Altitude zonation optimized regional carbon sink gridding estimation method

Abstract

The present application relates to the technical field of ecological environment remote sensing monitoring data processing and regional ecological system carbon sink estimation, and particularly relates to a regional carbon sink gridding estimation method based on elevation zoning optimization. The method obtains remote sensing vegetation index grid, periodical meteorological grid, digital elevation model and land use secondary classification grid of a region to be evaluated, generates carbon sink estimation basic grid data through spatial alignment and periodical binding; generates an elevation zoning grid based on the digital elevation model, and associates the elevation zoning identification with a photosynthesis temperature control parameter group composed of the minimum temperature, the optimum temperature and the maximum temperature, and calculates the total primary productivity grid by grid; then, according to the land use secondary classification code, the autotrophic respiration parameter and the heterotrophic respiration parameter are called to calculate the ecological system respiration, and the periodical net ecological system productivity grid is generated by difference, and the abnormal filtering, cumulative checking and partitioning summarization are performed. The present application effectively improves the spatial consistency and type parameter continuity of the carbon sink gridding estimation in the region with elevation difference.

Description

Technical Field

[0001] This invention relates to the fields of ecological environment remote sensing monitoring data processing, geospatial raster data calculation, and regional ecosystem carbon sink estimation, and particularly to a regional carbon sink raster estimation method optimized by altitude zoning. Background Technology

[0002] In the fields of remote sensing monitoring data processing for ecological environment and estimation of regional ecosystem carbon sinks, existing schemes for regional terrestrial ecosystem carbon sinks typically acquire remote sensing vegetation indices, meteorological data, land use data, and basic geographic data. These multi-source data are then processed through projection, resampling, cropping, spatial overlay, and raster cell statistics to organize the input data into a unified spatial unit. Such schemes often employ light energy utilization rate models, net primary productivity estimation models, carbon density models, or carbon storage models, combined with factors such as temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and land use type, to generate regional carbon sink, carbon storage, carbon accumulation rate, or zonal statistical results.

[0003] Existing solutions often use temperature data as a general meteorological input factor or employ a uniform photosynthetic temperature response parameter across the entire region in the calculation of total primary productivity. In regions with significant elevation differences and distinct vertical zonation, the temperature background, vegetation habitat, and photosynthetic temperature adaptation ranges corresponding to different elevation raster cells vary. The lack of a stable matching relationship between fixed temperature control parameters and the elevation zone where the raster is located can easily lead to inconsistencies in parameter alignment between different elevation zones in the total primary productivity raster.

[0004] Furthermore, existing land use classification data is mostly used for ecosystem type statistics, carbon density assignment, or zonal summarization, and rarely used as a direct basis for calling ecosystem respiration parameters by land use secondary category codes. In areas where forest ecosystems, grassland ecosystems, aquatic and wetland ecosystems, or wetland peatlands coexist, if there is a lack of stable connection between autotrophic and heterotrophic respiration parameters and land use secondary category codes, difficulties in processing such as inconsistencies in calculation objects, discontinuous zonal summarization calibers, and inconsistent periodic cumulative records can easily arise between the ecosystem respiration grid and the total primary productivity grid. Therefore, it is necessary to address the issue of how to call photosynthetic temperature control parameter groups through elevation zone identification and respiration parameter groups through land use secondary category codes to form a net ecosystem productivity grid, focusing on the regional carbon sink rasterization estimation in areas with significant elevation differences. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for estimating regional carbon sinks using a rasterized approach optimized for altitude zoning, comprising:

[0006] S100: Obtain remote sensing vegetation index raster, periodic meteorological raster, digital elevation model and land use secondary classification raster of the area to be evaluated, perform spatial alignment and periodic binding, and generate basic raster data for carbon sink estimation.

[0007] S200. Based on the digital elevation model in the carbon sink estimation basic grid data, generate an elevation zone grid, write an elevation zone identifier for each grid cell, and establish a correspondence between the elevation zone identifier and the photosynthetic temperature control parameter group to generate zone temperature control parameter data. The photosynthetic temperature control parameter group includes the minimum temperature, the optimal temperature, and the maximum temperature.

[0008] S300. Based on the carbon sink estimation base grid data and the zonal temperature control parameter data, read the vegetation index value and the same period meteorological driving value grid by grid, and call the photosynthetic temperature control parameter group according to the altitude zone identifier to calculate the total primary productivity and generate the periodic total primary productivity grid.

[0009] S400. Based on the land use secondary classification raster in the carbon sink estimation basic raster data, read the land use secondary classification code, and call the autotrophic respiration parameters and heterotrophic respiration parameters of the corresponding ecosystem type according to the land use secondary classification code, calculate the ecosystem respiration, and generate a phase-by-phase ecosystem respiration raster.

[0010] S500. Based on the total primary productivity raster and the ecosystem respiration raster for each period, perform raster-by-raster subtraction to generate a net ecosystem productivity raster for each period. Then, perform outlier filtering, cumulative consistency check and partition summary on the net ecosystem productivity raster for each period to generate a carbon sink raster output set and partition statistics results for each period.

[0011] Further, in S100, the spatial alignment includes: projecting, resampling, and cropping the remote sensing vegetation index raster, the periodic meteorological raster, the digital elevation model, and the land use secondary classification raster to generate a unified raster index with the same raster row and column numbers; the periodic binding includes: writing the remote sensing vegetation index raster and the periodic meteorological raster into the same preset evaluation period identifier.

[0012] Further, in S200, generating the elevation zone grid includes: reading the elevation value of each grid cell in the digital elevation model, dividing each grid cell into a corresponding elevation zone according to a preset elevation threshold, and writing the elevation zone identifier into the elevation zone grid.

[0013] Furthermore, in S200, establishing a correspondence between the altitude zone identifier and the photosynthetic temperature control parameter group includes: reading the minimum temperature, optimal temperature, and maximum temperature corresponding to each altitude zone; performing an incremental relationship check on the minimum temperature, optimal temperature, and maximum temperature; and writing the minimum temperature, optimal temperature, and maximum temperature that have passed the incremental relationship check into the zone-specific temperature control parameter data.

[0014] Further, in S300, generating the phase-by-phase total primary productivity grid includes: determining the proportion of photosynthetically active radiation absorbed based on the vegetation index value; determining the amount of photosynthetically active radiation absorbed based on the radiation data in the meteorological driving value of the same period and the proportion of photosynthetically active radiation absorbed; and calculating the total primary productivity value of each grid cell based on the amount of photosynthetically active radiation absorbed and the photosynthetic temperature control parameter set.

[0015] Furthermore, in S400, after reading the land use secondary category code, the land use secondary category code is mapped to an ecosystem type identifier of forest ecosystem, grassland ecosystem, water and wetland ecosystem or wetland peatland, and the autotrophic respiration parameter and the heterotrophic respiration parameter are called based on the ecosystem type identifier.

[0016] Furthermore, in S400, the autotrophic respiration parameters include the autotrophic basal respiration coefficient and the autotrophic temperature sensitivity coefficient; the heterotrophic respiration parameters include the heterotrophic basal respiration coefficient and the heterotrophic temperature sensitivity coefficient; and the ecosystem respiration is calculated from the autotrophic respiration parameters, the heterotrophic respiration parameters, and the temperature data in the concurrent meteorological driving values.

[0017] Further, in S500, generating the phase-by-phase net ecosystem productivity grid includes: reading the total primary productivity value in the phase-by-phase total primary productivity grid and the ecosystem respiration in the phase-by-phase ecosystem respiration grid under the same grid row and column number, and subtracting the total primary productivity value from the ecosystem respiration to obtain the net ecosystem productivity value of the corresponding grid unit.

[0018] Furthermore, in S500, the outlier filtering includes: writing an outlier raster identifier to invalid raster, raster that exceeds the preset range of ecosystem type, and inter-period mutation raster in the phase-by-phase net ecosystem productivity raster, and removing the raster with the outlier raster identifier written in the partition summary.

[0019] Furthermore, in S500, the zoning summary includes: reading the zoning identifier of each grid cell based on the administrative region boundary data, and summarizing the effective net ecosystem productivity value according to the area of ​​the grid cell to generate the zoning statistical results; the cumulative consistency check includes: comparing the cumulative value of the period-by-period carbon sink grid output set with the cumulative value of the zoning statistical results to generate a cumulative consistency check result.

[0020] The key innovations of this invention include:

[0021] (1) Convert the digital elevation model in the basic grid data for carbon sink estimation into an elevation zonal grid, write an elevation zone identifier for each grid cell, and establish a correspondence between the elevation zone identifier and the photosynthetic temperature control parameter group composed of the lowest temperature, the optimal temperature and the highest temperature to form zonal temperature control parameter data for grid-by-grid calculation of total primary productivity.

[0022] (2) Map the land use secondary classification code in the land use secondary classification grid to the corresponding ecosystem type, and call the autotrophic respiration parameter and heterotrophic respiration parameter based on the ecosystem type to form a phased ecosystem respiration grid corresponding to the ecosystem type of each grid unit.

[0023] (3) Under the same grid row and column number and the same preset evaluation period, the total primary productivity grid and the ecosystem respiration grid of each period are subtracted grid by grid to generate the net ecosystem productivity grid of each period. The net ecosystem productivity grid of each period is then subjected to outlier filtering, cumulative consistency check and partition summary to form the carbon sink grid output set and partition statistics results of each period.

[0024] The following are its main beneficial effects:

[0025] (1) To address the problem of difficulty in matching the unified photosynthetic temperature response parameters across the entire domain with grid cells of different altitude zones in the existing scheme, the correspondence between the altitude zone identifier and the photosynthetic temperature control parameter group is used to enable the minimum temperature, optimal temperature and maximum temperature in the total primary productivity calculation to enter the grid-by-grid calculation process according to the altitude zone, forming a zonal parameter call link corresponding to the grid elevation conditions.

[0026] (2) In view of the problem that existing land use classification data are mostly used for classification statistics or carbon density assignment and are not sufficiently linked with ecosystem respiration parameters, the autotrophic respiration parameters and heterotrophic respiration parameters of the corresponding ecosystem type are called by the land use secondary category coding, so that the ecosystem respiration is calculated in grid-by-grid according to the types such as forest ecosystem, grassland ecosystem, water and wetland ecosystem or wetland peatland.

[0027] (3) To address the issues of inconsistency in calculation objects and discontinuous periodic cumulative records among the total primary productivity grid, ecosystem respiration grid, and zonal statistical results, a continuous data connection relationship is formed between the periodic net ecosystem productivity grid, the periodic carbon sink grid output set, and the zonal statistical results by performing grid-by-grid subtraction under the same grid row and column number, outlier filtering, cumulative consistency check, and zonal summary. Attached Figure Description

[0028] Figure 1 A flowchart illustrating a method for elevation-zone-optimized regional carbon sink gridding estimation provided in this application embodiment;

[0029] Figure 2 This is a structural block diagram of a regional carbon sink rasterization estimation method optimized by altitude zoning provided in this application embodiment. Detailed Implementation

[0030] Example 1: Refer to Figure 1 This is a flowchart illustrating a method for estimating regional carbon sinks using elevation zoning optimization, provided in an embodiment of the present invention. The flowchart may include at least steps S100-S500:

[0031] S100: Obtain remote sensing vegetation index raster, periodic meteorological raster, digital elevation model and land use secondary classification raster of the area to be evaluated, perform spatial alignment and periodic binding, and generate basic raster data for carbon sink estimation.

[0032] S200. Based on the digital elevation model in the carbon sink estimation basic grid data, generate an elevation zone grid, write an elevation zone identifier for each grid cell, and establish a correspondence between the elevation zone identifier and the photosynthetic temperature control parameter group to generate zone temperature control parameter data. The photosynthetic temperature control parameter group includes the minimum temperature, the optimal temperature, and the maximum temperature.

[0033] S300. Based on the carbon sink estimation base grid data and the zonal temperature control parameter data, read the vegetation index value and the same period meteorological driving value grid by grid, and call the photosynthetic temperature control parameter group according to the altitude zone identifier to calculate the total primary productivity and generate the periodic total primary productivity grid.

[0034] S400. Based on the land use secondary classification raster in the carbon sink estimation basic raster data, read the land use secondary classification code, and call the autotrophic respiration parameters and heterotrophic respiration parameters of the corresponding ecosystem type according to the land use secondary classification code, calculate the ecosystem respiration, and generate a phase-by-phase ecosystem respiration raster.

[0035] S500. Based on the total primary productivity raster and the ecosystem respiration raster for each period, perform raster-by-raster subtraction to generate a net ecosystem productivity raster for each period. Then, perform outlier filtering, cumulative consistency check and partition summary on the net ecosystem productivity raster for each period to generate a carbon sink raster output set and partition statistics results for each period.

[0036] S100: Obtain remote sensing vegetation index raster, periodic meteorological raster, digital elevation model and land use secondary classification raster of the area to be evaluated, perform spatial alignment and periodic binding, and generate basic raster data for carbon sink estimation.

[0037] In this embodiment, S100 is executed by the raster data access module and the spatial alignment module in the regional carbon sink rasterization estimation system. The raster data access module receives remote sensing vegetation index raster, period-by-period meteorological raster, digital elevation model, and land use secondary classification raster of the area to be evaluated; the spatial alignment module projects, resamples, clips, and organizes the raster row and column numbers of the above raster data, and writes the remote sensing vegetation index raster and period-by-period meteorological raster within the same preset evaluation period into the same preset evaluation period identifier, forming the basic raster data for carbon sink estimation called for subsequent raster-by-raster calculations.

[0038] The remote sensing vegetation index raster is data expressing vegetation index values ​​in the form of raster cells. The vegetation index value is the vegetation status field of each raster cell within the corresponding preset assessment period. The period-by-period meteorological raster is a meteorological variable raster corresponding to the preset assessment period. In one embodiment, the period-by-period meteorological raster includes temperature data and radiation data. The temperature data participates in the temperature response processing and ecosystem respiration calculation in the total primary productivity calculation, and the radiation data participates in the calculation of absorbed photosynthetically active radiation. The digital elevation model is raster data expressing the elevation values ​​of each raster cell. Subsequently, in S200, an elevation zonation raster is generated based on the elevation values. The land use secondary classification raster is data expressing the land use secondary classification code of each raster cell. Subsequently, in S400, autotrophic respiration parameters and heterotrophic respiration parameters are called based on the land use secondary classification code.

[0039] The triggering condition for S100 is the completion of the data entry of remote sensing vegetation index rasters and periodic meteorological rasters within the target preset assessment period, or the version update of digital elevation model and land use secondary classification rasters. The raster data access module reads the spatial reference, resolution, extent boundary, number of raster rows and columns, invalid value code, and data batch identifier of each input raster. When the spatial references of the input rasters are inconsistent, the spatial alignment module projects the input rasters based on the preset spatial reference. When the spatial resolutions of the input rasters are inconsistent, the spatial alignment module resamples based on the preset spatial resolution. When the spatial extent of each input raster exceeds the boundary of the area to be assessed, the spatial alignment module clips it according to the boundary of the area to be assessed. The raster data after projection, resampling, and clipping have the same raster row and column numbers, and each raster unit is associated through a unified raster index.

[0040] During spatial alignment, the unified raster index includes raster row number, raster column number, spatial coordinates, raster cell area, and identifier of the area to be evaluated. The spatial alignment module writes remote sensing vegetation index values, temperature data, radiation data, elevation values, and land use secondary category codes under the same unified raster index, generating a raster-by-raster basic record. The basic record does not change the physical meaning of the original data of each input raster, but organizes data from different sources, with different spatial references, or different evaluation periods into the same raster cell and the same preset evaluation period. Subsequently, S200 generates an elevation zonation raster based on the elevation values ​​in the basic record, S300 calculates total primary productivity based on the vegetation index values ​​and contemporaneous meteorological driving values ​​in the basic record, and S400 calculates ecosystem respiration based on the land use secondary category codes in the basic record.

[0041] The period binding is performed by the spatial alignment module after spatial alignment is completed. Specifically, the spatial alignment module reads the data dates of the remote sensing vegetation index raster, the data dates of the periodic meteorological raster, and the preset evaluation period rules, and writes the vegetation index values, temperature data, and radiation data within the same preset evaluation period into the same preset evaluation period identifier. In the case where multiple periodic meteorological rasters exist within the same preset evaluation period, the spatial alignment module aggregates the meteorological variables within the period according to the preset evaluation period rules, generating meteorological driving values ​​for the same period as the remote sensing vegetation index raster. In one embodiment, the preset evaluation period is a monthly period, and the spatial alignment module assigns the corresponding temperature data and radiation data for that month to the same period identifier; in another embodiment, the preset evaluation period is an 8-day period, and the spatial alignment module writes the meteorological variables within the corresponding 8-day window into the same period identifier.

[0042] Regarding anomaly handling, the raster data access module retains the input raster batch, data source identifier, and invalid value code when reading input rasters. If a remote sensing vegetation index raster is missing a vegetation index value in a certain raster cell, the spatial alignment module writes an input missing identifier into that raster cell. If a periodic meteorological raster is missing temperature or radiation data in a certain raster cell, the spatial alignment module retains the unified raster index of that raster cell and writes a meteorological missing identifier into it. If a digital elevation model is missing an elevation value, the raster cell will not have an elevation zone identifier written into it in subsequent step S200. If a land use secondary classification raster is missing a land use secondary classification code, the raster cell will not have its respiration parameter group called into it in subsequent step S400. The above identifiers are output along with the carbon sink estimation base raster data and are read by subsequent steps.

[0043] In one engineering implementation, a regional carbon sink rasterization estimation system is deployed on an ecological environment monitoring data processing server. The server receives a 250m × 250m remote sensing vegetation index raster, periodic meteorological raster, digital elevation model, and land use secondary classification raster of the area to be evaluated. The raster data access module reads the spatial reference and raster range of the above raster files, and the spatial alignment module resamples the periodic meteorological raster, digital elevation model, and land use secondary classification raster to the same raster row and column numbers as the remote sensing vegetation index raster. Subsequently, according to a preset evaluation cycle, the vegetation index value, temperature data, radiation data, elevation value, and land use secondary classification code are written into a unified raster index to form the basic raster data for carbon sink estimation. This basic raster data for carbon sink estimation includes the raster row and column number, preset evaluation cycle identifier, vegetation index value, temperature data, radiation data, elevation value, land use secondary classification code, and input missing identifier for each valid raster unit in the area to be evaluated.

[0044] The carbon sink estimation baseline raster data generated in S100 is written into the baseline raster data storage area of ​​the regional carbon sink rasterization estimation system. Subsequently, S200 reads the elevation values ​​and unified raster index corresponding to the digital elevation model from the baseline raster data storage area, and generates an elevation zonation raster based on these elevation values; S300 reads the vegetation index values ​​and contemporaneous meteorological driving values ​​from the baseline raster data storage area; and S400 reads the land use secondary category code from the baseline raster data storage area. Thus, the carbon sink estimation baseline raster data output by S100 becomes the data basis for S200, S300, and S400, ensuring that each main step is executed under the same raster row and column numbers and the same preset evaluation period.

[0045] S200. Based on the digital elevation model in the carbon sink estimation basic grid data, generate an elevation zone grid, write an elevation zone identifier for each grid cell, and establish a correspondence between the elevation zone identifier and the photosynthetic temperature control parameter group to generate zone temperature control parameter data. The photosynthetic temperature control parameter group includes the minimum temperature, the optimal temperature, and the maximum temperature.

[0046] In this embodiment, step S200 is executed by the elevation zoning parameter module in the regional carbon sink raster estimation system. The elevation zoning parameter module receives the carbon sink estimation basic raster data generated in step S100 and reads the elevation values ​​and unified raster indexes corresponding to the digital elevation model. Based on the elevation values ​​of each raster unit, the elevation zoning parameter module divides the raster units into corresponding elevation zones according to a preset elevation threshold, generating an elevation zoning raster. Subsequently, it writes an elevation zone identifier to each raster unit and establishes a correspondence between the elevation zone identifier and the photosynthetic temperature control parameter group, generating zoning temperature control parameter data.

[0047] The elevation zonation raster represents the elevation zonation data of each raster cell under a unified raster index. The elevation zonation identifier is the zonation field recorded in the elevation zonation raster, which is generated by matching the elevation value with a preset elevation threshold. The photosynthetic temperature control parameter set is a set of parameters describing the photosynthetic temperature control curve, which in this embodiment includes the minimum temperature, the optimum temperature, and the maximum temperature. The minimum temperature is the low-temperature boundary parameter participating in the photosynthetic temperature response calculation, the optimum temperature is the peak temperature parameter participating in the photosynthetic temperature response calculation, and the maximum temperature is the high-temperature boundary parameter participating in the photosynthetic temperature response calculation. The zonation temperature control parameter data establishes a correspondence between the elevation zonation identifier and the above three temperature parameters, and is subsequently called by S300.

[0048] The trigger condition for S200 is that S100 generates basic raster data for carbon sink estimation and completes the basic raster data storage. When the elevation zoning parameter module receives the output batch identifier of the basic raster data for carbon sink estimation, it reads the elevation value of each raster cell. For raster cells with valid elevation values, the elevation zoning parameter module performs interval matching between the elevation value and the preset elevation threshold to generate an elevation zone identifier. For raster cells with missing elevation values, the elevation zoning parameter module retains a unified raster index and writes an elevation missing identifier, and does not include the raster cell in the valid parameter call range of the zoning temperature control parameter data.

[0049] In one implementation, the preset altitude threshold is provided by an altitude zonation parameter table. This table includes altitude zone identifiers, lower altitude limits, upper altitude limits, minimum temperature, optimum temperature, and maximum temperature. After reading the elevation values ​​of the grid cells, the altitude zonation parameter module writes the altitude zone identifiers corresponding to the lower and upper altitude limit intervals into the altitude zonation grid. Subsequently, it reads the minimum, optimum, and maximum temperatures corresponding to these altitude zone identifiers and writes them into the zonation temperature control parameter data. In another implementation, the preset altitude threshold is generated by the elevation distribution of the area to be evaluated. The altitude zonation parameter module forms multiple altitude zones based on the quantile intervals of the elevation values ​​and configures a photosynthetic temperature control parameter set for each altitude zone.

[0050] Before writing the photosynthetic temperature control parameter group, the altitude zonation parameter module performs an incremental relationship check. Specifically, the altitude zonation parameter module reads the minimum temperature, optimum temperature, and maximum temperature corresponding to the same altitude zone and checks the order of their values. When the minimum temperature is lower than the optimum temperature and the optimum temperature is lower than the maximum temperature, the photosynthetic temperature control parameter group corresponding to that altitude zone is written into the zonation temperature control parameter data. When the three do not satisfy the incremental relationship, the altitude zonation parameter module writes a parameter anomaly flag for that altitude zone and retains the original parameter record corresponding to that altitude zone. For altitude zones with parameter anomaly flags, S300 reads the anomaly flag when calling the photosynthetic temperature control parameter group and writes the corresponding raster cell into the total primary productivity calculation anomaly record.

[0051] In one engineering implementation, the area to be evaluated includes basins, mountains, and plateaus. The regional carbon sink grid estimation system divides the grid cells into multiple elevation zones based on the elevation values ​​of each grid cell in the digital elevation model. For the same grid row and column number, the elevation zone parameter module reads the elevation value field formed in S100, matches it with a preset elevation threshold, and writes it into an elevation zone identifier. Subsequently, based on the elevation zone identifier, it reads the corresponding minimum, optimum, and maximum temperatures, and encapsulates them together with the grid row and column number and the preset evaluation period identifier into zone temperature control parameter data. Thus, in the subsequent S300 calculation of total primary productivity grid by grid, it not only reads the vegetation index value and the concurrent meteorological driving value of the grid cell, but also reads the photosynthetic temperature control parameter set corresponding to the elevation zone to which the grid cell belongs.

[0052] Regarding boundary constraints, if a grid cell is located at an elevation zone boundary, the elevation zone parameter module writes the elevation zone identifier according to the interval to which the grid cell's elevation value belongs. In one embodiment, the elevation zone parameter module writes a boundary identifier for grid cells near the elevation zone boundary, and after S300 reads the boundary identifier, it still performs calculations according to the photosynthetic temperature control parameter group of the elevation zone to which the grid cell belongs. In another embodiment, the elevation zone parameter module writes the boundary identifier into the zonal temperature control parameter data for subsequent manual verification or parameter version recording. The aforementioned boundary identifier does not change the correspondence between the elevation zone identifier and the photosynthetic temperature control parameter group in the claims.

[0053] The zonal temperature control parameter data output by S200 includes a unified raster index, altitude zone identifier, minimum temperature, optimum temperature, maximum temperature, parameter version, and parameter anomaly identifier. This zonal temperature control parameter data is subsequently called by S300, where the altitude zone identifier serves as the index field for calling the photosynthetic temperature control parameter group grid by grid, and the minimum, optimum, and maximum temperatures serve as temperature response parameters in the calculation of total primary productivity. S200 also generates an altitude zonal raster, which preserves the spatial distribution of the altitude zone to which each raster cell belongs and maintains the same raster row and column numbers as the base raster data for carbon sink estimation.

[0054] S300. Based on the carbon sink estimation base grid data and the zonal temperature control parameter data, read the vegetation index value and the same period meteorological driving value grid by grid, and call the photosynthetic temperature control parameter group according to the altitude zone to calculate the total primary productivity and generate the periodic total primary productivity grid.

[0055] In this embodiment, S300 is executed by the total primary productivity calculation module in the regional carbon sink raster estimation system. The total primary productivity calculation module receives the carbon sink estimation basic raster data generated in S100 and the zonal temperature control parameter data generated in S200; under the same raster row and column number and the same preset evaluation period identifier, it reads the vegetation index value, the same-period meteorological driving value, the altitudinal zone identifier, and the corresponding photosynthetic temperature control parameter group for each raster cell; based on the above data, it calculates the total primary productivity value of each raster cell and writes the calculated total primary productivity value into the period-by-period total primary productivity raster.

[0056] Total primary productivity is the productivity field of a raster unit formed by vegetation photosynthesis within a corresponding preset evaluation period. The concurrent meteorological driving value is a meteorological variable within the same preset evaluation period as the remote sensing vegetation index value, which in this embodiment includes temperature data and radiation data. The vegetation index value participates in the generation of the proportion of photosynthetically active radiation absorbed, the radiation data participates in the generation of the amount of photosynthetically active radiation absorbed, and the temperature data, together with the photosynthetic temperature control parameter set, participates in the calculation of the photosynthetic temperature response. The photosynthetic temperature control parameter set is provided by the zonal temperature control parameter data of S200 and is called according to the altitude zone identifier.

[0057] The trigger condition for S300 is that S200 generates zonal temperature control parameter data and completes the parameter version writing. The total primary productivity calculation module reads the preset assessment period identifier to be calculated and extracts the vegetation index value and the corresponding meteorological driving value from the carbon sink estimation base raster data. At the same time, it extracts the altitude zone identifier, minimum temperature, optimum temperature, and maximum temperature corresponding to the same raster row and column number from the zonal temperature control parameter data. If a raster cell has a missing vegetation index identifier or a missing meteorological identifier in S100, or a parameter anomaly identifier in S200, the total primary productivity calculation module writes the raster cell into the total primary productivity calculation anomaly record and writes an invalid value identifier into the period-by-period total primary productivity raster.

[0058] Specifically, the total primary productivity calculation module first generates the absorbed photosynthetically active radiation ratio based on the vegetation index value; the absorbed photosynthetically active radiation ratio is an intermediate field expressing the degree of photosynthetically active radiation absorption by the vegetation in the raster unit. Then, the total primary productivity calculation module generates the absorbed photosynthetically active radiation amount based on the radiation data in the concurrent meteorological driving values ​​and the absorbed photosynthetically active radiation ratio. Next, the total primary productivity calculation module reads the temperature data of the same raster unit and retrieves the minimum, optimum, and maximum temperatures corresponding to the altitude zone to which the raster unit belongs from the zonal temperature control parameter data to generate the temperature response field of the raster unit. Finally, the total primary productivity calculation module calculates the total primary productivity value of the raster unit based on the absorbed photosynthetically active radiation amount and the temperature response field, and writes it into the phase-by-phase total primary productivity raster.

[0059] In one implementation, the total primary productivity calculation module uses a light energy utilization model to calculate total primary productivity. The light energy utilization model reads the absorbed photosynthetically active radiation and light energy utilization parameters, and incorporates a temperature response field formed from air temperature data, minimum temperature, optimum temperature, and maximum temperature into the calculation. Altitude zone identifiers serve as parameter call indexes during this calculation process, controlling the use of different photosynthetic temperature control parameter sets by raster units in different altitude zones within the same preset evaluation period. Therefore, when calculating total primary productivity values, basin raster, mountain raster, and plateau raster within the same evaluation area read the minimum temperature, optimum temperature, and maximum temperature corresponding to their respective altitude zones.

[0060] In one engineering implementation, the regional carbon sink raster estimation system performs calculations for a preset assessment period. The total primary productivity calculation module reads the basic raster data for carbon sink estimation row by row according to a unified raster index. For a valid raster cell, the module reads the vegetation index value, temperature data, and radiation data, and then reads the elevation zone identifier written in S200 for that raster cell. Based on the elevation zone identifier, the module extracts the minimum temperature, optimum temperature, and maximum temperature from the zonal temperature control parameter data and sends these fields into the calculation process of the light energy utilization model. The calculated total primary productivity value, along with the raster row and column number, the preset assessment period identifier, the elevation zone identifier, and the parameter version, is written into the period-by-period total primary productivity raster. For all valid raster cells within the same period, the module generates a complete period-by-period total primary productivity raster in the same processing order.

[0061] Regarding anomaly handling, if the vegetation index value exceeds the preset vegetation index range, the total primary productivity calculation module writes a vegetation index anomaly flag to that raster cell and does not write its total primary productivity value to a valid raster. If radiation data is missing, a radiation missing flag is written; if temperature data is missing, a temperature missing flag is written; if the elevation zone identifier cannot be matched with a photosynthetic temperature control parameter group in the zonal temperature control parameter data, a temperature control parameter missing flag is written. The above anomaly flags are written to the subsidiary record of the phase-by-phase total primary productivity raster and are read when S500 performs outlier filtering.

[0062] The phase-by-phase total primary productivity raster output by S300 includes a unified raster index, a preset assessment period identifier, total primary productivity value, altitudinal zone identifier, parameter version, and calculation anomaly identifier. This phase-by-phase total primary productivity raster serves as the carbon sequestration input for the phase-by-phase net ecosystem productivity raster generated by S500. S500 reads the total primary productivity value from the phase-by-phase total primary productivity raster under the same raster row and column number and subtracts it from the ecosystem respiration rate in the phase-by-phase ecosystem respiration raster generated by S400.

[0063] S400. Based on the land use secondary classification raster in the carbon sink estimation basic raster data, read the land use secondary classification code, and call the autotrophic respiration parameters and heterotrophic respiration parameters of the corresponding ecosystem type according to the land use secondary classification code to calculate the ecosystem respiration volume and generate a phase-by-phase ecosystem respiration raster.

[0064] In this embodiment, S400 is executed by the ecosystem respiration calculation module in the regional carbon sink rasterization estimation system. The ecosystem respiration calculation module receives the basic raster data for carbon sink estimation generated in S100 and reads the land use secondary classification code corresponding to the land use secondary classification raster. The ecosystem respiration calculation module generates an ecosystem type identifier based on the land use secondary classification code and calls the corresponding autotrophic respiration parameters and heterotrophic respiration parameters based on the ecosystem type identifier. Then, combined with the temperature data in the meteorological driving values ​​of the same period, it calculates the ecosystem respiration on a raster-by-raster basis to generate a period-by-period ecosystem respiration raster.

[0065] The land use secondary category code is a coding field representing the secondary land use type or ecosystem secondary type to which the raster unit belongs. After reading the land use secondary category code, the ecosystem respiration calculation module maps it to an ecosystem type identifier for forest ecosystem, grassland ecosystem, water and wetland ecosystem, or wetland peatland. In one embodiment, an ecosystem type identifier is associated with a set of respiration parameters; the respiration parameter set includes autotrophic respiration parameters and heterotrophic respiration parameters; the autotrophic respiration parameters include the autotrophic baseline respiration coefficient and the autotrophic temperature sensitivity coefficient, and the heterotrophic respiration parameters include the heterotrophic baseline respiration coefficient and the heterotrophic temperature sensitivity coefficient. These parameters are used in the calculation of the ecosystem respiration of each raster unit.

[0066] The trigger condition for S400 is that S100 generates basic raster data for carbon sink estimation and completes the writing of land use secondary category codes. The ecosystem respiration calculation module reads the preset assessment period identifier to be calculated, and reads the land use secondary category code and temperature data from the contemporaneous meteorological driving values ​​grid by grid under the unified raster index. For raster units with valid land use secondary category codes and valid temperature data, the ecosystem respiration calculation module generates an ecosystem type identifier according to the mapping rules between the secondary category code and the ecosystem type identifier; then, based on the ecosystem type identifier, it reads the corresponding respiration parameter group and inputs the respiration parameter group and temperature data into the ecosystem respiration calculation link.

[0067] Specifically, the ecosystem respiration calculation module first generates an ecosystem type identifier based on the land use secondary category code; then, based on the ecosystem type identifier, it reads the autotrophic basal respiration coefficient, autotrophic temperature sensitivity coefficient, heterotrophic basal respiration coefficient, and heterotrophic temperature sensitivity coefficient from the respiration parameter table; subsequently, it generates autotrophic respiration and heterotrophic respiration respectively based on the temperature data in the concurrent meteorological driving values; finally, it synthesizes the autotrophic and heterotrophic respiration to generate the ecosystem respiration of the corresponding raster unit. This ecosystem respiration, along with the raster row and column number, the preset assessment period identifier, the land use secondary category code, the ecosystem type identifier, and the respiration parameter version, is written into the period-by-period ecosystem respiration raster.

[0068] In one implementation, the respiration parameter table is provided by an ecosystem classification parameter library. The respiration parameter table includes a land use secondary category code, an ecosystem type identifier, an autotrophic basal respiration coefficient, an autotrophic temperature sensitivity coefficient, a heterotrophic basal respiration coefficient, and a heterotrophic temperature sensitivity coefficient. After reading the land use secondary category code, the ecosystem respiration calculation module first matches the corresponding record in the respiration parameter table. If multiple records are matched, the parameter version corresponding to that period is called according to the preset assessment period identifier. If no record is matched, a respiration parameter missing identifier is written, and an invalid value identifier is written in the period-by-period ecosystem respiration raster. This process preserves the raster row and column numbers for S500 to read during outlier filtering and zoning aggregation.

[0069] In one engineering implementation, a certain raster cell corresponds to a forest ecosystem type in the land use secondary classification raster. The ecosystem respiration calculation module reads the land use secondary classification code of the raster cell and maps it to a forest ecosystem type identifier; then, it reads the autotrophic and heterotrophic respiration parameters corresponding to the forest ecosystem from the respiration parameter table; the module reads the temperature data of the same preset assessment period for the raster cell and calculates the ecosystem respiration based on the autotrophic, heterotrophic, and temperature data. For another raster cell, if the land use secondary classification code is mapped to a wetland peatland type identifier, the ecosystem respiration calculation module calls the respiration parameter group corresponding to the wetland peatland and generates the ecosystem respiration according to the same calculation link. The ecosystem respiration of each raster cell is written into the periodic ecosystem respiration raster under the same raster row and column number.

[0070] Regarding anomaly handling, if the land use secondary category code of a raster cell is null or does not fall within the coverage area of ​​the respiration parameter table, the ecosystem respiration calculation module writes an anomaly flag for the secondary category code; if the temperature data of the raster cell is missing, the ecosystem respiration calculation module writes a missing temperature flag; if the ecosystem type identifier is inconsistent with the respiration parameter table version, the ecosystem respiration calculation module retains the original land use secondary category code and writes a parameter version mismatch flag. These anomaly flags are output with each subsequent period of the ecosystem respiration raster and used as input for outlier filtering and valid raster selection in S500.

[0071] The phase-by-phase ecosystem respiration raster output by S400 includes a unified raster index, a preset assessment period identifier, a land use secondary category code, an ecosystem type identifier, autotrophic respiration parameter versions, heterotrophic respiration parameter versions, ecosystem respiration volume, and respiration calculation anomaly identifiers. This phase-by-phase ecosystem respiration raster serves as the consumption input for the subsequent phase-by-phase net ecosystem productivity raster generated by S500. S500 reads the ecosystem respiration volume under the same raster row and column number and subtracts it from the total primary productivity value generated by S300.

[0072] S500. Based on the total primary productivity raster and the ecosystem respiration raster for each period, perform raster-by-raster subtraction to generate a net ecosystem productivity raster for each period. Then, perform outlier filtering, cumulative consistency check and partition summary on the net ecosystem productivity raster for each period to generate a carbon sink raster output set and partition statistics results for each period.

[0073] In this embodiment, S500 is executed by the net ecosystem productivity generation module and the anomaly filtering and partitioning summary module in the regional carbon sink gridded estimation system. The net ecosystem productivity generation module receives the period-by-period total primary productivity grid generated in S300 and the period-by-period ecosystem respiration grid generated in S400; it reads the total primary productivity value and ecosystem respiration under the same grid row and column number and the same preset assessment period identifier, and subtracts the total primary productivity value from the ecosystem respiration value to obtain the net ecosystem productivity value of the corresponding grid unit, thus generating the period-by-period net ecosystem productivity grid. The anomaly filtering and partitioning summary module performs anomaly filtering, cumulative consistency checks, and partitioning summary on the period-by-period net ecosystem productivity grid, generating a period-by-period carbon sink grid output set and partitioned statistical results.

[0074] The net ecosystem productivity raster is data expressing the net ecosystem productivity value of each raster unit under a unified raster index. The period-by-period carbon sink raster output set is a collection of net ecosystem productivity raster units organized according to a preset assessment period. The zonal statistical results are statistical records formed by summarizing the net ecosystem productivity values ​​of effective raster units based on administrative region boundary data or zonal boundary data using area weights. The cumulative consistency check results are verification records generated by comparing the cumulative values ​​of the period-by-period carbon sink raster output set with the cumulative values ​​of the zonal statistical results.

[0075] The trigger condition for S500 is the completion of output for both the phase-by-phase total primary productivity raster and the phase-by-phase ecosystem respiration raster within the same preset assessment period. The net ecosystem productivity generation module reads the total primary productivity value, elevation zone identifier, and calculation anomaly identifier from the phase-by-phase total primary productivity raster; simultaneously, it reads the ecosystem respiration, ecosystem type identifier, and respiration calculation anomaly identifier from the phase-by-phase ecosystem respiration raster. For raster cells with both valid total primary productivity value and valid ecosystem respiration at the same raster row and column number, the net ecosystem productivity generation module subtracts the ecosystem respiration from the total primary productivity value to generate the net ecosystem productivity value, which is then written into the phase-by-phase net ecosystem productivity raster.

[0076] When generating the period-by-period net ecosystem productivity raster, the net ecosystem productivity generation module retains key index fields from S300 and S400. Specifically, the period-by-period net ecosystem productivity raster includes raster row and column numbers, preset assessment period identifiers, total primary productivity values, ecosystem respiration, net ecosystem productivity values, elevation zone identifiers, land use secondary category codes, ecosystem type identifiers, parameter versions, and calculation anomaly identifiers. If a raster cell lacks a total primary productivity value or ecosystem respiration, the net ecosystem productivity generation module does not perform the difference calculation and writes the invalid raster cell into the invalid raster identifier. The invalid raster identifier is read by the anomaly filtering and zoning summary module.

[0077] The anomaly filtering and partitioned aggregation module performs outlier filtering on the period-by-period net ecosystem productivity raster. Specifically, the module reads the invalid raster identifier, ecosystem type identifier, net ecosystem productivity value, and preset assessment period identifier from the period-by-period net ecosystem productivity raster. For invalid rasters, an anomaly raster identifier is written; for rasters whose net ecosystem productivity values ​​exceed the preset range for the corresponding ecosystem type, an anomaly raster identifier is written; for rasters where the same raster unit exhibits a cross-period abrupt change between adjacent preset assessment periods, a cross-period abrupt change identifier is written. Rasters with anomaly raster identifiers retain the original net ecosystem productivity value and the anomaly source field, but are removed during partitioned aggregation.

[0078] In one implementation, the inter-period mutation check involves the anomaly filtering and zoning module reading the net ecosystem productivity values ​​for the same raster row and column number in the previous preset assessment period and the net ecosystem productivity values ​​in the current preset assessment period, and comparing them based on a preset range for ecosystem type to generate an inter-period mutation identifier. In another implementation, the anomaly filtering and zoning module merges input missing identifiers, temperature control parameter missing identifiers, respiration parameter missing identifiers, and parameter version mismatch identifiers to generate an outlier filtering record. This outlier filtering record includes the raster row and column number, preset assessment period identifier, anomaly raster identifier, an anomaly source field, and a reserved value field.

[0079] The zoning aggregation is performed by the anomaly filtering and zoning aggregation module based on administrative region boundary data. Specifically, the module reads the administrative region boundary data, spatially matches each raster cell with the administrative region boundary data, and generates zoning identifiers. For raster cells with valid net ecosystem productivity values ​​and no anomaly raster identifiers, the module reads the raster cell area and aggregates the net ecosystem productivity values ​​according to the raster cell area using area weighting, generating zoning statistical results. The zoning statistical results include zoning identifier, preset assessment period identifier, number of valid raster cells, proportion of valid raster cells, net ecosystem productivity aggregated value, and cumulative value fields. In one implementation, the administrative region boundary data is the standard administrative region vector boundary; in another implementation, the zoning boundary data is the preset ecological function zoning boundary within the area to be assessed.

[0080] The cumulative consistency check is performed by the anomaly filtering and partition aggregation module after partition aggregation. Specifically, the module reads the cumulative effective net ecosystem productivity of the period-by-period carbon sink raster output set within a specified preset assessment period, and reads the cumulative values ​​of the partition statistics within the same preset assessment period; then it compares the difference between the two and writes the comparison result into the cumulative consistency check result. The cumulative consistency check result includes the preset assessment period range, partition identifier, raster cumulative value, partition statistical cumulative value, difference field, and check status field. If the difference field exceeds the preset consistency condition, the module writes the corresponding partition identifier into the cumulative check anomaly record and retains the raster row and column numbers that participated in the accumulation within the corresponding preset assessment period.

[0081] In one engineering implementation, after the regional carbon sink raster estimation system completes the S300 and S400 calculations for a preset assessment period in a given month, the net ecosystem productivity generation module reads the period-by-period total primary productivity raster and the period-by-period ecosystem respiration raster according to a unified raster index. For the same raster row and column number, the module reads the total primary productivity value and ecosystem respiration, and calculates the difference to obtain the net ecosystem productivity value. Subsequently, the anomaly filtering and zoning summary module reads the ecosystem type identifier and writes anomaly raster identifiers for invalid rasters, rasters exceeding the preset range of ecosystem types, and inter-period mutation rasters. The module writes zoning identifiers for valid raster units based on administrative boundary data and summarizes them according to the area weight of the raster unit area to form the zoning statistical results for that month. These zoning statistical results are written together with the period-by-period carbon sink raster output set into the output storage area.

[0082] The phased carbon sink raster output set generated by S500 includes phased net ecosystem productivity rasters, outlier filtering records, and parameter version fields corresponding to multiple preset assessment periods. The zonal statistical results include zonal identifiers, preset assessment period identifiers, effective raster proportions, summarized net ecosystem productivity values, and cumulative consistency check results. When a subsequent assessment period begins, the regional carbon sink raster estimation system reads the phased carbon sink raster output set and cumulative consistency check results from the previous preset assessment period and uses them as historical inputs for inter-period mutation checks and cumulative consistency checks. Thus, S100 to S500 form a continuous data link from input raster alignment, elevation zoning parameter retrieval, total primary productivity calculation, ecosystem respiration calculation, net ecosystem productivity generation to zonal statistical records.

[0083] Example 2: Figure 2 A structural block diagram of a regional carbon sink gridding estimation method optimized by altitude zonation according to an embodiment of the present invention is shown. Figure 2 As shown, the structure may include:

[0084] The raster data access and alignment module 01 is used to acquire remote sensing vegetation index raster, periodic meteorological raster, digital elevation model, and land use secondary classification raster of the area to be evaluated. It performs spatial alignment and periodic binding on the remote sensing vegetation index raster, the periodic meteorological raster, the digital elevation model, and the land use secondary classification raster to generate basic raster data for carbon sink estimation. Specifically, the raster data access and alignment module receives input objects from external remote sensing data sources, meteorological data sources, elevation data sources, and land use classification data sources, and reads the spatial reference, resolution, raster range, raster row and column number, data batch, and preset evaluation period for each input object. When the spatial references of the remote sensing vegetation index raster, the periodic meteorological raster, the digital elevation model, and the land use secondary classification raster are inconsistent, projection processing is performed. When the spatial resolution or raster range is inconsistent, resampling and cropping are performed. The process involves: After spatial alignment, each input object is written with the same raster row and column number, and associated with vegetation index values, concurrent meteorological driving values, elevation values, and land use secondary category codes under the same preset evaluation period; for raster units with missing inputs, non-overlapping raster ranges, or mismatched invalid value codes, the raster data access and alignment module writes an input missing identifier and retains the original raster row and column numbers; the carbon sink estimation basic raster data includes a unified raster index, a preset evaluation period identifier, vegetation index values, concurrent meteorological driving values, elevation values, land use secondary category codes, and input missing identifiers; the raster data access and alignment module provides the digital elevation model and elevation values ​​from the carbon sink estimation basic raster data to the elevation zonation parameter module, provides the vegetation index values ​​and concurrent meteorological driving values ​​to the total primary productivity calculation module, and provides the land use secondary category codes and concurrent meteorological driving values ​​to the ecosystem respiration calculation module.

[0085] The elevation zonation parameter module 02, connected to the raster data access and alignment module, is used to generate an elevation zonation raster based on the digital elevation model in the carbon sink estimation basic raster data. It writes elevation zonation identifiers to each raster unit and establishes a correspondence between the elevation zonation identifiers and a photosynthetic temperature control parameter group, generating zonation temperature control parameter data. The photosynthetic temperature control parameter group includes minimum temperature, optimum temperature, and maximum temperature. Specifically, the elevation zonation parameter module receives the carbon sink estimation basic raster data from the raster data access and alignment module, reads the elevation value corresponding to the unified raster index, and performs elevation zonation matching on each raster unit based on a preset elevation threshold. After matching, the elevation zonation parameter module writes the elevation zonation identifier into the elevation zonation raster and reads the corresponding elevation value. The altitude zone parameter module calculates the minimum, optimum, and maximum temperatures. Before writing the zonal temperature control parameter data, the module checks the incremental relationship of the minimum, optimum, and maximum temperatures. Records with mismatched incremental relationships are marked with a parameter anomaly flag, and the original temperature parameters are retained. For raster cells with missing elevation values, the altitude zone parameter module writes an elevation missing flag and does not assign a photosynthetic temperature control parameter group to that raster cell. The zonal temperature control parameter data includes a unified raster index, altitude zone identifier, minimum temperature, optimum temperature, maximum temperature, parameter version, and parameter anomaly flag. The altitude zone parameter module provides the zonal temperature control parameter data to the total primary productivity calculation module, which then calls the corresponding photosynthetic temperature control parameter group according to the altitude zone identifier.

[0086] The total primary productivity calculation module 03, connected to the raster data access and alignment module and the altitude zonal parameter module, is used to read vegetation index values ​​and concurrent meteorological driving values ​​grid by grid based on the carbon sink estimation base raster data and the zonal temperature control parameter data, and to calculate total primary productivity by calling the photosynthetic temperature control parameter group according to the altitude zone identifier, generating a period-by-period total primary productivity raster. Specifically, the total primary productivity calculation module receives carbon sink estimation base raster data from the raster data access and alignment module, and receives zonal temperature control parameter data from the altitude zonal parameter module; the total primary productivity calculation module reads vegetation index values, concurrent meteorological driving values, altitude zone identifiers, minimum temperature, optimum temperature, and maximum temperature under the same raster row and column number and the same preset evaluation period identifier; then, it generates the absorbed photosynthetic effective radiation ratio based on the vegetation index values, and calculates the absorbed photosynthetic effective radiation ratio based on the radiation data in the concurrent meteorological driving values ​​and the absorbed photosynthetic effective radiation ratio. The effective radiation ratio generates the absorbed photosynthetically active radiation (EPA), and a temperature response field is generated based on the temperature data in the concurrent meteorological driving values ​​and the photosynthetic temperature control parameter group. The total primary productivity calculation module writes the absorbed EPA and the temperature response field into the calculation record under the same raster row and column number, and generates the total primary productivity value of the corresponding raster unit. For raster units with missing vegetation index values, missing radiation data, missing temperature data, mismatched altitudinal zone identifiers, or presence of parameter anomaly identifiers, the total primary productivity calculation module writes a total primary productivity calculation anomaly identifier. The period-by-period total primary productivity raster includes a unified raster index, a preset evaluation cycle identifier, total primary productivity value, altitudinal zone identifier, parameter version, and total primary productivity calculation anomaly identifier. The total primary productivity calculation module provides the period-by-period total primary productivity raster to the net ecosystem productivity and summary module, allowing it to read the total primary productivity value under the same raster row and column number.

[0087] The ecosystem respiration calculation module 04, connected to the raster data access and alignment module, is used to read the land use secondary classification code from the land use secondary classification raster in the carbon sink estimation basic raster data, and to call the autotrophic respiration parameters and heterotrophic respiration parameters of the corresponding ecosystem type according to the land use secondary classification code, calculate the ecosystem respiration, and generate a period-by-period ecosystem respiration raster. Specifically, the ecosystem respiration calculation module receives the carbon sink estimation basic raster data from the raster data access and alignment module, and reads the land use secondary classification code and the contemporaneous meteorological driving value corresponding to the unified raster index. The ecosystem respiration calculation module maps the land use secondary classification code to an ecosystem type identifier of forest ecosystem, grassland ecosystem, water and wetland ecosystem, or wetland peatland, and reads the autotrophic respiration parameters and heterotrophic respiration parameters according to the ecosystem type identifier. The autotrophic respiration parameters include the autotrophic basal respiration coefficient and autotrophic temperature. The heterotrophic respiration parameters include the heterotrophic basal respiration coefficient and the heterotrophic temperature sensitivity coefficient. The ecosystem respiration calculation module generates the corresponding ecosystem respiration volume for each raster unit based on the autotrophic respiration parameters, the heterotrophic respiration parameters, and the temperature data from the concurrent meteorological driving values. For raster units with missing land use secondary category codes, mismatched ecosystem type identifiers, missing temperature data, or inconsistent respiration parameter versions, the ecosystem respiration calculation module writes an ecosystem respiration calculation anomaly identifier. The period-by-period ecosystem respiration raster includes a unified raster index, a preset assessment cycle identifier, a land use secondary category code, an ecosystem type identifier, an autotrophic respiration parameter version, a heterotrophic respiration parameter version, ecosystem respiration volume, and an ecosystem respiration calculation anomaly identifier. The ecosystem respiration calculation module provides the period-by-period ecosystem respiration raster to the net ecosystem productivity and aggregation module, allowing it to read the ecosystem respiration volume under the same raster row and column number.

[0088] The Net Ecosystem Productivity and Summary Module 05 connects the Total Primary Productivity Calculation Module and the Ecosystem Respiration Calculation Module. It is used to perform grid-by-grid subtraction based on the phase-by-phase Total Primary Productivity Raster and the phase-by-phase Ecosystem Respiration Raster to generate a phase-by-phase Net Ecosystem Productivity Raster. It also performs outlier filtering, cumulative consistency checks, and partitioned summarization on the phase-by-phase Net Ecosystem Productivity Raster to generate a phase-by-phase carbon sink raster output set and partitioned statistical results. Specifically, the net ecosystem productivity and aggregation module receives period-by-period total primary productivity grids from the total primary productivity calculation module and period-by-period ecosystem respiration grids from the ecosystem respiration calculation module. The net ecosystem productivity and aggregation module reads the total primary productivity value and ecosystem respiration under the same grid row and column number and the same preset assessment period identifier, and calculates the difference between the total primary productivity value and the ecosystem respiration value to generate the net ecosystem productivity value for the corresponding grid unit. For grid units with abnormal total primary productivity calculation identifiers or abnormal ecosystem respiration calculation identifiers, the net ecosystem productivity and aggregation module writes an invalid grid identifier. Subsequently, the net ecosystem productivity and aggregation module writes abnormal grid identifiers for invalid grids, grids exceeding the preset range for ecosystem type, and inter-period mutation grids in the period-by-period net ecosystem productivity grids, and removes them in the partitioned aggregation. The system writes anomaly grid identifiers to the grids; the net ecosystem productivity and aggregation module reads the partition identifiers of each grid cell based on administrative boundary data, and aggregates the effective net ecosystem productivity values ​​according to the grid cell area using area weighting to generate partition statistics; the net ecosystem productivity and aggregation module compares the cumulative value of the period-by-period carbon sink grid output set with the cumulative value of the partition statistics to generate a cumulative consistency check result; the period-by-period carbon sink grid output set includes period-by-period net ecosystem productivity grids, outlier filtering records, parameter versions, and preset assessment period identifiers; the partition statistics include partition identifiers, preset assessment period identifiers, effective grid ratios, net ecosystem productivity aggregated values, and cumulative consistency check results; the net ecosystem productivity and aggregation module retains the period-by-period carbon sink grid output set and the partition statistics results for use in the next preset assessment period for outlier filtering and cumulative consistency checks.

Claims

1. A rasterized estimation method for regional carbon sinks optimized by altitude zonation, characterized in that, include: S100: Obtain remote sensing vegetation index raster, periodic meteorological raster, digital elevation model and land use secondary classification raster of the area to be evaluated, perform spatial alignment and periodic binding, and generate basic raster data for carbon sink estimation. S200. Based on the digital elevation model in the carbon sink estimation basic grid data, generate an elevation zone grid, write an elevation zone identifier for each grid cell, and establish a correspondence between the elevation zone identifier and the photosynthetic temperature control parameter group to generate zone temperature control parameter data; the photosynthetic temperature control parameter group includes the minimum temperature, the optimal temperature, and the maximum temperature. S300. Based on the carbon sink estimation base grid data and the zonal temperature control parameter data, read the vegetation index value and the same period meteorological driving value grid by grid, and call the photosynthetic temperature control parameter group according to the altitude zone identifier to calculate the total primary productivity and generate the periodic total primary productivity grid. S400. Based on the land use secondary classification raster in the carbon sink estimation basic raster data, read the land use secondary classification code, and call the autotrophic respiration parameters and heterotrophic respiration parameters of the corresponding ecosystem type according to the land use secondary classification code, calculate the ecosystem respiration, and generate a phase-by-phase ecosystem respiration raster. S500. Based on the total primary productivity raster and the ecosystem respiration raster for each period, perform raster-by-raster subtraction to generate a net ecosystem productivity raster for each period. Then, perform outlier filtering, cumulative consistency check and partition summary on the net ecosystem productivity raster for each period to generate a carbon sink raster output set and partition statistics results for each period.

2. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S100, the spatial alignment includes: projecting, resampling, and cropping the remote sensing vegetation index raster, the periodic meteorological raster, the digital elevation model, and the land use secondary classification raster to generate a unified raster index with the same raster row and column numbers; the periodic binding includes: writing the remote sensing vegetation index raster and the periodic meteorological raster into the same preset evaluation period identifier.

3. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S200, generating the elevation zone grid includes: reading the elevation value of each grid cell in the digital elevation model, dividing each grid cell into a corresponding elevation zone according to a preset elevation threshold, and writing the elevation zone identifier into the elevation zone grid.

4. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S200, establishing a correspondence between the altitude zone identifier and the photosynthetic temperature control parameter group includes: reading the minimum temperature, optimal temperature and maximum temperature corresponding to each altitude zone; performing an incremental relationship check on the minimum temperature, optimal temperature and maximum temperature; and writing the minimum temperature, optimal temperature and maximum temperature that have passed the incremental relationship check into the zone-specific temperature control parameter data.

5. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S300, generating the phase-by-phase total primary productivity grid includes: determining the proportion of photosynthetically active radiation absorbed based on the vegetation index value; determining the amount of photosynthetically active radiation absorbed based on the radiation data in the meteorological driving value of the same period and the proportion of photosynthetically active radiation absorbed; and calculating the total primary productivity value of each grid cell based on the amount of photosynthetically active radiation absorbed and the photosynthetic temperature control parameter set.

6. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S400, after reading the land use secondary category code, the land use secondary category code is mapped to an ecosystem type identifier of forest ecosystem, grassland ecosystem, water and wetland ecosystem or wetland peatland, and the autotrophic respiration parameter and the heterotrophic respiration parameter are called based on the ecosystem type identifier.

7. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S400, the autotrophic respiration parameters include the autotrophic basal respiration coefficient and the autotrophic temperature sensitivity coefficient; the heterotrophic respiration parameters include the heterotrophic basal respiration coefficient and the heterotrophic temperature sensitivity coefficient; the ecosystem respiration is calculated from the autotrophic respiration parameters, the heterotrophic respiration parameters, and the temperature data in the contemporaneous meteorological driving values.

8. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S500, generating the phase-by-phase net ecosystem productivity grid includes: reading the total primary productivity value in the phase-by-phase total primary productivity grid and the ecosystem respiration in the phase-by-phase ecosystem respiration grid under the same grid row and column number, and subtracting the total primary productivity value from the ecosystem respiration to obtain the net ecosystem productivity value of the corresponding grid unit.

9. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S500, the outlier filtering includes: writing an outlier raster identifier to invalid raster, raster that exceeds the preset range of ecosystem type, and inter-period mutation raster in the phase-by-phase net ecosystem productivity raster, and removing the raster with the outlier raster identifier written in the partition summary.

10. The method for estimating regional carbon sinks using elevation zoning optimization according to claim 1, characterized in that, In S500, the zoning summary includes: reading the zoning identifier of each grid cell based on the administrative region boundary data, and summarizing the effective net ecosystem productivity value according to the area of ​​the grid cell to generate the zoning statistical results; the cumulative consistency check includes: comparing the cumulative value of the period-by-period carbon sink grid output set with the cumulative value of the zoning statistical results to generate the cumulative consistency check results.

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