449 results about "Carbon storage" patented technology

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 discloses a monitoring system for forest ecological carbon sink calculation, and belongs to the field of ecological environment monitoring and carbon sink evaluation. Comprising a foundation optical remote sensing module, a crown biomass calculation module, a soil carbon component identification module, a vertical carbon flux detection module, a regional microclimate analysis module, a time sequence big data coupling module, a carbon source and carbon sink model fusion module and a result correction feedback module. The method comprises the following steps: collecting vegetation three-dimensional structure data through a multi-frequency laser radar, calculating unit-area canopy carbon storage acceleration in combination with seasonal climate interference parameters, and fusing turbulent carbon exchange and soil carbon change data to construct a regional carbon flux coupling model; the system collects cross-rosa chinensis carbon change data to construct a multi-dimensional feature tensor diagram, dynamically updates a weight and a fitting function, realizes carbon sink dynamic estimation and feedback optimization based on a biology-climate-time three-dimensional cooperation mechanism, and improves forest carbon sink monitoring precision and stability. The beneficial effect is that scientificity and accuracy of ecological environment monitoring and carbon sink evaluation are improved.

The invention relates to the technical field of carbon sequestration capacity monitoring, in particular to a carbon sequestration capacity monitoring and evaluating method for an island ecosystem, which comprises the following steps: S1, multi-source data fusion and habitat partitioning: dividing an island habitat type partitioning map; s2, stratified sampling and carbon reserve actual measurement: measuring the carbon content, and constructing a carbon reserve actual measurement database; s3, constructing a dynamic carbon sink model: carrying out a whole growth cycle environment simulation experiment on sea grass and algae in different habitats, and establishing the dynamic carbon sink model taking habitat types as classification units; s4, carbon sequestration capability quantification and bottleneck diagnosis: calculating carbon sequestration contribution values of various habitat types, identifying low-efficiency carbon sequestration areas through contribution value comparison, and analyzing environmental limitation factors of the low-efficiency carbon sequestration areas; and S5, integrating a sink increasing technology and generating a path: designing a habitat specific sink increasing scheme for the identified low-efficiency carbon sink area. According to the invention, high-precision monitoring, intelligent evaluation and system optimization of the island ecosystem carbon sequestration capability are realized.

The invention provides a carbon neutralization evaluation method for an ecological park, and the method comprises the steps: obtaining the basic data of various carbon assets in the ecological park, and the basic data comprises the natural ecological system carbon sink capability and human activity carbon emission intensity data; according to the carbon asset basic data, a time sequence analysis method is adopted to carry out modeling on the change trend of the carbon sink capacity and the carbon emission intensity, and a change trend model is obtained; modeling the spatial distribution of the carbon reserves and the carbon flux by utilizing a geographic information system technology and combining a change trend model to obtain a spatial distribution model; key variables are extracted from the spatial distribution model, and the effects of different factors on the carbon assets are quantified by adopting a multiple regression analysis method; acquiring carbon asset monitoring data, evaluating data quality, and if an abnormal value exists, performing correction by adopting a data cleaning algorithm; and according to the corrected carbon asset data, adopting a random forest model to predict the carbon sink capacity and the carbon emission intensity, and generating a dynamic evaluation result.

The invention relates to the technical field of ecological environment monitoring and geographic information, in particular to a coastal wetland soil sample point quality evaluation method and system based on multi-source environmental data. According to the method, remote sensing, climate, terrain, ocean and historical land coverage data are fused, and indexes are extracted and standardized; an environment similarity score (weighted Markov / neighbor weighted Euclidean), a historical consistency score (multi-temporal coverage + transfer penalty) and a source reliability score (metadata integrity + anomaly detection + NDVI-SOC residual) are constructed respectively; comprehensive scores are obtained through self-adaptive weight fusion, A / B / C grades are divided, and a report and a high-quality sample point set are output. The system comprises a data access module, a scoring engine module and a visualization module, and the precision and robustness of soil mapping and carbon storage evaluation can be remarkably improved.

The invention discloses a coastal zone carbon sink data acquisition management system and method, and particularly relates to the technical field of carbon sink evaluation, and the method comprises the following steps: dividing carbon flux parameter partitions based on vegetation types, sediment characteristics and historical carbon storage levels, and establishing initial reference values; plant biomass, soil organic carbon content and non-carbon dioxide greenhouse gas flux are regularly collected according to fixed sampling points, and a carbon sink observation data sequence is formed; when data exception triggers an evaluation process, generating a carbon sink credibility index and an ecological interference response index; inputting the two indexes into a prediction model to output an adjustment vector, generating an adjustment strategy in combination with a weight, and dynamically updating an initial carbon flux reference value of each partition; according to the method, regionalized management is realized by constructing carbon flux parameter partitions, a carbon sink observation data sequence is established, an evaluation index is dynamically generated, intelligent updating of a carbon flux reference value is completed in combination with a prediction model, and the precision, responsiveness and adaptive adjustment capability of carbon sink monitoring are improved.

The invention discloses a negative carbon filling mining method for a gangue high-porosity material, and relates to the technical field of CO2 storage and filling mining, which comprises the following steps: spraying a rapid cementing material while blanking a gangue bulk material, forming a high-porosity filling body in a goaf, continuously injecting liquid CO2 into the closed high-porosity filling body through a pipeline, and filling the high-porosity filling body into a high-porosity filling body. The underground efficient sealing of CO2 is realized; the method is simple in design, the filling technology and CO2 storage are combined, efficient mining and filling are achieved, coal resource mining is not affected, the mine green mining and negative carbon filling construction process is promoted, a new concept of carbon storage is provided, wide application and research significance is achieved, and compared with a solid filling mining method, the method has the advantage that the method has a wide application prospect. And the gangue is fixed by using the rapid binding material to form a high-porosity material with bearing performance, so that the cost of a filling mining technology is reduced, and the original tamping process is simplified.

The invention relates to a collaborative optimization scheduling method and system based on low-carbon demand response, and the method comprises the following steps: constructing a source-network-load-carbon storage emission flow metering model, and obtaining the carbon emission data of each part during the operation of a power system; obtaining a dynamic carbon emission factor according to the carbon emission data of each part during the operation of the power system, issuing the dynamic carbon emission factor to a user side, guiding a user to change the power utilization habit, and achieving the dynamic transfer of the power utilization load; a stepped carbon transaction mechanism is formulated according to the power utilization load transfer condition of the user, and the user is stimulated to optimize the carbon emission cost through carbon quota distribution and carbon price grading; and constructing a multi-objective optimization problem with minimum carbon emission intensity and minimum total cost of the power system, and solving the multi-objective optimization problem through a near-end strategy optimization PPO algorithm to obtain an optimal scheduling strategy.

The invention discloses a carbon storage space construction method for an artificial reconstruction plugging key layer, and the method comprises the following steps: S1, carrying out geological exploration, and determining the thickness and lithology of each overlying rock stratum; s2, determining the height of a gas guide fissure zone generated after the coal seam is mined by filling based on theoretical analysis and actual measurement data; s3, on the basis of geological data and the height of the gas-conducting fissure zone, the position of an artificial reconstruction plugging key layer and the position of a grouting layer are determined; s4, filling mining is carried out, grouting is carried out on overlying strata to reconstruct and block a key layer, and a carbon storage space is formed; and S5, carbon dioxide gas is injected into the goaf through a pipeline, carbon dioxide concentration monitoring is conducted on the working face while negative carbon filling is conducted, earth surface rock movement monitoring is conducted on the earth surface, and the negative carbon filling effect is judged. According to the method, the carbon storage space is formed by manually rebuilding and blocking the key layer while the gangue is filled, the space after coal mining can be effectively utilized for storing carbon dioxide, and emission of greenhouse gas is effectively reduced.

The invention provides a park green land vegetation optimization system based on carbon sink capability improvement and a method thereof, relates to the field of urban ecological environment, and aims to improve the carbon sink benefit of a green land through scientific optimization, the system comprises a data acquisition module, a carbon sink evaluation module, a vegetation optimization module and an intelligent monitoring module. The data acquisition module acquires data such as soil quality, climate conditions and vegetation types by using a multi-source sensor; the carbon sequestration evaluation module quantifies the carbon sequestration capacity of the green land through a carbon fixed quantity formula and a carbon storage quantity model; the vegetation optimization module adopts an intelligent optimization algorithm to generate a capability of giving consideration to carbon sink based on the optimization objective function; and the intelligent monitoring module evaluates a green land optimization effect through real-time monitoring data and dynamically adjusts vegetation configuration. The carbon sink optimization method provided by the invention comprises four steps of data acquisition, carbon sink evaluation, vegetation optimization design and dynamic monitoring, and efficient configuration is realized for different green land types by utilizing an accurate model and an optimization algorithm.

The present invention relates to the field of carbon storage monitoring technology, which is a sampling device for monitoring wetland carbon storage. The sampling device includes a square frame, a supporting frame, etc. The supporting frame is securely mounted on the square frame, with a U-shaped frame fixed at its top. The U-shaped frame houses a mounting plate, and a lifting plate is also slidingly mounted on the supporting frame. The sampling outer cylinder is fixedly mounted on the lifting plate, with an inner sampling cylinder inserted inside. Additionally, the sampling device comprises a lifting drive component, a depth control component, and a sampling component. The sampling device can both improve the accuracy of sampling work at different soil depths and eliminate detection errors with high degree of automations. At the same sampling position, multiple sets of samples can be collected simultaneously to ensure the accuracy of sampling results.

The present invention discloses a comprehensive system for the marine sequestration of carbon by injecting a slurry of diverse residual biomasses into deep-sea sediments. Central to the innovation is a meticulously designed flexible pipe system, which efficiently transports the slurry from storage units to the seafloor, significantly reducing the energy required for the overall injection process. The system also includes an adapted bulk carrier vessel, uniquely modified for seamless biomass transport, handling, and quality maintenance. The vessel is equipped with state-of-the-art energy generation systems, emphasizing renewable sources, and incorporates environmental considerations to minimize ecological impact. The injection process is optimized through a series of specialized equipment and detailed operational parameters, ensuring precise control and adaptability to various sediment types, depths, and environmental conditions. Additionally, the invention offers several unique embodiments catering to different needs, providing a flexible, cost-efficient, and environmentally responsible solution to ocean-based carbon storage. The system leverages the vastness of the oceans and the unique properties of various biomasses, offering a cutting-edge response to the global challenge of carbon sequestration.

The invention relates to the technical field of forestry investigation, and discloses a forestry investigation system for carbon sink forest management, which comprises a data acquisition module, a data processing module, a data integration module, a model construction and analysis module, a decision and early warning module, an output module and an implementation monitoring module. Through multi-dimensional index investigation, information can be obtained from multiple levels of an ecological system, the carbon cycle process and ecological functions of the carbon sink forest are comprehensively known, more comprehensive data support is provided for scientific management, in addition, more variables influencing carbon sink are introduced, so that the model better conforms to the actual situation, the accuracy and generalization ability of the model are enhanced, and the method is suitable for popularization and application. According to the method, carbon reserve changes of the carbon sink forest under different conditions can be better predicted, finally, effect prediction of multiple management schemes is provided for managers through scene simulation and model analysis, scientific and reasonable management decision making is assisted, and meanwhile, an early warning mechanism can find potential risks in time and guarantee stable development of the carbon sink forest.

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.

A method for calculating carbon storage in a mixed forest ecosystem is provided. The method includes: acquiring basic geographic data, meteorological data, eco-physiological parameter, thinning management history data, and validation data; proposing an improved biome-biogeochemical cycles (Biome-BGC) model suitable for simulating carbon storage of a mixed forest ecosystem under management by improving a phenology module, adding a thinning operation management module, and optimizing the eco-physiological parameter, based on an existing Biome-BGC model; simulating, by taking a pine-oak mixed forest as a research object, the carbon storage based on the improved Biome-BGC model; validating the improved model; analyzing sensitivity of the eco-physiological parameter by an extended Fourier amplitude sensitivity test (EFAST) method; and selecting a highly sensitive parameter, and analyzing an effect of the highly sensitive parameter on the carbon storage by a path analysis method. The improved model exhibits good performance in calculating the carbon storage of the mixed forest.

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 discloses a forest aboveground carbon reserve estimation system and method based on machine learning, and relates to the field of forest carbon reserves, and the method comprises the steps: collecting radar data, optical remote sensing data and forest aboveground carbon reserve actual measurement data, and carrying out the data preprocessing of the radar data and the optical remote sensing data; acquiring forest vertical structure information by using the radar data after data preprocessing; utilizing the optical remote sensing data after data preprocessing to obtain vegetation spectral characteristics; constructing a carbon reserve estimation model by adopting XGBoost, and adjusting hyper-parameters of the carbon reserve estimation model through a Bayesian optimization framework; and carrying out forest aboveground carbon reserve estimation to generate a forest aboveground carbon reserve distribution map with continuous space. According to the method, the hyper-parameters of the carbon reserve estimation model are adjusted through the Bayesian optimization framework, the complex mapping relation between the hyper-parameters and the performance of the carbon reserve estimation model is learned, and oriented efficient exploration of the hyper-parameter space is achieved.

The invention relates to a subtropical forest aboveground carbon reserve estimation method fused with a multi-modal remote sensing technology. The method comprises the following steps: acquiring and preprocessing multi-modal remote sensing data of a research area; feature extraction is carried out based on the preprocessed multi-modal remote sensing data; adopting a multi-scale feature fusion method to perform complementary fusion on the extracted feature data; based on the fused feature data, performing model training by adopting a hybrid machine learning method to obtain a carbon reserve estimation model; and estimating the carbon reserve by using the carbon reserve estimation model. According to the invention, subtropical forest aboveground carbon reserves can be accurately estimated, and spatial distribution characteristics and main influence factors of the subtropical forest aboveground carbon reserves can be systematically analyzed.

The invention relates to the technical field of carbon sink trend extraction, in particular to an extraction method performed by a carbon sink nonlinear trend extraction system based on ensemble empirical mode decomposition, which comprises the following steps: S1, acquiring forest carbon sink time sequence data to form a forest carbon sink time sequence data set, the forest carbon sink time sequence data are vegetation coverage rate VCR, soil coverage rate SCR, vegetation carbon content Cveg, soil carbon content Coil and total carbon storage capacity Ctotal at different seasons and times. According to the method, the overall carbon sink capacity of the forest can be evaluated more accurately by monitoring the carbon storage capacity in the vegetation and the soil, and how the carbon sink is influenced by climatic factors can be better understood by monitoring the changes according to the fact that the carbon storage capacity of the vegetation and the soil possibly fluctuates along with seasonal changes, so that the carbon sink capacity of the forest can be evaluated more accurately. Meanwhile, in the process of monitoring the change of the carbon storage capacity in different seasons, a long-term change trend chart of the forest carbon sink is extracted according to the rule of the influence of the non-linear change of the carbon storage capacity of the vegetation and the soil on the forest carbon sink capacity.

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.

A method for monitoring subterranean hydrocarbon storage sites includes simulating a seismic experiment using a baseline model. The method also includes perturbing the baseline model to produce one or more perturbed baseline models. The method also includes selecting a plurality of candidate acquisition geometries to probe the one or more perturbed baseline models. The method also includes extracting a set of simulated data from the simulated seismic experiment that corresponds to the plurality of candidate acquisition geometries. The method also includes executing a model probing exercise for the extracted set of simulated data for each candidate acquisition geometry and each of the one or more perturbed baseline models.

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 relates to the technical field of carbon burying and utilization, and particularly discloses a method for increasing the carbon dioxide burying amount by using a gas-soluble foaming agent. The gas-soluble foaming agent is adopted, in-situ foaming can be achieved through formation water, the carbon storage space is increased, and the dynamic stability effect can be achieved after foam is broken; in-situ foaming is realized around a shaft through segmented alternate injection of a front gas-soluble foaming agent slug and a rear CO2 slug; by setting a real-time injection pressure feedback mechanism and dynamically adjusting the injection mode, early breakthrough and loss of carbon dioxide are reduced, the sealing efficiency is remarkably improved, and the burying effect of carbon dioxide is effectively improved.

The invention relates to the technical field of agricultural environmental protection, and discloses a farmland emission reduction and carbon sequestration collaborative optimization system, which is characterized in that a data processing module is used for collecting farmland multi-source data of main grain products and preprocessing the collected data to obtain preprocessed multi-source data; the model building module is used for screening key factors which have obvious influence on farmland carbon reserves on the basis of the preprocessed multi-source data, and building a farmland emission reduction and carbon sequestration model; the collaborative optimization module is used for searching a Pareto optimal solution set in a parameter space by adopting a non-dominated sorting genetic algorithm, and introducing a fuzzy logic controller to process target conflicts to obtain a collaborative optimization scheme of farmland emission reduction and carbon sequestration; the real-time monitoring module is used for monitoring farmland environment change and emission reduction and carbon sequestration effects in real time and regularly adjusting and optimizing a collaborative optimization scheme; the synergism and effectiveness of the technology are improved, collaborative improvement of farmland yield increase and emission reduction carbon sequestration is achieved, and the problem that yield increase and emission reduction carbon sequestration are not collaborative in the prior art is solved.

The disclosed method includes: determining a subsurface space of interest; arranging a source sensor array relative to a receiver sensor array of a Surface Distributed Acoustic Sensing (S-DAS); transmitting, from the source sensor array, a first set of seismic signals indicating baseline measurements; receiving, using the receiver sensor array, the baseline measurements and thereby generate baseline data; injecting fluid into the subsurface space of interest; transmitting, using the source sensor array, a second set of seismic signals indicating fluid plume measurements; receiving, using the receiver sensor array, the fluid plume measurements and thereby generate fluid plume data; determining, based on the baseline data and the fluid plume data, time-shift data and thereby generate fluid plume extent data; formatting the fluid plume extent data into data values that characterize an extent or rate of spread of the fluid plume; and visualizing the extent or rate of spread of the fluid plume.

The invention discloses a carbon storage space construction method for negative carbon filling mining, which comprises the following steps of: determining the position of a hard and thick rock stratum according to the lithology of overlying strata, determining the height of a gas guide fissure zone based on actual measurement and theoretical calculation, constructing a sealing wall in a to-be-constructed goaf filling area, dividing the goaf filling area into a plurality of spaces arranged at intervals, each space is sealed; gangue filling and grouting are carried out in a caving area above a coal body in a certain area in front of and behind a goaf, and it is ensured that no gas leaks out of a carbon storage space. According to the method, the space after mining is efficiently utilized, safe filling treatment of waste such as gangue is achieved, the storage technology of greenhouse gas such as carbon dioxide is combined, carbon emission is remarkably reduced, and meanwhile resource recycling is promoted.

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 field of forest carbon sink prediction, in particular to a regional forest carbon spatial distribution acquisition method, which comprises the following steps of: judging forest types, vegetation growth states and soil information by combining satellite remote sensing with unmanned aerial vehicle aerial photography information, calculating forest carbon density through the information, and drawing the forest carbon density on a geographic image through a GIS (Geographic Information System) technology. The forest carbon space distribution diagram is obtained, the problems in the prior art are solved, the calculation precision can be improved by improving the fine granularity, the carbon reserve of a single tree can be estimated more accurately, then the carbon reserve condition of the whole forest is deduced, and the carbon space distribution diagram of the forest is obtained by detecting the air carbon dioxide content of the target area. And whether the vegetation growth condition information of the target area is accurate is determined, so that whether forest carbon density calculation is accurate is verified, and the accuracy of forest carbon spatial distribution drawing is improved.