14 results about "Terrestrial ecosystem" patented technology

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 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 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 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.

The invention relates to the technical field of environmental ecology, in particular to application of a plant-litter-soil continuum in a terrestrial ecosystem. The method comprises the following steps: S1, setting a plurality of standard sample plots in a research area; s2, litter samples and soil samples with different depths in the sample plot are collected; s3, calculating an important value, a community diversity index and a stability index of the plant; s4, evaluating a response mechanism of the plant to soil elements through the homeostatic state model; and S5, disclosing a migration path and a driving mechanism of elements in the plant-litter-soil continuum by utilizing statistical analysis and a structural equation model. According to the application of the plant-litter-soil continuum in the terrestrial ecosystem, provided by the invention, the complex relationship among plant-litter-soil and microbial biomass stoichiometric characteristics is disclosed; the plants, the litters and the soil are closely associated and jointly promote nutrient circulation of the system.

The application discloses a kind of ecological carbon sink potential prediction method and system based on fusion attention mechanism, it is related to ecological carbon sink monitoring and image processing technical field, the method includes: obtaining the reflectivity image of the scene to be evaluated, and the meteorological variable data of the time period to be evaluated;Image local feature is extracted from reflectivity image by CNN, meteorological variable feature is extracted from meteorological variable data by BiLSTM;Meteorological time series vector is calculated based on attention mechanism;The dynamic weight of image local feature and meteorological time series vector feature is calculated, and the weight fusion feature is obtained by the respective dynamic weight;Weight fusion feature is input into fully connected layer and is processed, feature variable is mapped to prediction space to obtain the predicted ecological carbon sink data of the scene to be evaluated in the time period to be evaluated;Solve the technical difficulties that current terrestrial ecosystem carbon sink estimation cannot accurately predict carbon sink change under the real demand of large range and high precision.

The invention discloses a terrestrial ecosystem atmospheric phosphorus sedimentation downscaling method based on space-time quality constraint, and belongs to the technical field of atmospheric science data processing. Comprising a data preprocessing step, a hierarchical sampling strategy-based model initialization step, a mass conservation constraint-based iterative model retraining and optimization step and a spherical high-resolution atmospheric phosphorus settlement data set generation step. The method comprises the following steps of: establishing a unified space reference, generating a unified land mask by taking data with a minimum land coverage range in all data sets as a reference, determining a downscaling target resolution, processing high-resolution auxiliary variable data, unifying all high-resolution auxiliary variables for model training to the target resolution through a resampling method, and obtaining a high-resolution auxiliary variable data set; according to the method, to-be-downscaled low-resolution data is processed, a generated land mask is uniformly applied to all processed auxiliary variable data and target variable data, raster data outside the mask range is removed, and it is ensured that geographic boundaries and effective data ranges of all data sets are completely consistent.

This invention is a demonstration device that combines a multi-level modular frame, a terrestrial ecosystem module, an aquatic ecosystem module, a reservoir, a control panel, an electronic controller, a media humidity sensor, a temperature sensor, a display, a water pump, and a water channel. All three modules are individual containers located at different levels. The pump is connected to the reservoir and supplies water to the terrestrial ecosystem module through channels that are at least partially located in the visible portion of the frame. The controller periodically reads the sensors, displays the data and system status, activates the pump when the humidity is below a lower threshold, maintains the pump state when the value is between the two thresholds, and turns the pump off when the humidity reaches an upper threshold. This arrangement allows the relationship between media conditions, sensor data, controller decisions, and water distribution to be observed in a single demonstration device that can be produced as a learning kit.

The invention discloses a land ecosystem carbon flux prediction method and system based on space-time decomposition. Relates to the technical field of environmental science. The method comprises the following steps: acquiring original carbon flux data and correspondingly matched environment covariable data; decomposing the original carbon flux data into a spatial component sample set I1 and a time component sample set I2; calculating to obtain a feature set S0 and a feature set FT according to the environment covariable data; key factors are screened from the feature set S0 to form a final space input feature set FS, and a space component result O1 is obtained through prediction according to the environment covariable data corresponding to the I1 and the final space input feature set FS; according to the environment covariable data corresponding to the I2 and the feature set FT, predicting to obtain a time component result O2; adding the space component model prediction result O1 and the time component model prediction result O2 to obtain a final carbon cycle estimation value; and predicting by using the estimated value to obtain a carbon cycle space result.

The invention discloses a terrestrial ecosystem carbon monitoring satellite three-vision stereo image construction and dense matching DSM acquisition method, which comprises the following steps: carrying out 5 * 5 block SIFT registration and RANSAC gross error removal on 19-degree foresight, rearview panchromatic and multispectral images, establishing an eight-parameter affine model, carrying out bicubic convolution resampling, and then carrying out DDS (Dense Scale Invariant Feature Transform) calculation on the DDS; multiplicative fusion is carried out in a W * W window according to a red-green-blue three-waveband linear fitting coefficient, and a 3.5 m four-waveband fusion image is generated; converting the four-band DN values of the front-view, front-view and rear-view fused image into a single band in a geometric average manner, and binding a corresponding RPC (Remote Procedure Call); initializing the equal-height layer grid; constructing n layers of 2-time resolution decreasing pyramids; from the top layer to the bottom layer, elevation searching is carried out at 1.5 times of grid step length, three-view images are projected through RPC, the minimum cost of 5 * 5 window correlation coefficients is taken, SGM is used for aggregating the optimal elevation, and DSM is refined and output layer by layer. According to the method, the consistency of the resolution and the spectrum of the three-view image of the carbon monitoring satellite is realized, the DSM precision and efficiency are improved, and the method is suitable for inversion of forest canopy height and carbon reserves.