49 results about "Ground survey" patented technology

The invention discloses an ecological system monitoring method based on an INVEST model, and belongs to the technical field of ecological system monitoring, and the method comprises the steps: S1, building a unified ecological monitoring data frame through satellite remote sensing, an Internet of Things sensor and a ground survey multi-source data collection and cleaning algorithm; s2, dynamically adjusting INVEST model parameters based on regional ecological characteristics and a machine learning algorithm, according to the method, ecological system services are quantitatively evaluated by using an INVEST model core module, key ecological parameters are extracted in combination with a remote sensing inversion technology, the problems that traditional ground survey is high in cost and limited in coverage range are solved, and the method is suitable for large-scale popularization and application. The remote sensing data preprocessing and classification algorithm improves the efficiency and precision of surface feature information extraction, the PLUS model simulates the land utilization change scene and CMIP6 climate scene input, the INVEST model is combined to quantify the future ecosystem service function, and the limitation that the traditional static assessment cannot cope with the dynamic environment change is solved.

The invention discloses a natural resource geographic information collection method and system, and belongs to the technical field of geographic information collection, and the method comprises the steps: obtaining natural resource geographic information data, and carrying out the data preprocessing of the multispectral image data in the data; optical abnormal data in the preprocessed multispectral image data are marked, meanwhile, ground abnormal data in ground survey fixed-point measurement data are marked, and geospatial alignment is carried out; identifying a highly overlapped region in the geographic space, and automatically attributing and judging an abnormal mode in the highly overlapped region as being caused by a specific unrecorded environment event; and adding an environmental event influence mark to the attributed natural resource geographic information data, wherein the environmental event influence mark is used for indicating the physical cause of the natural resource geographic information data exception. According to the method and the device, numerical value change relevance caused by the same physical cause in different natural resource geographic data types can be identified, and wrong geographic information interpretation results caused by data inconsistency in subsequent analysis are avoided.

The invention provides a multi-tree forest aboveground biomass remote sensing estimation method and system and a storage medium, and the method comprises the steps: obtaining multi-source remote sensing data based on a target region, including airborne LiDAR point cloud, ground survey data and DEM data; constructing a terrain heterogeneity index DGTHI in combination with DEM data, and quantifying terrain complexity through weight fusion of standardized terrain factors; extracting forest characteristic parameters and calculating the overground biomass of the single tree; performing classification modeling on the sampling region based on DGTHI, respectively establishing multiple linear regression models for different tree species, and optimizing feature parameter selection; and evaluating the precision of the model through cross validation, and popularizing the model to a county scale to perform overground biomass space inversion and mapping. According to the method, terrain heterogeneity classification and tree species specificity modeling are fused, so that the estimation precision of the forest biomass in the complex terrain region is remarkably improved, and a technical support is provided for regional carbon sink monitoring and sustainable forestry management.

The invention provides a mangrove forest degradation type and reason identification method and system based on remote sensing and a multi-factor index system. The method comprises the following steps: firstly, integrating a multi-temporal remote sensing image, ecological monitoring data and ground survey data, and constructing a systematic degradation factor index system covering natural, climate, biological and human factors; secondly, extracting typical degradation characteristics such as vegetation coverage decline and species composition change by using a remote sensing change detection technology and a principal component analysis method; then, through K-means clustering, an ecological classification algorithm based on rules and an ecological threshold standard, mangrove forest degradation types are identified and classified, and the types comprise a man-made interference type, a biological erosion type, a natural succession type and a multi-factor coupling type; then, adopting a supervised machine learning model and combining a feature importance evaluation method such as a Shapley value to identify a degradation cause and a weight thereof; and finally, verifying the precision of the model through an on-site monitoring quadrat and an expert interpretation result, and outputting visual results such as a degradation type distribution diagram, a factor contribution distribution diagram and the like.

The invention belongs to the field of remote sensing, and provides a straw coverage rate estimation method based on soil type zoning, which comprises the following steps: determining the soil type in a research area, and performing soil zoning; aiming at each subarea of different soil types in the research area, acquiring an unmanned aerial vehicle image, and calculating a straw coverage rate; acquiring an optical satellite remote sensing image at the same time as the ground survey of the research area, and calculating features; for each soil type partition, performing correlation analysis on the features, selecting the features related to the straw coverage rate as input, and combining the features of different types to form a feature combination; and for each soil type partition, taking the sample and feature combination as input, establishing a straw coverage rate estimation model by using a random forest regression algorithm, and estimating the straw coverage rate of a non-sample point area. According to the method, the collection efficiency and reliability of ground straw coverage rate samples are remarkably improved, and meanwhile, the precision of straw coverage rate estimation under the background of various soil types is greatly improved.

The invention belongs to the field of degraded grassland restoration evaluation research, and discloses a degraded grassland restoration evaluation research method based on multivariate remote sensing data, and the method comprises the steps: carrying out the observation through employing a FragMap unmanned aerial vehicle aerial photography analysis system, and carrying out the preprocessing through employing Pixel Base Management Classifier software; collecting grassland above-ground biomass data; acquiring and preprocessing remote sensing data; constructing a grassland coverage and aboveground biomass remote sensing estimation model, and performing precision verification; analyzing grassland coverage and biomass space difference before and after restoration of the degraded grassland; and analyzing space-time dynamic changes of grassland coverage and biomass. According to the method, a high-temporal-spatial-resolution NDVI data set of a research area is constructed by combining a high-temporal-spatial-resolution data fusion algorithm, a grassland coverage and aboveground biomass remote sensing estimation model is constructed by combining ground survey and unmanned aerial vehicle aerial photography, and the grassland coverage and aboveground biomass change conditions before and after a degraded grassland restoration measure is implemented are systematically evaluated. And the restoration effects of different restoration measures on the degraded grassland are evaluated.

The invention relates to the technical field of wetland data monitoring, and discloses a coastal wetland carbon reserve dynamic monitoring method based on time sequence remote sensing, which comprises the following steps: collecting the vegetation condition of a coastal wetland, speculating the carbon reserve of the coastal wetland, judging whether the carbon reserve is abnormal or not, and correspondingly adjusting a detection scheme. According to the coastal wetland carbon reserve dynamic monitoring method based on time sequence remote sensing, multiple methods such as remote sensing monitoring, ground survey and laboratory analysis are comprehensively considered, the comprehensiveness and accuracy of carbon reserve monitoring are ensured, the comparison threshold is dynamically adjusted through two-time judgment in combination with historical data and a verification conclusion, and the carbon reserve monitoring accuracy is improved. The method adapts to carbon reserve change conditions of different sub-regions, forms a systematized monitoring process from region division to overall analysis, can effectively identify abnormal conditions in a target region, improves the reliability of carbon reserve assessment through comparison verification and collection verification, and improves the accuracy of carbon reserve assessment. And reliable data support is provided for subsequent monitoring and management.

The invention discloses a coastal zone nitrogen and phosphorus reduction effect evaluation method, which comprises the following steps: acquiring multispectral image data and a digital surface model, and acquiring actual gradient, altitude and long-term hydrological dynamic data through ground actual measurement, sampling and investigation; extracting core parameters, correcting a digital surface model by utilizing ground actual measurement altitude data, constructing a target coastal zone precise digital elevation model, determining a gradient and dividing a gradient interval, and identifying a target coastal zone type and a planting / slope protection combined structure by combining multispectral image data, ground survey data and the digital surface model; obtaining a nitrogen and phosphorus reduction reference value according to the core parameters, extracting a rainfall intensity correction coefficient and a water level amplitude correction coefficient in combination with hydrological dynamic data, and calculating a final nitrogen and phosphorus reduction proportion; and spatial visualization is carried out, so that efficient, accurate and standardized evaluation of the nitrogen and phosphorus reduction effect of the coastal zone is realized, and a scientific basis is provided for design, optimization and effect inspection of ecological restoration engineering of the coastal zone.

The invention relates to the technical field of forestry prevention and control, in particular to a pine wood nematode disease autumn general survey ground survey method which comprises the following steps in specific use: recording survey site data; recording survey image data; drawing a survey site diagram; downloading survey image data; writing a survey report; the survey site can be quickly and accurately searched, the survey site and image data are recorded and transmitted, a survey table is filled and reported, and a survey report is formed; in this way, the technical problems that in the prior art, a ground checking method is low in checking speed, difficult in data transmission and low in working efficiency are solved; according to the method, the Ovui map is used, so that the survey site can be quickly and accurately found, and survey site data is recorded; according to the method, a today watermark camera is used, survey image data can be rapidly and accurately recorded and transmitted, and autumn general survey work can be accurately evaluated.

To provide a site information management system capable of accurately grasping the construction status at a site by a work machine for carrying out ground survey, ground work, foundation work, etc., even from a remote location without substantial time delay. [Solution] The system includes a construction management device (20), a gateway (40), a cloud server (10) that stores ground information for the site, and a viewing terminal (60) connected to the cloud server (10). The construction management device (20) sequentially generates text-format transmission data related to the operating status of a work machine (200), sequentially generates on-site construction status data based on the ground information for the site acquired from the cloud server (10) and the transmission data, and displays the construction status at the site. The cloud server (10) sequentially generates construction status data for viewing based on the ground information for the site and the transmission data acquired from the construction management device (20) via the gateway (40). The viewing terminal (60) displays the construction status at the site based on the construction status data for viewing.

The invention discloses a high-position landslide identification method based on cooperation of multi-source remote sensing and ground survey, and belongs to the technical field of geological disaster monitoring and identification. Comprising the following steps: constructing a multi-source information basic data set; generating deformation characteristic data representing a deformation activity state; environment characteristic data representing landslide forming conditions are constructed; screening landslide candidate areas which simultaneously meet the deformation activity criterion and the landslide formation condition criterion; performing comprehensive feature analysis and type discrimination on the landslide candidate region to obtain a landslide identification conclusion and corresponding uncertainty information; determining a ground survey checking scheme according to the uncertainty information and executing the ground survey checking scheme; if yes, taking the landslide identification conclusion as a final result, and outputting a corresponding landslide type and uncertainty information; and if not, correcting the landslide identification conclusion according to the check result, updating the uncertainty information, taking the corrected conclusion as a final result, and outputting the corresponding landslide type and the updated uncertainty information.

The invention provides a natural ecosystem investigation method. The natural ecosystem investigation method comprises the following steps: S1, acquiring a high-resolution remote sensing image and DEM data, and dividing ecosystem types; s2, typical ecological problems of the ecological system are determined, sample plot design and sample plot dynamic arrangement are carried out, investigation points are arranged in a sample plot, and sampling analysis is carried out; and S3, performing data analysis according to the plaque partition map, the sample plot location map and the remote sensing image map. According to the dynamic survey method combining quadrat / transect and sampling point actual ground survey, the mutual verification of ground, remote sensing and model data is realized by combining a satellite remote sensing and model simulation technology with multiple data sources, typical / important ecological problem partitions in a watershed ecosystem range are found out and verified, and a watershed ecological system is established. Support is provided for design and implementation of the ecological engineering project, and a data index basis is provided for acceptance of the ecological engineering project.

The application relates to the technical field of G01C11 / 00, in particular to a surveying information data collection method and a storage medium. The surveying information data collection method comprises the following steps: S1. using a flight device to carry a position module and a camera module, acquiring ground surveying image information by shooting through the camera module; and S2. editing and storing region range position information through a setting module, transmitting the region range position information to the flight device through an information transmission module, and starting the camera module to shoot images in the region range. Through the surveying information data collection method and system, the position data information of specific surveying can be fed back to the flight device, and surveying images of specific position regions can be acquired.

The invention discloses a seasonal analysis method for evaluating the carbon emission effect of urban greening layout, belongs to the technical field of urban greening layout, and aims to solve the problem that some studies in the prior art pay attention to the carbon sink function of urban greening, but most studies cannot fully consider the influence of seasonal variation on the carbon emission effect. Comprising the following steps: S1, performing field investigation and field acquisition on greening layout data of different regions and different seasons of a city; s2, combining a remote sensing technology and ground survey; and S3, establishing carbon emission including plant growth, maintenance management and material production including seedling cultivation, greening facility manufacturing and daily use in different seasons by using a life cycle evaluation method. According to the seasonal analysis method for evaluating the carbon emission effect of the urban landscaping layout, through seasonal analysis, the carbon sink function and carbon emission characteristics of urban landscaping in different seasons can be determined, a scientific basis is provided for urban landscaping planning, and optimization and adjustment of the landscaping layout are guided.

The invention relates to the field of data analysis, in particular to a plough layer salt and alkali conditioning optimization method based on soybean response, and the method comprises the steps: obtaining a sample point original prediction error sequence through calculating the original prediction error of a sparse ground exploration sample point; the method comprises the following steps of: performing joint weighting on geographic space proximity and surface feature similarity to obtain a spatial residual propagation factor; performing principal component analysis on multi-dimensional surface soil attributes of a grid neighborhood to obtain grid unit local feature heterogeneity assessment; carrying out correlation analysis on a sample point error absolute value and local feature heterogeneity and modulating a spatial residual propagation factor to obtain a yield prediction value of a grid unit; position correction and response enumeration evaluation are carried out on the candidate conditioning doses to obtain the optimal conditioning doses of the grid units, so that the problems of yield prediction distortion and variable prescription mismatching caused by the fact that high-density surface remote sensing and sparse deep sampling points are difficult to fuse are solved.

The utility model belongs to the technical field of building ground measurement, and particularly relates to a large-area ground flatness measuring device which comprises a main body, and a mounting seat is fixedly mounted at the bottom of the main body; a measuring mechanism is fixedly mounted at the bottom of the mounting seat; wherein the measuring mechanism comprises a measuring assembly, and one side of the measuring assembly is fixedly provided with a positioning assembly; the measuring assembly comprises a fixing seat and a connecting arm, a support is fixedly installed at the bottom of the fixing seat, the connecting arm drives the detection wheel to be hinged to the support, a connecting rod is hinged to one end of the connecting arm, and the top of the connecting rod abuts against the pressure sensor. According to the utility model, the mounting seat is mounted at the bottom of the main body, and the connecting flanges are arranged at the two sides of the mounting seat, so that extension splicing can be carried out, the measuring device is suitable for large-area ground flatness detection, and meanwhile, the positioning mechanism is arranged to spray paint and position a position with a measurement problem, so that subsequent finishing is facilitated.

The invention discloses a disaster state prediction method and system based on three-dimensional geologic body modeling, and relates to the technical field of geological disaster prediction, and the method comprises the steps: collecting and fusing multi-source data, collecting underground geologic body chromatography data through seismic tomography and geological radar, and obtaining surface form data through unmanned aerial vehicle aerial photogrammetry and ground survey; seamless joint and unified expression of underground geophysical prospecting data and surface form data are achieved through the multi-source data acquisition and fusion technology, the precision and comprehensiveness of geological disaster prediction are remarkably improved, and particularly, the seismic tomography and geological radar technology is adopted, unmanned aerial vehicle aerial photogrammetry and ground survey are combined, and the geological disaster prediction precision and comprehensiveness are improved. A three-dimensional geologic structure database containing underground geologic structures and surface form information is constructed, data sources of disaster prediction are enriched, and the accuracy and timeliness of data are ensured through a space-time consistency correction formula.

The present application relates to the technical field of ecological restoration, and more particularly to a caragana laying ecological restoration method based on remote sensing and intelligent monitoring. The method comprises the following steps: obtaining multispectral remote sensing images and ground survey data of the target grassland, and extracting vegetation coverage, soil erosion intensity and surface roughness; evaluating the degradation degree of the target grassland according to the vegetation coverage, soil erosion intensity and surface roughness, and determining the grassland degradation zoning map; determining the caragana laying parameters based on the grassland degradation zoning map; leveling and cleaning the target grassland; laying caragana on the pretreated target grassland surface according to the caragana laying parameters, and collecting monitoring images of the laying area in the target grassland by using a UAV at a preset period. The present application can accurately identify the degradation level and spatial difference of the grassland, thereby providing scientific and reasonable parameter settings for caragana laying, significantly improving the pertinence and effectiveness of the restoration measures, and optimizing the resource utilization efficiency.

The application belongs to the technical field of geodetic survey and geophysical exploration, and discloses a multi-frequency multi-mode GNSS transoceanic height transfer and global height datum unification method, which comprises the following steps: 1, deploying multi-frequency multi-mode GNSS receivers at multiple local leveling / gravity joint survey points, and synchronously carrying out GNSS static observation; 2, acquiring satellite precise clock orbit products; 3, calculating the gravitational potential of the position where the satellite is located; 4, solving the elevation of the ground survey point by means of a model for determining the gravitational potential and the elevation based on single-station undifferenced multi-frequency multi-mode GNSS signals; 5, cyclically executing steps 1-4 to acquire the elevations of various transoceanic observation points; 6, obtaining the height difference between two different transoceanic survey points through difference operation; and 7, determining the height datum difference between the two different transoceanic survey points based on the least square method, so as to realize the unification of the transoceanic different height datum. The application solves the long-standing problem of transoceanic and transsea height transfer, and realizes the unification of global height datum.

The present invention discloses a method and device for calculating vegetation phenological diversity based on phenological camera time series images, which is used to solve the technical problem that most existing vegetation phenological diversity calculation methods adopt manual ground survey methods, resulting in low efficiency in calculating vegetation phenological diversity. The method includes obtaining phenological camera time series images of multiple vegetations, and preprocessing the phenological camera time series images of each vegetation based on the bicubic interpolation method, outputting multiple crown selection area maps of each vegetation; generating a green index annual change curve corresponding to each vegetation based on the multiple crown selection area maps of each vegetation; extracting data from the green index annual change curve corresponding to each vegetation, and determining the vegetation physical quantity corresponding to each vegetation; using a preset phenological diversity index function to perform calculations based on the vegetation physical quantity corresponding to each vegetation, and determining the vegetation phenological diversity index.

The invention belongs to the field of uranium prospecting technical methods, and particularly relates to a roll-shaped uranium deposit prospecting method, which comprises the following steps of: (1) collecting basic geological information of a uranium metallogenic ground in a working area through geological survey; (2) establishing a working area deep space geologic structure by using a geophysical measurement technology method; (3) carrying out hydrogeological survey, and establishing a hydraulic connection between a surface water system and each stratum sand body; (4) establishing a uranium metallogenic basic geological condition analysis model, and predicting the uranium metallogenic potential of the working area; and (5) carrying out drilling verification, tracing and controlling the front line of the interlayer oxidation zone, and discovering and positioning the rolled uranium ore body. According to the method, the prospecting of the roll-shaped uranium ore deposit is decomposed into five links of ground survey, geophysical survey, hydrogeological survey, basic geological condition analysis and drilling verification, so that the technical problem that the existing prospecting exploration working technical method is relatively single is solved.

The invention discloses a three-dimensional geological exploration and data integration system and method based on multi-technology collaboration, and relates to the technical field of geological exploration, a detailed exploration scheme is formulated on a unified data management platform, and the aerial survey range of an unmanned aerial vehicle, the arrangement position and depth of a drill hole, a geological radar and a seismic exploration line, and a gravity / magnetic method exploration area are determined. Determining parameter setting (such as drilling sampling interval and geological radar detection frequency) of each exploration device, generating an exploration task list and distributing the exploration task list to each field exploration team; a multi-technology cooperative exploration system (intelligent drilling, underground detection, aviation exploration and ground exploration) realizes'surface-underground-air 'omnibearing data coverage, the lithology identification accuracy is improved to 92% from 75% in the prior art, and the mineral resource estimation error is controlled to be within 8% from 20% or above. The problems of missed detection and misjudgment (such as precise recognition of hidden faults and deep ore bodies) of a traditional single technology are effectively avoided.

This invention discloses an intelligent extraction and assessment method for ecological factors of musk deer habitat based on multi-source image fusion, belonging to the field of ecological remote sensing monitoring and intelligent assessment technology. It addresses the problems of inconsistent multi-source extraction of ecological factors and insufficient reliability of suitability assessment results for musk deer habitat. The method acquires optical remote sensing images, radar remote sensing images, UAV images, topographic data, meteorological data, vector geographic data, and ground survey data within the assessment area. After unified preprocessing, ecological factors such as vegetation, topography, water resources, climate, land cover, and human disturbance are extracted. Then, through multi-source fusion, sample matching, suitability probability calculation, key factor extraction, and result verification and correction, the suitability level of musk deer habitat and the contribution of ecological factors are obtained.

A ground survey system (1) includes: at least one ground survey device (10) disposed in the interior of an underground space (41); and an information processing device (20). The ground survey device (10) includes at least one first detector (11) and at least one second detector (12) arranged at a distance from each other to detect cosmic ray muons. The information processing device (20) comprises a control unit (22). The control unit (22) counts the number of muons arriving from the direction connecting the first detector and the second detector by having the first detector (11) and the second detector (12) detect muons substantially simultaneously. The ground survey system (1) detects muons with the ground survey device (10) disposed at a plurality of positions in the underground space (41) simultaneously or in succession, which is achieved by disposing a plurality of the ground survey device (10) and / or by taking measurements while moving the ground survey device (10).

The embodiment of the present application discloses a kind of method and device for determining magnetic distribution information based on multi-platform magnetic force data.The method comprises: obtaining the magnetic force data measured by at least two measuring platforms on the area to be explored;Wherein, the measuring platform includes aerial survey platform, ground survey platform and drilling survey platform;Based on the magnetic force data corresponding to the area to be explored and the preset parameters to be inverted, a target function is constructed;Wherein, the unknown parameters are added to the target function as the parameters to be inverted, and the parameters to be inverted include at least one preset base point difference parameter and the magnetic parameters to be determined;The base point difference parameter is used to adjust the reference gap between different magnetic force data in the target function;Determine the parameter value corresponding to the magnetic parameters to be determined in the target function, and determine the magnetic distribution information generated by the magnetic body contained in the area to be explored based on the parameter value.The technical scheme of the embodiment of the present application can improve the accuracy of magnetic distribution information.

The invention relates to the technical field of remote sensing, in particular to a leaf life inversion method based on a PROSAIL model, which performs minimum mean square error matching in combination with a remote sensing observation spectrum, can quantitatively estimate the average leaf life of pixels on regional and time sequence scales, provides important input for carbon income and expenditure simulation of an ecological system, and has a good application prospect. By introducing the functional character of the leaf life, the spatial and temporal distribution and the change rule of the canopy leaf age structure can be described. Compared with a traditional ground survey method, the method has the advantages that the leaf life information can be obtained on the regional scale and the long-time sequence, the space coverage and the time continuity of leaf age structure detection are greatly improved, and new key input is provided for ecological system age structure, carbon cycle model parameterization and vegetation restoring force analysis.

The utility model relates to the field of underground equipment detection, in particular to a convenient underground liquid injection hole sieve tube position detection system, which comprises a ground measurement host, a display, a logging cable winch and a first fixing block, a logging cable is wound on the surface of the logging cable winch, the top of the first fixing block is fixedly connected with a second fixing block, and the second fixing block is fixedly connected with the display. And an inner cavity of the second fixing block is rotationally connected with wellhead pulley equipment. When the threaded block moves downwards, through transmission of the connecting block, the first protruding block and the second protruding block, the three adjusting blocks expand outwards and make stable contact with a well mouth and a supporting face, and therefore the stability of the well mouth pulley device in the placing process is improved, and the detection error caused by shaking or vibration of the measuring head is reduced; due to expansion of the adjusting block, the stability is enhanced, the measuring head is effectively prevented from colliding with the well wall in the well logging process, and the service life of the measuring head is prolonged.

The utility model provides a kind of measuring device for highway reconnaissance design belongs to road surveying equipment technical field.The utility model embodiment provides the measuring device for highway reconnaissance design, including staff component, drill, direct current motor, power component and support and adjusting mechanism, by rotating and setting drill in the end of staff component, direct current motor and the power component of power supply to direct current motor are built-in in the inside of staff component, when needing to insert staff component into the soil of ground survey point, only need to insert drill into the soil of ground survey point, then start direct current motor, make drill automatic drilling into the soil of ground survey point by direct current motor drive drill rotation, simultaneously, drill drives staff component to insert into the preset position in ground soil, so as not to need to insert staff component into the ground survey point by measurement personnel manually, save work time and improve measurement efficiency, can greatly reduce the labor intensity of measurement personnel, not easy to cause measurement personnel to appear fatigue.

This invention relates to the field of ecological environment monitoring and carbon cycle assessment technology, and discloses a forest carbon sink prediction method based on spatial heterogeneity decoupling and hierarchical distributed autoregressive meta-learning fusion. The method first integrates ground survey data, remote sensing temporal features, meteorological driving factors, topographic factors, and soil attribute data to construct a multi-source heterogeneous feature system. Then, it decouples and models different categories of features, and divides ecologically homogeneous clusters based on a self-organizing map neural network. For each ecological cluster, it constructs an independent nonlinear autoregressive model for distributed prediction. Based on this, a meta-learning fusion model is constructed, and the outputs of each distributed model are dynamically weighted and biased to obtain the predicted forest vegetation carbon density, and the forest vegetation carbon storage and annual carbon sink are calculated. This method can effectively handle spatial heterogeneity and temporal lag effects, constructs a progressive error convergence structure, and improves the accuracy, stability, and cross-regional generalization ability of forest carbon sink prediction.

The present application relates to the field of data analysis, and more particularly to a plough layer saline-alkali conditioning optimization method based on soybean response, which comprises: obtaining a sample original prediction error sequence by calculating the original prediction error of sparse ground survey samples; obtaining a spatial residual propagation factor by jointly weighting geographical spatial proximity and surface feature similarity; obtaining a grid cell local feature heterogeneity evaluation by performing principal component analysis on the multi-dimensional surface soil properties of the grid neighborhood; and obtaining a yield prediction value of the grid cell by performing correlation analysis on the absolute value of the sample error and the local feature heterogeneity and modulating the spatial residual propagation factor; and obtaining the optimal conditioning dose of the grid cell by performing position correction and response enumeration evaluation on the candidate conditioning dose, thereby solving the problem of yield prediction distortion and variable prescription mismatch caused by the difficulty in fusing high-density surface remote sensing and sparse deep-layer samples.