443 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 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 semantic edge and segmentation-based agricultural plot form local updating method and device. The method comprises the following steps of: preparing a plot boundary vector of a previous period of a specified application area and a later-period target area remote sensing image which finally needs to be locally updated and extracted; selecting and designing a multi-task learning network model capable of simultaneously generating semantic segmentation and semantic edges; using the semantic segmentation and semantic edge multi-task learning model to train a previous-stage plot boundary vector and a later-stage remote sensing image to obtain a multi-task learning model weight, predicting high-resolution remote sensing image data of a target application area, and obtaining a line result and a surface result of agricultural cultivated land of the application area; and performing small pattern spot removal processing on a surface prediction result, comparing results of two-stage semantic segmentation, and selecting updated land parcel elements according to a threshold value. The updated land parcel elements are classified and processed according to the following conditions: 1, common edges do not exist: if the common edges do not exist, an edge vector result generated by a multi-task learning model through later remote sensing is directly adopted; 2, existence of a common edge: in the two-stage remote sensing images, the area of the agricultural plot may change (increase or decrease), the two-stage images are compared according to an edge fusion algorithm, the same edge in the two-stage images is reserved, and the changed edge is updated; according to the invention, local updating of the remote sensing image plot is finally realized.

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 provides an initial construction land parcel detection method fusing remote sensing time-space spectrum characteristics, which comprises the following steps: carrying out wave band operation on different time phase remote sensing images by utilizing a land cleaning land parcel detector, and realizing primary screening detection on potential change land parcels based on spectral characteristic variation caused by land cleaning; a double-branch deep convolutional neural network of a convolutional neural network based on an object-scene is used for extracting double spatial features, a pseudo-change region caused by farming activities and vegetation phenological changes is eliminated through decision-making level fusion of feature spaces, and finally high-precision initial development plot pattern spots of the construction land are output. According to the invention, the spatial features of the target object and the scene thereof can be synchronously extracted by using the double-branch deep network, and high-precision detection of the initial development plot of the construction land is realized; according to the method, high-precision extraction of the initial development plot of the construction land is realized, the problem of false detection caused by crop rotation and vegetation phenological change is solved, and the accuracy and reliability of a detection result are remarkably improved.

The invention provides a land space planning management method and system based on big data. The method comprises the following steps: acquiring original planning graph data; constructing an approval behavior event sequence; based on the prediction of the improved graph neural network, generating a prediction graph and a future purpose prediction result according to the path propagation of the improved graph neural network; according to the prediction map and a future use prediction result, identifying a use conflict trend possibly occurring in the next time period in the territorial space, quantifying the planning tension change intensity between the regions, and positioning a potential high-risk land parcel set; and according to the high-risk land parcel set, in combination with a future use prediction result, a use violation penalty value, an approval state vector, planning tension change intensity and original planning graph data, executing structural rule matching, and generating a structured management suggestion set.

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 relates to a farmland parcel identification method based on optical-Ka frequency band SAR feature fusion, and the method comprises the steps: carrying out the feature extraction of an optical remote sensing image through employing an improved ResNet50 network, carrying out the feature extraction of a Ka-SAR image through employing a complex convolution network, triggering a gating mechanism when the cloud coverage rate of the optical remote sensing image exceeds a threshold value, and carrying out the recognition of a farmland parcel. If the cloud coverage rate of the optical remote sensing image does not exceed the threshold value, carrying out feature fusion by adopting a cross-modal attention fusion mechanism; and outputting a farmland plot identification probability graph based on the obtained fusion features based on a UNet + + decoder, and performing optimization and iteration on a result by adopting a geometric constraint loss function to obtain a final identification model. The cross-modal attention fusion method is adopted to perform feature fusion, physical-level collaborative fusion for data features is realized, and meanwhile, the problem that an output result does not meet agricultural management requirements due to the fact that farmland parcels cannot be completely recognized and specific regular geometric attributes of farmland are ignored in a multi-cloud scene is solved.

The invention provides a farmland plot identification method, device and equipment based on multi-source data, and the method comprises the steps: obtaining first remote sensing data and second remote sensing data of a research region; wherein the resolution of the second remote sensing data is higher than that of the first remote sensing data; based on the first remote sensing data and a first target model, dividing the research area into at least one type of first agricultural plots; the at least one type of target area represents land parcel distribution of different land utilization types of the research area; based on the at least one type of target area, the second remote sensing data and a second target model, generating a target type block corresponding to the research area; the target category blocks represent land parcel distribution of the target land utilization type in the research area. By adopting the method, the precision of agricultural plot identification is improved.

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.

A land-use planning system includes a data collection module configured to extract a shape file associated with a property address of a plot of real property in a jurisdiction. The shape file includes a location, a geometry, and attribution of a point, a line, and / or a polygon features of the plot of real property. An artificial intelligence (AI) model is adapted to analyze the shape file. The AI model is fine-tuned based on a regulation governing lot subdivision in the jurisdiction. A recommendation engine is integrated with the AI model to generate an optimal plot boundary suggestion to adhere to the governmental regulation while maximizing financial viability of split lots from the property address. A visualization component creates a visual representation of the split lots in the jurisdiction displaying the optimal plot boundary suggestion on a rendering of the shape file.

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 provides a cultivated land planting plot boundary extraction method and system based on a high-resolution remote sensing image. The method comprises the following steps: for a high-resolution image, firstly carrying out data processing work such as geometric correction and image enhancement, then respectively carrying out boundary extraction by using a boundary recognition network to obtain basic space information of a land parcel object, and obtaining surface feature attributes by using a semantic segmentation network to preliminarily eliminate the influence of confused surface features; and finally, optimizing the boundaries of the land parcels by using a post-processing method, and further eliminating the influence of confused ground features to obtain a final land parcel object. The scheme provided by the invention can be used for high-resolution remote sensing images, and is high in extraction precision, accurate in boundary, good in effect and low in manual correction cost.

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 relates to the technical field of agricultural product production management, and discloses an agricultural product production base information dynamic monitoring and analysis system. The system comprises a basic data acquisition module for acquiring base and land parcel information and coding and storing the base and land parcel information; the production process dynamic monitoring module is used for collecting and fusing production activity data according to product forms; the environment data integration module is used for collecting, processing and analyzing environment parameters through an Internet of Things sensor network; the detection data integration module is used for detecting product quality data by using multi-mode equipment, screening abnormal values and storing the abnormal values in a block chain; and the traceability code generation module is used for generating batch traceability codes according to the multi-module data so as to realize whole-process data association and consumer query. The problems of disordered information management, incomplete production monitoring, lagged environment monitoring, lack of association of quality detection, difficulty in tracing and the like in a traditional management mode are solved, the management level of an agricultural product production base is improved, the quality safety of agricultural products is guaranteed, the credibility of consumers is enhanced, and agricultural modernization development is promoted.

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.

Implementations set forth herein relate to utilizing S2 cell values to characterize arbitrary portions of land parcels and storing the S2 cell values in association with a non-fungible token (NFT) that is stored on a blockchain network, or other peer-to-peer (P2P) network. The S2 cell values can be generated by iteratively using bounding shapes that are selected to extend over at least a portion of a respective parcel of land, and each bounding shape can be represented by one or more single dimensional values. When a generated bounding shape extends outside of a boundary of a parcel of land, subcells of the bounding shape can be generated to define further bounding shapes. A land NFT for the list of cell values for the bounding shapes can be stored at a blockchain address for an authenticated owner of the parcel of land.

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 discloses a natural resource survey result analysis method and system based on image recognition, and relates to the technical field of natural resource survey monitoring, and the method comprises the steps: obtaining historical remote sensing information and geographic information of a target section, and determining at least one divided land parcel of the target section; analyzing each divided plot according to historical remote sensing information of the target section, and determining gradient feature information of each divided plot; remote sensing data information of the target plot in different time sequence segments is collected, and the real-time gradual change feature of each divided plot is obtained; the remote sensing technology is adopted to divide the plot contour of the target plot in advance, and then the historical remote sensing feature distribution condition of each divided plot in different periods is collected, so that an effective reference is provided for the real-time remote sensing feature distribution expression of crops in each divided plot, and whether the abandoned phenomenon exists or not is effectively judged. Therefore, the purpose of accurately monitoring the abandoned phenomenon of the agricultural cultivated land is effectively achieved.