333 results about "Carbon sink" 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 wetland carbon sink benefit evaluation method and system based on remote sensing data, and relates to the technical field of carbon emission evaluation. A wetland carbon sink benefit evaluation system based on remote sensing data comprises a carbon sink evaluation zoning module and a carbon sink benefit evaluation module. According to the invention, through multi-modal remote sensing data fusion and fine grid division, high-resolution analysis of spatial heterogeneity of a wetland region is realized, different types of carbon sink regions and distribution boundaries thereof can be accurately identified, and scientificity and particles of carbon sink partitioning are improved; a dynamic index characteristic graph layer is constructed through a remote sensing time sequence, a hydrological pulse response factor graph layer is constructed in combination with hydrological data, and clustering division is performed on the hydrological pulse response factor graph layer, so that dynamic identification and pixel level benefit calculation of a dynamic carbon sink area are realized.

The invention discloses a vegetation carbon sink space optimization method and system based on interpretable machine learning. The method comprises the steps that firstly, multi-source environment data such as administrative division, environment factors and target variables of a target area are acquired, and a space table data set is formed; training an XGBoost regression model based on the data set, predicting the vegetation carbon sink amount and evaluating the performance of the model; quantifying the contribution of each environmental factor to the carbon sink by combining an SHAP interpreter, generating a feature importance and interpretability map, fitting through a LOWESS algorithm to obtain an environmental factor and carbon sink response relation curve, and extracting an optimal threshold interval; further predicting a carbon sink gain according to an optimization threshold value, delimiting optimization partitions, and forming a space optimization scheme; and finally outputting a vegetation carbon sink optimization suggestion report. According to the method, scientific quantification of carbon sink space optimization can be realized, and the interpretability and decision support value of a carbon sink improvement strategy are improved.

The invention relates to the technical field of forest wetland carbon sink monitoring and evaluation, and particularly discloses a forest wetland carbon sink intelligent monitoring and evaluation system and method. According to the method, a vegetation carbon sequestration potential evaluation result is obtained by analyzing vegetation structure feature data of forest, water and soil composite ecology of the forest wetland, a water-soil-carbon cooperative evaluation result is obtained by analyzing specific hydrological-soil carbon cycle key elements of the forest wetland, and environmental disturbance response factors are obtained by combining various environmental disturbance factors. Through multi-source data fusion and intelligent modeling, a carbon sink quantitative evaluation value is output, and abnormal feedback is triggered; the problems that in the prior art, adaptability to a forest wetland compound ecological system is insufficient, evaluation refinement is insufficient, and dynamic response is lacked are solved. According to the method, accurate and dynamic monitoring and evaluation of forest wetland carbon sink are realized, carbon sink short plates can be accurately positioned, optimization support is provided, and technical support is provided for protection, restoration and optimization management of forest wetland carbon sink resources.

The invention discloses a typhoon influence distinguishing method and system based on seawater CO2 partial pressure data, and the method comprises the steps: obtaining sea area situation monitoring data in a target sea area typhoon transit period through a multi-source observation platform, and constructing a standardized data set and a climate state background field; a DBSCAN clustering algorithm is adopted to perform water mass division, and the typhoon characteristic water mass distribution is determined in combination with a Manchester-HuitiniU test and correlation analysis. And calculating a seawater carbon dioxide partial pressure abnormal field based on the climate state background field, constructing a typhoon influence index sequential sequence, identifying a core influence area, and generating a typhoon influence trace path. And then seawater carbon dioxide partial pressure grid point reconstruction is carried out, and a typhoon influence space map is constructed. And finally, analyzing space-time change of carbon dioxide flux of air-sea, evaluating carbon sink stability, and generating a typhoon-carbon sink sensitivity zoning map. Seawater carbon dioxide partial pressure is used as a core index, limitation of a traditional method is overcome, and reliable technical support is provided for typhoon marine environment influence assessment.

The invention provides a low-carbon modular artificial wetland system and a carbon sink collaborative purification method thereof, and relates to the technical field of artificial wetlands, the low-carbon modular artificial wetland system comprises a modular box body, and a water inlet layer, a carbon sink layer and a purification layer which are sequentially arranged in the modular box body from top to bottom; the water inlet layer is used for filtering suspended matters through coarse sand; the carbon sequestration layer is used for adsorbing carbon dioxide through biochar and carbon sequestration microorganisms, and meanwhile, the carbon sequestration capacity is enhanced through the plant-microorganism synergistic effect; the purification layer is used for purifying a water body through an iron-based phosphorus removal material and a zeolite denitrification filler. The technical problems of low-carbon material selection, carbon sink potential excavation, renewable energy source coupling and greenhouse gas emission inhibition of an existing constructed wetland system are solved, the technical effects of efficient sewage purification and carbon emission reduction are achieved, and a carbon emission reduction closed loop of the whole life cycle is achieved.

The invention relates to a multi-scale urban garden carbon sink improvement and ecological collaborative regulation and control system, in particular to the field of urban gardens, and aims to construct a computable and evolvable knowledge graph, deeply fuse multi-source data and domain rules and dynamically drive a space optimization decision. Static planning is upgraded into a'prediction-simulation-learning 'closed-loop process; an optimization algorithm uses a knowledge graph to perform efficient optimization, and a multi-target equalization scheme is generated; carrying out high-fidelity and uncertainty-containing long-term dynamic deduction and risk assessment on the scheme by the digital twinborn body; a simulation result feeds back a calibration knowledge rule through meta reinforcement learning, a success mode feedback knowledge base is extracted from the calibration knowledge rule, and the process realizes collaborative self-evolution of planning knowledge, an optimization model and a simulation environment, so that the accuracy, robustness and foresight of decision making are continuously improved, and the decision making efficiency is improved. And finally, multi-scale collaborative optimization of carbon sink, ecological and social services and economic cost is achieved.

The invention discloses an artificial intelligence-based agricultural waste carbon emission reduction scenario simulation method and system, and the method comprises the steps: obtaining multi-source geographic space data of a target region, uniformly fusing the multi-source geographic space data into a grid system with a preset resolution, and carrying out the calculation of the multi-source geographic space data based on a space weighted distribution model, the statistical yield of provincial agricultural products is distributed to each grid of a grid system, and the theoretical resource quantity and the high-precision spatial distribution diagram of the agricultural wastes are obtained in combination with a grass-grain ratio database. Method for determining carbon emission and carbon sink quantitative parameters of agricultural wastes under various utilization paths through dynamic accounting model, simulating carbon emission reduction potential and spatial distribution under different resource utilization scenes based on artificial intelligence model according to carbon emission and carbon sink quantitative parameters of agricultural wastes under various utilization paths, and planting front-end crops and structure and space layout is optimized. A quantifiable and visual scientific decision-making tool is provided for regional low-carbon agricultural planning, and the accuracy and feasibility of an emission reduction strategy are remarkably improved.

The invention discloses a site-level CCUS dynamic source-sink matching optimization method for an oil field enterprise, relates to the technical field of large-scale deployment of carbon capture, utilization and storage of the oil field enterprise, and particularly relates to the site-level CCUS dynamic source-sink matching optimization method for the oil field enterprise. Comprising the following steps: integrating a carbon source end full life cycle technical economy evaluation system and a storage target area'geology-potential-economy 'three-dimensional grading model to form a dynamic database; on the basis of the dynamic database, a mixed integer linear programming model fusing source sink dynamic priority coefficients is constructed, three scenes of cost minimization, oil displacement income maximization and carbon sink subsidy excitation are set, and a constraint system is coupled; according to the method, carbon source technology economic evaluation and storage target area three-dimensional grading are fused, the specific injection-production cycle, policy incentive and pipe network constraint of an oil field are converted into time-varying weight coefficients, traditional static optimization limitation is broken through, and site-level source-sink dynamic accurate matching is achieved.

The invention belongs to the technical field of carbon sink evaluation, and discloses a typical weather-oriented tea garden carbon sink dynamic profit and loss evaluation method and system. Historical meteorological information and historical carbon sink monitoring information of the tea garden are collected, and a typical weather type library of the tea garden is constructed; determining a typical weather type corresponding to the current day of the tea garden, and calculating a carbon sink fixed amount and a carbon sink output amount of the tea garden; generating a correction factor for correction according to the management activity information of the tea garden to obtain a net carbon sink value; generating a total score based on comprehensive analysis of the net carbon sink value, and evaluating the carbon sink profit and loss condition of the tea garden; the carbon sink meteorological influence parameters before and after the monitoring time point are collected for comprehensive analysis to calculate the carbon sink fixed quantity and the carbon sink output quantity, calculation deviation caused by parameter fluctuation at a single time point can be avoided, and therefore the method better fits the continuous physiological process of photosynthesis / respiration of the tea trees, and the detection accuracy is improved. And the calculation result of the carbon sink fixed quantity / output quantity is closer to the actual condition.

The invention discloses a road construction carbon emission monitoring method and system, and relates to the technical field of carbon emission monitoring. The method comprises the steps of obtaining earth surface feature information, vegetation types and distribution areas of a construction area, obtaining disturbance areas of different vegetation types, calculating disturbance coefficients, loss coefficients and carbon sink loss amounts of the disturbance areas, calculating the total carbon emission amount of a construction period, constructing an emission evaluation model, and outputting a predicted emission amount of a subsequent construction period in combination with a project scheme. Judging whether the predicted emission exceeds a preset emission threshold value or not, if not, keeping the project scheme unchanged, and if yes, suggesting to modify the project scheme; the carbon sink loss amount caused by vegetation damage can be accurately calculated, so that the total carbon emission amount is more comprehensively and accurately evaluated, and a scientific basis is provided for construction scheme optimization.

The invention discloses a forest carbon flux statistical method and system under the influence of a wildfire, and the method comprises the steps: obtaining forest multi-dimensional data including fire point data, and constructing a multi-scale collaborative database; constructing a carbon source-carbon sink dynamic coupling model according to the multi-scale collaborative database; obtaining a forest multi-dimensional remote sensing index, and constructing a correlation matrix; correcting the carbon source-carbon sink dynamic coupling model according to the correlation matrix; and generating a forest spatialization decision map based on the multi-scale collaborative database and the carbon source-carbon sink dynamic coupling model. According to the technical scheme provided by the invention, by fusing forest multi-scale data, a nationwide unified grid system is constructed, and large-scale forest fire carbon flux statistics and accurate quantification are realized; a carbon source-carbon sink dynamic coupling model is constructed, a forest multi-dimensional remote sensing index is used for correction, and the monitoring precision of the fire influence is remarkably improved; and the emission factors are dynamically calibrated, so that the inter-region difference is reduced, and the universality of the method is enhanced.

The invention provides a forest carbon reserve prediction method, device and equipment based on forestry carbon sink monitoring, and relates to the technical field of data analysis. According to the method, firstly, a forest optical image and climate-related data are acquired, and the forest optical image at least comprises a red light band and a near-infrared band; secondly, extracting an optical global semantic vector from the forest optical image, and performing semantic constraint on the optical global semantic vector based on growth condition semantic information in the forest optical image to form an optical growth semantic vector; then, a climate global semantic vector is extracted from climate related data; thirdly, performing semantic fusion on the optical growth semantic vector and the climate global semantic vector to obtain a forest global semantic vector; and finally, performing semantic reduction based on the forest global semantic vector to form a carbon reserve prediction result. Based on the above content, the problem that the reliability of forest carbon reserve prediction is relatively low in the prior art can be improved.

The invention discloses a composite carbon sink estimation method based on multi-mode mangrove forest canopy data, and belongs to the technical field of carbon sink calculation in ecological environment monitoring, and the method comprises the steps: obtaining laser radar point cloud data, a hyperspectral remote sensing image and ground actual measurement data of a mangrove forest region; preprocessing the laser radar point cloud data, the hyperspectral remote sensing image and the ground actual measurement data to obtain standardized data; structure parameters and biochemical parameters are inversed based on the standardized data; fusing the structure parameters and the biochemical parameters to construct a comprehensive inversion model; the mangrove forest carbon reserve is calculated through the comprehensive inversion model; and verifying the precision of the comprehensive inversion model through ground measured data, and outputting a final carbon sink estimation result.

The invention relates to the technical field of computer simulation, and provides an ecological restoration measure carbon sink effect quantitative simulation prediction method and system based on digital modeling. The method comprises the following steps: collecting ecological element information of a target drainage basin, extracting a multi-dimensional spatial distribution feature set, and establishing an ecological environment response simulation model under engineering disturbance in combination with digital baseline data; constructing a carbon sink effect quantitative model based on construction operation situation information, and embedding the carbon sink effect quantitative model into associated nodes of the ecological environment response simulation model to realize coupling; the dynamic influence of engineering construction operation on the drainage basin carbon sink capacity is simulated based on the coupling model, the multi-target optimization decision matrix is generated, the pre-optimization decision suggestion is output, collaborative simulation of ecological environment response and carbon sink effect quantification is achieved, and the accuracy of hydropower engineering carbon sink influence prospective evaluation and the scientificity of decision suggestion are improved.

The invention discloses an oyster carbon sink value evaluation method, model and equipment based on carbon sequestration amount, and a medium. The method comprises the following steps: collecting oyster breeding data in an oyster breeding process; the method comprises the following steps: respectively calculating an oyster body carbon sequestration amount, an oyster attached organism carbon sequestration amount and an oyster biological sediment carbon sequestration amount according to oyster breeding data, and summarizing the oyster body carbon sequestration amount, the oyster attached organism carbon sequestration amount and the oyster biological sediment carbon sequestration amount into a total oyster breeding carbon sink amount; and calculating the carbon sink value of the oysters according to the total carbon sink amount of the oyster culture. According to the method, a traditional culture shellfish carbon sequestration basic metering method is improved, carbon sequestration amount calculation is carried out on oyster bodies and biological sediments of attached organisms respectively, the more accurate oyster culture carbon sequestration total amount can be obtained, and the carbon sequestration income of oysters is calculated based on the carbon sequestration total amount. The method is beneficial to enriching the basic research in the field of shellfish culture carbon sink accounting, and enables the ecological service value of the shellfish culture industry to be compensated through carbon sink transaction.

The invention discloses an electric power and carbon management collaborative optimization method and system for a multi-industry symbiotic zero-carbon park, and the method comprises the steps: constructing a mixed integer programming model which comprises an electric power dispatching sub-model, a carbon collection sub-model and a source-sink matching sub-model, and defining a coupling relation between an electric power dispatching variable and a carbon management variable; designing a multi-objective optimization function, and bringing coal consumption cost, start-stop cost, carbon transaction cost, wind curtailment penalty cost, deep peak regulation cost, peak regulation compensation benefit and transportation cost into a unified optimization framework; and setting time-space coordination constraint conditions, including power balance constraint, output upper and lower limit constraint, climbing rate constraint, capture-transport volume balance constraint and carbon sink capacity limitation constraint, to realize coordination optimization of power production and carbon logistics in time and space dimensions. According to the method, the total cost of the system is effectively reduced, the utilization efficiency of carbon sink resources is improved, real-time controllability of carbon emission intensity is ensured, and the problem of global optimum deficiency caused by a traditional two-stage optimization method is solved.

The invention discloses a mine ecological restoration engineering carbon emission metering method based on an LCA method, and relates to the technical field of carbon emission metering, and the method comprises the following steps: S1, constructing an abandoned mine ecological restoration engineering full life cycle boundary; s2, establishing a carbon emission accounting framework based on LCA; s3, constructing a mine ecological restoration full-life-cycle carbon emission factor library; s4, complete-cycle carbon emission refined lightweight calculation is carried out; s5, carbon footprint full-period positioning is carried out; four stages of exploration design, construction, operation and maintenance and decommissioning are comprehensively included in an accounting range through a full life cycle boundary, a coupling relation between a carbon emission source and a carbon sink item in each stage is determined, and the emission sources are accurately split according to construction sub-stages; in combination with system, module and factor hierarchical disassembly of a three-level framework, a carbon emission generation mechanism is fundamentally analyzed, so that the problem that the carbon emission generation mechanism is not clearly known is solved.

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 discloses an effect evaluation method, system and device for an electricity-carbon market collaboratively supporting dual-carbon target path and a storage medium, and the method comprises the steps: decoupling a dual-carbon target path into an electricity carbon emission reduction path and an electricity carbon sink increase path which are collaboratively supported by the electricity-carbon market layer by layer, and determining the new investment scale of each year according to the paths. The method comprises the following steps: respectively carrying out full life cycle cost (LCC) analysis on an electric power carbon emission reduction project and an electric power carbon increment and sink project, and measuring and calculating leveling cost per kilowatt-hour (LCOE) on the basis and taking the leveling cost as an expected price for investment decision; and further performing coupling calculation on the annual newly-added investment scales of the two types of projects, the investment decision expected price and the electricity-carbon market price obtained through simulation deduction, and finally measuring and calculating the investment incentive intensity required for tracking the dual-carbon target path and the collaborative incentive intensity of the electricity-carbon market. And calibrating the deviation of the two types of excitation intensities, determining the over-excitation risk cost or the under-excitation risk cost, and taking the over-excitation risk cost or the under-excitation risk cost as an effect evaluation core index of the electricity-carbon market collaborative support double-carbon target path. The evaluation method provided by the invention synchronously covers two types of risks of excessive excitation and insufficient excitation, can realize accurate evaluation of the effect of supporting a dual-carbon target path by various electricity-carbon market mechanisms, and provides direct decision support for a market supervision mechanism to carry out electricity-carbon market mechanism design.

The invention relates to a carbon sink quantification method and system based on multi-source data fusion and carbon flux large model inversion, and belongs to the technical field of meteorological monitoring, and the method comprises the steps: obtaining multi-source data of a target area and historical inversion data of a carbon flux large model; based on the ground carbon flux detection data and the historical inversion data of the carbon flux large model, performing dynamic calibration and parameter optimization on the pre-trained carbon flux inversion large model in the target region to obtain a region optimization model; inputting carbon-related data and meteorological and soil auxiliary data inverted by satellite remote sensing into the regional optimization model, and performing inversion to generate space-time continuous lattice point carbon flux data of the target region; based on the space-time continuous lattice point carbon flux data of the target region and the lattice point area of the target region, determining the actual carbon sink amount of the target region; and determining the net carbon sink increment of the target area based on the actual carbon sink amount of the target area, the carbon sink amount of the target area under the baseline scene and the carbon leakage evaluation value, thereby improving the carbon sink monitoring effect.

The invention discloses a Yellow River basin heritage area ecological corridor environment design system based on digital twinning, belongs to the technical field of ecological corridor environment design, and aims to solve the problem that the Yellow River basin heritage area ecological corridor design is insufficient in accuracy and scientificity. The system comprises a multi-source ecological data acquisition module, an ecological data preprocessing module, a digital twin construction module, an ecological corridor planning design module and a visual output module. According to the method, terrain data, ecological element data and land utilization data are collected and preprocessed, ecological digital twin bodies of the heritage areas of the Yellow River basin are constructed, and in combination with an InVEST model, a minimum cost path algorithm, an RUSLE water and soil loss model and a CASA carbon sink model, ecological node recognition, optimal ecological corridor path planning and corridor environment design simulation are completed, so that the ecological digital twin bodies of the heritage areas of the Yellow River basin are constructed. And visually displaying the result. According to the method, accurate mapping of the ecological scene is achieved, the scientificity of ecological corridor design is improved, and support is provided for ecological corridor construction.

The invention discloses a multi-element participation and dynamic optimization national park carbon sink function management system, method, equipment and medium, and belongs to the technical field of ecological system carbon sink monitoring and management, and the system comprises a carbon sink sensing module which is used for collecting carbon sink data of ecological systems such as forests and wetlands in real time; the multi-source data integration module is used for fusing remote sensing images, meteorological parameters and manual patrol data; the analysis and optimization module is used for dynamically evaluating the carbon sink capacity based on a model algorithm and providing management optimization suggestions; the collaborative participation module is used for realizing a co-construction and sharing mechanism of researchers, managers and the public; and the feedback and early warning module is used for giving out early warning for abnormal change of the carbon sink function and feeding back the early warning to the management terminal. According to the invention, full-process dynamic monitoring and scientific management of the national park carbon sink function are realized, the real-time performance, precision and governance collaboration of carbon sink capability assessment are improved, and an eco-friendly, scientific and efficient public-participated carbon sink function management platform is constructed.

The invention discloses a zero-carbon comprehensive energy digital management method and equipment, belongs to the field of energy management, and is used for solving the problem of inaccurate energy digital management regulation and control. Obtaining a dynamic carbon flow model of carbon emission space-time distribution and a dynamic carbon sink model of carbon absorption space-time change; performing coupling calculation on the dynamic carbon flow model and the dynamic carbon sink model on a unified spatial-temporal scale to fit and generate a net carbon spatial-temporal tensor of the park in a scheduling period; the net carbon space-time tensor is used for quantifying the net carbon emission of each region in each time slice in the park; tensor decomposition is carried out on the net carbon space-time tensor, and target areas which are adjacent in space but opposite in function are selected; and regulating and controlling energy supply and load demands among the target regions based on the carbon balance levels and the time dynamic modes of the target regions so as to generate a collaborative optimization strategy.

The invention belongs to the technical field of forest carbon sink management, and discloses a forest carbon sink spatio-temporal dynamic monitoring method based on multi-source data fusion, comprising the following steps: acquiring multi-source data associated with carbon sink spatio-temporal dynamic monitoring in the southeast of Tibetan, and preprocessing the multi-source data; constructing a carbon sink estimation model; constructing a coupling influence model based on the multi-factor influence factors; and based on an influence mechanism analysis result, a natural driving path and a manual driving path are distinguished, a dominant driving mechanism is defined, and a targeted improvement strategy is formulated in combination with the characteristics of the southeast Tibetan forest ecosystem. By adopting the method, the time-space dynamic data of the structure and the carbon sequestration function of the southeast Tibetan forest ecosystem are accurately obtained; the coupling influence mechanism of biological factors, environmental factors and human factors on the carbon sequestration function of the southeast Tibetan forest is systematically analyzed; a dominant path and an interaction mechanism for natural and human factors to drive the carbon sink change of the southeast Tibetan forest are defined, and technical support is provided for regional forest ecological system protection and carbon sink management.

The invention discloses a carbon sink intelligent evaluation platform based on solid waste resource utilization, and the platform constructs a digital elevation model and a canopy height model through aerial remote sensing and ground environment data collection, and evaluates the vegetation net primary productivity in combination with a light energy utilization rate model. Training a soil organic carbon inversion model by adopting machine learning, and analyzing multi-stage hyperspectral image data; and establishing a soil carbon dynamic model to simulate a carbon solid storage and turnover process. Remote sensing data, LiDAR structure parameters and ground actually measured biomass are fused through random forest regression, and the biomass estimation precision is optimized. And finally integrating the plant and soil carbon sequestration amounts, calculating the total carbon sequestration amount of the ecological system and evaluating the temporal and spatial variation characteristics of the total carbon sequestration amount. According to the platform, intelligent and precise carbon sink evaluation is realized, and a scientific basis is provided for ecological restoration and carbon sink management.

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 relates to the crossing field of agricultural information technology and urban sustainable development, and discloses an urban micro-agriculture three-dimensional edible landscape intelligent low-carbon benefit evaluation and adjustment and optimization method and an urban micro-agriculture three-dimensional edible landscape intelligent low-carbon benefit evaluation and adjustment and optimization system. According to the method, data are collected through a multi-modal behavior sensing device and a plant physiology monitoring array, a behavior-ecology synchronous time sequence set is constructed, a plant growth dynamic simulation model fusing behavior disturbance factors is established, carbon sink, energy consumption and food output efficiency are quantified, and a plant growth dynamic simulation model is established. And based on a multi-target particle swarm optimization algorithm, generating a spatial layout and interaction strategy combined adjustment and optimization scheme. The system comprises a behavior perception module, an ecological monitoring module, a space-time alignment module, a model simulation module, a benefit calculation module and a visual pushing module. According to the method, the low-carbon benefit evaluation precision and the community participation sustainability are remarkably improved, the actual measurement prediction error is reduced by 42%, and the comprehensive benefit is improved by 28%.

The invention provides a garden carbon sink function zoning method fusing multi-source remote sensing data, and relates to the technical field of garden carbon sink evaluation and remote sensing monitoring. The method comprises the following steps: acquiring multi-source remote sensing data such as optical remote sensing, radar remote sensing and laser radar; performing radiometric calibration, atmospheric correction and geometric correction preprocessing on the data; vegetation characteristic parameters such as a normalized vegetation index, a leaf area index and surface temperature are extracted; calculating garden carbon sink efficiency parameters based on the vegetation characteristic parameters; calculating garden carbon sink function zoning parameters in combination with topographic data; performing carbon sink function zoning on the garden area by adopting a clustering algorithm, and dividing high, medium and low carbon sink function level areas; and outputting a carbon sink function division spatial distribution diagram and a data report. According to the method, evaluation comprehensiveness is improved through multi-source data fusion, accurate quantification is realized through innovative parameter calculation, scientificity and repeatability are improved through an objective partitioning method, and garden carbon sink fine management is effectively supported.

This invention relates to the field of ecological environment management technology, specifically disclosing a refined method and system for visualizing regional vegetation carbon sequestration. The method includes: extracting land use types of a target area based on remote sensing data of land use types and biomass; determining forest areas based on land use types and establishing growth curves for the forest areas based on preset fitting curves; calculating the carbon sequestration amount of the forest areas based on the growth curves and determining the carbon sequestration ratio of different forest areas; allocating the total carbon sequestration amount to different sub-regions of the target area based on the carbon sequestration ratios, and visually converting the allocated target areas. This invention first selects a target area, calculates the carbon sequestration amount based on the forest areas within the target area, then redistributes the carbon sequestration to different areas according to land use types, and visualizes the redistribution results, facilitating the management of the area.