54 results about "Terrestrial ecosystem" patented technology

The invention discloses a water resource management system based on terrestrial ecosystem protection, and relates to the technical field of water resource management. The water resource management platform is in communication connection with a data collection and processing module, an index system construction module, a space coordinate system unification module, a unit analysis module, an ecological hydrological evaluation module and a management module, and all the modules are in electric signal connection. According to the method, hydrological characteristics and ecological requirements of different regions are identified more accurately by dividing ecological hydrological regions, comprehensive evaluation is performed on landform, ecological factors, climate hydrology and human activity data in a drainage basin by using a G-IS and a spatial analysis tool, ecological hydrological indexes are calculated, and the evaluation accuracy is improved. Therefore, targeted water resource management measures are formulated for each subarea, optimization of water resource allocation, improvement of water utilization efficiency, reduction of waste and guarantee of reasonable distribution and utilization of water resources are facilitated.

The invention discloses a multi-model coupled regional terrestrial ecosystem carbon reserve estimation method, which is suitable for the field of carbon cycle and carbon reserve estimation. The method comprises the following steps: firstly, collecting remote sensing data, and then estimating overground, underground and soil annual carbon density mean values of a regional terrestrial ecosystem by adopting an ARIMA model; the method comprises the following steps: clustering regions with different carbon densities by adopting a CatBoost model, dividing the carbon densities of a regional ecological system into low, medium and high levels, and avoiding the influence of spatial heterogeneity among different density levels on subsequent model training; an RNN model is constructed to evaluate the carbon density conditions of different levels of unit grids, and interannual dynamic carbon density parameters of different types of ecosystems are obtained based on multi-source data; and finally, calculating the carbon reserves of the unit grids, analyzing the annual average change trend and the spatial distribution condition of the carbon reserves, and realizing accurate evaluation of the regional terrestrial ecosystem carbon sink. The method is simple in step and good in using effect, and the change condition of the carbon sink capacity in the corresponding time can be obtained according to the sampling time interval of the input data.

The invention discloses a regional GPP assimilation inversion system fusing foundation-multi-source satellite chlorophyll fluorescence, and belongs to the technical field of terrestrial ecosystem carbon cycle monitoring. The signal unmixing and simulation generation module is used for unmixing the total fluorescence of the mixed pixels into pure chlorophyll fluorescence (SIF) and driving an ecological model to generate SIF and GPP simulation values based on environmental stress data; the state component decoupling module is used for decoupling the total GPP analog value into a light response fast component, a light response slow component and a light response memory component; the state evolution prediction module is used for predicting dynamic evolution of the slow component and the memory component; and the self-adaptive assimilation inversion module is used for performing inversion on the region GPP by taking the slow component and the memory component as state variables, taking the SIF observation value as observation data and combining a prediction result of the state evolution prediction module. According to the method, systematic deviation caused by model simplification or data singleness in a traditional method is overcome.

The invention relates to the technical field of ecology and hydrology, in particular to a terrestrial ecosystem water carbon flux estimation method considering water balance constraint, which comprises the following steps: estimating leaf scale photosynthetic rate and stomatal conductance by utilizing a photosynthesis model; the leaf scale photosynthetic rate and the stomatal conductance are upscaled into canopy vegetation total primary productivity and canopy conductance to construct an evapotranspiration model to estimate evapotranspiration data; constructing a water balance model according to the evapotranspiration data so as to estimate the available water amount of the soil; constructing a soil moisture stress function according to the available water amount of the soil so as to constrain the estimation process of the photosynthesis model and the evapotranspiration model; and acquiring historical water-carbon flux data and historical remote sensing observation data of a long sequence daily scale, and calibrating the model to obtain a water-balance-constraint-considered water-carbon flux estimation model of the terrestrial ecosystem capable of estimating the water-carbon flux data. Therefore, the problems that an existing water carbon flux prediction frame is difficult to adapt to climate changes, low in prediction accuracy and the like are solved.

The invention belongs to the technical field of ecological and hydrological branches under geophysics, and particularly relates to a groundwater ecological burial depth evaluation method fusing CatBoost regression and SHAP attribution, which comprises the following steps: (1) collecting ecological and hydrological observation data of each sample point in a research area for CatBoost regression modeling, SHAP attribution analysis and groundwater ecological burial depth evaluation; (2) respectively constructing an EVI regression model and an ET regression model by using a CatBoost machine learning algorithm based on the ecological and hydrological basic data in the step (1); (3) respectively carrying out SHAP attribution analysis on the EVI regression model and the ET regression model, and utilizing a Boltzmann function to establish a correlation between the SHAP value of the underground water burial depth in the EVI regression model and the ET regression model and the underground water burial depth; and (4) carrying out inflection point analysis on the SHAP value-underground water burial depth relation curve of the underground water burial depth in the EVI and ET regression models, and carrying out Min analysis on an analysis result to obtain the underground water ecological burial depth. According to the method, the defect of groundwater ecological burial depth analysis in the ecological water demand evaluation research of the arid region is overcome, and an effective tool is provided for groundwater dependent terrestrial ecosystem protection.

The invention relates to a numerical mode simulation method for CO2 flux of high-resolution rice, wheat and corn, which comprises the following steps: calculating a vegetation index and a land surface water index, and carrying out inversion to obtain key vegetation parameters of a land ecosystem; the meteorological data and the topographic data are processed, meteorological field initial and boundary condition files are generated, and CO2 chemical initial and boundary condition files are generated; integrating the gridded artificial source CO2 emission data file; applying the optimized photosynthetic and respiratory action parameters to a photosynthetic and respiratory action calculation formula of the terrestrial ecosystem, and constructing a CO2 flux simulation system of the crop system; outputting the CO2 flux of the rice, the wheat and the corn in the simulation area. The method has the advantages that CO2 flux seasonal change characteristics in the key phenological period in the growth process of rice, wheat and corn are simulated, carbon cycle characteristics in the growth process of crops can be better reflected, and more reliable data support is provided for ecological meteorological research.

The invention provides a terrestrial ecosystem service function monitoring and evaluation method, and the method comprises the steps: generating a biological feature vector and an environment feature vector according to biological data and environment data collected in an ecological protection region; performing species identification on the biological feature vector based on a biological large model, performing environment analysis on the environment feature vector based on an environment large model, and obtaining animal and plant information and environment quality evaluation conditions in the ecological protection area; and based on an ecological system evaluation model, carrying out comprehensive reasoning analysis on the organisms, the environment, the comprehensive feature vectors, animal and plant information in the ecological protection area and environment quality evaluation conditions, and evaluating an ecological system service function of the ecological protection area. Wherein the comprehensive feature vector is determined based on the fusion of the biological feature vector, the environment feature vector and the dynamically adjusted weight. According to the method, the overall ecological condition of the ecological protection area can be more comprehensively understood by adopting a large model technology, and more comprehensive, accurate, dynamic and scientific ecological system service function evaluation is provided.

The invention discloses a land ecosystem carbon reserve change prediction method based on a multi-land utilization scene, and relates to the technical field of ecosystem carbon reserve prediction. The method comprises the following steps: setting a spatial resolution of land utilization, obtaining historical land utilization data of a to-be-evaluated region, carrying out reclassification, forming a first-level land type of the to-be-evaluated region, obtaining a high-definition land utilization type graph of the to-be-evaluated region, constructing a driving factor influencing land utilization change, and obtaining a high-definition land utilization type graph of the to-be-evaluated region. Historical data of the driving factors are obtained to serve as land utilization driving samples, land utilization changes of the to-be-evaluated area are simulated through a Flus model, the land utilization scene type of the area is set according to a development planning strategy of the to-be-evaluated area, and according to the simulation result of the Flus model, the land utilization scene type of the to-be-evaluated area is set. And obtaining prediction results of the number of typical land utilization and the spatial distribution condition of the to-be-evaluated region under each scene type, and respectively calculating the total carbon reserve and carbon density of the to-be-evaluated region under each prediction result by using the InVEST model.

The invention discloses a method for analyzing sensitivity of terrestrial ecosystem carbon cycle to drought, and relates to the field of carbon neutralizer.The method comprises the steps that terrestrial ecological data are collected and preprocessed, a standardized soil humidity index is calculated, and a drought event is recognized through a three-dimensional clustering method; drought characteristics are extracted, the correlation degree of the standardized land ecological data and the drought characteristics is calculated by using a Pearson's correlation method, and importance degree sorting is performed on the standardized land ecological data in combination with an interpretable machine learning method to obtain main climate driving factors; analyzing the influence degree of the drought characteristics on the change trend of the main climate driving factors by using a multi-source linear regression method; and analyzing the influence degree of the main climate-driven factors on the carbon cycle during the drought period by using the partial correlation coefficient between the main climate-driven factors and the carbon flux. The invention discloses the change rule of the land carbon sink driven by different climates.

The invention relates to the technical field of carbon sequestration and emission reduction effect evaluation, and discloses a carbon sequestration and emission reduction effect evaluation method and device for watershed vegetation restoration, and the method comprises the steps: calculating a reference carbon sequestration and emission reduction amount corresponding to a watershed reference scene scheme through a watershed terrestrial ecosystem water-carbon coupling model; setting a leaf area index and a vegetation type in the target watershed, and constructing a watershed vegetation recovery scheme based on the leaf area index and the vegetation type; calculating carbon sequestration emission reduction caused by vegetation restoration corresponding to the watershed vegetation restoration scheme by using a watershed terrestrial ecosystem water-carbon coupling model; wherein the carbon sequestration emission reduction amount caused by vegetation recovery comprises the total hydroenergy carbon emission reduction amount, the total vegetation carbon sequestration amount and the total karst carbon sequestration amount; and evaluating the carbon sequestration emission reduction effect of the watershed vegetation recovery based on the reference carbon sequestration emission reduction and the carbon sequestration emission reduction caused by the vegetation recovery to obtain a carbon sequestration emission reduction effect evaluation result. According to the method, the carbon sequestration and emission reduction effect of watershed vegetation recovery is comprehensively and reliably evaluated.

The invention relates to a digital twin construction method and system of a terrestrial ecosystem, and the method comprises the steps: obtaining animal and plant information and environment quality evaluation conditions according to biological and environmental data collected in an ecological protection area; processing animal and plant information, an environment quality evaluation condition, a biological feature vector generated based on biological data, an environment feature vector generated based on environment data and a comprehensive feature vector generated by fusing the two types of vectors based on the evaluation large model to obtain an ecological system service function evaluation result; generating a comprehensive characteristic matrix based on animal and plant information, environment quality evaluation conditions and ecological system service function evaluation results, and performing deep learning on the comprehensive characteristic matrix to construct a digital twinborn engine; and after a digital twinborn large model is constructed based on the digital twinborn engine and the model static substrate information, in response to real-time data input into the digital twinborn large model, rendering a linkage state of species, environment and ecosystem service functions on a visual interface.

The invention discloses a terrestrial ecosystem water vapor flux stable isotope multi-source estimation method, which comprises the following steps: collecting monitoring data and environmental data of a preset area, and preprocessing the monitoring data and the environmental data; performing water vapor motion characteristic analysis on the monitoring data according to a stable isotope to obtain division data, and inputting the division data into a stable isotope model to obtain water vapor flux; performing time-varying influence analysis on environmental data according to the water vapor flux to obtain an influence factor, and constructing a terrestrial ecosystem water vapor flux multi-source estimation model according to the influence factor and the monitoring data; and optimizing the terrestrial ecosystem water vapor flux multi-source estimation model, inputting to-be-estimated data into the terrestrial ecosystem water vapor flux multi-source estimation model, and outputting an estimation result. The method not only can improve the multi-source estimation precision of the water vapor flux of the terrestrial ecosystem, but also has good interpretability, and can be directly applied to a water vapor flux multi-source estimation system.

The invention provides a method and a device for acquiring an upscaling leaf moisture utilization efficiency map, and relates to the technical field of ecology. The method for acquiring the leaf moisture utilization efficiency map comprises the following steps: acquiring environmental ecological data, related to plant leaf moisture utilization efficiency, of a target area in a preset time period; according to the environmental ecological data, obtaining a carbon isotope fractionation value landscape map of the target area in a preset time period; and based on the carbon isotope fractionation value landscape map, utilizing a leaf moisture utilization efficiency calculation equation to obtain a leaf moisture utilization efficiency map of the target area in a preset time period. According to the method, derivation from the in-situ leaf scale moisture utilization efficiency to the regional large-scale carbon-water coupling index can be realized, so that a large-scale evaluation index with physiological significance is provided for carbon-water circulation and coupling research of a terrestrial ecosystem.

The invention relates to the technical field of ecological environment monitoring, and discloses a quantitative identification method for the influence of hydropower development impounding on a terrestrial ecosystem, and the method comprises the following steps: S1, laying a plurality of sampling points along the boundary of a reservoir towards the land direction; s2, collecting an ecological response variable and an environmental factor variable of each sampling point and a horizontal distance from the sampling point to a reservoir boundary as water storage influence variables, and constructing the collected data into a data matrix; s3, taking the data matrix as a response variable; s4, introducing an environment factor variable as a control variable based on a sorting analysis result; and S5, performing variance decomposition analysis based on a partial sorting analysis result, and calculating an independent explanation variance and a total explanation variance of the water storage influence variable. The land space gradient sampling points are arranged based on the water storage boundary, the spatial propagation characteristics of the water storage influence on the land are collected in a covering mode, and the effects of enhancing the representativeness of the sampling points and ensuring the capture integrity of the ecological gradient are achieved.

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

The application provides a land ecosystem gross primary productivity determination method and system, and the method comprises the following steps: collecting historical eco-hydro-meteorological data and measured values of land ecosystem gross primary productivity in a research area; constructing a generalized water-energy complementary gross primary productivity model, wherein the generalized water-energy complementary gross primary productivity model comprises a comprehensive coordination index, an energy limitation correction parameter and an available water amount correction parameter, the water amount limitation reference productivity and the energy limitation reference productivity are nonlinearly coupled by the comprehensive coordination index, the energy limitation correction parameter and the available water amount correction parameter; calibrating the comprehensive coordination index, the energy limitation correction parameter and the available water amount correction parameter; inputting the to-be-calculated eco-hydro-meteorological data into the generalized water-energy complementary gross primary productivity model after parameter calibration, and obtaining the target land ecosystem gross primary productivity. The application improves the estimation accuracy of the gross primary productivity.

The invention belongs to the technical field of gas emission of terrestrial ecosystems, and particularly discloses a method for measuring respiration and nitrous oxide emission of a facility greenhouse ecosystem, which comprises the following steps: selecting a sampling point at the middle position in a facility greenhouse according to the layout and structural characteristics of the facility greenhouse; a ventilation opening of the facility greenhouse is closed and covered with a heat preservation cotton quilt, so that the facility greenhouse is in a dark closed environment, and gas in the greenhouse is collected through an injector and then stored through a gas bag; collecting the gas sample for multiple times within several hours to form a time gradient; measuring the concentration of carbon dioxide and the concentration of nitrous oxide in the gas sample to obtain gas concentration data, and recording the gas concentration data; according to the gas concentration data and the environment information of the facility greenhouse, the ecological system respiration and nitrous oxide emission rate of the facility greenhouse are determined. The method is suitable for measuring the respiration rate and the nitrous oxide emission rate of the ecological system in the facility greenhouse, the operation is simple and convenient, and the accuracy of obtained data is relatively high.

To provide a nutrient supply management system capable of maximizing the amount of carbon dioxide absorbed and stored in the atmosphere by both blue and green carbon.SOLUTION: The nutrient supply management system includes an arithmetic unit that executes calculations related to nutrient salt supply management for marine and terrestrial ecosystems. The arithmetic unit includes a supplyable nutrient salt amount estimation unit that calculates the amount of supplyable nutrient salt based on the emissions of nutrient salts from point and non-point sources in the target area. The arithmetic unit also includes a decarbonization promotion effect evaluation unit that evaluates the effect of marine and terrestrial ecosystems on the supply of nutrient salts. The arithmetic unit also includes a nutrient salt proper distribution unit that sets allocations of nutrient salt supply to marine and terrestrial ecosystems based on the effect of promoting decarbonization.SELECTED DRAWING: Figure 1

The invention discloses a terrestrial ecosystem carbon monitoring satellite laser-assisted block adjustment method, which comprises the following steps of: three-dimensional image connection point generation: constructing a multi-stage pyramid for forward-looking and backward-looking 19-degree panchromatic images, and carrying out layer-by-layer matching inspection to obtain intra-scene and inter-scene connection points; free net adjustment: taking the connection point as control, gradually tightening a threshold and eliminating gross errors to obtain free net adjustment RPC irrelevant to absolute elevation; preparing a laser control point; laser-three-dimensional combined adjustment: taking the laser control point and the three-dimensional image connection point as observation values together, and carrying out forward intersection to obtain a corrected intersection control point; and final RPC determination: revising the image RPC again by using the revised intersection control point, and obtaining a final adjustment parameter after iterative convergence. According to the method, combined refinement of the free network and the laser absolute elevation is achieved through three-dimensional connection point hierarchical optimization, laser elevation replacement and distance reciprocal weighted coupling correction, and the geometric precision and reliability of block adjustment are remarkably improved.

The present application relates to a kind of digital twin construction method and system of terrestrial ecosystem, the method includes: according to the biological and environmental data collected in ecological protection area, obtain plant and animal information and environmental quality assessment situation;Based on the evaluation model, the plant and animal information, environmental quality assessment situation, biological feature vector generated based on biological data, environmental feature vector generated based on environmental data and the comprehensive feature vector generated by the fusion of two kinds of vectors are processed, and the ecosystem service function evaluation result is obtained;Based on plant and animal information, environmental quality assessment situation, ecosystem service function evaluation result generates comprehensive feature matrix, carries out deep learning to the comprehensive feature matrix and constructs digital twin engine;After digital twin engine and model static base information are based on and digital twin big model is constructed, in response to the real-time data of input digital twin big model, the linkage state of species, environment and ecosystem service function is rendered in visual interface.

The utility model provides a landscape ecological box capable of circulating and purifying water, which comprises a base station and a landscape wall arranged on one side of the base station, and planting blocks and a water channel are divided in the base station; a plurality of grids are arranged on the surface of the landscape wall, spraying systems are arranged in the grids, and water is taken from the spraying systems through water channels; a bottom plate of the grid comprises a soil layer and a water filtering plate, a confluence slope is arranged below the water filtering plate, seeping water is guided to an irrigation groove in the bottom layer of the landscape wall, and the planting blocks are irrigated through an irrigation system. According to the landscape ecological box, an aquatic ecological system and a terrestrial ecological system are combined, the ecological diversity is higher, the anti-risk capacity is higher, and the maintenance cost is lower; wherein a water system in the ecological box is subjected to biological purification through terrestrial plants, and cyclic utilization of water resources is achieved.

The present application relates to a kind of carbon flux synchronous measurement experimental equipment, including the monitoring device for studying soil carbon flux and the transparent cylinder for cultivating plant, the middle part of the transparent cylinder is provided with baffle, for separating the ground part and the soil part of plant in two independent chambers, for accommodating the chamber side wall of plant soil part is also provided with liquid supply interface for providing nutrient solution to plant, the baffle is opened with the perforation for facilitating plant to pass through, the two ends of the transparent cylinder are connected on the monitoring hole of monitoring device respectively.The experimental equipment of the present application can be used to monitor the related parameters of soil respiration under ground, and also can be used to monitor the carbon flux variation parameters above ground, and at the same time, two groups of monitoring data above ground and underground are obtained, which is beneficial to further study the relationship of soil respiration, and has important significance for promoting the carbon flux research of terrestrial ecosystem.

The application provides a method for monitoring and evaluating the service function of a terrestrial ecosystem, which comprises: generating biological feature vectors and environmental feature vectors according to biological data and environmental data collected in an ecological protection zone; performing species identification on the biological feature vectors based on a biological large model and performing environmental analysis on the environmental feature vectors based on an environmental large model to obtain information about animals and plants and an environmental quality evaluation situation in the ecological protection zone; and performing comprehensive reasoning analysis on the biological, environmental and comprehensive feature vectors and the information about animals and plants and the environmental quality evaluation situation in the ecological protection zone based on an ecosystem evaluation model to evaluate the service function of the ecosystem of the ecological protection zone, wherein the comprehensive feature vectors are determined based on the fusion of the biological and environmental feature vectors and dynamically adjusted weights. The application can comprehensively understand the overall ecological condition of the ecological protection zone by using the large model technology and provide a more comprehensive, accurate, dynamic and scientific evaluation of the service function of the ecosystem.

The invention discloses an ecological carbon sink potential prediction method and system based on a fusion attention mechanism, and relates to the technical field of ecological carbon sink monitoring and image processing, and the method comprises the steps: obtaining a to-be-evaluated scene reflectivity image and meteorological variable data of a to-be-evaluated time period; image local features are extracted from the reflectivity image through CNN, and meteorological variable features are extracted from meteorological variable data through BiLSTM; calculating a meteorological time sequence vector based on an attention mechanism; dynamic weights of the image local features and the meteorological time sequence vector features are calculated, and weight fusion features are obtained through the dynamic weights corresponding to the image local features and the meteorological time sequence vector features; inputting the weight fusion features into a full connection layer for processing, and mapping feature variables to a prediction space to obtain predicted ecological carbon sink data of the scene to be evaluated in the time period to be evaluated; the technical difficulty that the carbon sink change cannot be accurately predicted under the large-range and high-precision practical demand of the current land ecosystem carbon sink estimation is solved.

The fusion foundation multi-source satellite chlorophyll fluorescence regional GPP assimilation inversion system belongs to the technical field of terrestrial ecosystem carbon cycle monitoring, and comprises an observation data acquisition module; a signal unmixing and simulation generation module, which is used for unmixing total fluorescence into pure chlorophyll fluorescence SIF, and driving an ecological model to generate SIF and GPP simulation values based on environmental stress data; a state component decoupling module, which is used for decoupling total GPP simulation values into a light response fast component, a slow component and a memory component; a state evolution prediction module, which is used for predicting dynamic evolution of the slow component and the memory component; and an adaptive assimilation inversion module, which is used for taking the slow component and the memory component as state variables, taking SIF observation values as observation data, and combining a prediction result of the state evolution prediction module to perform inversion on regional GPP. The system overcomes systematic deviation caused by model simplification or data singularity in traditional methods.

This invention relates to a method for estimating soil organic carbon sequestration by crop residue return to the field, comprising: acquiring and processing multi-source data; simulating the photosynthetic carbon assimilation and CO2 flux released by respiration of major cereal crops; extracting the net CO2 flux of MCCs (Mechanical Control Cells) in terrestrial ecosystems; calculating the net assimilated carbon allocation of each component of MCCs during their growth cycle; determining the distribution of biomass carbon in different straw management practices; and calculating the total soil organic carbon sequestration by MCC residue return to the field in all grid units based on the local soil organic carbon conversion rate. The beneficial effects of this invention are: by quantifying the allocation of net assimilated carbon to components such as rhizosphere deposition, crop roots and stubble, collectable straw, and grains, this invention provides crucial support for assessing the carbon cycle and soil organic carbon sequestration potential of farmland ecosystems.

The invention relates to the technical field of global terrestrial ecosystem carbon cycle component remote sensing estimation, in particular to a collaborative inversion method, system and device for a global terrestrial ecosystem carbon cycle component, and the method comprises the following steps: obtaining global-scale ground station observation data and image data, and carrying out the preprocessing; establishing a database based on the preprocessed data, performing carbon balance correction and carbon component separation on ground station observation data in the database, and matching the ground station observation data with image data to construct a data set; and training the random forest model by using the data set to obtain a global terrestrial ecosystem carbon cycle component collaborative inversion model, and carrying out product production by using the global terrestrial ecosystem carbon cycle component collaborative inversion model. According to the method, a global terrestrial ecosystem carbon cycle component remote sensing product which simultaneously meets the mass conservation constraint and is high in precision can be provided, improvement of understanding of dynamic changes of terrestrial ecosystem carbon cycles is facilitated, and a solid foundation is provided for global carbon accounting and carbon trading.

The present invention discloses a method for monitoring terrestrial ecosystem carbon sources and sinks based on satellite remote sensing, comprising the following steps: 1) preparing satellite remote sensing data; 2) preparing ground observation data; 3) calculating vegetation cover based on the Normalized Difference Vegetation Index; 4) calculating the carbon density of aboveground and belowground biomass; 5) optimizing and calibrating key algorithm parameters; 6) calculating the autotrophic respiration rate of vegetation; 7) calculating the heterotrophic respiration rate of soil; and 8) characterizing the carbon source and sink of the vegetation ecosystem by net ecosystem carbon exchange. This method addresses the shortcomings of existing estimation methods, such as their inability to monitor over a large area, high cost, and inapplicability to areas with high spatial heterogeneity. By using satellite remote sensing data and ground observation data of a target pixel as input, this method calculates the ecosystem carbon source and sink, representing the carbon exchange between the vegetation ecosystem and the atmosphere in the target pixel. This method offers the advantages of wide monitoring range, high accuracy, and high feasibility.

The invention discloses a land ecosystem carbon source sink assimilation prediction method and device based on adaptive moment estimation, equipment and a medium. The method comprises the following steps: collecting a meteorological data set; the meteorological data set is input into the optimized carbon cycle model to predict the carbon flux, the carbon cycle model comprises a photosynthesis model and a respiratory action model, the photosynthesis model is used for obtaining photosynthesis flux, and the respiratory action model is used for obtaining respiratory action flux; wherein the optimization process of the carbon cycle model comprises the following steps: carrying out data assimilation on model parameters of the carbon cycle model by adopting an adaptive moment estimation algorithm, and constraining carbon flux to obtain an initially optimized carbon cycle model; fitting photosynthesis flux and respiratory flux based on the carbon cycle model of the initial optimization model parameters, and automatically constraining flux sum with poor fitting effect according to the fitting effect to obtain a final optimized carbon cycle model.

The present application relates to the technical field of ecological environment monitoring, and discloses a quantitative identification method for the influence of water storage in water and electricity development on terrestrial ecological system, comprising the following steps: S1, arranging a plurality of sampling points along the reservoir boundary towards the land; S2, collecting the ecological response variable, the environmental factor variable and the horizontal distance from the sampling point to the reservoir boundary as the water storage influence variable for each sampling point respectively, and constructing the collected data into data matrices respectively; S3, taking the data matrices as the response variable; S4, introducing the environmental factor variable as the control variable based on the sorting analysis result; S5, performing variance decomposition analysis based on the partial sorting analysis result, and calculating the independent explained variance and the total explained variance of the water storage influence variable. Through the setting of land space gradient sampling points based on the water storage boundary, the spatial propagation characteristics of the water storage influence on the land are collected in a covering manner, so that the representativeness of the sampling points is enhanced, and the integrity of the ecological gradient is ensured.