A small-scale ecosystem service function value space accounting method and device

Abstract

The application relates to a small-scale ecosystem service function value space accounting method and device, the method comprises the following steps: acquiring a static equivalent factor table of a first region, correcting the static equivalent factor table of the first region according to land utilization, crop yield per unit and economic coefficient data of a second region, and obtaining a static equivalent factor table of the second region; constructing a time-space dynamic adjustment factor of the second region, including an NPP time-space adjustment factor, a precipitation time-space adjustment factor and a soil conservation time-space adjustment factor, wherein the NPP is the net primary productivity of vegetation; acquiring a land utilization type grid map of the second region, calculating a static ecological value space distribution of the second region according to the land utilization type grid map and the static equivalent factor table of the second region; and adjusting the static ecological value space distribution of the second region by using the time-space dynamic adjustment factor, so as to obtain an ecosystem service value space distribution of the second region.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of regional ecological value accounting, and particularly relates to a small-scale ecosystem service function value space accounting method and device. BACKGROUND

[0002] For quantifying the value of ecosystem services, there are many methods for evaluating the value of ecosystem services, and the research results obtained by different methods have great differences. Costanza et al. proposed the equivalent factor method based on the global average situation, and constructed the initial value equivalent factor table. Since there are spatial differences in ecosystem service functions, there will be some problems when it is directly applied in China. Based on this, Xie Gaodi et al. conducted research and constructed the "China's per unit area ecological service value equivalent", and then improved the per unit area value equivalent factor table in 2015, and constructed the ecological system service value equivalent method in China. However, this value evaluation method is for large-scale ranges such as countries, and when applied to small-scale ecosystem service value evaluation, the accounting results are not very accurate due to large spatial differences. SUMMARY

[0003] The purpose of the present application is to provide a small-scale ecosystem service function value space accounting method and device, which aims to correct the equivalent factor table and unit equivalent value of large-scale ecosystems in space and time, obtain the static equivalent factor table and unit equivalent value of small-scale ecosystems, construct the space-time dynamic adjustment factor, establish the space-time dynamic equivalent factor table of small-scale ecosystems and the small-scale ecosystem service function value space accounting method, and then account the ecological value of small-scale ecosystems.

[0004] In a first aspect, a small-scale ecosystem service function value space accounting method is provided, comprising:

[0005] Obtaining a static equivalent factor table of a first region, correcting the static equivalent factor table of the first region according to land use, crop yield per unit and economic coefficient data of a second region to obtain a static equivalent factor table of the second region, wherein the second region is a sub-region of the first region;

[0006] Constructing a space-time dynamic adjustment factor of the second region, the space-time dynamic adjustment factor comprising an NPP space-time adjustment factor, a precipitation space-time adjustment factor and a soil conservation space-time adjustment factor, the NPP being the net primary productivity of vegetation;

[0007] Obtaining a land use type grid map of the second region, and calculating a static ecological value space distribution of the second region according to the land use type grid map of the second region and the static equivalent factor table;

[0008] The spatial distribution of static ecological value in the second region is adjusted using the aforementioned spatiotemporal dynamic adjustment factor to obtain the spatial distribution of ecosystem service value in the second region.

[0009] In one possible implementation, the method for revising the static equivalent factor table of the first region based on land use, crop yield, and economic coefficient data of the second region to obtain the static equivalent factor table of the second region includes:

[0010] Based on land use, a mapping is established between the ecosystem secondary classification items in the static equivalent factor table of the second region and the ecosystem secondary classification items in the static equivalent factor table of the first region, to obtain the first intermediate quantity of the equivalent factor table.

[0011] Obtain crop yield data for the first and second regions, calculate the first revision coefficient, multiply all values ​​in the first intermediate quantity of the equivalent factor table by the first revision coefficient to obtain the second intermediate quantity of the equivalent factor table, wherein the first revision coefficient is the ratio of crop yield data for the second region to crop yield data for the first region;

[0012] Obtain GDP, urbanization rate, and social development stage coefficient data for the first and second regions, calculate the second revision coefficient, and multiply all values ​​of the second intermediate quantity in the equivalent factor table by the second revision coefficient to obtain the static equivalent factor table for the second region. The second revision coefficient is the ratio of the product of GDP, urbanization rate, and social development stage coefficient of the second region to the product of GDP, urbanization rate, and social development stage coefficient of the first region.

[0013] In one possible implementation, the method for constructing the spatiotemporal dynamic adjustment factor for the second region includes:

[0014] Obtain NPP, annual average precipitation per unit area, and soil retention simulation data for the first and second regions;

[0015] Calculate the ratio of NPP in the second region to that in the first region to obtain the spatiotemporal adjustment factor of NPP;

[0016] The ratio of the annual average precipitation per unit area in the second region to that in the first region is calculated to obtain the precipitation spatiotemporal adjustment factor.

[0017] The ratio of the simulated soil retention in the second region to that in the first region is calculated to obtain the spatiotemporal regulation factor of soil retention.

[0018] In one possible implementation, the soil retention simulation is calculated using the USLE soil loss equation.

[0019] In one possible implementation, the method of adjusting the spatial distribution of static ecological value in the second region using the spatiotemporal dynamic adjustment factor to obtain the spatial distribution of ecosystem service value in the second region includes:

[0020] The data on food production, raw material production, climate regulation, gas regulation, environmental purification, nutrient cycling maintenance, biodiversity maintenance, and aesthetic landscape services in the static ecological value spatial distribution of the second region are multiplied by the NPP spatiotemporal adjustment factor.

[0021] Multiply the data on water resource supply and hydrological regulation functions in the spatial distribution of static ecological value in the second region by the precipitation spatiotemporal regulation factor;

[0022] Multiply the soil conservation function data in the spatial distribution of static ecological value in the second region by the soil conservation spatiotemporal adjustment factor;

[0023] Summarizing the above results, the equivalent factor F of the adjusted ecosystem service function per unit area in the second region was obtained. fi , of which F fi The unit area value equivalent factor of the f-th ecosystem service function for the i-th ecosystem type after adjustment;

[0024] For each grid cell in the land use type raster map of Region 2, its ecosystem service value (ESV) is calculated using the following formula. The ESVs of each grid cell are then summed to obtain the spatial distribution of ecosystem service value in Region 2, where A... i Let V be the area of ​​the i-th type of ecosystem, and V0 be the unit equivalent factor value.

[0025]

[0026] In one possible implementation, the unit equivalent factor value V0 is calculated using the following formula, where j represents the number of grain types in the region, with a total of m types, N represents the total area of ​​all grain crops, and n... j Let p be the planting area of ​​the j-th type of grain. j Let q be the average price of the j-th type of grain. j Let be the yield per unit area of ​​the j-th type of grain.

[0027]

[0028] Secondly, a spatial accounting device for the value of small-scale ecosystem service functions is provided, including:

[0029] The first correction unit is used to obtain a static equivalent factor table for the first region, and correct the static equivalent factor table for the first region based on land use, crop yield, and economic coefficient data for the second region to obtain a static equivalent factor table for the second region, wherein the second region is a sub-region of the first region; the second correction unit constructs spatiotemporal dynamic adjustment factors for the second region, which include spatiotemporal adjustment factors for NPP, precipitation, and soil retention, wherein NPP is net primary productivity of vegetation; the static distribution calculation unit is used to obtain a land use type raster map for the second region, and calculate the spatial distribution of static ecological value for the second region based on the land use type raster map and the static equivalent factor table; the spatial accounting unit uses the spatiotemporal dynamic adjustment factors to adjust the spatial distribution of static ecological value for the second region to obtain the spatial distribution of ecosystem service value for the second region.

[0030] This invention proposes a method and apparatus for spatial accounting of the value of small-scale ecosystem services, which has the following advantages: It modifies the equivalent factor table, specifically for small-scale ecosystems. Based on land use, crop yield, and economic coefficients, it modifies the equivalent factor table for large-scale ecosystems, constructing an equivalent factor table for ecosystem services value that is suitable for small-scale ecosystems, thereby improving the accuracy of the calculation results. Using a land use type raster map of the small-scale ecosystem, and based on the land use type raster map and the spatiotemporal dynamic equivalent factor table, the spatial distribution of ecosystem service value of the small-scale ecosystem is obtained using the equivalent factor method. Attached Figure Description

[0031] Figure 1 This is a flowchart of a method for spatial accounting of the value of small-scale ecosystem service functions disclosed in an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of the static equivalent factor table of the Chinese terrestrial ecosystem disclosed in an embodiment of the present invention;

[0033] Figure 3 This is a schematic diagram of the static equivalent factor table for the Ordos region in 2020 disclosed in an embodiment of the present invention;

[0034] Figure 4 This is a schematic diagram of the spatial distribution table of static ecological value in the Ordos region in 2020 as disclosed in an embodiment of the present invention;

[0035] Figure 5 This is a schematic diagram illustrating the spatial distribution of ecosystem service value in the Ordos region in 2020, as disclosed in an embodiment of the present invention.

[0036] Figure 6This is a schematic block diagram of a small-scale ecosystem service function value spatial accounting device disclosed in an embodiment of the present invention. Detailed Implementation

[0037] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0038] Figure 1 This is a flowchart of a method for spatial accounting of the value of small-scale ecosystem service functions disclosed in an embodiment of the present invention.

[0039] In step S101, the static equivalent factor table of the first region is obtained. Based on the land use, crop yield per unit area and economic coefficient data of the second region, the static equivalent factor table of the first region is corrected to obtain the static equivalent factor table of the second region, wherein the second region is a sub-region of the first region.

[0040] Specifically, based on land use, a mapping is established between the ecosystem secondary classification items in the static equivalent factor table of the second region and the ecosystem secondary classification items in the static equivalent factor table of the first region, resulting in the first intermediate quantity of the equivalent factor table. Further, the primary classification of ecosystems includes farmland, forest, grassland, wetland, desert, and water bodies; the secondary classifications of farmland include dryland and paddy fields; the secondary classifications of forest include coniferous, mixed broadleaf and coniferous, broadleaf, and shrubland; the secondary classifications of grassland include steppe, shrubland, and meadow; the secondary classification of wetland includes wetland; the secondary classification of desert includes desert and bare land; and the secondary classifications of water bodies include river systems and glaciers / snow cover.

[0041] Obtain crop yield data for the first and second regions, calculate the first revision coefficient λ1, and multiply all values ​​of the first intermediate quantity in the equivalent factor table by the first revision coefficient λ1 to obtain the second intermediate quantity in the equivalent factor table.

[0042] Specifically, the calculation of the first revision coefficient λ1 is shown in formula (1):

[0043]

[0044] Where H1 represents the crop yield per unit area in the first region, and H2 represents the crop yield per unit area in the second region.

[0045] Obtain GDP, urbanization rate, and social development stage coefficient data for the first and second regions, calculate the second revision coefficient λ2, and multiply all values ​​of the second intermediate quantity in the equivalent factor table by the second revision coefficient λ2 to obtain the static equivalent factor table for the second region.

[0046] Specifically, the calculation of the second revision coefficient λ2 is shown in formula (2):

[0047]

[0048] Wherein, GDP1 is the per capita GDP of the first region, GDP2 is the per capita GDP of the second region, cz1 is the urbanization rate of the first region, cz2 is the urbanization rate of the second region, sb1 is the social development stage coefficient of the first region, and sb2 is the social development stage coefficient of the second region. The calculation of the social development stage coefficient is shown in formula (3):

[0049]

[0050] Where e is the base of the natural logarithm, and E is the Engel coefficient.

[0051] In step S102, a spatiotemporal dynamic adjustment factor for the second region is constructed. The spatiotemporal dynamic adjustment factor includes a spatiotemporal adjustment factor for NPP, a spatiotemporal adjustment factor for precipitation, and a spatiotemporal adjustment factor for soil retention. NPP (Net Primary Productivity) is the net primary productivity of vegetation.

[0052] Furthermore, the NPP spatiotemporal adjustment factor P it The calculation method is shown in formula (4):

[0053]

[0054] Among them, B it Let B be the NPP of the second region's ecosystem in the i-th region in the t-th year, and let B be the annual average NPP of the first region's ecosystem.

[0055] Precipitation Spatiotemporal Modulation Factor R it The calculation method is shown in formula (5):

[0056]

[0057] Among them, W it Let W be the average precipitation per unit area in the i-th region of the second region's ecosystem in year t, and let W be the annual average precipitation per unit area in the first region's ecosystem.

[0058] Soil retention spatiotemporal regulation factor S it The calculation method is shown in formula (6):

[0059]

[0060] Among them, E it Let E be the simulated soil retention of region i in year t of the second region ecosystem, and let E be the simulated average soil retention per unit area of ​​region i.

[0061] The NPP, annual average precipitation per unit area, and soil retention simulation values ​​mentioned above were all obtained from publicly available data.

[0062] Furthermore, the soil retention simulation was calculated using the soil loss equation (USLE).

[0063] In step S103, a land use type raster map of the second region is obtained. Based on the land use type raster map and the static equivalent factor table of the second region, the spatial distribution of the static ecological value of the second region is calculated.

[0064] In step S104, the spatial distribution of static ecological value in the second region is adjusted using the spatiotemporal dynamic adjustment factor to obtain the spatial distribution of ecosystem service value in the second region.

[0065] Specifically, the calculation method of the spatiotemporal dynamic equivalent factor is shown in formula (7):

[0066]

[0067] Among them, F fit Let F be the spatiotemporal dynamic equivalent factor per unit area of ​​the ecosystem of region i in year t, for the type f ecosystem service function of region i. f1 The annual average unit area value equivalent factor of the study area for food production, raw material production, climate regulation, gas regulation, environmental purification, nutrient cycling maintenance, biodiversity maintenance, and aesthetic landscape services for various ecosystems other than aquatic types; F f2 The annual average unit area value equivalent factor of the study area serving the functions of all ecosystems of aquatic types and the water resource supply and hydrological regulation functions of various ecosystems; F f3 F is the annual equivalent value per unit area of ​​soil conservation function for various ecosystems. f1 F f2 F f3 All data are from the static equivalent factor table for the second region. P it R is the spatiotemporal modulating factor of NPP in region i of the second region's ecosystem in year t; it S is the spatiotemporal moderating factor of precipitation in region i in year t of the second region's ecosystem; it The spatiotemporal regulation factor for soil retention in region i of the second region's ecosystem in year t.

[0068] For each grid cell of the land use type raster map of the second region, its ecosystem service value (ESV) in year t is calculated using formula (8). t Then, the Ecosystem Services Value (ESV) of each grid is aggregated. t The spatial distribution of ecosystem service value in the second region in year t is obtained.

[0069]

[0070] Among them, A i Let V0 be the area of ​​the i-th type of region, and V0 be the unit equivalent factor value. Further, the unit equivalent factor value V0 is calculated using formula (9):

[0071]

[0072] Where j represents the types of grains in the region, totaling m types, N represents the total area planted with all grains, and n j Let p be the planting area of ​​the j-th type of grain. j Let q be the average price of the j-th type of grain. j Let N be the yield per unit area of ​​the j-th type of grain. j p j q j All of these were obtained through publicly available information.

[0073] In a specific embodiment, based on the characteristics and changes of the Ordos ecosystem each year, the static equivalent factor table and unit equivalent value of China's terrestrial ecosystem are spatiotemporally corrected to obtain a static equivalent factor table and unit equivalent value that conforms to the Ordos ecosystem. Then, based on the correction of land use, crop yield per unit area and economic coefficients, a spatiotemporally dynamic adjustment factor is constructed. The ecological values ​​of the various service functions after adjustment are summed, and finally the spatial distribution of the Ordos ecosystem service value is calculated.

[0074] First, obtain a table of static equivalent factors for China's terrestrial ecosystems, such as... Figure 2 As shown, a mapping was established between the secondary classification items of the Ordos static equivalent factor table of ecosystems and the secondary classification items of the static equivalent factor table of Chinese terrestrial ecosystems. Specifically, the Ordos ecosystem was divided into 5 primary types and 8 secondary types according to land use type. The primary types include farmland, forest, grassland, desert, and water area. The secondary types include dryland, shrubland, forestland, high-coverage grassland, medium-coverage grassland, low-coverage grassland, sandy land, and water system. Then, the dryland, shrubland, water system, and sandy land in the Ordos static equivalent factor table were mapped one-to-one with the dryland, water system, shrubland, and desert in the static equivalent factor table of Chinese terrestrial ecosystems, respectively. The equivalent factor of forestland was determined according to its area ratio with shrubland. The equivalent factors of high-coverage grassland, medium-coverage grassland, and low-coverage grassland were determined by weighting the areas of high, medium, and low-coverage grasslands, respectively, to obtain the first intermediate quantity of the Ordos equivalent factor table.

[0075] Data on average grain yield per unit area in China and Ordos were obtained, and the first revision coefficient λ1 was calculated according to formula (1). Data on average GDP, average urbanization rate, and average Engel coefficient in China, as well as GDP, urbanization rate, and Engel coefficient in Ordos, were obtained, and the second revision coefficient λ2 was calculated according to formulas (2) and (3). All data in the first intermediate quantity of the Ordos equivalent factor table were multiplied by λ1 to obtain the second intermediate quantity of the equivalent factor table; then all data in the second intermediate quantity of the equivalent factor table were multiplied by λ2 to obtain the static equivalent factor table of Ordos. For example, a schematic diagram of the static equivalent factor table of Ordos region in 2020 is shown below. Figure 3 As shown.

[0076] Secondly, the spatiotemporal dynamic adjustment factors of Ordos were constructed. Data on NPP, precipitation per unit area, and soil conservation simulation in Ordos, as well as data on the average NPP, precipitation per unit area, and soil conservation simulation in China, were obtained. The spatiotemporal adjustment factors of NPP, precipitation, and soil conservation were calculated using formulas (4) to (6).

[0077] Then, based on the land use type raster map of Ordos, the area of ​​each ecosystem was calculated. Based on the land use type raster map and the static equivalent factor table of Ordos, the spatial distribution of the static ecological value of Ordos was calculated. For example, a schematic diagram of the spatial distribution of the static ecological value of the Ordos region in 2020 is shown below. Figure 5 As shown.

[0078] Finally, the static ecological value spatial distribution table of Ordos was adjusted using formula (7). The grain planting area, average grain price, and grain yield per unit area of ​​Ordos were obtained, and the unit equivalent factor value of Ordos was calculated using formula (9). Then, for each grid cell of the Ordos land use type raster map, its annual ecosystem service value (ESV) was calculated using formula (8). The ecosystem service value (ESV) of each grid cell was then summarized to obtain the spatial distribution of Ordos's ecosystem service value over the years. For example, a schematic diagram of the spatial distribution of Ordos's ecosystem service value in 2020 is shown below. Figure 5 As shown.

[0079] Figure 6 This is a schematic block diagram of a small-scale ecosystem service function value spatial accounting device disclosed in an embodiment of the present invention. The device 600 includes:

[0080] The first correction unit 601 is used to obtain a static equivalent factor table for the first region, and correct the static equivalent factor table for the first region based on land use, crop yield, and economic coefficient data for the second region to obtain a static equivalent factor table for the second region, wherein the second region is a sub-region of the first region; the second correction unit 602 constructs a spatiotemporal dynamic adjustment factor for the second region, which includes a spatiotemporal adjustment factor for NPP, a spatiotemporal adjustment factor for precipitation, and a spatiotemporal adjustment factor for soil retention, wherein NPP is the net primary productivity of vegetation; the static distribution calculation unit 603 is used to obtain a land use type raster map for the second region, and calculate the spatial distribution of static ecological value for the second region based on the land use type raster map and the static equivalent factor table; the spatial accounting unit 604 uses the spatiotemporal dynamic adjustment factors to adjust the spatial distribution of static ecological value for the second region to obtain the spatial distribution of ecosystem service value for the second region.

[0081] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A spatial accounting method for the value of small-scale ecosystem service functions, characterized in that, The method includes: A static equivalent factor table for a first region is obtained. Based on land use, crop yield, and economic coefficient data for a second region, the static equivalent factor table for the first region is revised to obtain a static equivalent factor table for the second region, where the second region is a sub-region of the first region. The revision of the static equivalent factor table for the first region based on land use, crop yield, and economic coefficient data for the second region includes: establishing a mapping between the ecosystem secondary classification items in the static equivalent factor table for the second region and the ecosystem secondary classification items in the static equivalent factor table for the first region based on land use conditions, obtaining a first intermediate value for the equivalent factor table; obtaining data from the first and second regions... The crop yield data for the region is used to calculate the first revision coefficient. All values ​​in the first intermediate quantity of the equivalent factor table are multiplied by the first revision coefficient to obtain the second intermediate quantity of the equivalent factor table. The first revision coefficient is the ratio of the crop yield data for the second region to that for the first region. The GDP, urbanization rate, and social development stage coefficient data for the first and second regions are obtained. The second revision coefficient is calculated. All values ​​in the second intermediate quantity of the equivalent factor table are multiplied by the second revision coefficient to obtain the static equivalent factor table for the second region. The second revision coefficient is the ratio of the product of the GDP, urbanization rate, and social development stage coefficient of the second region to the product of the GDP, urbanization rate, and social development stage coefficient of the first region. A spatiotemporal dynamic adjustment factor for the second region is constructed. This factor includes a spatiotemporal adjustment factor for NPP (Net Primary Productivity), a spatiotemporal adjustment factor for precipitation, and a spatiotemporal adjustment factor for soil retention. NPP is the net primary productivity of vegetation. The construction of the spatiotemporal dynamic adjustment factor for the second region includes: acquiring NPP, annual average precipitation per unit area, and simulated soil retention data for both the first and second regions; calculating the ratio of NPP in the second region to that in the first region to obtain the spatiotemporal adjustment factor for NPP; calculating the ratio of annual average precipitation per unit area in the second region to that in the first region to obtain the spatiotemporal adjustment factor for precipitation; and calculating the ratio of simulated soil retention in the second region to that in the first region to obtain the spatiotemporal adjustment factor for soil retention. Obtain a land use type raster map of the second region, and calculate the spatial distribution of static ecological value of the second region based on the land use type raster map and static equivalent factor table. The spatial distribution of static ecological value in the second region is adjusted using the aforementioned spatiotemporal dynamic adjustment factor to obtain the spatial distribution of ecosystem service value in the second region.

2. The method according to claim 1, characterized in that, The soil retention simulation was calculated using the USLE soil loss equation.

3. The method according to claim 1, characterized in that, The method for adjusting the spatial distribution of static ecological value in the second region using the spatiotemporal dynamic adjustment factor to obtain the spatial distribution of ecosystem service value in the second region includes: The data on food production, raw material production, climate regulation, gas regulation, environmental purification, nutrient cycling maintenance, biodiversity maintenance, and aesthetic landscape services in the static ecological value spatial distribution of the second region are multiplied by the NPP spatiotemporal adjustment factor. Multiply the data on water resource supply and hydrological regulation functions in the spatial distribution of static ecological value in the second region by the precipitation spatiotemporal regulation factor; Multiply the soil conservation function data in the spatial distribution of static ecological value in the second region by the soil conservation spatiotemporal adjustment factor; Summarizing the above results, the equivalent factor F of the adjusted ecosystem service function per unit area in the second region was obtained. fi , of which F fi The unit area value equivalent factor of the f-th ecosystem service function for the i-th ecosystem type after adjustment; For each grid cell in the land use type raster map of Region 2, its ecosystem service value (ESV) is calculated using the following formula. The ESVs of each grid cell are then summed to obtain the spatial distribution of ecosystem service value in Region 2, where A... i Let V be the area of ​​the i-th type of ecosystem, and V0 be the unit equivalent factor value.

4. The method according to claim 3, characterized in that, The unit equivalent factor value V0 is calculated using the following formula, where j represents the types of grains in the region, with a total of m types, N represents the total area of ​​all grain crops, and n... j Let p be the planting area of ​​the j-th type of grain. j Let q be the average price of the j-th type of grain. j Let be the yield per unit area of ​​the j-th type of grain.

5. A spatial accounting device for the value of small-scale ecosystem service functions, comprising: The first correction unit is used to obtain a static equivalent factor table for a first region, and correct the static equivalent factor table for the first region based on land use, crop yield, and economic coefficient data for a second region to obtain a static equivalent factor table for the second region, wherein the second region is a sub-region of the first region; wherein, the step of correcting the static equivalent factor table for the first region based on land use, crop yield, and economic coefficient data for the second region to obtain a static equivalent factor table for the second region includes: establishing a mapping between the ecosystem secondary classification items of the static equivalent factor table for the second region and the ecosystem secondary classification items of the static equivalent factor table for the first region based on land use conditions, obtaining a first intermediate quantity of the equivalent factor table; obtaining the static equivalent factor table for the first region; and correcting the static equivalent factor table for the second region based on land use, crop yield, and economic coefficient data for the second region. The crop yield data for the first and second regions are used to calculate a first revision coefficient. All values ​​in the first intermediate quantity of the equivalent factor table are multiplied by the first revision coefficient to obtain the second intermediate quantity of the equivalent factor table. The first revision coefficient is the ratio of the crop yield data for the second region to that for the first region. The GDP, urbanization rate, and social development stage coefficient data for the first and second regions are obtained, and a second revision coefficient is calculated. All values ​​in the second intermediate quantity of the equivalent factor table are multiplied by the second revision coefficient to obtain the static equivalent factor table for the second region. The second revision coefficient is the ratio of the product of the GDP, urbanization rate, and social development stage coefficient of the second region to the product of the GDP, urbanization rate, and social development stage coefficient of the first region. The second correction unit constructs spatiotemporal dynamic adjustment factors for the second region. These factors include spatiotemporal adjustment factors for NPP (Net Primary Productivity), precipitation, and soil retention. NPP is the net primary productivity of vegetation. The construction of these factors for the second region includes: acquiring NPP, annual average precipitation per unit area, and soil retention simulation data for both the first and second regions; calculating the ratio of NPP in the second region to that in the first region to obtain the NPP spatiotemporal adjustment factor; calculating the ratio of annual average precipitation per unit area in the second region to that in the first region to obtain the precipitation spatiotemporal adjustment factor; and calculating the ratio of soil retention simulation data in the second region to that in the first region to obtain the soil retention spatiotemporal adjustment factor. The static distribution calculation unit is used to obtain the land use type raster map of the second region, and calculate the spatial distribution of the static ecological value of the second region based on the land use type raster map and the static equivalent factor table. The spatial accounting unit uses the aforementioned spatiotemporal dynamic adjustment factor to adjust the spatial distribution of static ecological value in the second region, thereby obtaining the spatial distribution of ecosystem service value in the second region.

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