134 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 an intelligent measurement and calculation method and system for forest carbon reserves, and relates to the technical field of carbon reserve measurement and calculation, and the system obtains a forest electronic distribution diagram through a GIS technology and surveying and mapping data, collects various carbon reserve related data, and then carries out the correction and denoising of the collected data through a FLAASH algorithm and other preprocessing technologies; the AI sampling optimization model extracts forest features based on a convolutional neural network CNN, and dynamically adjusts a sampling area; secondary acquisition is carried out, data preprocessing is carried out, the total carbon reserve of the forest is estimated by calculating the carbon reserve of each grid, and the forest succession stage, the carbon sink change and the ecological carbon cycle are further analyzed; and finally, in combination with the dynamic influence coefficient of the carbon reserves and a preset threshold value Q, judging the change trend of the carbon reserves, triggering early warning and giving a coping strategy.

The invention discloses a forest carbon reserve and carbon sink monitoring and evaluating method based on a multi-source remote sensing technology. The method comprises the following steps: multi-source remote sensing data acquisition: respectively acquiring optical remote sensing data and radar remote sensing data; tree species classification and identification: carrying out tree species classification on the forest in the research area to realize tree species scale space distribution information extraction; for different tree species, biomass model parameters obtained through field investigation are combined, a biomass estimation model based on the tree species is established, model input parameters are biomass model parameters, and vegetation biomass is output; calculating the carbon reserve: calculating the vegetation carbon reserve by utilizing the inverted vegetation biomass and combining the carbon content coefficients of different tree species; estimating the soil carbon reserve, and finally obtaining the total carbon reserve of the forest ecosystem: calculating the carbon reserve variation of the forest ecosystem at different time points based on the multi-source remote sensing data of the long-term sequence. According to the invention, large-range, high-precision and continuous forest carbon reserve and carbon sink monitoring and evaluation considering tree species difference is realized.

The invention relates to the technical field of carbon sink calculation, in particular to a forestry carbon sink calculation model, a forestry carbon credit calculation method and a storage medium. The model comprises an overground biological carbon sink amount estimation module used for calculating overground biological carbon sink data of a target area, an underground soil carbon sink amount estimation module used for calculating soil carbon sink data of the target area, and a litter carbon reserve estimation module used for calculating litter carbon sink data of the target area. The combined loss calculation module is used for calculating carbon loss data; and the final carbon sink total quantity fusion module is used for calculating the carbon sink quantity according to the aboveground biological carbon sink data, the soil carbon sink data, the litter carbon sink data and the carbon loss data. A forestry carbon sink calculation model based on multiple dimensions is established through multiple types of carbon sink estimation modules, and the problem that the requirement for rapid authentication of the global carbon market cannot be met due to high manual dependency is solved; the problems of low calculation precision, high cost and the like caused by insufficient model dynamics, single model calculation dimension and the like are solved.

The invention provides a single tree segmentation-biological parameter estimation method based on a vehicle-mounted LiDAR point cloud, and belongs to the technical field of urban landscaping intelligent monitoring. The point cloud individual tree segmentation algorithm based on tree geometric feature constraint is designed for solving the problem that individual tree segmentation is difficult due to crown overlapping in an urban scene, and the method takes a tree geometric structure as a constraint, combines point cloud reflection intensity information, a clustering algorithm, a main direction index and other means, and obtains the individual tree segmentation algorithm based on the tree geometric feature constraint. And accurate extraction of trunks and crowns in the scene point cloud is realized. Aiming at the problems of high feature redundancy, poor model interpretability and the like in an existing estimation method, a random forest model is taken as a basis, an adaptive feature selection algorithm is introduced to improve variable screening efficiency, hyper-parameters are dynamically adjusted by utilizing pigeon inspired optimization, and generalization and stability of the model are enhanced; an estimation model used for estimating biological parameters such as leaf area index, biomass and carbon reserve is designed.

The invention relates to the technical field of mine ecological restoration and carbon reserve estimation, in particular to a coal mining subsidence area ecological system carbon reserve estimation method and system.The method comprises the steps that S1, a coal mining subsidence area is divided according to land utilization types, and the range and area of each land utilization type are determined; s2, dividing the coal mining subsidence area according to a space state, and forming a land utilization grid table with a unique code with each land utilization type; s3, obtaining an initial carbon density parameter corresponding to the land utilization type, calculating the surface subsidence, and carrying out differential correction on the carbon density parameter of each subarea of the coal mining subsidence area; and S4, calculating the total carbon reserves of different collapse stages, analyzing the carbon reserves, the carbon sequestration amount and the spatial distribution of each land utilization type, and comprehensively analyzing the time change characteristics of the carbon reserves. According to the method, the carbon density change is analyzed in combination with land utilization and the collapse state, and the time-space evolution characteristics of the carbon reserves in the coal mining subsidence area are evaluated.

The invention discloses a highway area vegetation carbon sink plaque calculation method. The method comprises the following steps: step 1, acquiring multi-source remote sensing data; 2, data preprocessing; step 3, dividing vegetation types; step 4, vegetation feature extraction; 5, constructing a biomass estimation model; step 6, laboratory determination; step 7, spectral analysis; 8, calculating carbon reserves; step 9, carbon sink plaque identification; and step 10, carbon sink plaque feature analysis. The invention provides the carbon sink measuring and calculating method specially aiming at the highway area vegetation, the carbon sink quantity of the highway area vegetation is quickly obtained by comprehensively applying multi-source data and various technical means, and the carbon sink plaque characteristics of the highway area vegetation are deeply analyzed, so that a scientific and comprehensive basis is provided for ecological protection and carbon sink management.

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 plant ecological carbon sink measurement and calculation, in particular to a tea garden carbon reserve dynamic monitoring and prediction method based on meteorological data, a typical sample plot in a tea garden is selected, meteorological data and basic carbon reserve of the typical sample plot are acquired, and the meteorological data comprise real-time data and forecast data; establishing dynamic monitoring, and performing heat damage identification and freeze damage identification on real-time data; establishing a carbon reserve dynamic correction model; a carbon reserve prediction model is established, and when heat damage and / or freezing damage occur in prediction data, the carbon reserve dynamic correction model is used for prediction to obtain a prediction result; according to the method, the damage of high-temperature stress to the tea trees has a gradual superposition characteristic, high-temperature inhibits photosynthesis, so that calculation is performed in a summation form, cold waves increase respiratory consumption, and the damage mainly depends on the intensity peak value and the cooling rate of a single event; by providing more accurate dynamic measurement and calculation as the supplement of static measurement and calculation, the change condition of the carbon reserves of the tea garden can be reflected in time.

The invention discloses a forest ecosystem carbon reserve determination method based on multi-source remote sensing data, and the method comprises the steps: constructing and analyzing a dominant tree species multi-temporal multi-feature classification data set according to Sentinel-1 and Sentinel-2 multi-source remote sensing data and research area forest resource checking vector data extraction; classifying the dominant tree species according to the multi-feature multi-temporal remote sensing data; and estimating the forest carbon reserves of different dominant tree species according to the optimal classification data set and the forest stock. According to the method, forest multi-feature and multi-temporal feature data are obtained by means of multi-source remote sensing data, and combined dimension reduction and separability analysis are performed, so that advantageous tree species spatial distribution is extracted, a forest stock and biomass linear model is fitted, and carbon reserve spatial distribution and features of a research area are estimated. And basic data and a practical basis are provided for further strengthening forest ecological system protection and implementing forest carbon reserve accurate improvement measures.

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 provides a soil carbon reserve measuring and calculating method and system and a medium, and belongs to the technical field of organic carbon reserves, and the method comprises the following steps: obtaining surface layer reflectivity spectral data of each layer of soil after construction of a disturbance area; dividing a plurality of grids based on the spatial distribution characteristics of the reflectivity spectrum; according to the coordinates of the center position of each grid, the soil texture and land utilization type corresponding to each grid in the database are called, and according to the reflectivity spectral characteristics of each grid, the soil organic carbon content on each grid is inverted through a pre-trained organic carbon content estimation model; according to the center position coordinate of each grid, calling the corresponding soil bulk density on each grid in the database, and determining the soil organic carbon reserve on each grid based on the soil bulk density and the soil organic carbon content; wherein the database stores soil texture, volume weight and land utilization type data corresponding to different coordinates; and obtaining the soil organic carbon reserve of the disturbance area according to the soil organic carbon reserve of each grid. The method can efficiently calculate the soil carbon reserve in the field.

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 provides an urban green land carbon storage and sink quantification method based on remote sensing and field investigation, and relates to the technical field of environmental science and engineering, remote sensing technology and ecological assessment, and the method comprises the steps: obtaining a high-definition remote sensing image, combining a green land planning file, determining the distribution of various types of green lands, calculating an NDVI, and extracting an effective green land space; and generating a sampling point scheme according to the area proportion. Growing parameters of arbors and shrubs in the quadrat are investigated on site, biomass is calculated and converted into carbon reserves, an NDVI and carbon density model is established, and a carbon density spatial distribution diagram is generated. And constructing a carbon sink model based on the relationship between the age of the arbor and the carbon reserves, calculating the annual carbon sink, establishing a relationship model between the NDVI and the carbon sink, and generating a carbon sink spatial distribution diagram. And integrating the two diagrams to output carbon storage and sink capability evaluation results of different green land types, thereby providing a scientific basis for urban ecological planning.

The invention provides a multi-mode remote sensing highway vegetation carbon reserve accurate inversion method based on tail gas stress correction, and belongs to the field of remote sensing images. Comprising the following steps: acquiring satellite remote sensing data, unmanned aerial vehicle data, ground actual measurement data and traffic flow data; vegetation biomass inversion based on multivariate data fusion, including biomass inversion of individual tree scale, sample area scale and road domain scale; converting the road domain biomass into road domain carbon reserves; calculating the traffic pollutant discharge amount; the day-by-day and hour-by-hour pollutant concentration of the vegetation sample plot is simulated according to the traffic pollutant discharge amount; constructing a carbon reserve dynamic correction model, and correcting road domain carbon reserves based on a photosynthetic inhibition effect and a respiration promotion effect; according to the method, satellite remote sensing, unmanned aerial vehicle remote sensing and ground measured data are fused, a multi-modal data closed loop is constructed, the limitation of a single data source in temporal-spatial resolution and coverage range is solved, multi-scale biomass inversion from a single tree to a road domain is realized, and the carbon reserve estimation precision is improved.

The invention relates to the technical field of carbon sink calculation, in particular to a grassland carbon sink calculation model, a grassland carbon credit calculation method and a storage medium. And calculating overground biological carbon reserve, underground root carbon reserve and soil organic carbon content by using a multi-task learning model based on a Transform architecture and a bidirectional long-short-term memory network. According to the method, multi-dimensional calculation of the carbon sink amount is achieved, the model generalization ability and the calculation precision are ensured, meanwhile, the manual dependency degree is reduced, and the calculation efficiency is further improved.

The invention provides an ecological pasture carbon reserve dynamic prediction method and system based on meteorological data, and relates to the technical field of carbon reserve prediction, and the method comprises the steps: collecting a variety of data, constructing a carbon reserve calculation model, and calculating the basic carbon reserve of a pasture according to pasture parameter data. Analyzing the influence of the pasture parameter data on the target ecological pasture area to obtain a carbon cycle parameter, and calculating a carbon reserve influence index according to the influence of the cow breeding factor on the pasture basic carbon reserve. And constructing a multitask learning model optimized based on a secretary bird algorithm, inputting carbon cycle parameters and meteorological data, and outputting to obtain meteorological influence carbon data. And generating a carbon reserve change rule according to the carbon reserve influence index and the meteorological influence carbon data, and making a carbon management strategy according to the carbon reserve change rule. According to the method, the accuracy and scientificity of dynamic prediction of the carbon reserves of the ecological pasture are improved, and powerful support is provided for sustainable management and carbon emission reduction of the ecological pasture.

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 present invention relates to the field of ocean engineering technology, and specifically relates to a blue carbon monitoring and intelligent regulation system for ocean ranching based on the supply of surplus energy from offshore wind power, including a surplus wind energy capture and standardization module, an environmental parameter acquisition module, a blue carbon storage calculation module, an ecological regulation parameter generation module, and an execution feedback optimization module; wherein: The surplus wind energy capture and standardization module: is used to collect the surplus electric energy of the offshore wind farm in real time; The environmental parameter acquisition module: collects a multi-source environmental parameter set; The blue carbon storage calculation module: calculates and outputs the blue carbon storage index hourly; The ecological regulation parameter generation module: is used to generate a regulation parameter set. The present invention realizes the integrated coordination of multi-source environmental monitoring, dynamic assessment of carbon storage, and intelligent ecological regulation by constructing a closed-loop linkage mechanism for surplus wind energy and blue carbon regulation, effectively improving the blue carbon formation efficiency of ocean ranching and the utilization rate of wind power resources.

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 provides a regional forest vegetation carbon sequestration capability assessment method, and belongs to the technical field of forest vegetation resource monitoring and carbon sink assessment. According to the method, 13 representative core sample plots serve as hubs, unmanned aerial vehicle multi-source remote sensing and satellite images are fused, 20-meter-resolution carbon density mapping is achieved, and a space-time coupling carbon sequestration index is constructed to evaluate the carbon reserve stability and the carbon sequestration potential. Arranging 13 20-meter core sample plots in a typical subarea in a structured manner, and measuring and calculating the carbon density of arbor, shrub and grass; extracting optical and laser features of the unmanned aerial vehicle to establish a subarea-level carbon density inversion model; training a star-sky-ground fusion estimation model by taking the sub-region unmanned aerial vehicle carbon density grid as a supervision label, and expanding the model to a region; and calculating a space-time coupling carbon sequestration index according to the carbon density time sequence and interference monitoring information. The method gives consideration to sampling efficiency and estimation precision, and is suitable for large-area forest carbon sink monitoring and management.

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.

The invention relates to the technical field of carbon reserves, in particular to a carbon reserve prediction method, device and equipment and a medium. According to the method, firstly, a prediction model is applied to the feature value of each grid, the prediction model learns the function of the internal relevance between the grids based on the feature value of each grid, and predicts the future carbon reserve of each grid based on the relevance to obtain the carbon storage initial prediction quantity of the grid; as grids of different scene types have different influences on the carbon reserve, the initial predictive quantity is adjusted based on the scene types after the initial predictive quantity is obtained, so that the final predictive quantity with relatively high accuracy is obtained. In addition, due to the fact that the internal relevance between the grids is considered, the accuracy of final pre-measurement is further improved.

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.