368 results about "Land parcel" patented technology

The invention relates to the technical field of agricultural intelligent decision making, and discloses an agricultural intelligent analysis and decision making method based on multi-modal data, which comprises a multi-modal agent, an agent collaborative decision making technology, an intelligent decision making method and a crop identification and diagnosis method. The multi-modal intelligent agent comprises an intelligent agent framework and multi-modal capability construction; the intelligent agent collaborative decision-making technology comprises intelligent agent ecological construction, a land parcel analysis method and a land parcel economy evaluation model; the intelligent decision-making method comprises the steps of agricultural knowledge graph construction, understanding and decision making. The crop identification and diagnosis method comprises vision-language model preprocessing and intelligent identification and diagnosis. According to the agricultural intelligent analysis and decision-making method based on the multi-modal data, the technical problem in traditional agricultural decision-making is solved through processing, analysis and technical innovation of the decision-making process of agricultural multi-source data, and accurate analysis and scientific decision-making support is provided for all stages of agricultural production before production, during production and after production.

The invention relates to the technical field of topographic survey, in particular to an automatic surveying and mapping method and system for a complex topographic land parcel for urban and rural planning. The method comprises the following steps: acquiring satellite remote sensing data and a digital elevation model corresponding to an urban and rural planning survey area, and performing survey area terrain pre-detection to generate an urban and rural planning complex terrain survey area plot; the method comprises the following steps: carrying out element semantic recognition and segmentation on an urban and rural planning complex terrain plot to obtain terrain obstacle distribution corresponding to each building, vegetation and water body element in the urban and rural planning complex terrain plot; obtaining a corresponding three-dimensional surveying and mapping boundary constraint of the complex terrain land parcel and carrying out surveying and mapping path obstacle planning to generate a terrain constraint surveying and mapping planning path corresponding to the urban and rural planning complex terrain land parcel; and performing automatic navigation surveying and mapping processing on the urban and rural planning complex terrain plot to generate urban and rural planning complex terrain plot surveying and mapping data. According to the invention, the efficient, accurate and automatic navigation surveying and mapping process of the plot under the complex terrain condition can be realized.

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 relates to the technical field of product traceability, in particular to a traceability system and method based on a block chain technology, and the system comprises a right confirmation registration module, a parameter verification module, a quality inspection label module, a logistics locking module and a traceability auditing module. According to the method, compliance evaluation is carried out by comparing environmental parameters bound with the operation time period and the land parcel information with an agricultural standard boundary, systematic judgment of land parcel growth conditions can be realized, confidence modeling is carried out on a quality inspection data layer based on a difference value amplitude and a batch mean value, credible label data of batch quality is formed, and the reliability of the quality inspection data layer is improved. Through sequence comparison of storage time periods and carrying timestamps and environmental parameter change frequency deviation judgment, abnormal carrying behaviors and storage fluctuation conditions can be identified, a traceability identification value and quality traceability code bidirectional verification mechanism is introduced in a query response stage, and credible labels, quality inspection states and position information are displayed in an aggregated manner. And the completeness, the accuracy and the result credibility of the traceability query result are obviously improved.

The invention relates to the technical field of land parcel management, in particular to a land parcel full life cycle compliance management and operation monitoring system, which comprises a multi-source data acquisition module for acquiring multi-dimensional land parcel data such as spatial geographic ownership planning and approval from a plurality of heterogeneous data sources in real time; the data fusion and storage module performs data cleaning and standardized fusion, adopts a distributed cloud storage architecture and introduces data version management to support historical tracing; the intelligent compliance judgment engine generates a compliance state judgment result and a compliance risk report based on the dynamic compliance rule base and machine learning; the interactive visual monitoring module is used for dynamically displaying the compliance state of the land parcel space information life cycle stage and the key index trend; and the automatic early warning and intervention module is used for performing graded early warning and triggering a rectification or emergency intervention process. According to the invention, the problems of difficulty in compliance judgment, low efficiency, non-visual monitoring and slow risk response of existing land parcel management data integration are solved, and intelligent compliance management and operation monitoring are realized.

The invention relates to the technical field of value accounting, and discloses an ecological system total production value accounting method based on GIS spatial analysis, and the method comprises the steps: carrying out the accounting of regional basic data and satellite image data, and constructing a bidirectional dynamic semantic mapping library corresponding to land change investigation land parcel classification-ecological system type; internet of Things monitoring data and statistical report data are obtained, and a standardized data set is obtained through space-time fusion of spatial interpolation-boundary correction and a sliding window smoothing method; constructing an urban area-typical district double-level accounting index system, and synchronously calculating a real object quantity and a value quantity; a model correction factor is called based on a GIS, indexes are quantified to grid units, a result is obtained through neighborhood analysis, and after parameters are calibrated, a multi-year ecological value trend map is generated in combination with the GIS; and outputting a customized result according to scenes such as ecological compensation, and outputting a final result after the customized result is qualified through three-level quality control verification. According to the method, the requirements of practical affairs such as ecological compensation and EOD projects on accounting precision and practicability can be met.

The invention provides an examination method and system for a territorial space control detailed planning achievement, and the method comprises the steps: 1, formulating a control and regulation achievement library element standard according to a target planning plot and the basic information of territorial space planning, compiling a territorial space controllability detailed planning GIS result file according to the basic information and a control and regulation result library element standard; 2, according to the basic information, control data and review rules are determined; 3, summarizing rule types according to the management and control data and the review rules, determining the rule type to which the management and control data belongs, and setting a review process corresponding to the rule type; and 4, according to the review process, reviewing the territorial space controllability detailed planning GIS result file to obtain a review result. According to the method, the content format of the GIS result file is unified, the review rule is cleared and solidified, the free cutting space of reviews is compressed, the review process can be standardized and processed, and the review efficiency and quality are improved.

The invention relates to the field of crop cultivation, and particularly discloses a multi-crop interplanting method with a high land utilization rate. According to the method, a multi-crop interplanting land distribution scheme is designed on the basis of user planting requirements, planting molds are built on land parcels with serious soil problems, and the planting molds are filled with crop growth supporting materials to serve as planting soil; planters can interplant various crops in the planting soil according to a multi-crop interplanting land distribution scheme, crops with serious soil-borne diseases, such as solanaceae or medicinal materials, can be planted on the same land for many years, planting can be carried out in land parcels with serious soil problems, the land utilization efficiency is improved, and the planting cost is reduced. The crop yield per unit land area can be increased in an interplanting mode, land resources are fully utilized, meanwhile, the planting production cost is reduced, and the economic output per unit area is increased.

The invention discloses an urban reserve land intelligent classification method and system based on spatial data fusion, and relates to the technical field of data processing, and the method comprises the steps: carrying out the formalized expression of a land use rule of a preset urban region, and constructing a land domain knowledge graph; collecting multi-source spatial data, performing feature extraction and alignment, and generating a high-dimensional feature vector of each plot; and performing hybrid classification evaluation based on the high-dimensional feature vector of each land parcel, synchronously outputting land use types, development potential levels and land reference value intervals of the land parcels, and calling a land domain knowledge graph to perform compliance verification and correction. The technical problems that an existing urban reserve land classification method depends on artificial experience and lacks accurate and multi-dimensional data fusion and compliance check, so that the accuracy and practicability of a classification result are low are solved, and the purpose that the classification accuracy and practicability of the urban reserve land are improved through multi-source spatial data fusion and an intelligent classification framework is achieved. And the accuracy and practicability of urban reserve land classification are improved.

The invention belongs to the technical field of data processing, and discloses a multi-source heterogeneous data fused remote sensing map dynamic database construction method and system, and the method comprises the steps: firstly obtaining multi-source heterogeneous remote sensing data of a target area, extracting remote sensing time sequence data of a land parcel after preprocessing, and obtaining a remote sensing time sequence; constructing a time sequence semantic track containing a key semantic feature time sequence for each land parcel; identifying a semantic evolution trend by using a semantic drift detection model, and generating an abandoned suspicious score; the static factors, the dynamic factors and the prior knowledge of the land parcels are fused, a structure causal graph is constructed by means of a causal discovery algorithm, and abandoned causal credibility is reasoned based on a graph neural network model; and automatically generating abandoned land labels for the land parcels of which the double scores exceed the threshold value, and finally writing the land parcel information into a dynamic database. And the problems of construction lag and information incompleteness of the dynamic database are solved.

The invention provides a rice planting area identification method and device based on multi-temporal remote sensing data, equipment and a storage medium. The method comprises the following steps: acquiring the multi-temporal remote sensing data according to a rice phenological period; determining a spectral index sequence of the multi-temporal remote sensing data to construct a spectral index time sequence curve, and generating planting characteristic data in the target area according to a spectral change curve; determining a spectrum time sequence template matched with the rice growth rule according to the planting characteristic data, performing matching analysis on the planting mode of each land block, and marking a land block set of rice planting mode characteristics; performing cross comparison on the plot set and the rice planting reference sample to generate a rice planting mode sample set, and constructing a rice planting area identification model based on the rice planting mode sample set; and analyzing the remote sensing data of the land parcels to be identified in the research area according to the rice planting area identification model, and determining a rice planting area identification result. According to the scheme, the accuracy of rice identification can be effectively improved.

The invention relates to the technical field of ecological restoration scene modeling, in particular to an ecological restoration scene modeling method and system platform applied to territorial space planning, and the method comprises the following steps: based on a successful ecological restoration technical scheme case and a to-be-restored land parcel unit. According to the method, normalization processing is carried out on multi-dimensional attributes between successful ecological restoration technical scheme cases and to-be-restored land parcel units, a source-target land parcel feature fingerprint set is constructed, and specific attributes such as annual average temperature, precipitation, soil types, pH values, altitudes, native vegetation types and labor cost are combined; modeling is realized on data source selection granularity and expression dimension. Furthermore, an importance coefficient is set according to the influence degree of each dimension in a historical repair success case, feature difference weight calculation is guided, and a technical migration adaptation degree score is obtained by combining normalized difference calculation, so that a quantifiable source-place adaptation capability evaluation index is established, and the limitation that judgment depends on experience in the prior art is broken through.

The invention relates to the technical field of land reserve, in particular to a multi-source integration and dynamic updating method and system for land reserve data, and the method comprises the steps: obtaining multi-source land data, constructing a unified space-time database through hierarchical coordinate fusion, and achieving the data integration. And then, land parcel ownership characteristics are extracted, compliance evaluation is completed, and policy change data are synchronously analyzed to generate planning constraints. Idle risk assessment is carried out based on spatio-temporal data and policy constraints, land value fluctuation is predicted, and accurate valuation data is obtained through idle risk weighted correction. And finally, according to risk assessment and policy constraints, a low-efficiency land taking strategy is generated, all data and strategies are uploaded to a management platform in real time, value abnormal block marking and land reserve dynamic optimization tasks are executed respectively, and full-process closed-loop management from data integration to intelligent decision making is realized.

The invention discloses an intelligent site selection method and system for farmland occupation and compensation balance, and belongs to the technical field of intelligent site selection, and the method comprises the steps: S1, collecting and preprocessing multi-source spatio-temporal data, so as to construct a basic database; s2, constructing a spatial adjacency relation graph, inputting data in the basic database into a graph neural network model, and generating a dynamic evaluation weight vector for a to-be-selected plot; s3, calculating a final utility value of each evaluation index, and calculating a multi-scale ecological balance score of the land parcel by adopting a multiplicative aggregation model in combination with the dynamic evaluation weight vector; s4, predicting the future quality evolution trend of the land parcels by adopting a long-short-term memory network model, and the method can accurately capture and respond to the spatial-temporal dynamic characteristics of the cultivated land ecosystem, so that the evaluation result is more fit with the physical reality.

The invention discloses a supplied land idle risk assessment method and system based on spatio-temporal data, and belongs to the technical field of geographic information, and the method comprises the steps: screening out a first land parcel from supplied land parcels according to the static data of each supplied land parcel; calculating an idle risk assessment index corresponding to the first land parcel according to the static data; extracting historical construction time-space sequence data from the space remote sensing data of the first land parcel from the time when the first land parcel is supplied to now; extracting space-time trend change characteristic data through a time window moving average method by adopting a long-short-term memory network model and taking the historical construction space-time sequence data as input, and predicting a development progress corresponding to the first land parcel according to the space-time trend change characteristic data; and when the development progress and the idle risk assessment index do not meet the preset conditions, determining that the first plot has an idle risk. Through the method and the device, the problem of low timeliness and accuracy of supplied land idle risk assessment can be solved.

The invention provides a natural resource archive retrieval and utilization method combining a large model and a knowledge graph technology, and relates to the technical field of data processing, the method comprises the following steps: identifying business entities in the field of natural resources and semantic association thereof, and constructing an RDF triple with attribute constraint; performing geometric feature preserving type coordinate simplification on the plot entity vector boundary coordinate point sequence through a Douglas-Peucker compression algorithm to generate a key coordinate point set after noise reduction; on the basis of the key coordinate point set, vector geometric superposition operation is carried out on polygon boundaries of the two plot entities, the area proportion of overlapped regions is calculated according to the intersection-to-union ratio, and when the intersection-to-union ratio exceeds a preset threshold value, entity space alignment is carried out, so that a triple set of space alignment is obtained; and fusing the triple set with the aligned space, and constructing the natural resource domain knowledge graph. According to the invention, redundant information interference is effectively reduced.

The invention relates to the technical field of remote sensing land prediction, in particular to a farmland non-grain spatial distribution prediction method and system, and the method comprises the steps: abstracting a farmland plot into a graph node, defining an edge weight as a weighted combination of an inter-plot Euclidean distance, crop type similarity and irrigation system connectivity, constructing a three-layer dynamic graph structure comprising land parcels, neighborhoods and administrative units; taking the three-layer dynamic graph structure as input, and performing node feature extraction by adopting a graph attention long-short-term memory network to obtain a non-grain ratio preliminary predicted value; non-stationary state space-variational Kalman filtering is adopted to correct the preliminary prediction value of the non-grain ratio, and a plot-level prediction value is obtained; and performing spatial reconstruction on the plot-level predicted value by using policy-sensitive Kriging interpolation. According to the invention, spatial continuity and time serialization cultivated land non-grain trend prediction is realized.

The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing driven land utilization monitoring system. According to the invention, by extracting a ground feature boundary contour in a remote sensing image and constructing a morphological parameter set with geometric structure proportion characteristics, a path category data system for dividing a land spatial form based on structural characteristics is established, and normalization processing and a Gaussian mixture model are introduced to realize ground feature aspect ratio clustering. Constructing a structural difference index set in combination with the distribution concentration ratio, clearly identifying the path type to track the land parcel direction or the structure change trajectory, and calculating a disturbance factor in the multi-temporal remote sensing image based on the land type number change and the connection direction number of the patch adjacent region; and the main direction, the boundary contour similarity and the spatial disturbance of the land parcel in the specified period are comprehensively judged, so that the dynamic change identification of the land utilization state is realized, and the land utilization form change amplitude and the time period characteristics can be accurately reflected by setting a judgment reference and a change state marking mechanism.

The invention relates to the technical field of irrigation area water and soil resource management, and discloses an irrigation plot multi-element information coding method comprising the following steps: S1, plot coding architecture design; s2, constructing a parcel code segmentation parameter database; s3, collecting and storing multi-element information; and S4, determining the land parcel code. According to the method, the multi-element information of the irrigation district canal system and the plot is visually and conveniently expressed by adopting the limited character length according to the established rule, the water consumption information and the plot multivariate attribute information on each plot are fully combined, and a unique identification code is compiled for each plot for identity recognition of the plot; water and soil resource management efficiency and scientific management level of the irrigation area are improved, and digital twinborn construction and modernization development of the irrigation area are assisted.

The invention belongs to the field of land parcel information extraction technology, and provides an agricultural machinery operation suitability evaluation method comprising the following steps: S1, based on a remote sensing image and a digital elevation model, extracting field parcel geometric features, road features, field obstacle features and terrain parameters, and calculating field parcel indexes; and S2, a multi-dimensional environment correction factor is calculated, the obstacle influence function and the agricultural machinery operation efficiency loss are integrated, a multi-parameter weighted agricultural machinery operation suitability evaluation model is constructed, and an agricultural machinery operation suitability index is calculated. The invention also correspondingly provides an agricultural machinery operation suitability evaluation system. The method not only reflects the direct influence of field obstacles on agricultural machinery operation, but also objectively quantifies the efficiency loss in actual operation through path planning simulation, and provides a scientific basis for precise reconstruction of farmland and intelligent scheduling of agricultural machinery.

An improved parcel growth prediction system that uses parcel data, population data, and artificial intelligence to predict the growth of a geographic area at a micro level (e.g., a real estate parcel level) is described herein. For example, the improved parcel growth prediction system may generate a graph model and apply the graph model as an input to an artificial intelligence model to predict the likelihood that a particular parcel may be developed some time in the future. Ultimately, implementing the improved parcel growth prediction system described herein may lead to more precise placements of infrastructure projects and / or to infrastructure projects that more precisely support the needs of the population of a geographic area as time passes.

The invention discloses a space-time knowledge graph-based facility layout scheme generation method. The method comprises the steps of S1, constructing an urban facility layout knowledge base; s2, acquiring a reference case place set of the target grid to be optimized; s3, extracting a facility significant co-occurrence mode in the reference case place set, and taking the facility significant co-occurrence mode as a recommended facility configuration mode of the target grid to be optimized; and S4, according to the feature vector of the city built environment of the target to-be-optimized grid obtained in the S1, inputting the feature vector and the recommended facility configuration mode of the target to-be-optimized grid obtained in the S3 into the constructed facility layout generation model, and obtaining an output result which is a facility layout scheme. According to the method, the facility distribution rule knowledge and the facility layout optimization intelligence are integrated, and the facility configuration recommendation and the facility layout optimization scheme can be automatically output for a specific land parcel.

The invention relates to a two-dimensional and three-dimensional boundary point association method based on improved boundary point coding and a medium, and the method comprises the steps: carrying out the preprocessing of original land parcel red line data, sequentially numbering land parcels, converting all the land parcels into plane boundary point elements, determining a first boundary point in each plane boundary point element, processing each land parcel into a clockwise land parcel, and carrying out the coding of the clockwise land parcels. Performing two-dimensional boundary point continuous numbering on all vertexes of the land parcel, taking the land parcel after encoding the two-dimensional boundary points as a two-dimensional surface element, and converting the land parcel into a land parcel three-dimensional stereoscopic model comprising three-dimensional boundary points, boundary lines and boundary surfaces; and continuously numbering all the three-dimensional boundary points in sequence by using a cross section analysis method to obtain a land block after coding the three-dimensional boundary points, and establishing an association relationship between the three-dimensional boundary points with successfully matched coordinates and the corresponding two-dimensional boundary points. Therefore, automatic coding of the three-dimensional boundary points of the land parcel red line data and automatic association between the two-dimensional boundary points and the three-dimensional boundary points are realized, and the three-dimensional boundary point management efficiency in land parcel management is improved.

The invention relates to the technical field of data analysis, in particular to a land resource management data analysis method and system based on cloud computing, and the method comprises the following steps: obtaining a difference time node plot number and a purpose field, recognizing a number evolution chain and establishing mapping, extracting a land class sequence to generate a stability label, analyzing the spatial continuity to construct an attribution path, and analyzing the attribution path. And indexing a utilization rate fluctuation trend paragraph, and identifying a purpose fusion direction to generate a fusion layer set. According to the method, through joint comparison of a serial number structure, coordinate overlapping and a purpose field, a stable land class transition chain is established, it is ensured that land class time sequence features are effectively described, the contiguous direction of a space dot matrix and the consistency of land class affiliation are combined, splicing of the space affiliation relation between land parcels is achieved on the regional level, and the splicing efficiency of the space affiliation relation between land parcels is improved. The identification precision and the spatial expression definition of the land type change are improved, and the spatial analysis capability of the land type change trend and the dynamic perception capability of the land utilization efficiency are effectively enhanced.

The invention discloses a high-precision remote sensing image cultivated land boundary extraction method, which comprises the following steps of: acquiring high-resolution remote sensing image data, preprocessing the data, and obtaining cultivated land parcel vector data through manual annotation; constructing a multi-task depth semantic segmentation model based on a coding and decoding structure; constructing a mixed loss function; acquiring a high-resolution remote sensing image of a cultivated land area to be detected and performing data preprocessing; inputting a high-resolution remote sensing image of a cultivated land area to be detected into the trained high-resolution remote sensing image cultivated land extraction model based on multi-task learning; and converting the cultivated land semantic segmentation result into cultivated land parcel vector data containing latitude and longitude coordinates. According to the method, through staged Transform coding based on overlapping patches and efficient sequence reduction, efficient multi-scale coding is realized, the problem of insufficient remote dependence capture is solved, and the computing power bottleneck of high-resolution self-attention is relieved.

A method for identification of land improvements in a given parcel of land that includes generating a first training data set by clipping a large image of a parcel of land into individual parcel images each including images of improvements, and each improvement being labeled with an improvement type, providing the individual parcel images to a first classification model, training the first classification model based on the individual parcel images to identify unlabeled improvements in a parcel image and to obtain a multi-label classifier, generating a second training data set of images, and training a second, semantic segmentation model based on the second training data set.

The invention discloses a corn yield estimation method based on multispectral remote sensing and a three-dimensional convolutional neural network, and the method comprises the following steps: obtaining a multi-temporal remote sensing image of the whole growth period of corn in a target region, and obtaining a multi-temporal remote sensing image of land parcels by land parcels; generating a yield grid map in the target area by adopting an inverse distance weight method based on ground actual measurement yield data; segmenting the yield grid map by taking the boundaries of the land parcels as masks, and taking the average value of all pixels in each land parcel as a yield value; pairing the yield value of each land parcel with the multi-temporal remote sensing images one by one, and constructing an image-yield pairing sample set; matching a sample set by using an image-yield, and training a three-dimensional convolutional neural network model; identifying a to-be-estimated multi-temporal multispectral remote sensing image by using the trained three-dimensional convolutional neural network model to realize plot-level corn prediction; according to the method, high-precision plot-level corn yield prediction is realized by fusing the multi-temporal multispectral remote sensing image and the three-dimensional convolutional neural network.

The invention provides a vehicle turning path planning method and device for irregular land parcels, and is applied to the technical field of path planning, and the method comprises the steps: carrying out the initialization of a pheromone field based on the boundary data of a geographic information system and internal obstacle data, and constructing a rasterized map for representing a passable region; based on the current state of the vehicle, determining the minimum distance of obstacles in the surrounding environment of the target vehicle; based on the real-time movement speed, the minimum turning radius of the target vehicle is determined; determining a dynamic corridor parameter of the target vehicle based on the minimum distance and the minimum turning radius of the surrounding obstacle; based on the dynamic corridor parameters and the pheromone field of the rasterized map, generating a turning point probability density field of the target vehicle, and sampling the turning point probability density field to obtain a turning point set; and constructing a turning path of the target vehicle based on the turning point set, and determining the turning cost of the turning path. According to the invention, Pareto optimization of energy consumption and efficiency in a complex scene can be realized.

The invention belongs to the technical field of data analysis and processing, and particularly relates to a joint review and judgment method for territorial space planning, compiling and reviewing full-chain business, which comprises the following steps of: 1, reading a project declaration text, a reply text, a planning layer and a management and control layer, planning polygon elements and control polygon elements are read from the planning layer and the control layer, and corresponding enclosing rectangles are generated; 2, inputting a project application text marking sequence into the pointer network model, and performing polygon superposition operation on a project plot polygon and a retrieval result to form a spatial superposition unit set; and step 3, reading the territorial space planning management and control rule base, and generating a project joint review opinion list including a modified point location list and a review conclusion. According to the method, the examination efficiency can be remarkably improved, the manual operation amount is reduced, the examination consistency is improved, and high-precision and high-reliability intelligent support is provided for territorial space planning management.

The invention discloses a farmland plot remote sensing automatic extraction method and system based on an improved SAM model, and relates to the field of agricultural remote sensing image intelligent interpretation, and the method comprises the steps: obtaining a target remote sensing image, and carrying out the automatic blocking processing, normalization processing and coordinate registration processing, and obtaining a target remote sensing processing image; reasoning the target remote sensing processing image according to the target detection model to obtain a candidate bounding box; performing feature extraction on the target remote sensing processing image to obtain a pixel-level cultivated land probability graph; and constructing an RSParcel-SAM model according to a convolutional low-rank adaptive fine tuning strategy, a sparse hybrid expert network and a composite prompt injection mechanism, and inputting a target remote sensing image, a candidate bounding box and a pixel-level cultivated land probability graph to obtain a cultivated land parcel. According to the method, the problems of insufficient field adaptation, lack of semantic understanding and contradiction between strong prompt dependence and automation are solved, and high-precision, high-efficiency and high-robustness full-automatic extraction of the cultivated land parcels is realized.