93 results about "Carbon stock" patented technology

The present invention relates to the technical field of dynamic carbon sink accounting, and specifically relates to a dynamic carbon sink accounting system based on multi-modal AI remote sensing monitoring and blockchain-based evidence storage. The system collects optical remote sensing, radar, photosynthetically active radiation and meteorological data, performs unified spatiotemporal calibration on the data, and then fuses the calibrated data by means of a cross-modal attention mechanism, so as to generate multi-modal feature vectors, and inputs same into a TCN model for carbon stock and trend prediction. A prediction result and metadata are uploaded to a blockchain by means of smart contracts, so as to generate a carbon sink NFT including a geographic fence and a confidence level, thereby realizing trusted evidence storage. A residual mapping function is established in view of on-chain historical data, so as to dynamically optimize the model, and improve the accounting accuracy. The system improves the fusion capability and prediction accuracy, and enhances the credibility and transparency of carbon asset management and transactions.

The invention discloses a coastal culture pond expansion recognition and mangrove forest ecological occupation and supplement balance evaluation method, and belongs to the technical field of environment remote sensing monitoring and ecological evaluation. Aiming at the problems that a mangrove forest ecological system is damaged by expansion of a coastal culture pond and a dynamic monitoring and quantitative evaluation mechanism is lacked, the evaluation method is provided and comprises the following steps: preprocessing a multi-temporal satellite remote sensing image; using a convolutional neural network computer model to supervise, classify and distinguish culture ponds, mangrove forests and other land types; extracting boundaries of the two-time-phase culture pond and identifying a newly-added area; in combination with the mangrove forest distribution map, obtaining an occupied area through spatial overlay analysis; establishing a biomass regression model based on the vegetation index value of the infringed area to estimate the biomass per unit area, and hierarchically calculating the carbon reserve loss amount; and calculating a compensation area according to the carbon loss amount and the unit carbon reserve of the mature mangrove forest in the target area, and generating an occupation and compensation balance scheme in combination with unutilized mud flat spatial distribution. The method is used for dynamic monitoring, accurate quantification and scientific compensation of mangrove forest ecological loss.

The invention discloses a forest land ecosystem carbon reserve accounting method and system, and the method comprises the steps: obtaining and screening feature variables, such as optical remote sensing data, vegetation indexes, texture factors, satellite-borne laser radar feature parameters, so as to determine features having the most influence on a target variable, and removing redundant and irrelevant variables; the method comprises the following steps of: screening characteristic variables, reserving variables which contribute to the model prediction effect, improving the precision and stability of the model, constructing a canopy height inversion model by adopting a random forest method based on the screened characteristic variables, realizing accurate estimation of the canopy height, and finally calculating the biomass of vegetation of the forest ecological system by using a different-speed growth equation. And finally, summarizing the biomass of the vegetation of the forest ecological system to obtain the total biomass of the vegetation, and multiplying the total biomass of the vegetation by the carbon-containing coefficient to obtain the vegetation carbon reserve of the forest ecological system, so that wide-area and efficient forest parameter monitoring is realized, the monitoring cost is reduced, the environmental adaptability is improved, and the problems of data continuity and standardization are solved.

The invention provides a blue carbon market adaptive accounting method based on multi-source data and Bayesian updating, and belongs to the technical field of natural resource planning and ecological management. The method comprises the following steps: firstly, constructing a standardized multi-source fusion data set through a systematic process, and then preprocessing collected data to generate a standardized blue carbon multi-source fusion data set; then, through a Bayesian-based carbon reserve estimation model, outputting a monitoring point carbon reserve prior value, fusing a monitoring point carbon reserve mean value with a spatial prior value, and updating monitoring point carbon reserve distribution; and finally, constructing a carbon credit risk index system, calculating risk indexes of the plot layer and the region layer, updating a plot layer carbon reserve mean value by using the updated monitoring point carbon reserve distribution, and generating a blue carbon project reference transaction price according to the carbon reserve mean value and the risk indexes. According to the invention, a full-chain blue carbon intelligent accounting system is constructed, and interdisciplinary fusion of an ecological model, deep learning and a carbon market mechanism is realized.

The invention discloses a multi-scenario land utilization carbon reserve simulation method based on combination of deep learning and a PLUS-InVEST model. The method comprises the following steps: collecting and preprocessing historical land utilization, natural environment and social economic data; analyzing land utilization change characteristics; optimizing an LEAS module of the PLUS model by using a deep neural network, excavating a nonlinear relationship between land utilization expansion and driving factors, and generating an expansion probability graph; configuring a neighborhood weight and a transfer matrix of the CARS module; predicting future land utilization requirements under different scenes by adopting a long-short-term memory neural network; inputting the demand into a CARS module, and simulating and generating a future land utilization space pattern under multiple scenes in combination with differential constraint conditions; based on the InVEST model carbon reserve module and the carbon density data, calculating, comparing and analyzing the carbon reserve of each scene; and outputting a result, carrying out precision verification, and proposing a land utilization planning and carbon regulation strategy. According to the method, the land utilization simulation precision and the carbon reserve evaluation scientificity are improved, and decision support is provided for regional low-carbon land utilization.

The invention relates to the technical field of environmental science and engineering, in particular to a method for accounting water and soil conservation small watershed carbon sink. The method for accounting the water and soil conservation small watershed carbon sink comprises the steps that a small watershed area is selected; obtaining parameter data of the small watershed area based on the selected small watershed area; calculating a reference line carbon reserve CBSL, t and a project scene carbon sink CPROJ, t after the small watershed region is implemented for t years; and based on the reference line carbon reserve CBSL, t and the project scene carbon sink CPROJ, t of the small watershed region after t years after the small watershed region is implemented, the carbon sink CDRt of the small watershed region after t years after the small watershed region is implemented is obtained by combining net carbon sink accounting, the small watershed region and related parameter data are selected, a calculation formula is adopted to calculate the reference line carbon reserve CBSL of the small watershed region after t years after the small watershed region is implemented, and the carbon sink CDRt of the small watershed region after t years after the small watershed region is implemented is obtained. According to the method, the accurate carbon sink amount CDRt is finally obtained through calculation of the project scene carbon sink amount CPROJ, t and the project scene carbon sink amount CPROJ, t, the vacancy in the prior art is made up, and the practicability is high.

The invention relates to the technical field of data measurement and calculation, in particular to an ecological system carbon source sink rapid calculation method for a mining area scale. The method comprises the following steps: acquiring mining area remote sensing image data, ground actual measurement data and mining area mining activity records, and constructing a multi-source mining area basic data set; performing spatial registration and time alignment on the multi-source mining area basic data set to obtain an aligned multi-source fusion data set; based on the aligned multi-source fusion data set, mine occupied map spots are identified, land utilization type information of the map spots is extracted, a land utilization type data set is formed, and a carbon library classification data set is generated in combination with mining area carbon library type definition; therefore, by integrating multi-source data, optimizing space and time alignment and refining the carbon reserve calculation process, the problems of data dispersion, inaccurate calculation and the like in a traditional method are solved, and the scientificity and reliability of carbon source sink measurement and calculation of the mining area ecosystem are improved.

The invention discloses a carbon source and sink accounting method based on flux observation, an ecological system carbon reserve accounting system and a flux observation carbon source and sink accounting system are established, and the ecological system carbon reserve accounting system obtains carbon reserves of plants, soil, water and ground mud based on a sample point investigation method to estimate the carbon reserves of the ecological system. Estimating regional carbon reserves in combination with remote sensing survey; the flux observation carbon source sink accounting system is based on the constructed wetland carbon sink monitoring system and monitors data in real time; regional ecological system carbon reserve dynamic accounting is carried out by combining sample plot investigation with a carbon sink model and a remote sensing image technology, compared with the prior art, long-term fixed observation sample plots are set from multiple angles of lake wetland water, soil and gas generation, and Hongze lake wetland carbon sink observation data acquisition is carried out; and carrying out parameter adjustment and correction by utilizing a modern technical means and a large model technology, carrying out Hongze lake carbon sink model construction, and realizing Hongze lake carbon sink value accounting.

The invention relates to the technical field of land data planning, and discloses a reasonable land planning system based on machine learning carbon storage, and the system comprises a multi-source data fusion module, a carbon storage prediction module, a three-generation coordination discrimination module, a land use intelligent optimization module, a scene interaction deduction module, and a planning result generation module. By integrating data such as standardized land utilization and carbon density, a machine learning model is utilized to predict the dynamic state of the carbon density in real time, and the functional coordination degree of the three plants is quantitatively evaluated; and then, by taking the improvement of the carbon reserves and the coordination of the three plants as targets, carrying out spatial simulation and iterative optimization in combination with multi-objective optimization and a cellular automaton, comparing different policy carbon sink effects through scene deduction, and finally outputting an optimization scheme, thereby realizing the real-time closed loop of evaluation and optimization, and synergistically improving the carbon sink benefits and the three-plant function.

The invention relates to the technical field of agricultural remote sensing and ecological monitoring, in particular to a dendrocalamus brandisii biomass region estimation method combining remote sensing data and a heterosexual model. The method mainly solves the problem of insufficient estimation precision of dendrocalamus brandisii biomass caused by terrain interference and phenological period change in the prior art. According to the method, a multi-scale feature data set is generated through collaborative preprocessing of multi-source remote sensing data; training a random forest biomass prediction model based on ground measured data; performing phenological phase identification by using a time sequence satellite image, and establishing a phenological period self-adaptive parameter lookup table; performing terrain invariant feature conversion by adopting a conditional generative adversarial network to eliminate terrain interference; the phenological period parameters and the standardized features are fused, and a high-precision biomass spatial distribution diagram is output through a dynamic weighted fusion reasoning algorithm; and finally, automatic conversion and visual monitoring from biomass to carbon reserves are realized through a carbon sink accounting module.

The invention discloses an ecological and economic multi-target collaborative decision-making system and method for comprehensive treatment engineering in the technical field of ecological environment treatment, and the system comprises a data collection module which is used for obtaining the historical data of carbon reserves and undetermined influence factors; the data screening module is used for acquiring model influence factors and dividing the model influence factors into governance regulation factors and non-regulation factors; the reference analysis module is used for obtaining a governance regulation factor reference value based on the carbon reserves and the species diversity index; the adjustment amplitude analysis module is used for setting the adjustment amplitude and determining the numerical change of a non-adjustment factor; the model construction module is used for obtaining a carbon reserve prediction model; and the carbon reserve assessment decision module is used for carbon reserve prediction and adjustment amplitude determination. According to the method, the ecological target and the economic target are jointly used as the basis of reference definition, the regulation and control scheme is generated based on the basis, and decision support with both ecological and economic benefits is provided for treatment engineering through modular cooperative operation.

The invention discloses a dynamic monitoring and accounting system for organic carbon reserves of lake and reservoir sediments, belongs to the technical field of carbon cycle monitoring, and aims to solve the problems of spatial-temporal resolution contradiction and insufficient multi-source data fusion caused by a single data source in a traditional method. A space-time continuous fusion data product is generated in combination with an adaptive fusion algorithm, the system comprises a multi-source data acquisition module, a preprocessing module, an uncertainty quantification module, a fusion processing module and a verification feedback module, deep fusion of space-based remote sensing, foundation in-situ and experimental analysis data is achieved, and through independent actual measurement data verification and parameter feedback optimization, the space-time continuous fusion data product is obtained. And the system forms a precision improvement closed loop, so that the stability and accuracy of long-term operation are ensured.

The invention discloses a mining area ecological restoration effect evaluation method coupling ecosystem service value and carbon reserve, which comprises the following steps: step (1), carrying out localization adjustment on equivalent values of various land classes in combination with actual land utilization characteristics of a mining area; performing ecological system service value evaluation in the mining area ecological restoration process by adopting an equivalent factor method; step (2), adopting a carbon reserve module of the InVEST model to measure and calculate the carbon reserve of the mining area; and (3) on the basis of the results of the step (1) and the step (2), calculating a correlation coefficient between the carbon reserves and the ecosystem service value, measuring a tradeoff cooperative relationship between the ecosystem service value and the carbon reserves according to the positive, negative and absolute values of the correlation coefficient, and judging the significance of the tradeoff cooperative relationship between the ecosystem service value and the carbon reserves through T test. The method has the following beneficial effects that the limitation of single index analysis in traditional evaluation is broken through, and a new method is provided for scientifically quantifying comprehensive benefits of ecological restoration of the mining area and optimizing a restoration technology path.

This invention discloses a method for predicting soil organic carbon (SOC) content based on UAV multispectral data, belonging to the field of soil remote sensing monitoring technology. The method constructs a multi-source heterogeneous fusion dataset by collecting soil visible-near-infrared spectral data and environmental data such as topography and climate. The SG-FD algorithm is used to preprocess the spectra to enhance feature signals. A dynamic deep separable convolutional network (DS-DCNN) is constructed, and a scale pyramid dynamic weight module is used to adaptively extract key spectral bands. Environmental driving factors are deeply fused to achieve high-precision prediction of forest soil SOC content. Finally, the SHAP framework is introduced to analyze the contribution of each factor. This invention overcomes the limitations of traditional single-spectral modeling and effectively solves the problems of low SOC inversion accuracy and poor model interpretability in complex forest environments, providing support for forest carbon storage estimation.

The invention discloses a knowledge-guided and process-driven forest soil layered carbon sink simulation system, which comprises the following steps of: screening a continuous and complete soil profile according to forest soil organic carbon layered observation data; optimizing process model parameters of the terrestrial ecosystem at each measuring point by adopting a Bayesian data assimilation technology; processing the current vegetation terrain soil attribute data to obtain multi-modal standardized data as an input variable of a random forest model, performing heterogeneity learning and scale expansion on optimization parameters by using the random forest model, and simulating the organic carbon reserve of the current layered soil based on steady-state hypothesis and external driving data of a lattice point scale; and based on an instantaneous hypothesis, generating a future forest soil layered carbon sink simulation result by taking scale extension parameters and future external driving data as driving and combining current layered soil organic carbon reserves, so as to realize accurate, digital and intelligent monitoring and evaluation of the forest soil carbon sink capacity.

The invention discloses a haloxylon ammodendron forest biomass estimation method based on unmanned aerial vehicle multi-source data collaborative inversion, and relates to the technical field of environment remote sensing and information, and the method comprises the steps: obtaining a training sample set; obtaining unmanned aerial vehicle multispectral image data and unmanned aerial vehicle laser radar point cloud data of each training sample plot; extracting a first type of feature set comprising vegetation index features and texture features; extracting a second type of feature set comprising a height feature and a density feature; fusing the two types of feature sets to form a joint feature set; screening the joint feature set to construct a target feature subset; and carrying out model training by utilizing a machine learning algorithm to obtain an above-ground biomass estimation model. According to the method, the technical problem that the existing single remote sensing data source is low in precision in estimating the biomass on the desert sparse haloxylon ammodendron forest land is solved, high-precision and automatic estimation from the sample land to the regional scale is realized, and technical support is provided for accurate accounting of the desert carbon reserve in the arid region.

The invention provides a coupling MCCA-inVEST model-based carbon reserve prediction method, and relates to the technical field of mixed land utilization prediction and carbon cycling, the method comprises the steps of obtaining influence factor data corresponding to a to-be-evaluated mixed land, and generating MCCA training data; according to the influence factor data and the MCCA training data, constructing an MCCA model, and based on the MCCA model and a Markov chain, obtaining a land type prediction demand in a preset scene; constructing a land utilization conversion rule based on a random forest model and simulating different types of mixed land spatial distribution; taking the secondary land utilization classification system as a target classification, and performing spatial superposition on the Chinese carbon density data set and the vegetation type distribution data to obtain secondary land utilization carbon density parameters; and inputting mixed land spatial distribution and secondary land utilization carbon density parameters into an inVEST model to obtain a regional carbon reserve prediction result and a carbon sink capacity distribution result. According to the invention, the regional applicability and precision of carbon reserve prediction can be improved.

The application discloses a kind of urban vegetation carbon storage remote sensing estimation methods of mixed Swin Transformer conditional generation adversarial network, including remote sensing image data preprocessing;CNN local feature is constructed and CNN local feature branch is extracted, and Swin Transformer global feature is constructed and Swin Transformer global feature branch is extracted;Multi-scale discriminator is constructed and three-stage training strategy is used, and the final carbon storage prediction result and uncertainty are output.The data input of the application uses open source remote sensing image, improves the estimation accuracy by hybrid network architecture, simultaneously, the uncertainty information of estimated is output synchronously by the probability modeling module built in the model, fills the short board that only " single point numerical result " is provided in prior art, improves the reliability and practicality of model, provides support for urban ecological planning and carbon sink transaction.

The application provides a kind of dynamic evaluation method for carbon storage of bivalve, which comprises the following steps: monitoring and collecting environmental data of typical aquaculture sea area, calculating a functional function, carrying out on-site flow experiment to determine physiological and biological parameters of bivalve, converting to obtain carbon parameters, based on dynamic energy budget theory, combining multiple environmental factors and carbon parameters to construct a carbon budget model integrating the whole physiological process, and finally simulating the carbon storage flux of bivalve in the growth cycle. The application solves the problems of static evaluation of bivalve carbon sink, insufficient consideration of environmental factor fluctuation, incomplete description of key physiological processes and insufficient precision of carbon budget quantification, and realizes the daily dynamic and accurate evaluation of bivalve carbon storage, quantifies the carbon storage contribution of shell formation and biogenic sedimentation.

The invention is suitable for the field of carbon emission, and provides a carbon footprint tracking accounting method and system for a low-carbon park, and the method comprises the following steps: constructing a park carbon flow knowledge graph with physical assets as nodes and carbon flow paths as edges, the physical assets in the park corresponding to unique digital identities, and the physical assets in the park corresponding to unique digital identities; configuring a carbon emission or carbon transfer calculation model for each physical asset; collecting time sequence operation data uploaded by the sensor and material transfer data uploaded by the logistics node, and associating the time sequence operation data and the material transfer data to the corresponding asset node according to the digital identity; inputting the data into a rule engine, and analyzing the data into an atomic carbon flow event; and activating related nodes in the carbon flow knowledge graph, and calling the calculation model to obtain carbon inflow, carbon outflow or carbon stock change of the nodes. Real-time operation data and logistics data are analyzed into a standardized atomic carbon flow event through a rule engine, automatic calling of a node calculation model in a knowledge graph is driven, and accounting is more efficient.

The present application relates to the field of agricultural ecological environment management and carbon sink monitoring technology, and more particularly to a tea tree lossless tea garden carbon fixation and sink increase method, comprising: pyrolyzing agricultural waste to obtain biochar and making the biochar into a specific standard biochar-based fertilizer; determining tea garden soil organic matter, cation exchange capacity and soil bulk density, calculating soil quality comprehensive coefficient by using improved Nemerow comprehensive index method and dividing soil quality grades according to the soil quality comprehensive coefficient; applying the biochar-based fertilizer in a differentiated application amount according to the soil quality grades; determining tea tree aboveground biomass after fertilization and calculating tea tree carbon storage according to a corresponding carbon storage model selected according to the age of the tea tree; simultaneously determining soil parameters to calculate tea garden soil carbon storage; and finally taking the tea tree carbon storage and the soil carbon storage as the total carbon sink of the tea garden. The present application realizes systematic, accurate and lossless monitoring of tea garden carbon fixation and sink increase technology.

The invention belongs to the technical field of forest carbon sink metering and monitoring, and particularly discloses a forestry carbon sink dynamic baseline investigation method based on a historical sample plot. The method disclosed by the invention comprises the following steps: collecting historical sample plot data in different periods, and integrating the historical sample plot data to a data platform for storage management; a project sample plot is arranged in the carbon sink project area and investigated, and project sample plot data is obtained; performing spatial analysis by using a geographic information system, and selecting a historical sample plot of which the relative error of tree species composition and stand density does not exceed 15% from a data platform as a contrast sample plot; fitting a growth curve of carbon reserves along with forest age or time by adopting a statistical model based on historical data of a contrast sample plot as a dynamic baseline; and calculating a difference value between the project carbon reserves and the dynamic baseline carbon reserves as the carbon sink quantity. According to the method, historical sample plot data can be fully utilized, the cost is reduced, and the accuracy, flexibility and adaptability of carbon sink calculation are improved. The method is suitable for forest carbon sink metering and carbon sink project monitoring.

The present disclosure relates to a method for determining carbon storage information, a storage medium, an electronic device, and a program product. The method includes: obtaining reference images of a target area before and after the construction of a hydropower project; determining land use change information within the target area based on the reference images; determining the carbon density of different types of land under the land use change information; and determining the carbon storage change information within the target area under the influence of the hydropower project according to the land use change information and the carbon density. In this way, the accuracy of the obtained carbon storage change information can be ensured, the impact of the hydropower project on the carbon storage change in the target area can be accurately quantified, and thus strong support can be provided for environmental protection and sustainable development.

The invention provides a drainage basin green carbon library construction method and device based on evaluation-feedback regulation and a storage medium, and relates to the technical field of green carbon libraries, and the method comprises the steps: obtaining a core carbon data set under a drainage basin scale; simulating a net carbon sink estimated value through the ecosystem model of the process to obtain a net carbon reserve variation, and correcting an estimated value of the productivity of the net ecosystem according to a comparison result of the net carbon sink estimated value and the net carbon reserve variation to obtain a corrected watershed carbon sink potential; dividing the drainage basin into a plurality of green carbon reservoir functional areas based on the division standards of carbon reserves, carbon sink potential and carbon emission, and obtaining green carbon reservoir construction measures for different functional areas; and after the measures are implemented, obtaining drainage basin net ecosystem carbon balance trend evaluation data of each functional area, obtaining regulation and control feedback of each carbon library construction measure based on the change trend of the data, and further adjusting the carbon library construction measures. By adopting the green carbon library construction method provided by the invention, a feasible method can be provided for systematic construction of the green carbon library.

The utility model relates to the technical field of carbon reserve detection, and discloses a mounting structure of an underground carbon reserve detector, which comprises a machine body, a vibration mechanism is arranged at the top of the machine body, support plates are fixedly connected to two sides of the bottom of the machine body, and a support mechanism is arranged outside the two support plates. Two vertical plates are fixedly connected to the bottom of the machine body, a cleaning mechanism is arranged on the adjacent sides of the two vertical plates, the supporting mechanism comprises two sliding blocks, the exteriors of the two sliding blocks are slidably connected to the exteriors of the supporting plates, and a plurality of sliding grooves are formed in the exteriors of the two supporting plates; the exteriors of the two sliding blocks are slidably connected to the interiors of the sliding grooves. According to the utility model, the flexible height adjustment of the fixing block ensures that the detector is stably supported in a complex terrain, so that the mounting and dismounting efficiency of the detector is remarkably improved, the device can be quickly stabilized and supported, and shaking during use is prevented.

The application relates to the technical field of forest resource monitoring, in particular to a forest carbon storage calculation system and method, which comprises the following steps: obtaining target data corresponding to a target forest; obtaining stand characteristics, climate characteristics and external influence characteristics corresponding to the target forest based on the target data; obtaining forest types, stand densities, stand age groups and soil characteristics based on the stand characteristics; obtaining vegetation carbon storage based on the forest types and the stand densities; obtaining soil carbon storage based on the soil characteristics and the stand age groups; obtaining a carbon storage calibration coefficient based on the climate characteristics and the external influence characteristics; and obtaining forest carbon storage based on the vegetation carbon storage, the soil carbon storage and the carbon storage calibration coefficient. The application helps to improve the calculation accuracy of carbon storage.

The invention discloses a baseline-based natural river and lake wetland carbon sink accounting method and system. The method relates to the technical field of wetland carbon sink accounting, and comprises the following steps: acquiring greenhouse gas flux and hydrodynamic characteristic data in a non-submerged plant baseline state, and calculating a reference scene emission sum; acquiring underwater acoustic volume and water surface optical attenuation data of a water area, performing fusion decoupling on the acoustic volume data by taking the optical attenuation data as a compensation parameter, and calculating living body biomass carbon reserves in a project scene; extracting molecular marker characteristic data in the bottom mud sediment, stripping exogenous carbon interference by using a mixed traceability model, and calculating the net increment of authigenic organic carbon; based on the carbon reserves and the net increment, the baseline scene emission amount avoided relative to the non-submerged plant baseline state is included, the boundary carbon leakage amount is deducted, and the net extra carbon sink amount is obtained through calculation. According to the invention, high precision and verification settlement of the carbon sink amount of the complex degraded water body are realized.

The invention discloses a Qinghai-Tibet Plateau soil carbon sequestration monitoring method based on a capacitance sensor array, and belongs to the field of soil carbon sequestration monitoring, and the method comprises the steps: deploying a sensor array to collect capacitance signals, and eliminating noise and adapting to the characteristics of a frozen soil alternating region in combination with a time domain filtering and adaptive adjustment technology; identifying moisture and mineral interference types by using a support vector machine, and performing signal correction by fusing multi-point data through Kalman filtering; extracting a carbon quantity change feature vector based on the correction signal, and integrating time sequence information to dynamically capture a change trend; adjusting and judging the fluctuation trend of the carbon reserves through the parameters of the mapping model, and finally generating a carbon sequestration monitoring report and a carbon reserve change index which are fused with the deviation correction result. According to the invention, the problems of serious signal interference and insufficient measurement precision in a complex environment are effectively solved, and the accuracy and reliability of soil carbon sequestration monitoring are remarkably improved.

The invention discloses a method for measuring carbon reserve of celery more accurately and simply, and belongs to the technical field of agricultural ecological carbon sink measurement. The method comprises the following steps: firstly, collecting a celery sample in a quadrat, measuring plant height, stem diameter and relative chlorophyll content (SPAD value), then obtaining the fresh weight of an overground part through destructive sampling, and constructing a three-parameter fresh weight prediction model containing H, Dand SPAD by utilizing multiple regression; secondly, performing non-destructive field measurement in a to-be-measured area to obtain plant heights, stem diameters and SPAD values of a large number of samples, and substituting the plant heights, the stem diameters and the SPAD values into the model to calculate the predicted fresh weight of a single plant; and finally, combining the planting density and the carbon content conversion coefficient to calculate the carbon reserve of the celery in unit area. According to the method, the defects that a traditional drying method is high in destructiveness and long in period are overcome, the model prediction precision is remarkably improved by introducing SPAD physiological indexes, rapid, in-situ and low-cost measurement of the celery carbon reserves is achieved, the relative error can be controlled within 5%, and the method is suitable for accurate accounting of farmland carbon sequestration.

The invention relates to the technical field of forestry monitoring, in particular to a forestry carbon sink dynamic monitoring method and system based on multi-source image data, and the method comprises the steps: collecting multi-source data to form a multi-source data set; inverting vegetation biomass and carbon density, initial reserve of organic carbon in surface soil and annual input of litter; calculating the decomposition rate and residual quantity of the litter according to the meteorological data; based on the soil initial carbon reserve, the litter input quantity and the microbial respiratory capacity, calculating the soil carbon library variation; integrating the dynamic process of the carbon library, and calculating the vegetation carbon variation and the total carbon sequestration amount per month; repeating the steps S1 to S4 periodically, updating data and parameters, and outputting a periodic carbon sequestration amount; and accumulating data to generate an annual carbon sink dynamic curve and a spatial distribution map. The dynamic carbon sequestration process is completely reflected, and the deviation with the actual carbon sequestration capacity is eliminated.