Karst carbon sink based on artificial interference measurement deviation intelligent correction method and system

Abstract

The present application relates to the technical field of data mining software, and discloses a karst carbon sink based on artificial interference measurement deviation intelligent correction method and system, the method comprises the following steps: obtaining original carbon sink measurement data, monitoring point position, sampling time and artificial interference data, constructing an artificial interference factor dynamic database according to remote sensing interpretation records, ground verification records and monitoring traceability records, spatiotemporally matching the original carbon sink measurement data with the artificial interference factor dynamic database, calculating measurement error samples, generating an interference response function and an artificial interference threshold interval, and generating corrected carbon sink measurement data according to the correction level when the artificial interference factor meets the threshold interval and storing the corrected carbon sink measurement data. According to the present application, the artificial interference factor is structured, the response relationship is calculated, and the threshold is triggered for correction, so that the artificial disturbance measurement deviation can be calculated, and the corrected carbon sink measurement data can be corresponded with the data source, the interference source and the processing process.

Description

Technical Field

[0001] This invention relates to the field of data mining software technology, specifically to a method and system for intelligent correction of measurement deviations in karst carbon sinks based on human interference. Background Technology

[0002] Data mining software technology typically revolves around collecting, transmitting, cleaning, correlating, calculating, storing, and retrieving multi-source data records, database tables, sensor sampling values, manually entered information, and business terminal logs. Server programs compare, filter, and output data based on field attributes, time series, spatial location, threshold conditions, and statistical models. Among these, the traditional intelligent correction method and system for measurement deviations in karst carbon sinks based on human interference refers to collecting data such as hydrological monitoring values, soil or water carbonate parameters, meteorological records, land use types, engineering activity ranges, and human disturbance intensity for carbon sink measurement records in karst areas. This data is written to a database via a terminal or interface, and the server performs matching, normalization, outlier marking, deviation estimation, and correction value generation according to sampling time, monitoring point location, indicator fields, and interference categories. The calculation results are then stored in a measurement result table for querying and display.

[0003] In karst carbon sink measurement scenarios, servers typically collect data such as hydrological monitoring values, carbonate parameters, meteorological records, land use types, and engineering activity ranges. These data are then matched, normalized, anomaly flagged, and bias estimated based on sampling time, monitoring point location, and indicator fields. Current processing methods often use disturbance type or single intensity parameters in calculations, failing to structurally correlate the intensity, scope, and duration of the disturbance with the disturbance type. This results in insufficient correspondence between human activity records across multiple dimensions. Consequently, it becomes difficult to distinguish between natural driving factors and human disturbance factors in carbon sink fluctuations, leading to a lack of traceable data links in the correction results and unclear boundaries for subsequent accounting calculations. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent correction method and system for measurement deviations in karst carbon sinks based on human interference, addressing the problems of insufficient correspondence between human activity records and carbon sink measurement data in traditional karst carbon sink measurement, unclear distinction between the sources of carbon sink fluctuations caused by natural driving factors and human disturbance factors, and lack of traceable evidence for correction results. To this end, this invention forms a technical solution oriented towards structured database construction for human interference factors, response relationship calculation, threshold-triggered correction, and result association storage.

[0005] To achieve the above objectives, this invention provides an intelligent correction method for measurement deviations of karst carbon sinks based on anthropogenic interference, comprising the following steps: acquiring original carbon sink measurement data, monitoring point locations, sampling times, and anthropogenic interference data of a karst watershed; classifying the anthropogenic interference data into interference type, intensity, scope of influence, and duration based on remote sensing image interpretation records, ground verification records, and monitoring data traceability records, and constructing a dynamic database of anthropogenic interference factors; matching the original carbon sink measurement data with the dynamic database of anthropogenic interference factors according to monitoring point locations and sampling times, calculating carbon sink measurement error samples, mining the nonlinear correlation between anthropogenic interference factors and carbon sink measurement error samples, and generating an interference response function and anthropogenic interference threshold intervals; when the anthropogenic interference factors in the area to be corrected meet the anthropogenic interference threshold intervals, determining the correction level according to the interference type, intensity, scope of influence, and duration of influence, calling the interference response function to dynamically correct the deviation of the original carbon sink measurement data, and generating corrected carbon sink measurement data; and storing and outputting the corrected carbon sink measurement data in association with the original data source, interference source, response basis, and processing process records.

[0006] Furthermore, the process of constructing the dynamic database of anthropogenic interference factors may include: extracting land cover change boundaries and engineering activity patches from the remote sensing image interpretation records; extracting activity categories and field impact boundaries from the ground verification records; extracting monitoring point numbers and sampling periods from the monitoring data tracing records; aligning the extraction results according to the monitoring point location and sampling time; when the extraction results corresponding to the same monitoring point location and the same sampling time have consistent interference directions, generating anthropogenic interference factor records containing interference type, intensity, range of influence, and duration, and writing the anthropogenic interference factor records into the dynamic database of anthropogenic interference factors.

[0007] Furthermore, the intensity of the effect recorded by the human-caused interference factor can be determined by the change area corresponding to the land cover change boundary, the spatial proportion corresponding to the engineering activity patch, and the influence level corresponding to the on-site influence boundary. The duration can be determined by the time span of the same interference type appearing continuously within the sampling period. When the change area, spatial proportion, and influence level all meet the preset recording conditions, the intensity of the effect is written into the human-caused interference factor record. When any recording condition is not met, the corresponding interference type is set to a pending verification status.

[0008] Furthermore, the process of calculating carbon sink measurement error samples may include: retrieving original carbon sink measurement data according to the monitoring point number and sampling period; performing spatiotemporal matching of the original carbon sink measurement data with records of human interference factors; when the monitoring point number falls within the influence range and the sampling period falls within the duration, marking the original carbon sink measurement data as interfered measurement data; when the monitoring point number does not fall within the influence range or the sampling period does not fall within the duration, marking the original carbon sink measurement data as reference measurement data, and generating carbon sink measurement error samples based on the difference between the interfered measurement data and the reference measurement data.

[0009] Furthermore, the process of generating the interference response function and the artificial interference threshold interval may include: using the carbon sink measurement error sample as the response object, and using the interference type, intensity, range of influence, and duration as the interpretation object, establishing a sample set according to the monitoring point location and sampling time within the same karst basin, performing nonlinear correlation fitting on the sample set to obtain the interference response function; when the response change within a continuous sampling period meets the preset interval division conditions, determining the artificial interference threshold interval based on the corresponding intensity and duration.

[0010] Furthermore, after obtaining the interference response function and the artificial interference threshold range, the process of determining the correction level of the region to be corrected may include: retrieving the artificial interference factor record corresponding to the region to be corrected at the sampling time, and matching the interference type of the region to be corrected with the applicable interference type of the interference response function; when both the intensity and duration of the interference fall within the artificial interference threshold range, the region to be corrected is classified into the trigger correction level; when the intensity or duration of the interference does not fall within the artificial interference threshold range, the region to be corrected is classified into the reference correction level.

[0011] Furthermore, the process of calling the interference response function to generate corrected carbon sink measurement data may include: when the area to be corrected is included in the triggered correction level, the interference type, intensity, range of influence, and duration of the area to be corrected are used as function inputs to calculate the deviation response value, and the original carbon sink measurement data is corrected with the deviation response value to generate corrected carbon sink measurement data; when the area to be corrected is included in the reference correction level, the original measurement state of the original carbon sink measurement data is retained and a reference identifier is generated.

[0012] Furthermore, the process of associating and storing the corrected carbon sink measurement data with the original data source, interference source, response basis, and processing record may include: establishing a correction basis record for the corrected carbon sink measurement data, and writing the sampling time, monitoring point location, interference type, intensity, range of influence, duration, deviation response value, and correction level of the original carbon sink measurement data into the correction basis record; when the corrected carbon sink measurement data is generated by the triggering correction level, writing the interference response function and the human interference threshold range into the correction basis record; when the corrected carbon sink measurement data is generated by the reference correction level, writing the reference identifier into the correction basis record.

[0013] Furthermore, the process of outputting the corrected carbon sink measurement data may include: reading the monitoring point location, sampling time, correction level, and deviation response value from the correction basis record; generating standardized output records according to the field requirements of the carbon sink assessment data table, carbon storage accounting data table, carbon trading pricing data table, and long-term dynamic monitoring data table; setting a verification flag for the standardized output record when the correction basis record lacks interference sources or response evidence; and writing the standardized output record into the corresponding data table when the correction basis record contains interference sources and response evidence.

[0014] This invention also provides an intelligent correction system for measurement deviations of karst carbon sinks based on anthropogenic interference. This system supports the aforementioned intelligent correction method for measurement deviations. The system includes a data access unit, an interference factor database unit, a response relationship analysis unit, a dynamic deviation correction unit, and a verification output unit. The data access unit receives raw carbon sink measurement data, monitoring point locations, sampling times, remote sensing image interpretation records, ground verification records, and monitoring data traceability records. The interference factor database unit forms a dynamic database of anthropogenic interference factors based on interference type, intensity, range of influence, and duration. The response relationship analysis unit performs spatiotemporal matching between the raw carbon sink measurement data and the dynamic database of anthropogenic interference factors, calculates carbon sink measurement error samples, and generates interference response functions and anthropogenic interference threshold intervals. When the anthropogenic interference factors in the area to be corrected meet the anthropogenic interference threshold interval, the dynamic deviation correction unit calls the interference response function according to the correction level to generate corrected carbon sink measurement data. The verification output unit associates and stores the corrected carbon sink measurement data with the correction basis and outputs it.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, raw carbon sequestration measurement data, along with monitoring point locations, sampling times, and anthropogenic interference data, are used as inputs. Interference types, intensity, impact range, and duration are extracted through remote sensing image interpretation records, ground verification records, and monitoring data tracing records to construct a dynamic database of anthropogenic interference factors, transforming anthropogenic disturbances into matchable structured data objects. The raw carbon sequestration measurement data is matched with the database according to monitoring point locations and sampling times to calculate carbon sequestration measurement error samples. Through nonlinear correlation fitting, an interference response function and anthropogenic interference threshold range are generated, providing a calculation basis for distinguishing the sources of deviation between natural and anthropogenic disturbances. When the anthropogenic interference factors in the area to be corrected meet the threshold range, the interference response function is called according to the correction level to generate corrected carbon sequestration measurement data. The results are then linked and stored with the original data source, interference source, response basis, and processing records, forming a traceable data link and ensuring that the measurement results have verifiable evidence. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is the main flowchart of the intelligent correction method for measurement deviation of karst carbon sink based on human interference in this invention.

[0018] Figure 2 The present invention constructs a data flow graph for a dynamic database of interference factors.

[0019] Figure 3 A logic diagram is generated to show the relationship between the carbon sink measurement error sample and the interference response in this invention.

[0020] Figure 4 This is a state transition diagram of the correction hierarchy for the region to be corrected in this invention.

[0021] Figure 5 The calibration basis for this invention is a record and standardized output data flow diagram.

[0022] Figure 6 This is a logic block diagram of the intelligent correction system for measurement deviation of karst carbon sink based on human interference, as presented in this invention. Detailed Implementation

[0023] The technical solutions described in this invention are explained below with reference to specific embodiments and accompanying drawings. The original carbon sink measurement data referred to in the embodiments refers to hydrological monitoring values, carbonate parameters, meteorological records, land use records, and carbon sink values ​​output by conventional measurement models related to carbon sink measurement within the karst watershed. The anthropogenic interference data referred to in the embodiments refers to data that can characterize human activities such as urbanization, farmland reclamation, vegetation clearing, industrial and mining development, and soil and water conservation within the karst watershed. The remote sensing image interpretation records, ground verification records, and monitoring data traceability records referred to in the embodiments serve as the image source, field source, and monitoring link source of the anthropogenic interference data, respectively. Figures 1 to 6 These are respectively used to explain the main process of the method, the construction of the interference factor library, the generation of error sample and response relationship, the correction level processing, the output of correction basis, and the system support relationship.

[0024] Example 1 Please see Figures 1 to 5 This embodiment provides an intelligent correction method for measurement deviations of karst carbon sinks based on human interference. The method takes the original carbon sink measurement data, monitoring point locations, sampling time, and human interference data from the karst watershed as input, and outputs corrected carbon sink measurement data and corresponding correction basis records. The execution process includes S1 to S5. S1 is used to obtain the data objects involved in the correction; S2 is used to construct a dynamic database of human interference factors; S3 is used to establish carbon sink measurement error samples, interference response functions, and human interference threshold ranges; S4 is used to generate corrected carbon sink measurement data based on threshold triggering relationships; and S5 is used to associate and store the corrected carbon sink measurement data with the correction basis records and output them. The above process is executed in conjunction with a server, database, and data access interface. The acquisition end, verification end, and monitoring end only serve as data sources and do not change the main processing line of the method.

[0025] S1. Acquire raw carbon sink measurement data, monitoring point locations, sampling times, and anthropogenic interference data for the karst watershed. Raw carbon sink measurement data is provided by monitoring equipment, measurement programs, or existing measurement databases within the karst watershed. This data includes at least the monitoring point number, sampling time, measurement index field, and raw carbon sink value. Monitoring point locations define the spatial allocation of the raw carbon sink measurement data within the karst watershed, while sampling time defines its temporal allocation. Anthropogenic interference data is provided jointly by remote sensing image interpretation records, ground verification records, and monitoring data tracing records. Remote sensing image interpretation records reflect land cover change boundaries and engineering activity patches; ground verification records reflect activity types and on-site impact boundaries; and monitoring data tracing records reflect the monitoring point number, sampling period, and source status related to the monitoring link.

[0026] In S1, after receiving the raw carbon sink measurement data, the server uses the monitoring point number, sampling time, and raw carbon sink value as the basic fields for subsequent matching, and establishes a correspondence between the monitoring point location and the monitoring point number. Remote sensing image interpretation records, after entering the server via the remote sensing data interface, form two types of input objects: land cover change boundaries and engineering activity patches. Ground verification records, after entering the server via the ground verification terminal or verification data interface, form two types of input objects: activity category and field impact boundary. Monitoring data tracing records, after being retrieved from the monitoring database, form two types of input objects: monitoring point number and sampling time period. Each input object retains its source identifier before entering subsequent processing; the source identifier is used to establish a correction basis record in S5.

[0027] S2, based on remote sensing image interpretation records, ground verification records, and monitoring data tracing records, classifies anthropogenic interference data into interference type, intensity, impact range, and duration, constructing a dynamic database of anthropogenic interference factors. S2 does not merely write anthropogenic activity records into the database; rather, it converts anthropogenic interference data from different sources into records of anthropogenic interference factors that can participate in matching and calculation. These records include interference type, intensity, impact range, duration, monitoring point number, sampling period, and source identifier. Interference type characterizes the category of anthropogenic activity; intensity characterizes the degree of impact of anthropogenic activity on the karst basin; impact range characterizes the spatial boundary of the anthropogenic activity; and duration characterizes the time span of consecutive occurrences of the same interference type within the sampling period.

[0028] The internal processing of S2 can be divided into S211 to S214. S211 extracts land cover change boundaries and engineering activity patches from remote sensing image interpretation records. Land cover change boundaries characterize the spatial outline of changes in land cover status, while engineering activity patches characterize the spatial occupancy of construction, mining, or remediation activities on the image. S212 extracts activity categories and field impact boundaries from ground verification records. Activity categories correspond to interference types, and field impact boundaries supplement the source of spatial boundaries in remote sensing image interpretation records. S213 extracts monitoring point numbers and sampling periods from monitoring data tracing records and maps monitoring point numbers to monitoring point locations, ensuring a unified matching object for time and spatial fields. S214 aligns the extraction results from S211 to S213 according to monitoring point locations and sampling times. When the extraction results corresponding to the same monitoring point location and the same sampling time show consistent interference indications, an artificial interference factor record containing interference type, intensity, impact range, and duration is generated and written into the artificial interference factor dynamic database.

[0029] In S2, the intensity of the effect is jointly determined by the change area corresponding to the land cover change boundary, the spatial proportion corresponding to the engineering activity patch, and the impact level corresponding to the field impact boundary. The change area comes from the land cover change boundary in the remote sensing image interpretation record, the spatial proportion comes from the spatial relationship between the engineering activity patch and the corresponding watershed unit, and the impact level comes from the records of the field impact boundary and activity category in the ground verification record. The duration is determined by the time span of the same interference type occurring consecutively within the sampling period. When writing the artificial interference factor record, the server first determines whether the change area, spatial proportion, and impact level all meet the preset recording conditions; when the change area, spatial proportion, and impact level all meet the preset recording conditions, the intensity of the effect is written into the artificial interference factor record; when any of the recording conditions of change area, spatial proportion, and impact level is not met, the corresponding interference type is set to a pending verification status so that subsequent steps can identify that the record has not yet entered the complete calculation chain.

[0030] S3 matches the original carbon sink measurement data with the dynamic database of anthropogenic interference factors according to monitoring point location and sampling time, calculates carbon sink measurement error samples, explores the nonlinear correlation between anthropogenic interference factors and carbon sink measurement error samples, and generates an interference response function and anthropogenic interference threshold interval. The inputs to S3 include the original carbon sink measurement data obtained in S1 and the anthropogenic interference factor records generated in S2. The outputs include carbon sink measurement error samples, interference response function, and anthropogenic interference threshold interval. The carbon sink measurement error samples characterize the numerical differences between interfered measurement data and reference measurement data under the same karst basin, adjacent sampling conditions, or the same monitoring conditions. The interference response function characterizes the nonlinear correspondence between anthropogenic interference factors and carbon sink measurement error samples. The anthropogenic interference threshold interval is used to determine whether the area to be corrected has entered the correction trigger state.

[0031] The carbon sequestration measurement error sample generation process in S3 can be divided into S311 to S314. S311: Retrieve the original carbon sequestration measurement data according to the monitoring point number and sampling period, and confirm that the original carbon sequestration measurement data contains fields corresponding to the monitoring point number, sampling period, and original carbon sequestration value. S312: Perform spatiotemporal matching between the original carbon sequestration measurement data and records of human interference factors. The spatiotemporal matching is determined by whether the monitoring point number falls within the affected area and whether the sampling period falls within the duration. S313: When the monitoring point number falls within the affected area and the sampling period falls within the duration, the original carbon sequestration measurement data is marked as interfered measurement data. S314: When the monitoring point number does not fall within the affected area or the sampling period does not fall within the duration, the original carbon sequestration measurement data is marked as reference measurement data, and a carbon sequestration measurement error sample is generated based on the difference between the interfered measurement data and the reference measurement data.

[0032] After generating carbon sink measurement error samples, the server uses these samples as the response object and the interference type, intensity, range, and duration as the interpretation objects. It then establishes a sample set based on the monitoring point locations and sampling times within the same karst basin. Each sample in the set includes the monitoring point number, sampling time, interference type, intensity, range, duration, and carbon sink measurement error sample. The server performs nonlinear correlation fitting on the sample set to obtain the interference response function. This nonlinear correlation fitting is not limited to a single algorithm name but is based on the correspondence between the input, response, and output objects, enabling the interference response function to receive the interference type, intensity, range, and duration and output a deviation response value.

[0033] The artificial interference threshold interval is determined based on the response change within a continuous sampling period. When the response change within a continuous sampling period meets the preset interval division conditions, the server determines the artificial interference threshold interval based on the corresponding intensity and duration. The preset interval division conditions are used to distinguish the response states corresponding to the same type of interference under different intensities and durations. Boundary values ​​are assigned to adjacent valid threshold intervals according to the criteria for entering the interval. When there are artificial interference factor records in the sample set that are pending verification, these records are not used as direct samples for generating the artificial interference threshold interval, but are retained in the database for subsequent verification.

[0034] S4: When the anthropogenic interference factors in the area to be corrected meet the anthropogenic interference threshold range, the correction level is determined according to the interference type, intensity, range of influence, and duration. The interference response function is then called to dynamically correct the deviation of the original carbon sink measurement data, generating corrected carbon sink measurement data. The inputs to S4 are the original carbon sink measurement data of the area to be corrected, the records of anthropogenic interference factors, the interference response function, and the anthropogenic interference threshold range. The output is the corrected carbon sink measurement data or the original measurement status with a reference label.

[0035] The correction level determination process in S4 can be divided into S411 to S414. S411 retrieves the records of artificial interference factors corresponding to the region to be corrected at the sampling time, extracting the interference type, intensity, range of influence, and duration. S412 matches the interference type of the region to be corrected with the applicable interference type of the interference response function. Only when the interference type matches the applicable interference type of the interference response function does it proceed to threshold judgment. S413, when both the intensity and duration fall within the artificial interference threshold range, the region to be corrected is classified into the triggered correction level. S414, when either the intensity or duration does not fall within the artificial interference threshold range, the region to be corrected is classified into the reference correction level. The triggered correction level and the reference correction level are mutually exclusive; the same region to be corrected only enters one of the correction levels at the same sampling time.

[0036] At the triggered correction level, the server uses the type, intensity, range, and duration of interference in the area to be corrected as function inputs, calls the interference response function to calculate the deviation response value, and uses this value to correct the original carbon sink measurement data, generating corrected carbon sink measurement data. The deviation response value is an intermediate result, not directly used as the final output, but rather participates in the formation of corrected carbon sink measurement data along with the original carbon sink measurement data. At the reference correction level, the server retains the original measurement state of the original carbon sink measurement data and generates a reference identifier. This identifier is used in S5 to indicate that the data has not entered the deviation response value correction path. If the record of the human-caused interference factor in the area to be corrected is in a pending verification state, the server does not call the interference response function to generate a deviation response value, but instead passes the corresponding record to the correction basis record to retain the pending verification state, thus avoiding the pending verification state directly affecting the corrected carbon sink measurement data.

[0037] S5 associates, stores, and outputs the calibrated carbon sink measurement data with the original data source, interference source, response basis, and processing records. The inputs to S5 are the calibrated carbon sink measurement data or reference identifier generated in S4, the original data source from S1, the interference source from S2, the response basis from S3, and the processing records from S4. The outputs of S5 include calibration basis records and standardized output records. The calibration basis records are used to maintain the traceability of the calibrated carbon sink measurement data, and the standardized output records are used to access subsequent retrieval stages according to the field requirements of different data tables.

[0038] The associated storage process in S5 can be divided into S511 to S514. S511 establishes a calibration basis record for the carbon sink measurement data. S512 writes the sampling time, monitoring point location, interference type, intensity, range of influence, duration, deviation response value, and calibration level of the original carbon sink measurement data into the calibration basis record. S513, when the calibrated carbon sink measurement data is generated by the trigger calibration level, writes the interference response function and the artificial interference threshold range into the calibration basis record. S514, when the calibrated carbon sink measurement data is generated by the reference calibration level, writes the reference identifier into the calibration basis record. Through S511 to S514, the calibration result, original source, interference source, response basis, and processing procedure are written into the same associated storage chain.

[0039] During the output phase of S5, the server reads the monitoring point location, sampling time, correction level, and deviation response value from the calibration basis record, and generates standardized output records according to the field requirements of the carbon sink assessment data table, carbon storage accounting data table, carbon trading pricing data table, and long-term dynamic monitoring data table. The carbon sink assessment data table receives fields related to monitoring point location, sampling time, and calibrated carbon sink measurement data; the carbon storage accounting data table receives fields related to watershed units, measurement indicators, and calibrated carbon sink measurement data; the carbon trading pricing data table receives fields related to calibrated carbon sink measurement data, correction level, and calibration basis status; and the long-term dynamic monitoring data table receives fields related to sampling time series, deviation response value, and reference identifier. When the calibration basis record lacks interference sources or response evidence, the server sets a verification identifier for the standardized output record; when the calibration basis record contains interference sources and response evidence, the server writes the standardized output record to the corresponding data table. The verification identifier, as an output status, does not change the name or source of the calibrated carbon sink measurement data; it only indicates that the standardized output record needs to be verified before subsequent calls.

[0040] The above steps S1 to S5 form a complete data processing chain from input to output. S1 defines the source of the original carbon sink measurement data and the human-caused interference data; S2 converts the human-caused interference data into searchable and matchable human-caused interference factor records; S3 establishes a response relationship between the human-caused interference factor records and the original carbon sink measurement data; S4 determines the trigger correction level or the reference correction level based on the human-caused interference threshold range; and S5 establishes a link between the corrected carbon sink measurement data, the correction basis record, and the standardized output record. The data objects, processing results, and output destinations of each step are continuously corresponding and can be verified through database records, correction levels, deviation response values, reference identifiers, and verification identifiers.

[0041] Example 2 Please see Figure 6 This embodiment provides an intelligent correction system for measurement deviations of karst carbon sinks based on human interference. The difference between this embodiment and Embodiment 1 is that Embodiment 1 focuses on the method flow, while Embodiment 2 focuses on system unit collaboration. The system provides operational support for the method of Embodiment 1 through a data access unit, an interference factor database construction unit, a response relationship analysis unit, a dynamic deviation correction unit, and a verification output unit. The system output results are consistent with the corrected carbon sink measurement data, correction basis records, and standardized output records in Embodiment 1.

[0042] The data access unit receives raw carbon sink measurement data, monitoring point locations, sampling times, remote sensing image interpretation records, ground verification records, and monitoring data traceability records. After receiving the raw carbon sink measurement data, the data access unit transmits the monitoring point number, sampling time, and raw carbon sink value to the response relationship analysis unit, and simultaneously transmits the monitoring point location and sampling time to the interference factor database building unit. After receiving the remote sensing image interpretation records, ground verification records, and monitoring data traceability records, the data access unit transmits land cover change boundaries, engineering activity patches, activity categories, field impact boundaries, monitoring point numbers, and sampling periods to the interference factor database building unit. All data output by the data access unit carries a source identifier, which is retrieved by the verification output unit when forming the correction basis record.

[0043] The interference factor database building unit forms a dynamic database of anthropogenic interference factors based on interference type, intensity, impact range, and duration. After receiving land cover change boundaries, engineering activity patches, activity categories, field impact boundaries, monitoring point numbers, and sampling periods from the data access unit, the interference factor database building unit aligns these data according to monitoring point location and sampling time. When the extraction results corresponding to the same monitoring point location and the same sampling time show consistent interference indications, the interference factor database building unit generates an anthropogenic interference factor record and writes it into the dynamic database. When any of the recording conditions—change area, spatial proportion, or impact level—is not met, the interference factor database building unit sets a pending verification status for the corresponding interference type and stores this pending verification status along with the anthropogenic interference factor record.

[0044] The response relationship analysis unit performs spatiotemporal matching between the original carbon sink measurement data and the dynamic database of anthropogenic interference factors, calculates carbon sink measurement error samples, and generates interference response functions and anthropogenic interference threshold intervals. The unit uses the order of whether the monitoring point number falls within the affected area and whether the sampling period falls within the duration as the judgment order, marking the original carbon sink measurement data as interfered measurement data or reference measurement data, and generating carbon sink measurement error samples based on the difference between the interfered measurement data and the reference measurement data. The unit then uses the carbon sink measurement error samples as the response object, and establishes a sample set using interference type, intensity, affected area, and duration as the explanatory objects. An interference response function is generated through nonlinear correlation fitting. When the response change within a continuous sampling period meets the preset interval division conditions, the unit determines the anthropogenic interference threshold interval based on the corresponding intensity and duration.

[0045] When the anthropogenic interference factors in the area to be corrected meet the anthropogenic interference threshold range, the dynamic deviation correction unit calls the interference response function according to the correction level to generate corrected carbon sink measurement data. After receiving the anthropogenic interference factor records, interference response function, and anthropogenic interference threshold range for the area to be corrected, the dynamic deviation correction unit first matches the interference type of the area to be corrected with the applicable interference type of the interference response function, and then determines whether the intensity and duration of the interference fall within the anthropogenic interference threshold range. When both the matching result and the threshold judgment are satisfied, the dynamic deviation correction unit classifies the area to be corrected into the triggered correction level, and calculates the deviation response value using the interference type, intensity, range of influence, and duration of the area to be corrected as function inputs. The original carbon sink measurement data is then corrected using the deviation response value to generate corrected carbon sink measurement data. When the intensity or duration of the interference does not fall within the anthropogenic interference threshold range, the dynamic deviation correction unit classifies the area to be corrected into the reference correction level and generates a reference identifier.

[0046] The verification output unit associates, stores, and outputs the corrected carbon sink measurement data with the correction basis. The verification output unit receives the corrected carbon sink measurement data, deviation response value, correction level, and reference identifier from the dynamic deviation correction unit, and calls upon the original data sources retained by the data access unit and the interference sources retained by the interference factor database unit to form a correction basis record. The verification output unit writes the sampling time, monitoring point location, interference type, intensity, range of influence, duration, deviation response value, and correction level into the correction basis record. When the corrected carbon sink measurement data is generated by the triggering correction level, the verification output unit writes the interference response function and the artificial interference threshold range into the correction basis record; when the corrected carbon sink measurement data is generated by the reference correction level, the verification output unit writes the reference identifier into the correction basis record. The verification output unit then generates standardized output records according to the field requirements of the carbon sink assessment data table, carbon storage accounting data table, carbon trading pricing data table, and long-term dynamic monitoring data table.

[0047] In Example 2, the units can be deployed on the same server, or they can be jointly hosted by server programs, databases, and data interfaces with data communication relationships. The data access unit serves as the input terminal, the interference factor database building unit as the artificial interference factor record generation terminal, the response relationship analysis unit as the error sample and response relationship generation terminal, the dynamic deviation correction unit as the correction processing terminal, and the verification output unit as the result storage and output terminal. The data flow between units corresponds to S1 to S5 in Example 1. The input data output by the data access unit enters the interference factor database building unit and the response relationship analysis unit. The artificial interference factor dynamic database output by the interference factor database building unit enters the response relationship analysis unit and the dynamic deviation correction unit. The interference response function and artificial interference threshold range output by the response relationship analysis unit enter the dynamic deviation correction unit. The corrected carbon sink measurement data output by the dynamic deviation correction unit enters the verification output unit. The verification output unit outputs the correction basis record and the standardized output record.

[0048] The specific processes, field states, processing order, judgment conditions, parameter sources, unit collaboration, and carrier inheritance relationships in the embodiments are used to explain the possible implementations of the present invention and should not limit the present invention to the specific embodiments listed. Without departing from the scope of the technical solutions described in this invention, any equivalent substitutions, equivalent modifications, equivalent combinations, order adjustments, module-to-module replacements, equivalent changes in field names, equivalent inheritance of the executing entity, or equivalent changes in the carrier form that can be conceived by those skilled in the art should fall within the scope of protection of this patent; however, they should not be extended to unclaimed topics, nor should the substantive correspondence of the technical objects be changed through name changes.

Claims

1. A method for intelligent correction of measurement deviations in karst carbon sinks based on human interference, characterized in that, Obtain raw carbon sink measurement data, monitoring point locations, sampling time, and human interference data for karst watersheds; Based on remote sensing image interpretation records, ground verification records, and monitoring data tracing records, human interference data are classified into interference type, intensity, scope of impact, and duration, and a dynamic database of human interference factors is constructed. The original carbon sink measurement data is matched with the dynamic database of human interference factors according to the monitoring point location and sampling time. Carbon sink measurement error samples are calculated, and the nonlinear correlation between human interference factors and carbon sink measurement error samples is explored to generate interference response function and human interference threshold range. When the human interference factor in the area to be corrected meets the human interference threshold range, the correction level is determined according to the type of interference, intensity of action, range of influence and duration of duration. The interference response function is called to perform dynamic deviation correction on the original carbon sink measurement data and generate corrected carbon sink measurement data. The calibrated carbon sink measurement data is associated with, stored, and output as records of the original data source, interference source, response basis, and processing procedure. The process of calculating carbon sink measurement error samples includes: retrieving original carbon sink measurement data according to the monitoring point number and sampling period; performing spatiotemporal matching of the original carbon sink measurement data with the recorded human interference factors; when the monitoring point number falls within the influence range and the sampling period falls within the duration, the original carbon sink measurement data is marked as interfered measurement data; when the monitoring point number does not fall within the influence range or the sampling period does not fall within the duration, the original carbon sink measurement data is marked as reference measurement data; and generating carbon sink measurement error samples based on the difference between the interfered measurement data and the reference measurement data. The process of generating the interference response function and the artificial interference threshold interval includes: taking the carbon sink measurement error sample as the response object, taking the interference type, intensity, range of influence and duration as the interpretation object, establishing a sample set according to the monitoring point location and sampling time in the same karst basin, performing nonlinear correlation fitting on the sample set to obtain the interference response function; when the response change in a continuous sampling period meets the preset interval division condition, determining the artificial interference threshold interval according to the corresponding intensity and duration. After obtaining the interference response function and the artificial interference threshold range, the process of determining the correction level of the region to be corrected includes: retrieving the artificial interference factor record corresponding to the region to be corrected at the sampling time, matching the interference type of the region to be corrected with the applicable interference type of the interference response function, and classifying the region to be corrected into the trigger correction level when both the intensity and duration fall within the artificial interference threshold range, and classifying the region to be corrected into the reference correction level when neither the intensity nor the duration falls within the artificial interference threshold range. The process of generating calibrated carbon sink measurement data by calling the interference response function includes: when the area to be calibrated is included in the triggered calibration level, the interference type, intensity, range of influence and duration of the area to be calibrated are used as function inputs to calculate the deviation response value, and the original carbon sink measurement data is corrected with the deviation response value to generate calibrated carbon sink measurement data; when the area to be calibrated is included in the reference calibration level, the original measurement state of the original carbon sink measurement data is retained and a reference identifier is generated.

2. The intelligent correction method for measurement deviation of karst carbon sink based on human interference according to claim 1, characterized in that, The process of constructing the dynamic database of anthropogenic interference factors includes: extracting land cover change boundaries and engineering activity patches from the remote sensing image interpretation records; extracting activity categories and field impact boundaries from the ground verification records; extracting monitoring point numbers and sampling periods from the monitoring data tracing records; aligning the extraction results according to the monitoring point location and sampling time; when the extraction results corresponding to the same monitoring point location and the same sampling time have consistent interference directions, generating anthropogenic interference factor records containing interference type, intensity, range of influence, and duration; and writing the anthropogenic interference factor records into the dynamic database of anthropogenic interference factors.

3. The intelligent correction method for measurement deviation of karst carbon sinks based on human interference according to claim 2, characterized in that, The intensity of the human-caused interference factor record is determined by the change area corresponding to the land cover change boundary, the spatial proportion corresponding to the engineering activity patch, and the impact level corresponding to the on-site impact boundary. The duration is determined by the time span of the same interference type appearing continuously within the sampling period. When the change area, spatial proportion, and impact level all meet the preset recording conditions, the intensity of the interference factor is written into the human-caused interference factor record. When any recording condition is not met, the corresponding interference type is set to a pending verification status.

4. The intelligent correction method for measurement deviation of karst carbon sink based on human interference according to claim 1, characterized in that, The process of associating and storing calibrated carbon sink measurement data with the original data source, interference source, response basis, and processing record includes: establishing a calibration basis record for the calibrated carbon sink measurement data; writing the sampling time, monitoring point location, interference type, intensity, range of influence, duration, deviation response value, and calibration level of the original carbon sink measurement data into the calibration basis record; when the calibrated carbon sink measurement data is generated by the trigger calibration level, writing the interference response function and the human interference threshold range into the calibration basis record; and when the calibrated carbon sink measurement data is generated by the reference calibration level, writing the reference identifier into the calibration basis record.

5. The intelligent correction method for measurement deviation of karst carbon sink based on human interference according to claim 4, characterized in that, The process of outputting the corrected carbon sink measurement data includes: reading the monitoring point location, sampling time, correction level, and deviation response value from the correction basis record; generating standardized output records according to the field requirements of the carbon sink assessment data table, carbon storage accounting data table, carbon trading pricing data table, and long-term dynamic monitoring data table; setting a verification flag for the standardized output record when the correction basis record lacks interference sources or response evidence; and writing the standardized output record into the corresponding data table when the correction basis record contains interference sources and response evidence.

6. A smart correction system for measurement deviations in karst carbon sinks based on human interference, used to support the smart correction method for measurement deviations according to any one of claims 1 to 5, characterized in that, It includes a data access unit, an interference factor database construction unit, a response relationship analysis unit, a dynamic deviation correction unit, and a verification output unit; The data access unit receives raw carbon sink measurement data, monitoring point locations, sampling times, remote sensing image interpretation records, ground verification records, and monitoring data traceability records; The interference factor database building unit forms a dynamic database of artificial interference factors based on the type, intensity, scope, and duration of interference. The response relationship analysis unit performs spatiotemporal matching between the original carbon sink measurement data and the dynamic database of human interference factors, calculates carbon sink measurement error samples, and generates interference response functions and human interference threshold ranges. When the human interference factor in the area to be corrected meets the human interference threshold range, the dynamic deviation correction unit calls the interference response function according to the correction level to generate corrected carbon sink measurement data. The verification output unit will associate, store, and output the corrected carbon sink measurement data with the correction basis.

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