research still mainly focuses on the supply and demand evaluation of carbon sequestration service, and there is still a lack of discussion on the mismatch characteristics of carbon sequestration service supply and demand in key areas and time periods and the spatial flow law. How to quantify the supply and demand relationship and spatial flow characteristics of regional carbon sequestration service has become a key problem to be solved. The present application can effectively reveal the balance state of the supply and demand relationship based on the carbon sequestration service supply and demand ratio, and further realize the identification of the flow intensity, path number and path direction of carbon sequestration service space by analyzing the distance and resistance between the supply source, demand point and the distance and resistance based on the breaking point formula and field strength model. SUMMARY

[0004] The purpose of the present application is to provide a carbon sequestration service flow feature identification method based on supply and demand relationship, based on InVEST model, carbon emission coefficient method, taking carbon generated in the use process of various types of energy as the main source of carbon emission, and using land use type, population density and other factors to realize fine evaluation of carbon sequestration service supply and demand; based on the supply and demand ratio to realize the surplus or deficit relationship analysis of carbon sequestration service; based on the breaking point and field strength model to quantify the flow intensity of carbon sequestration service, and finally realize the feature identification of carbon sequestration service space flow, path number and path direction, so as to solve the problems raised in the background art.

[0005] In order to achieve the above purpose, the present application discloses a carbon sequestration service flow feature identification method based on supply and demand relationship, comprising the following steps:

[0006] S1, based on the Carbon module in the InVEST model, quantifying the carbon sequestration service supply amount by the carbon density of different land use types;

[0007] S2, based on the carbon emission coefficient method, taking the carbon emission generated in the use process of various types of energy as the total carbon sequestration service demand, obtaining the carbon emission per capita based on the population, and combining the 1km*1km population density grid data to realize fine evaluation of carbon sequestration service demand;

[0008] S3. Based on the supply-demand ratio, realize the supply-demand relationship analysis of carbon sequestration service;

[0009] S4. Based on hotspot analysis, realize the supply-demand balance analysis of carbon sequestration service;

[0010] S5. Based on the field strength model, simulate the spatial flow characteristics of carbon sequestration service, and quantify the flow intensity and direction from the supply area to the demand area.

[0011] Preferably, step S1 specifically comprises the following steps:

[0012] S1.1, obtain land use data, and construct carbon pool density table of different land use types; wherein the parameters in the carbon pool density table include aboveground biomass carbon storage, underground biomass carbon storage, soil carbon storage and dead organic matter;

[0013] S1.2, carbon sequestration service supply quantity quantification: based on the Carbon module in the InVEST model, the carbon density of different land use types is quantified to obtain the total carbon storage of the region, and the carbon sequestration service supply quantity is quantified.

[0014] S1.3, township scale carbon sequestration service supply quantity evaluation: based on the partition statistics in the ArcGIS spatial analysis tool, taking the township administrative area as the statistical unit, the carbon sequestration service supply quantity of each township is quantified.

[0015] Preferably, step S2 specifically comprises the following steps:

[0016] S2.1, total carbon emission quantity statistics of carbon sequestration service: based on the carbon emission coefficients of 15 types of energy consumption including raw coal, washed coal, other washed coal, coke, natural gas, liquefied natural gas, crude oil, gasoline, kerosene, diesel, fuel oil, liquefied petroleum gas, other petroleum products, heat and electricity, the total carbon emission quantity of the region, i.e. the total carbon sequestration service demand quantity, is obtained;

[0017] S2.2, fine evaluation of carbon sequestration service demand quantity at grid scale: based on the total carbon emission quantity and the total population, the per capita carbon emission quantity is obtained, and combined with the 1km×1km population density grid data, the fine evaluation of carbon sequestration service demand quantity at grid scale is realized;

[0018] S2.3, township scale carbon sequestration service demand quantity evaluation: based on the partition statistics in the ArcGIS spatial analysis tool, taking the township administrative division as the statistical unit, the carbon sequestration service demand quantity of each township is quantified.

[0019] Preferably, step S3 specifically comprises the following steps:

[0020] S3.1, calculate the supply-demand ratio: based on the supply-demand ratio of ecosystem service, the supply-demand relationship of carbon sequestration service is quantified, the essence of carbon sequestration service surplus or shortage is revealed, and the supply-demand characteristics of regional carbon sequestration service are reflected;

[0021] S3.2, analyze the supply and demand situation at the township level, evaluate the supply and demand state of carbon fixation service at the township scale: based on the supply and demand ratio of S3.1, the average supply and demand ratio of the area contained by each township is taken as the supply and demand ratio data of each township by using the zoning statistics in the spatial analysis tool of ArcGIS, so as to quantify the supply and demand state of carbon fixation service of each township.

[0022] Preferably, step S4 specifically comprises the following steps:

[0023] S4.1, hotspot analysis: the township scale supply and demand data in step S3.2 is subjected to hotspot analysis by using Getis-Ord Gi * statistical method in ArcGIS;

[0024] S4.2, division of supply and demand balance area: according to the results of hotspot analysis, five areas including deficit serious area, deficit general area, supply and demand balance area, surplus general area and surplus sufficient area are defined to realize the analysis of supply and demand balance state of regional carbon fixation service.

[0025] Preferably, step S5 specifically comprises the following steps:

[0026] S5.1, determination of supply area and demand area: based on the results of hotspot analysis, the surplus general area and the surplus sufficient area are taken as the supply area, and the deficit serious area and the deficit general area are taken as the demand area;

[0027] S5.2, simulation of spatial flow characteristics: the spatial flow of carbon fixation quantity shows the trend of attenuation with the increase of geographical distance, the service flow boundary is simulated by using the breaking point formula, the flow intensity of carbon fixation quantity per unit area is calculated based on the field strength model, so as to obtain the service flow between the supply area and the demand area;

[0028] S5.3, determination of main flow direction: the calculation results of S5.2 are applied to determine the maximum carbon fixation service flow direction of each supply area and the maximum carbon fixation service flow source of each demand area;

[0029] S5.4, the analysis results of S5.3 are applied, combined with the main flow direction marked by arrow symbol, to form the carbon fixation service spatial flow network, so as to realize the identification of carbon fixation service flow characteristics based on the supply and demand relationship.

[0030] Preferably, step S5.2 specifically comprises the following steps:

[0031] S5.2.1, taking the supply area particle as a source point and the demand area particle as a target point, and by means of the 'element point conversion' tool and the 'generate near neighbor analysis table' tool of ArcGIS, all possible supply-demand pairing combinations and distances are calculated, the distance from the supply area service particle to the breaking point is determined according to the breaking point formula, and the effective radiation range of the carbon fixation service is defined;

[0032] S5.2.2, based on the field strength model, the flow intensity of the unit area carbon fixation amount is calculated, and the service flow between the supply area and the demand area is obtained.

[0033] Therefore, the present application has the following beneficial effects:

[0034] (1) The present application creates an energy-population-land multi-source data collaborative framework, breaking through the limitations of traditional single-element evaluation: 15 types of energy carbon emission coefficients are used on the demand side, combined with population grids, to realize kilometer-level demand refinement, which is different from the existing technology which relies on county-level statistical mean value; four-dimensional carbon pool parameters and InVEST modeling are integrated to solve the spatial heterogeneity problem of traditional carbon density estimation; through grid and township double-scale aggregation, the quantification precision of supply and demand is improved.

[0035] (2) The present application creatively introduces the breaking point theory in view of the spatial competitive nature of ecosystem service flow: the competitive radiation boundary formula is used to replace the infinite decay assumption of the traditional gravity model, which is the first time to realize the accurate definition of the limited spatial domain of carbon fixation service; the flow intensity algorithm with clear physical mechanism is constructed by coupling the field strength model and the dynamic radiation area, which overcomes the theoretical defects of'service super-domain diffusion' in the existing method; through point neighbor analysis and maximum flow direction identification, the directional flow network conforming to the ecological process is output.

[0036] (3) The present application builds a'supply-demand-balance-flow' whole-chain analysis engine to form a carbon management decision tool that can be implemented: based on the Getis-Ord Gi* five-level partition, the priority intervention area is automatically identified, which is superior to manual demarcation efficiency; the generated directional flow network diagram directly reveals the carbon compensation path across administrative areas, supporting the accurate implementation of ecological transfer payment; the whole process integrates the ArcGIS / Python tool chain, the calculation time is shorter than the traditional method, and the real-time deduction demand at the provincial scale is met.

[0037] The technical solutions of the present application will be further described in detail below with the help of the drawings and examples. DESCRIPTION OF DRAWINGS

[0038] Figure 1 The map of a certain city main urban area, wherein (a) is the administrative partition of the main urban area of a certain city, and (b) is the township distribution map of the main urban area of a certain city;

[0039] Figure 2Carbon fixation service supply and average value of main city of a certain city from 2000 to 2020;

[0040] Figure 3 Carbon fixation service supply of different townships of main city of a certain city from 2000 to 2020;

[0041] Figure 4 Carbon fixation service demand of main city of a certain city from 2000 to 2020 and average value;

[0042] Figure 5 Carbon fixation service demand of different townships of main city of a certain city from 2000 to 2020;

[0043] Figure 6 Carbon fixation service supply-demand ratio of main city of a certain city from 2000 to 2020;

[0044] Figure 7 Carbon fixation service supply-demand ratio of different townships of main city of a certain city from 2000 to 2020;

[0045] Figure 8 Carbon fixation service supply-demand balance state of each township of main city of a certain city from 2000 to 2020;

[0046] Figure 9 Carbon fixation service spatial flow characteristics of main city of a certain city from 2000 to 2020. DETAILED DESCRIPTION

[0047] The technical solutions of the present application are further described below through the drawings and examples.

[0048] Unless otherwise defined, the technical terms or scientific terms used in the present application shall have the usual meanings understood by those with ordinary skills in the art to which the present application belongs.

[0049] In addition, it should be understood that although the present specification is described in terms of embodiments, each embodiment does not contain only one independent technical solution, and the description of the specification is only for the sake of clarity, and those skilled in the art should consider the specification as a whole, and the technical solutions in each example can be appropriately combined to form other embodiments that those skilled in the art can understand. These other embodiments are also covered by the protection scope of the present application.

[0050] The supply-demand balance of ecosystem carbon fixation service has become a core issue for mitigating climate change and optimizing ecological resource allocation. Although there are various methods for evaluating the supply, demand, and supply-demand relationship of ecosystem carbon fixation service, it is still necessary to optimize the exploration of how to quantify the balance relationship and flow characteristics of carbon fixation service in key areas.

[0051] In this context, the present application provides a carbon sequestration service flow feature identification method based on supply and demand relationship. Based on InVEST model and carbon emission coefficient method, taking carbon generated in the use process of various types of energy as the main source of carbon emission, and with the help of land use type and population density, the supply and demand of carbon sequestration service is evaluated in detail; based on the supply-demand ratio, the surplus or deficit relationship of carbon sequestration service is analyzed; based on the breaking point and field strength model, the flow intensity of carbon sequestration service is quantified, and finally the characteristics of carbon sequestration service space flow, path number, path direction, etc. are identified.

[0052] Embodiment

[0053] This embodiment takes a certain city as an example, as shown in Figure 1 The administrative division of the main city of a certain city is shown in Figure 1 (a), and the township distribution of the main city of a certain city is shown in Figure 1 (b), a carbon sequestration service flow feature identification method based on supply and demand relationship is provided, comprising the following steps:

[0054] S1, based on the Carbon module in the InVEST model, the carbon sequestration service supply is quantified by the carbon density of different land use types.

[0055] S1.1, based on the land use data of a certain city in 2000, 2005, 2010, 2015 and 2020, a carbon density table of different land use types is constructed, as shown in Table 1.

[0056] Table 1 Carbon density table of different land use types / ton

[0057] Name Above-ground biomass carbon stock Below-ground biomass carbon stock Soil carbon stock Dead organic matter Paddy field 3.62 1.62 9.29 1 Dry land 3.27 1.53 8.07 1 Forest land 64.6 11.28 51.14 1.81 Shrub land 64.6 11.28 51.14 1.81 Open woodland 64.6 11.28 51.14 1.81 Other forest land 4.82 11.28 51.14 1.81 High-cover grassland 4.82 7.71 12.76 1.54 Medium-cover grassland 4.82 7.71 12.76 1.54 Low-cover grassland 4.82 7.71 12.76 1.54 River 1.24 1.37 6.38 0.99 Lake 0.75 0.96 5.11 0.78 Reservoir pit 0.53 0.71 3.23 0.51 Beach 1.56 2.29 8.75 1.01 Town 1.03 1.35 5.32 0 Rural residential area 2.23 1.42 7.96 0 Industrial and mining construction land 1.47 1.15 5.45 0 Bare land 2.08 1.47 7.46 0.96

[0058] S1.2, carbon sequestration service supply is quantified. Based on the Carbon module in the InVEST model, the carbon sequestration service supply is quantified by the carbon density of different land use types, as shown in Figure 2 The carbon sequestration service supply of the main city of a certain city from 2000 to 2020 is shown in total , the total carbon storage C total of the study area is obtained. Spatially, the high-value area of carbon sequestration service supply almost coincides with the high-altitude area, mainly distributed in the parallel mountainous area, showing a strip-shaped distribution along the northeast-southwest direction, and the overall spatial distribution pattern almost remains unchanged; the areas with lower supply are mainly distributed in the low-altitude and high-population-density areas along the Yangtze River; in the time dimension, the overall supply of carbon sequestration service shows a continuous decreasing trend from 2000 to 2020.

[0059] C total =C above +C below +C soil +C dead

[0060] wherein C total represents the total carbon sequestration (tons), C above is the carbon storage of aboveground organisms (tons), C below refers to the carbon storage of belowground organisms (tons), C soil represents the carbon storage in the soil (tons), and C dead refers to the carbon storage of dead organic matter (tons).

[0061] The results of the calculation of the carbon sequestration service supply in the main city of a certain city by the above formula are shown in Table 2 below:

[0062] Table 2 Carbon sequestration service supply in the main city of a certain city / tons

[0063] Year Total carbon storage C total ]] 2000 328.63 2005 327.69 2010 325.44 2015 323.21 2020 313.76

[0064] S1.3, township scale carbon sequestration service supply assessment. Through the zoning statistics in the spatial analysis tool of ArcGIS, the carbon sequestration service supply of each township is quantified by taking the township administrative division as the statistical unit. For example, Figure 3 is the carbon sequestration service supply of different townships in the main city of a certain city from 2000 to 2020. Spatially, the supply of D10 township, D18 township and D26 township in D district, C9 township, C14 township in C district and E4 township in E district is higher; the low value area is concentrated in the central urban area, and the number of low supply townships shows an increasing trend. Figure 1

[0065] S2, based on the carbon emission coefficient method, taking the carbon emissions generated in the use process of various types of energy as the total carbon sequestration service demand, obtaining the per capita carbon emissions based on the population, and combining the 1 km×1 km population density grid data to realize the fine evaluation of carbon sequestration service demand, including the following sub-steps:

[0066] S2.1, total carbon emission of carbon sequestration service. Based on the consumption of 15 types of energy, i.e. raw coal, washed coal, other washed coal, coke, natural gas, liquefied natural gas, crude oil, gasoline, kerosene, diesel, fuel oil, liquefied petroleum gas, other petroleum products, heat and electricity in the main city of a certain city in 2000, 2005, 2010, 2015 and 2020, and their corresponding carbon emission coefficients, the total carbon emission of the region, i.e. the total carbon sequestration service demand, is obtained. Table 3 is the carbon emission coefficient and standard coal conversion coefficient of each energy, which is used to convert the energy consumption into standard coal for subsequent calculation. The calculation formula is as follows:

[0067]

[0068] wherein C e represents the total carbon emission (t), E j represents the physical quantity of the jth type of energy, and CEF​j Cj represents the carbon emission coefficient of the jth energy, P represents the total population, and f represents the carbon emission per capita.

[0069] Table 3 Carbon emission coefficients of various energies and standard coal conversion coefficients

[0070]

[0071]

[0072] S2.2, Fine assessment of carbon sequestration service demand at grid scale. Based on the total carbon emissions and the total population, the carbon emission per capita is obtained, combined with the 1 km x 1 km population density grid data, to realize fine assessment of carbon sequestration service demand at grid scale, as shown in Figure 4 which is the carbon sequestration service demand of the main city of a certain city from 2000 to 2020 at the grid scale. Spatially, the high demand areas of carbon sequestration service are mainly concentrated in the central, northwest and southwest of the study area, while the low demand areas are mainly distributed in the southeast and northeast. In the time dimension, the overall demand shows a fluctuating downward trend from 2000 to 2020. The calculation formula is as follows:

[0073] Ce(x) = p(x) * f(x)

[0074] In the formula, Ce(x) is the carbon emission generated by human social and economic activities, p(x) is the population density of grid x, and f(x) is the carbon emission per capita of grid x.

[0075] S2.3, Assessment of carbon sequestration service demand at township scale. Through the zoning statistics in the spatial analysis tool of ArcGIS, the carbon sequestration service demand of each township is quantified with the township administrative division as the statistical unit. As shown in Figure 5 which is the carbon sequestration service demand of different townships in the main city of a certain city from 2000 to 2020. Spatially, the demand of B4 and B6 townships in B area in Figure 1 is relatively high, while the demand of townships in I area is relatively low, and the number of high demand townships shows an overall increasing trend.

[0076] S3, Analysis of carbon sequestration service supply and demand relationship based on supply-demand ratio. Including the following sub-steps:

[0077] S3.1, Quantification of carbon sequestration service supply and demand relationship based on ecosystem service supply-demand ratio. The carbon sequestration service supply and demand data obtained in S1.2 and S2.2 above are applied to calculate, as shown in Figure 6The carbon sequestration service supply-demand ratio for a city's main urban area is shown in Figure 2. Spatially, carbon sequestration service surplus areas are primarily distributed in parallel mountainous regions, while carbon sequestration service shortage areas are concentrated in the central urban area, reflecting the spatial mismatch between carbon sink functional areas and high-carbon emission cities. Temporally, the carbon sequestration service supply-demand ratio decreased from 0.24 to 0.22 from 2000 to 2020, with shortage areas expanding. The results reveal the essential characteristics of carbon sequestration service surpluses or shortages and reflect the spatial pattern of carbon sequestration service supply and demand. The calculation formula is as follows:

[0078]

[0079] Where ESDR is the carbon sequestration service supply-demand ratio, S is the carbon sequestration service supply, D is the carbon sequestration service demand, S max The maximum supply of carbon sequestration service, D max To serve the maximum demand for carbon sequestration.

[0080] S3.2, the supply and demand status of carbon sequestration services at the township level is assessed by using the zoning statistics in the ArcGIS spatial analysis tool, with the township administrative divisions as statistical units. Based on the supply and demand ratio in S3.1, the average supply and demand ratio of the area included in each township is used as the supply and demand ratio data of each township to quantify the supply and demand status of carbon sequestration services in each township. Figure 7 The supply and demand ratio of carbon sequestration services in different towns in a city from 2000 to 2020 is shown, corresponding to Figure 1 Spatially, high supply-demand ratios were primarily found in D18 Town in District D, E4 Town in District E, and C14 Town in District C, while low ratios were primarily found in townships in Districts G and B. Temporally, the number of townships with positive carbon sequestration service supply-demand ratios decreased from 94.7% in 2000 to 85.8% in 2020. The declines were most pronounced in B6 Town in District B, E11 Town in District E, and A4 Subdistrict in District A. Although the carbon sequestration service supply-demand ratio increased in 24.8% of townships within a city's main urban area, these changes were primarily concentrated in some townships in District I, where the growth in demand for carbon sequestration services far outpaced the growth in supply.

[0081] S4. Based on hotspot analysis, realize carbon sequestration service supply and demand balance analysis. This includes the following steps:

[0082] S4.1. Apply the township-level supply-demand ratio data in S3.2 above and use the Getis-Ord Gi * Statistical methods are used to perform hot spot analysis. The calculation formula is as follows:

[0083]

[0084] In the formula, Gi * is the Getis-Ord Gi of element i* statistical quantity, w i,j is the spatial weight between element i and element j, x j is the attribute value of element j, is the average value of all element attribute values, S is the standard deviation of all element attribute values, and n is the total number of elements.

[0085] S4.2、According to S4.1 Gi * The results of the calculation, -3 and -2 are cold point areas, -1 is a sub-cold point area, 0 is a non-significant area, 1 is a sub-hot point area, 2 and 3 are hot point areas, and the cold point area, sub-cold point area, non-significant area, sub-hot point area and hot point area are divided into five areas defined as deficit serious area, deficit general area, supply and demand balance area, surplus general area and surplus sufficient area, and further realize the analysis of the balance state of regional carbon fixation service supply and demand, and obtain the carbon fixation service supply and demand balance state of some city in 2000-2020 as shown in Figure 8 . Figure 1 , in space, D26 town, C14 town and C13 town in the north constitute the surplus area, while the central urban area is the core area of carbon deficit, and the spatial mismatch characteristics of ecological source and high-carbon built-up area are distinct; in the time dimension, the central carbon fixation deficit area gradually expands from 2000 to 2020, and the supply and demand contradiction continues to increase.

[0086] S5、Based on the field strength model, the spatial flow characteristics of carbon fixation service are simulated, and the flow intensity and direction from the supply area to the demand area are quantified, including the following sub-steps:

[0087] S5.1、Based on the hot spot analysis results, the regional supply surplus area (including surplus general area and surplus sufficient area) is taken as the supply area and the demand deficit area (including deficit serious area and deficit general area) is taken as the demand area.

[0088] S5.2、The spatial flow of carbon fixation shows a trend of attenuation with the increase of geographical distance. Through the breaking point formula, the service flow boundary is simulated, and the flow intensity of carbon fixation per unit area is calculated based on the field strength model, so as to obtain the service flow between supply and demand areas. The calculation formula is as follows:

[0089] E sd = K sd I sd A

[0090]

[0091] In the formula, E sd represents the flow of carbon fixation from the supply area to the demand area; K sd represents the influence factor affecting the spatial flow of carbon fixation between the supply area and the demand area, with a value of 0-1, generally taking a value of 0.6; A represents the radiation area of carbon fixation from the supply area to the demand area; Isd represents the intensity of carbon fixation flow from supply area to demand area; D sd represents the distance between supply area and demand area; D s represents the distance from supply area service point to breaking point; E s and E d represent the carbon fixation amount of supply area and demand area respectively.

[0092] S5.2.1, taking supply area point as source point and demand area point as target point, using the "element point conversion" tool and "generate near neighbor analysis table" tool of ArcGIS, calculate all possible supply-demand pair combinations and D sd According to the following breaking point formula, determine the distance from supply area service point to breaking point, which is used to define the effective radiation range of carbon fixation service.

[0093]

[0094] S5.2.2, for each supply-demand pair, calculate the flow intensity and service flow according to the following formula.

[0095]

[0096] E sd = K sd I sd A

[0097] S5.3, apply the calculation results of S5.2.2 above to determine the maximum carbon fixation service flow direction of each supply area and the maximum carbon fixation service flow source of each demand area.

[0098] S5.4, apply the analysis results of S5.3 above, combined with the arrow symbol to mark the main flow direction, form the carbon fixation service space flow network, get the main city carbon fixation service space flow characteristics of a city from 2000 to 2020 as shown in Figure 9 : spatially, the direction of carbon fixation service space flow is from the surplus area in the north to the deficit area in the central city, forming a core-peripheral radiation structure. The total flow of carbon fixation service increases from 681.62t to 705.40t, among which, Figure 1 C14 town is always the largest carbon fixation service outflow township, B4 town and B6 town in B area are the largest inflow townships. The number of carbon fixation service space flow paths increases from 23 to 37 and then decreases to 24, showing an overall increasing trend.

[0099] Therefore, the present application is based on the InVEST model and the carbon emission coefficient method, taking various types of energy and the carbon generated in the use process thereof as the main source of carbon emission, and realizing fine evaluation of the supply and demand of carbon fixation service by means of land use types, population density and the like; realizing surplus or deficit relationship analysis of the supply and demand of carbon fixation service based on the supply-demand ratio; quantifying the flow intensity of carbon fixation service based on the breaking point and field strength model, and finally realizing feature identification of the spatial flow volume, path quantity and path direction of carbon fixation service, so as to explore the balance relationship and flow characteristics of the carbon fixation service of the key region.

[0100] The above only describes the preferred embodiments of the present application, and it should be noted that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, and these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A method for identifying a carbon sequestration service flow feature based on a supply-demand relationship, characterized in that, The method comprises the following steps: S1, based on the carbon module in the InVEST model, quantifying the carbon sequestration service supply of different land use types by carbon density; S2, based on the carbon emission coefficient method, taking the carbon emissions generated in the use process of various types of energy as the total carbon sequestration service demand, obtaining the carbon emissions per capita based on the population, and combining the 1km*1km population density grid data to realize fine evaluation of the carbon sequestration service demand; S3, based on the supply-demand ratio, realizing the supply-demand relationship analysis of carbon sequestration service; S4, based on the hotspot analysis, realizing the supply-demand balance analysis of carbon sequestration service; S5, based on the field strength model, simulating the spatial flow characteristics of carbon sequestration service, quantifying the flow intensity and direction from the supply area to the demand area. 2.The method of claim 1, wherein, Step S1 specifically comprises the following steps: S1.1, obtaining land use data, and constructing a carbon pool density table of different land use types; wherein the parameters in the carbon pool density table include aboveground biomass carbon storage, underground biomass carbon storage, soil carbon storage and dead organic matter; S1.2, carbon sequestration service supply quantity quantification: based on the carbon module in the InVEST model, quantifying the carbon sequestration service supply of different land use types by carbon density, and obtaining the total carbon storage of the region; S1.3, township scale carbon sequestration service supply quantity evaluation: taking the township administrative area as the statistical unit, quantifying the carbon sequestration service supply quantity of each township by using the zoning statistics in the ArcGIS spatial analysis tool. 3.The method of claim 1, wherein, Step S2 specifically comprises the following steps: S2.1, total carbon emission quantity statistics of carbon sequestration service: based on the carbon emission coefficients of 15 types of energy consumption including raw coal, washed coal, other washed coal, coke, natural gas, liquefied natural gas, crude oil, gasoline, kerosene, diesel, fuel oil, liquefied petroleum gas, other petroleum products, heat and electricity, the total carbon emission quantity of the region is obtained, that is, the total carbon sequestration service demand; S2.2, fine evaluation of grid scale carbon sequestration service demand: based on the total carbon emission quantity and the total population, the carbon emission per capita is obtained, and the 1km*1km population density grid data is combined to fine evaluate the grid scale carbon sequestration service demand; S2.3, township scale carbon sequestration service demand evaluation: taking the township administrative division as the statistical unit, quantifying the carbon sequestration service demand of each township by using the zoning statistics in the ArcGIS spatial analysis tool. 4.The method of claim 1, wherein, Step S3 specifically comprises the following steps: S3.1, calculating the supply-demand ratio: quantifying the supply-demand relationship of carbon sequestration service based on the supply-demand ratio of ecosystem service, obtaining the supply-demand state of carbon sequestration service, and analyzing the supply-demand characteristics of regional carbon sequestration service; S3.2, analyzing the supply-demand state of township level, and evaluating the supply-demand state of township scale carbon sequestration service: taking the township administrative division as the statistical unit, and taking the average supply-demand ratio of the region contained in each township as the supply-demand ratio data of each township based on the supply-demand ratio of S3.1, quantifying the supply-demand state of carbon sequestration service of each township.

5. The method of claim 4, wherein, Step S4 specifically comprises the following steps: S4.1, hotspot analysis: the township scale supply and demand data in step S3.2 is subjected to hotspot analysis using Getis-Ord Gi * statistical method in ArcGIS; S4.2, dividing the supply-demand balance area: according to the hotspot analysis results, define five areas of deficit serious area, deficit general area, supply-demand balance area, surplus general area and surplus sufficient area, and analyze the supply-demand balance state of regional carbon sequestration service.

6. The method of claim 1, wherein, Step S5 specifically comprises the following steps: S5.1, determine the supply area and demand area: based on the hotspot analysis results, take the surplus general area and surplus sufficient area as the supply area, and take the deficit serious area and deficit general area as the demand area; S5.2, simulate the spatial flow characteristics: the spatial flow of carbon sequestration shows a trend of attenuation with the increase of geographical distance, the service flow boundary is simulated by the breaking point formula, the flow intensity of carbon sequestration per unit area is calculated based on the field strength model, and the service flow between the supply area and the demand area is further obtained; S5.3, determine the main flow direction: apply the calculation results of S5.2 above, determine the maximum carbon sequestration service flow direction of each supply area and the maximum carbon sequestration service flow source of each demand area; S5.4, apply the analysis results of S5.3 above, combine the main flow direction marked by the arrow symbol, and form the carbon sequestration service spatial flow network.

7. The method of claim 6, wherein, Step S5.2 specifically comprises the following steps: S5.2.1, taking the supply area particle as the source point and the demand area particle as the target point, using the "element point conversion" tool and "generate neighbor analysis table" tool of ArcGIS, calculate all possible supply-demand pairing combinations and distances, determine the distance from the supply area service particle to the breaking point according to the breaking point formula, and define the effective radiation range of carbon sequestration service; S5.2.2, based on the field strength model, calculate the flow intensity of carbon sequestration per unit area, and obtain the service flow between the supply area and the demand area.

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