19 results about "Primary productivity" patented technology

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 remote sensing estimation method and a remote sensing estimation device for the primary productivity of marine phytoplankton in size fraction, and the method comprises the steps: building an estimation function of the photosynthetic quantum yield of the phytoplankton in the corresponding size fraction based on the relation between the light intensity and the photosynthetic quantum yield of the phytoplankton in the single size fraction; calculating the net primary productivity of the phytoplankton of the corresponding size fraction based on the photosynthetic quantum yield and the average light absorption coefficient of the phytoplankton of the single size fraction under the scale of the light intensity duration and the ocean depth measurement range; and adding the net primary productivity of the phytoplankton in the plurality of size fractions, and calculating to obtain the total primary productivity of the phytoplankton. By adopting the technical scheme, in a framework of light absorption and conversion of the phytoplankton, the light absorption coefficient of the phytoplankton with different size fractions and the size fraction difference of the photosynthetic quantum yield are considered at the same time, an effective scheme for quantitative expression estimation of the phytoplankton is established, the estimation error of the primary productivity caused by neglecting the size fraction difference can be effectively reduced, and the estimation accuracy of the primary productivity is improved. And the estimation accuracy is improved.

The present application relates to the technical field of remote sensing, in particular to a method for estimating total primary productivity of pantropical forest vegetation depending on leaf age, which comprises obtaining a weather basic data set and a leaf age-based vegetation leaf area index data set, grouping current leaves according to leaf age, including new leaves, mature leaves and old leaves, obtaining the maximum light energy utilization rate of all leaves, and outputting the final productivity through a remote sensing estimation model of total primary productivity. The present application considers the regulation of leaf phenology on canopy photosynthesis, distinguishes the photosynthetic capacity difference between leaf age components, and constructs a remote sensing estimation method suitable for total primary productivity of pantropical forest vegetation, so as to improve the simulation accuracy of total primary productivity of pantropical forest vegetation, and help to accurately monitor the evolution trend of photosynthesis of pantropical forest under climate change.

The invention discloses a crop remote sensing yield estimation method and device fusing meteorological data and planting information, a medium and a product, and relates to the technical field of agricultural informationization, and the method comprises the steps: obtaining basic data of a to-be-estimated area; determining daily total primary productivity of the crops according to the meteorological data and the remote sensing image data; determining overground biomass of the crops according to the daily total primary productivity and the key growth period of the crops; according to the variety information and the remote sensing image data, constructing a filling period vegetation index attenuation model; the filling stage vegetation index attenuation model is used for dynamically determining a harvest index; according to the above-ground biomass and the harvest index of the crop, determining a per unit yield result of the crop; the accuracy of crop yield estimation can be improved.

This invention discloses a method for assessing ecosystem service losses due to regional climate change. The region includes counties, cities, or important ecological function zones. The steps are as follows: S1. Collect remote sensing data and preprocess the data through band combination, geometric correction, and projection transformation. Select a standard color composite scheme, establish interpretation markers, and perform visual interpretation. S2. Calculate and statistically analyze the unit area yield value and equivalent factor of grain crops. The equivalent factor is 1 / 7 of the average market value of grain in the current year. S3. Statistically analyze land use types, calculate the magnitude of land use change, reflecting the changes in the total amount of different land use types and the overall trend of land use type changes. S4. Select vegetation cover as an indicator, and adjust the ecosystem service value based on two parameters: net primary productivity and vegetation cover. This invention is of great significance for formulating ecosystem management strategies under the background of future climate change.

The invention discloses a novel in-situ primary productivity testing system, and relates to the technical field of aquatic ecology monitoring. Comprising an excitation light source module, an in-situ culture module, a fluorescence detection module, a control module and a data processing module, the excitation light source module comprises at least two excitation light sources with different wavelengths, at least one of the excitation light sources comprises a quantum dot material, and the excitation light sources are used for performing spectrum regulation and control on light emitted by the light sources so as to output specific excitation light; the in-situ culture module is used for performing in-situ culture on target algae and maintaining an in-situ environment for algae growth; the control module is respectively connected with the excitation light source module and the in-situ culture module, and is used for controlling the running state of the in-situ culture module and the alternate lightening time sequence of the at least two excitation light sources; and the fluorescence detection module is used for detecting characteristic fluorescence emitted by target algae after being excited by the excitation light source, and acquiring an intensity parameter of the characteristic fluorescence.

The application discloses a CASA model net primary productivity simulation method and system, and the method comprises the following steps: collecting real-time position data of a side mold, pressure data of a hydraulic system and temperature data of a mold contact surface through a multi-sensor fusion module; based on the real-time position data, the pressure data and the temperature data, a dynamic friction and thermal deformation coupling model in a side mold movement process is constructed, and a position deviation trend in a current stroke stage is predicted; according to the position deviation trend and a preset mold closing accuracy requirement, a dynamic compensation strategy of the side mold stroke based on a fuzzy adaptive PID is generated; the dynamic compensation strategy is executed, the hydraulic cylinder flow and pressure are adjusted in real time through a high-frequency servo valve group, and position closed-loop correction is completed within one stroke cycle. By using the embodiment of the application, intelligent prediction and adaptive configuration of CASA model static parameters in a large range and a multi-vegetation type region can be realized, and the precision, the automation degree and the cross-region generalization capability of net primary productivity simulation are improved.

The application discloses a farmland corn yield estimation method based on high-resolution remote sensing data, comprising the following steps: determining the net primary productivity (NPP) of a corn farmland at a pixel level; establishing an NPP estimation model, calculating the cumulative NPP in a growing season according to phenological data, and collecting provincial NPP data; calculating the proportion of each pixel in the provincial NPP, obtaining the pixel-level corn yield according to the provincial statistical corn yield data, and performing yield monitoring and spatial variation analysis. The application predicts the farmland corn yield based on high-resolution satellite remote sensing data, evaluates the variation of regional corn yield from the perspective of yield refinement, and realizes accurate guidance of agricultural production.

The invention provides a crop yield remote sensing inversion method based on a chlorophyll fluorescence mechanism, and belongs to the technical field of agricultural crop growth monitoring, and the method comprises the steps: obtaining sunlight-induced chlorophyll fluorescence remote sensing data, photosynthetically active radiation data and crop type distribution data in the whole growth period of crops; and distinguishing the photosynthetic path according to the crop type distribution data, calculating by adopting a corresponding photoreaction mechanism model based on the obtained data to obtain the total primary productivity of the crop, obtaining the net primary productivity by combining the historical net primary productivity and the total primary productivity ratio, and obtaining the crop yield based on carbon content inversion. By utilizing coupling association between sunlight-induced chlorophyll fluorescence and a photosynthesis process, the problem that photosynthetic physiology in vegetation is difficult to effectively capture due to dependence on a static vegetation index in an existing crop technology is solved; the problem of how to accurately associate instantaneous sunlight-induced chlorophyll fluorescence remote sensing data with photosynthesis of crops in the whole growth period is solved.

The application discloses an intelligent prediction method for corn yield, a multilayer feedforward neural network model is obtained through training, the multilayer feedforward neural network model is trained through a genetic method, and the obtained prediction model has higher prediction accuracy when predicting the corn yield; the method can obtain more accurate prediction data of the corn growth state by assimilating vegetation net primary productivity data which has a greater influence on the corn yield, the network model is updated based on the prediction data, the model is better adapted to the current corn growth data, and the accuracy of the corn yield prediction is improved; the method can more scientifically and reasonably predict the corn yield by improving the prediction operation speed of the multilayer feedforward neural network model, so that the corn production and management measures can be accurately adjusted in time.

The invention discloses a method and a system for estimating the gross primary productivity of vegetation, relates to the field of ecological remote sensing and carbon cycle research, and is used for estimating the gross primary productivity of grassland vegetation by using an IPCM model provided by the invention, so that the precision can be greatly improved. And the problems of large systematic deviation and insufficient trend consistency of the original PCM model in the GPP estimation of the climate fluctuation region are effectively solved. Meanwhile, the calculation of the VPD and SWC joint stress factor is completely based on remote sensing data, the calculation process is simple, and the practicability and the operation efficiency of the new model are greatly improved. In addition, the combined stress factor also shows good environmental adaptability and stable estimation effect in an ecological region with complex and diverse climate conditions and remarkable annual fluctuation.

The application provides a kind of cultivated land production function simulation evaluation and limiting factor identification method and system, by dividing agricultural climate resource homogeneous region and distinguishing cultivated land crop type, weaken the water and heat condition difference of research area and the spatial heterogeneity of cultivated land production function caused by crop type difference.On this basis, with the accumulated total primary productivity of corresponding growth period stage of grid unit scale crop as the indicator of cultivated land production function, through geographic regression model and machine learning interpretability method, the dominant limiting factor and its trigger condition affecting the cultivated land production function are detected, and the model obtained based on statistical regression fitting is used to evaluate the cultivated land production function level of the whole research area, and the main limiting factors and improvement targets of cultivated land production function improvement under different climate conditions and different crop type scenarios are quantitatively calculated, to provide construction scheme for low-yield field improvement.The application solves the problem that the existing cultivated land production capacity limiting factor is difficult to quantitatively calculate, so that the low-yield field is difficult to improve.

This invention provides a spatial simulation method for regional crop yield based on remote sensing water-carbon coupling processes. Driven by remotely sensed soil moisture data and multi-source meteorological data, this method constructs a coupled iterative framework of crop growth, remote sensing water-carbon coupling, and water balance modules. It achieves regional-scale spatial simulation of crop leaf area index, evapotranspiration, total primary productivity, and crop yield at a fixed time scale. The spatial distribution of crop yield is obtained by cumulatively calculating total primary productivity over the crop's growth period. This invention does not rely on field sample data, can reflect spatial differences in crop yield within a region, and is suitable for regional agricultural productivity assessment and agricultural drought impact analysis.

1. Name of the product in this design: Electronic device with a graphical user interface displaying agricultural product system content. 2. Purpose of this design: To showcase the agricultural product system and its specific contents. 3. The key design features of this product are the content and layout of the user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. The application platform computer is an existing design, and other views are omitted. 6. Purpose of the graphical user interface: To display the agricultural product system and its specific details to users. 7. Human-computer interaction method of graphical user interface: The main view is the overlay screen of the main interface, which is a graphical user interface that displays the agricultural product system and its specific content; clicking the corresponding icon button in the main interface can enter the corresponding interface and download the corresponding file. 8. Other situations requiring explanation: The clickable button locations are in the usage status reference map, including derivative products, productivity level, aboveground biomass, grain yield per unit area, phenological period, vegetation index, crop growth, net primary productivity (NPP), planning analysis, identification of non-grain use in high-standard farmland, distribution of high-standard farmland, distribution of grain production functional zones, analysis of current seed value status in grain production functional zones, basic products, arable land properties, distribution map of heavy metal pollution, distribution map of arable land quality grades, distribution map of soil fertility, arable land types and distribution, and arable land classification. Distribution maps (irrigated land, dry land, paddy fields, orchards, tea gardens, nurseries), flat farmland distribution map, sloping farmland distribution map, planting space distribution map, potato planting distribution map, greenhouse distribution map, rice (2 seasons), wheat planting distribution map, rapeseed planting distribution map, corn planting distribution map, extended products, farmland spatial morphology: plot shape index, plot contiguousness, landscape index, farmland monitoring, increase and decrease of sloping farmland, increase and decrease of farmland, farmland utilization level, farmland pressure index, reclamation index, farming convenience, farmland radius, planting ratio, multiple cropping index.

The present application provides a kind of terrestrial ecosystem aboveground and underground net primary productivity estimation method and system, comprising obtaining vegetation aboveground and underground net primary productivity observation data and resource availability data;According to the aboveground net primary productivity observation data, the comprehensive rate framework parameter is calibrated, and the aboveground net primary productivity simulation value is estimated based on the comprehensive rate framework parameter;Based on the vegetation aboveground and underground net primary productivity observation data, the aboveground and underground net primary productivity distribution proportion is estimated;The aboveground net primary productivity simulation value obtained based on the aboveground and underground net primary productivity distribution proportion is used to estimate the underground net primary productivity simulation value.The present application has good applicability;It can be used to simulate the temporal and spatial distribution law of vegetation productivity, stably evaluate the evolution dynamic of vegetation net primary productivity, help to evaluate global carbon model, further accurately evaluate regional carbon balance level, and deepen the understanding of complex dynamic of global carbon balance under changing climate conditions.

The invention relates to the technical field of remote sensing, in particular to a remote sensing estimation method for total primary productivity of ubiquitous tropical forest vegetation depending on leaf age, which mainly comprises the following steps: acquiring a weather basic data set and a vegetation leaf area index data set based on leaf age, grouping current leaves according to leaf age, and calculating the total primary productivity of the ubiquitous tropical forest vegetation based on the leaf age. Comprising new leaves, mature leaves and old leaves, the maximum light energy utilization rates of the sunny leaves and the shaded leaves of all the leaves are obtained respectively, and final productivity is output through a vegetation total primary productivity remote sensing estimation model. The remote sensing estimation method suitable for the general primary productivity of the generic tropical forest vegetation is constructed by considering regulation and control of phenology of leaves on photosynthesis of canopies and distinguishing photosynthetic capability differences among leaf age components, so that the general primary productivity simulation precision of the generic tropical forest vegetation is improved, and the method is suitable for mass production of the generic tropical forest vegetation. Meanwhile, the evolution trend of the photosynthesis of the ubiquitous tropical forest under the climate change can be accurately monitored.

The application discloses a kind of in-situ measurement methods of aquatic primary productivity based on fluorescence excitation spectrum three-wavelength fitting model, belong to environmental monitoring and aquatic ecosystem technical field.The application includes: in-situ collection target water body water sample and filter to remove large particle impurities;Water sample is moved into fluorescence spectrophotometer sample cell, and after dark chamber balancing, the fluorescence intensity of 438nm, 485nm, 624nm three characteristic wavelengths is measured;According to water sample type, the integral area of fluorescence excitation spectrum is calculated using corresponding first-order linear fitting equation;Through the correlation model of integral area and primary productivity, the primary productivity of target water body is calculated.The application does not need sample pretreatment, simple and fast, measurement period is ≤30min, realizes in-situ non-invasive monitoring;Cover a variety of photosynthetic pigment characteristic absorption peak, wide application range, can tolerate a variety of stress conditions;Measurement precision is high, sensitivity is strong.

The invention discloses a method for measuring the optimal application amount of a degraded warm desert steppe sheep manure organic fertilizer, and relates to the technical field of damaged steppe ecosystem remediation, the method comprises the following steps: in a warm desert steppe area, selecting a degraded grassland with the vegetation coverage lower than 30%, the net primary productivity on the ground lower than 10g / g and the dominant plant of silver gray hedge; uniformly spreading the fermented and decomposed sheep manure organic fertilizer on the ground surface of an experiment area independently set for the corresponding sheep manure organic fertilizer addition amount value in the middle stage of the plant growth season, and not turning over; at the last stage of the plant growth season, the overground net primary productivity of the plants in each experiment area is measured; carrying out modeling analysis by using a threshold regression function in a'chngpt 'program package; and determining a numerical value corresponding to an inflection point which is identified by the model and has a significant change of the dependent variable along with the increase trend of the independent variable as an optimal additive amount threshold value. According to the method, the repairing object can be accurately judged, and the optimal adding amount threshold value of the sheep manure organic fertilizer can be quantitatively determined.