537 results about "Land resources" patented technology

The invention discloses a CCER forestry carbon sink project development system based on artificial intelligence technology monitoring, and relates to the technical field of carbon sink monitoring and optimization. According to the CCER forestry carbon sink project development system based on artificial intelligence technology monitoring, space-time estimation is carried out on CCER forestry carbon sink project data through the deep learning model, and the dynamic change of the carbon sink amount is accurately predicted. Spatial features are extracted through a convolutional neural network, time sequence data are analyzed in combination with a long-short-term memory network, and a carbon sink prediction model is constructed. And through statistical analysis and a spatial interpolation algorithm, carbon sink quantity change is monitored in real time, an abnormal trend is identified, and early warning is provided. Based on a mixed integer linear programming algorithm, forest land resource allocation and vegetation types are optimized, a carbon sink optimization scheme is generated, and carbon sink benefit maximization is promoted. And through an intelligent carbon sink management scheme, sustainable ecological development and green and economic popularization are assisted.

The invention relates to the technical field of land resource management, in particular to a land natural resource dynamic supervision system and method. The method comprises the following steps: carrying out multi-source data acquisition and preprocessing on a land natural resource area to obtain an initial data set; performing intelligent land classification processing according to the initial data set to obtain a land classification map; performing change detection graph extraction according to the land classification graph to obtain a change detection graph; constructing a three-dimensional land resource model according to the change detection graph to obtain the three-dimensional land resource model; and performing early warning trigger processing according to the three-dimensional land resource model and the change detection graph, and pushing resource supervision information so as to realize a dynamic supervision task of the land natural resources. According to the land natural resource dynamic supervision method based on multi-source data, deep learning, time sequence analysis and three-dimensional modeling, automation, intellectualization and dynamics of land resource supervision are achieved.

The invention relates to the technical field of land resource management, in particular to a land resource space optimization configuration method and system, and the method comprises the following steps: dividing grid cells based on a land research region, setting the initial land utilization state of each cell, comparing the land suitability of adjacent cells, updating the land utilization type, and determining the land utilization state of each cell; and recursively calculating the change in each time step, and iteratively executing the transfer specification to obtain a land utilization change state sequence. According to the invention, through recursive calculation and land utilization state updating, land utilization dynamic simulation, data continuity and regional adaptability enhancement, vacancy value filling and neural network adjustment, data and environmental factor feedback adjustment, prediction precision and trend judgment capability are improved, and economic, social and ecological benefits are quantified. The land use proportion and spatial layout are optimized, the land resource allocation efficiency is improved, policy adjustment and scene simulation are combined, differentiated decision support is provided, and social fairness and efficient resource utilization are promoted.

The invention relates to the technical field of land resource monitoring, in particular to a land resource dynamic monitoring and early warning method and system based on multi-source remote sensing data fusion, and the method comprises the steps: employing an unmanned plane to periodically collect optical images, SAR echoes and LiDAR point clouds, constructing a ground three-dimensional digital model, and carrying out the land parcel division; performing fusion to form a multi-dimensional feature vector, establishing an LSTM land parcel feature evolution model, and predicting a change rate interval of each feature in a current period based on a historical sequence; constructing a time sequence difference change detection algorithm, calculating a land parcel change rate, and screening potential abnormal land parcels by taking a prediction interval as an anomaly judgment threshold value; a double-branch convolutional neural network is adopted to identify crop states, growth stages and construction violation behaviors, abnormity is judged and determined, and confidence is given; spatial clustering is carried out on determined abnormal land parcels, accurate boundaries are obtained in combination with a three-dimensional model, multi-level early warning information is generated, and the decision-making efficiency and response speed of land resource monitoring are improved.

The invention discloses a soil sampling device for land resource planning and a sampling method thereof, and belongs to the technical field of soil sampling, the soil sampling device comprises a supporting seat fixedly supported above the ground at a sampling position, a stand column is fixedly mounted on the upper surface of the supporting seat, and a top seat is fixedly mounted at the top of the stand column; an adjusting motor is fixedly mounted at the top of the top seat, meanwhile, a threaded rod is fixedly mounted at the output end of the adjusting motor, a movable seat is arranged on the outer side of the stand column, and a sampling barrel is rotationally mounted in the middle of the movable seat. The cutting base is fixedly installed at the lower end of the sampling barrel, the drilling efficiency of the sampling barrel is improved, and a cutting assembly is arranged on the inner side of the cutting base. According to the soil sampling device for land resource planning and the sampling method of the soil sampling device, residual soil dust in previous sampling can be automatically cleaned before sampling, the lower end of sample soil can be segmented, automatic clamping and supporting are conducted, and the sample soil can be completely taken out conveniently.

Disclosed are a filling curing agent for preparing mine superfine tailing slag from solid waste residues, which belongs to the field of preparation of solid waste residues. The filling curing agent comprises a cementing material component obtained by means of a wet milling process while grinding, and an exciting agent component obtained by means of a mixing and stirring process; the cementing material component comprises, in parts by mass, 45-50 parts of blast furnace slag powder, 35-40 parts of steel slag powder, 15-20 parts of coal ash and 53.8 parts of water, and the exciting agent component comprises 100 parts of desulfurized gypsum powder and 59.5-60.6 parts of an activating agent; and the weight of the exciting agent component accounts for 10-15% of the weight of the filling curing agent. The filling curing agent disclosed in the present invention has low filling cost, high filling body strength and good durability, which reduces the occupation of land resources, reduces the impact on the ecological environment and residents' lives, realizes a virtuous cycle of mining and filling, and has good industrial prospects and social benefits.

The embodiment of the invention provides an AI analysis method and system applied to land resource investigation, and the method comprises the steps: obtaining the multi-source remote sensing image data of a target region, analyzing the spectrum and texture features of the multi-source remote sensing image data, generating a comprehensive land feature map, obtaining an initial land classification map through a land classification model, and obtaining the initial land classification map. And performing time sequence comparative analysis in combination with historical data to determine a dynamic area of land coverage change and generate a land resource change report. The method further comprises the functions of soil quality evaluation, change area visualization, abnormal area real-time monitoring, land classification model training, classification model adjustment according to user feedback and the like, and the efficiency and accuracy of land resource investigation are improved.

The invention discloses a cultivated land reserve resource potential grading method based on multi-dimensional cultivated land quality evaluation, particularly relates to the technical field of land resource management, and is used for solving the problems of insufficient cultivated land potential grading precision and lack of ecological constraints caused by single dimension and data splitting of an existing evaluation method. Interpreting land types by verifying and fusing cultivated land quality classification codes and remote sensing, complementing constraint fields such as ecological protection areas and pollution levels, and constructing a dynamic model associated with natural quality parameters and ecological limitation indexes; on the basis of land parcel type matching differentiation screening rules, threshold screening and suitability scoring are carried out on unutilized lands, abandoned garden lands and the like in a classified mode; eliminating ecological sensitive or pollution exceeding land parcels through logic verification, calculating a comprehensive potential score in combination with a multi-dimensional parameter weight and a dynamic threshold value, and dividing the comprehensive potential score into high, medium and low grades according to regional resource requirements; and the cultivated land quality multi-dimensional collaborative evaluation and ecological protection two-way decision is realized.

The invention discloses a rural land utilization evaluation system and method, and relates to the technical field of land management, and the system comprises a spatial analysis module which obtains a spatial distance value, a land utilization type value and a regional distribution value based on a land unit division result, carries out the superposition calculation of a spatial incidence relation matrix, and extracts the conflict intensity. According to the method, through comprehensive calculation of the spatial distance, the land utilization type and the regional distribution, the land conflict intensity and the dynamic characteristics thereof are quantitatively analyzed, the problem that the land resource conflict distribution is not clearly identified is solved, in the dynamic prediction process, the land dynamic characteristics are quantified through space and ecological connectivity difference operation, and the prediction accuracy is improved. According to the method, land utilization change requirements, economic value and ecological connectivity normalization processing and weighted calculation are effectively coped with, dynamic balance of economic benefits and ecological protection is achieved, limitation of single-dimension evaluation is avoided, and reasonable allocation of land resources is strengthened by adjusting the proportion of economic and ecological parameters through optimization verification and reducing evaluation deviation.

The invention discloses a large-scale infrastructure intensive land-saving development potential analysis method and system, and the method comprises the following steps: 1) constructing a large-scale infrastructure stock land geospatial database based on Arcgis, and collecting the related element data of the large-scale infrastructure stock land; 2) extracting land suitable for optimizing stock of large infrastructures, and screening and extracting municipal public facility land and road and traffic facility land which are larger than 5 hectare in land scale and are not dangerous; 3) constructing an AHP-entropy weight method hybrid model, optimizing the weight by means of a genetic algorithm to establish a site selection evaluation system, and comprehensively evaluating the alternative land; 4) constructing a land development population service coverage model to obtain the number of each development land service population; and 5) guiding a land redevelopment time sequence in combination with the comprehensive score of the alternative land and the number of serviceable population. The method provides a path for improving the utilization efficiency of land resources, eliminating the neighborhood effect of large infrastructures and realizing high-quality development.

The invention discloses a cross-department collaboration-oriented land transaction intelligent decision support method, particularly relates to the technical field of land transaction management, and is used for solving the problems of decision tense chaos and low approval efficiency caused by data timeliness difference in the prior art. The method comprises the following steps: acquiring real-time monitoring and periodic revision data of multiple service units, adding timestamps, and identifying time window differences to extract an associated data set; dynamically aligning timestamps and generating timeliness weights on the basis of flow topological characteristics and information orderliness analysis, constructing a space-time propagation path map, screening high-weight paths, and realizing dynamic splicing of lagged data and real-time data; an approval path scheme with timeliness alignment is generated through rule base matching and a risk early warning mechanism, and risks are detected in real time during execution to dynamically adjust a priority sequence, so that the consistency and execution efficiency of cross-department decision making are improved, and the compliance risk of land resource management and control is reduced.

The invention discloses a detection system for natural land resources, and relates to the technical field of resource detection, the detection system comprises a data preprocessing module, a fusion space-time diagram construction module, a multi-target enhancement module and a feedback module, an entropy law is combined with a semantic space-time diagram index, quantitative modeling of an ecological law is realized, and the real-time performance of the system is improved. Natural-human collaborative intervention simulation under multiple time scales, time-space semantic query response time improvement, prediction precision improvement and interdisciplinary fusion are supported, the entropy law of ecological economics is combined with time-space diagram index, the limitation that a traditional model only pays attention to physical indexes is broken through, ecological-economic balance is achieved through an entropy weight method and Monte Carlo simulation, and the prediction precision is improved. According to the method, self-adaptive decision making is supported, a perception-decision-execution integrated platform is constructed based on the real-time updating capability of space-time diagram indexes, a full-chain solution from data collection to dynamic optimization can be provided for natural resource intelligent management, a prediction model is combined with entropy increase constraint, and the ecological economic cost is quantified.

The invention discloses a GIS-based main body function area evaluation index system construction method, and relates to the technical field of land resource management, and the method comprises the steps: obtaining multi-source geographic data of a target main body function area, and carrying out the preprocessing to form a unified geocoding evaluation database; generating an evaluation index system of the main body function area by adopting a composite weighting algorithm according to the evaluation database and the main body function area type division result; inputting the multi-dimensional raster data of the evaluation index system into the spatial decision tree classification model to obtain a classification result; performing overlay analysis on the multi-dimensional raster data to obtain comprehensive evaluation raster data; according to the classification result and the comprehensive evaluation raster data, obtaining a function goodness of fit thermodynamic diagram of the main body function area; and according to the function goodness of fit thermodynamic diagram, performing dynamic updating based on the time sequence, and when the change rate of the monitoring data exceeds a preset threshold, triggering an iterative optimization process. According to the invention, land space planning and main body function area optimization adjustment are realized.

The invention discloses a water resource optimization scheduling method based on water and soil resource space coupling, and the method comprises the steps: dividing an agricultural land of a target region into grid units, collecting the basic data of each grid unit, calculating a water and soil resource space coupling evaluation index value based on the grid units and the basic data, and carrying out the water and soil resource space coupling evaluation index value. The water and soil resource coupling degree of each grid unit is calculated, and a hot spot area and a cold spot area of water and soil resource space coupling are identified by adopting a spatial autocorrelation analysis method; on the basis of hot spot region and cold spot region division distribution, determining a water resource optimization scheduling region and a regulation and control method by combining a water land resource space coupling evaluation index value; fine management and efficient utilization of water and soil resources are achieved, and the method has important significance in improving the utilization efficiency of agricultural water resources and promoting agricultural sustainable development.

The invention discloses a multi-task remote sensing semantic change detection method based on a visual state space model. The method mainly solves the problems that in the prior art, semantic segmentation and change detection subtasks lack consistency, and global feature information is not fully utilized. According to the implementation scheme, the method comprises the following steps: introducing a visual state space model into a feature extraction encoder, obtaining multi-level semantic features of image global context information modeling, and enhancing the multi-level semantic features; respectively obtaining a semantic segmentation result and a binary change result of the image from the enhanced multi-level features through a semantic segmentation decoder and a change detection decoder; and in combination with a semantic segmentation result and a binary change result, a semantic change result with higher discrimination is generated, and multi-class semantic change detection of the remote sensing image is realized. According to the method, the specific category information in the change area can be accurately classified while the image change area is efficiently extracted, and the method can be used for land resource utilization management and monitoring of the change of the land type of a specified area.

The invention relates to the technical field of land resource management systems, in particular to a land resource management system and method based on multi-dimensional data analysis, and the system comprises a data collection module which is used for obtaining multi-source heterogeneous land resource data; the data management and analysis module is used for performing fusion, quality evaluation, feature extraction, spatial-temporal dynamic analysis and prediction on the multi-source heterogeneous land resource data; the decision support module is used for providing land resource management decision suggestions based on the output of the data management analysis module; and the visualization module is used for performing three-dimensional visualization expression on results of the data management analysis module and the decision support module, and the system provides an omnibearing and multi-dimensional solution for land resource management, and can effectively meet current complex and changeable land resource management requirements.

According to the root zone limiting type grape rain-sheltering cultivation system and method based on agriculture and light complementation, existing photovoltaic panels, prefabricated steel frames and prefabricated cement piles in a photovoltaic field are used as infrastructures, rainwater is collected and drained by installing gutters and drainage pipelines, and water accumulation is avoided; a transparent polyethylene film is installed between two adjacent rows of prefabricated steel frames to serve as a rain sheltering film, and meanwhile a reflective film is laid in a gap area of the photovoltaic panels to achieve the effects of light supplement and disease and pest prevention. Grape root systems are limited in container systems composed of plastic outer packaging bags and nutrient soil, and the container systems are arranged above the reflective film at equal intervals. A grape shed frame is constructed through the transverse pulling frame wires and the stand columns to support grape vines to grow; the rain sheltering film is fixed through a clamping spring and a clamping groove and is provided with a drainage hole connected with a drainage pipe; the high-quality and high-efficiency grape cultivation scheme is adopted, the leisure and sightseeing functions are considered, land resources under the photovoltaic panel are effectively utilized, the contradiction between grape rain-sheltering cultivation and illumination requirements in an agriculture and light complementary mode is solved, and the utilization efficiency of land and light resources is improved.

The invention relates to the technical field of data processing, in particular to a land utilization change monitoring method based on big data, and the method comprises the steps: collecting each item of data and land utilization rate data of each region, obtaining the influence degree of each item of data on the land utilization rate, dividing each region into region combinations, according to the influence degree of each item of data on the land utilization rate and the correlation of each item of data of each region combination, obtaining a weight adjustment factor of each region combination, and according to the weight adjustment factor of each region combination and the initial weight of each region combination, obtaining an adjustment weight of each region combination, according to the land resource utilization rate of each region at the latest sampling moment and the adjustment weight of each region combination, the Moran index of each region at the latest sampling moment is obtained, and then the abnormal region is obtained, and the accuracy of abnormal region identification is improved.

The invention relates to the technical field of remote sensing data analysis, in particular to a land resource management data analysis system. According to the method, the spectral reflectivity change under the earth surface multi-direction illumination is obtained and the reflection gradient response information of the spectral reflectivity change is extracted, so that the spatial difference of the earth surface reflection characteristics at different angles can be more comprehensively presented; according to the method, surface land type division is more accurate in gray continuity and spatial structure expression, so that potential fission boundaries are identified and reasonable section classification is carried out through quantitative comparison and spatial aggregation analysis of structure texture differences in boundary identification between different regions, and the identification accuracy of the boundary identification between different regions is improved. The stability and variability of the interior and boundary structures of the land areas are effectively described, and on this basis, the area boundary is reconstructed and combined with texture and reflection clustering grouping, so that the land type state and the distribution boundary of each area can be finely judged.

The invention relates to the field of remote sensing technology and land resource management, and discloses a remote sensing image-based regional land utilization data change detection method, which comprises the following steps of: obtaining multi-temporal remote sensing image data of a research region; preprocessing of geometric correction, radiation correction and noise removal is carried out on the remote sensing image; carrying out preliminary classification on the image data by adopting an unsupervised classification method, and correcting a classification result in combination with field collected data; constructing a transfer matrix according to a classification result, performing change detection on the classification result of the multi-temporal image, and analyzing a conversion relation and area change among different land classes; and generating a thematic map to display land class distribution and change trend, and outputting a statistical analysis result. According to the method, quantitative analysis and visual display are combined, the land utilization change rule can be efficiently and accurately reflected, a scientific basis is provided for regional land resource management and planning, the applicability is high, and the implementation cost is low.

The invention belongs to the technical field of ecological restoration, and particularly relates to an ecological environment data processing method and system for ecological restoration, and the method comprises the steps: a data collection module comprises a plant library, a mining area three-dimensional model and an environment monitoring platform; the data processing module is used for performing grid region division on the mining area three-dimensional model and processing data acquired by the environment monitoring platform; and the analysis matching module is used for screening and matching the optimal plant species for each grid unit. The method comprises the following steps: constructing a geographic model of a mining area, equally dividing the geographic model into a plurality of grid units, respectively acquiring environmental data for each grid unit, adaptively screening and matching plant varieties suitable for the grid units from a plant library according to different attributes such as soil, illumination, terrain and the like of the grid units; therefore, land resources are utilized to the maximum extent, plants are promoted to fully adapt to different environments of the mining area, the survival rate of vegetation is increased, and the ecological restoration and improvement effect of the mining area is achieved.

The invention discloses a large-area photovoltaic land screening method, which comprises the following operation steps: S1, collecting and storing regional land resource space data, and collecting and storing large-scale DEM (Digital Elevation Model) data of a specified regional terrain; s2, inputting a specified photovoltaic land use policy, a selection tendency and sensitive area data, screening out land type data meeting specified photovoltaic land use policy conditions and the selection tendency, and rechecking and removing land parcels related to the sensitive area to obtain a preliminary range; s3, inputting topographic factors influencing photovoltaic land selection, carrying out topographic data processing, extracting corresponding data and carrying out vectorization processing; s4, mountain shadow overlay analysis and slope overlay analysis are sequentially carried out, and analyzed land pattern spots are obtained; and S5, carrying out concentration degree analysis and screening on the land pattern spots to obtain a large-area photovoltaic land preferential selection area. The photovoltaic land can be automatically and efficiently screened in a large area range, and the efficiency and accuracy of photovoltaic power station site selection are remarkably improved.

The invention relates to an intelligent monitoring method and system for unused land based on a full-process closed-loop supervision mechanism, and relates to the technical field of land resource management.The method comprises the steps that a task database is established by means of obtained land related data, image spot extraction is conducted on all images in the database through a change detection model, and image spots are obtained; the method comprises the following steps: extracting pattern spots, performing a series of processing such as optimization, checking and superposition on the extracted pattern spots to obtain data fusion pattern spots, processing the data fusion pattern spots through grading and time identification to obtain graded pattern spots, finally inputting the graded pattern spots into an established system of a full-process closed-loop supervision mechanism, and performing interpretation in the system through each monitoring module. And result backflow updating and intelligent monitoring processing are performed based on the interpretation result, so that the processing precision and efficiency of the monitored pattern spots are effectively improved, the land change condition is comprehensively tracked, and the problem of insufficient timeliness and accuracy of land supervision in the prior art is solved by combining active interpretation supervision.

The invention relates to the technical field of land resource management, in particular to a land stock index management method based on data analysis. The method comprises the following steps: establishing a cross-data-source data sharing mechanism through a block chain technology, and obtaining multi-source land data; performing natural resource, planning and building information fusion on the multi-source land data based on a knowledge graph to obtain a geographic space semantic network; performing multi-scale space-time clustering on the geographic space semantic network through a self-organizing mapping algorithm, and performing key feature capture of land utilization change based on an attention mechanism to obtain land utilization change feature data; and performing land utilization mode identification according to the land utilization change characteristic data to obtain a land utilization dynamic characteristic spectrum. Through a multi-agent system and a hierarchical reinforcement learning algorithm, a complex land utilization decision process can be simulated, and an optimal decision scheme is realized.

The invention relates to the technical field of natural resource saving, in particular to a construction project land-saving optimization method and system oriented to resource saving and efficient utilization, and provides a three-level index case library construction and dynamic weight matching technology. The method comprises the following steps: firstly, performing multi-level classification on historical cases based on industry types, regional conditions and construction scales, and extracting standardized land use data (L), unit capacity (E) and land saving effects (S) to construct a case library; secondly, dynamically allocating weight coefficients of industries, regions and scales through an analytic hierarchy process (AHP), calculating case similarity in combination with a weighted Euclidean distance, and accurately screening matched cases; according to the method, the land use nuclear reduction rate reaches 26.48% in projects such as a Minjiang old wood hole avionics hub project, and the intensive utilization level of land resources is remarkably improved.

The invention relates to the technical field of surveying and mapping acquisition devices, in particular to a surveying and mapping acquisition device for land resource management, which comprises a storage box, four adjustable supporting legs, surveying and mapping equipment, a concave seat, two mounting mechanisms, a supporting seat, two guide plates, a mounting seat, two driving mechanisms, a pushing mechanism, a closing mechanism and a limiting mechanism, the four adjustable supporting legs are arranged at the bottom end of the storage box and are used for supporting the storage box; the surveying and mapping equipment is located in the storage box; surveying and mapping equipment is mounted on the recess; the two mounting mechanisms are respectively positioned on two sides of the surveying and mapping equipment; the supporting seat is fixed at the bottom end of the concave seat; the surveying and mapping equipment storage box has the beneficial effects that through mutual matching and linkage of the rotating disc, the fixing strip, the sliding rod, the connecting plate and other components, the concave seat jacks open the sealing plate, so that surveying and mapping equipment is moved out of the storage box, the surveying and mapping equipment can work conveniently, various tedious manual operations are not needed, and the surveying and mapping equipment is moved out and stored more conveniently.

The invention relates to the technical field of municipal planning, in particular to a BIM + GIS-based municipal underground pipe network intelligent planning and conflict avoidance system and method, and the system comprises a BIM-GIS data fusion module which is used for integrating a BIM model and GIS topographic data; the construction process association module is used for analyzing the construction plan to generate a dynamic construction progress table, and constructing a directed graph based on the spatial position relationship of each construction unit in the BIM model; the conflict prediction and avoidance module is used for calculating the space conflict probability of the temporary pipe network and the permanent pipe network in real time in combination with the directed graph and GIS topographic data; the land-saving optimization module is used for carrying out iterative optimization on the temporary pipe network layout through a genetic algorithm based on GIS topographic data and construction area boundary constraints so as to minimize the total length and the occupied area of the temporary pipe network; and the dynamic visualization interaction module is used for providing a three-dimensional BIM-GIS fusion view. According to the method, management and control from static design to dynamic construction are achieved, and the scientificity of underground pipe network planning and the land resource utilization efficiency are improved.

The invention belongs to the technical field of land resource management and planning, and provides a land utilization change prediction and decision support system based on machine learning, which comprises a data acquisition and preprocessing module used for collecting multi-source land utilization data; the feature extraction and modeling module comprises a time sequence analysis sub-module and a spatial feature extraction sub-module; the prediction model module comprises a machine learning model training sub-module and a model evaluation sub-module; according to the method, a comprehensive land utilization data set is formed by integrating multi-source information such as satellite remote sensing data, geographic information system data, meteorological data and economic data; data cleaning and standardization processing are performed by using a deep learning algorithm, so that the quality and consistency of the data are ensured; through the time sequence analysis and spatial feature extraction technology, the spatial and temporal features of the land utilization change are comprehensively captured, then a high-precision prediction model is constructed, and the prediction precision of the land utilization change is remarkably improved.

The invention provides an engineering investigation surveying and mapping intelligent management method and system based on a geographic feature processing technology. The method comprises the following steps: acquiring building distribution density, ground gradient and underground rock stratum distribution data of a target area, deploying a ground deformation monitoring radar at a selected position based on the building density and the rock stratum data, generating ground deformation data through radar images, and then separating ground subsidence change and original terrain characteristics to form a subsidence map; meanwhile, image reflection characteristics are analyzed to mark dangerous areas. And then integrating the ground gradient, the settlement trend and the rock stratum structure complexity to construct a land bearing evaluation model. The influence weight is further adjusted in combination with engineering requirements, and a bearing force evaluation result is generated after the model is input. Therefore, a scientific three-dimensional development planning scheme is generated, and optimized utilization and risk management and control of land resources are realized. According to the invention, through multi-source data fusion and model calculation, full-process analysis from land deformation monitoring to load bearing evaluation is realized.

The invention relates to the technical field of resource accounting, and discloses a dynamic index accounting system for displacement of cultivated land resources and forest land resources. The system comprises a resource data acquisition unit for acquiring spatial distribution data of cultivated land resources, types and coverage data of forest land resources and replacement constraint condition data and performing space-time alignment to generate a resource multi-dimensional data set; the replacement index accounting unit is used for executing resource adaptability reconstruction processing based on the resource multi-dimensional data set and separating target resource data from abnormal resource data; the replacement scheme generation unit is used for generating an accounting result containing a replacement area, a weight and a priority by combining a preset replacement rate and a development rate; and the dynamic correction unit is used for identifying an exception type based on the exception resource data and correcting an accounting result in real time. The system can comprehensively capture resource dynamics, improves the accuracy and timeliness of replacement accounting, and adapts to complex resource management requirements.