52 results about "Land type" patented technology

The invention discloses an intelligent fusion processing method and system for forest and grass wet resource pattern spots and annual land change survey data, and belongs to the field of space-time big data in the natural resource industry, and the method comprises the steps: completing the pattern layer fusion based on the annual land change survey data in combination with forest and grass wet pattern spot survey results; superposing county and rural boundaries to form an administrative fusion layer; performing subcompartment division based on the remote sensing image; merging broken classes according to a principle of adjacent positions and similar types; eliminating a pattern spot sharp angle; land classes are refined, and attribute information is perfected; the public welfare forest range and the protection level are optimized; automatically checking and summarizing to form a result layer; and finally performing statistics to generate various thematic reports. According to the method, technologies such as database storage, spatial index construction and a fusion algorithm are adopted, the data processing efficiency is improved by more than 50%, and the sharp angle processing time is shortened; and the labor cost and the time investment are obviously reduced.

The invention relates to a remote sensing image segmentation method and system based on land utilization, and the method comprises the steps: collecting continuous periodic remote sensing images of the same region, marking a land type and a seasonal factor vector, and determining whether to carry out zoning or not according to a latitude span; then identifying the boundary of the miniature land parcel, calculating the boundary identification degree, delimiting a protection area, respectively calculating the seasonal factor vectors of the non-protection area and the protection area, and fusing the seasonal factor vectors into a global seasonal factor; secondly, preliminarily segmenting the image by adopting a fuzzy C-means clustering model in combination with a global seasonal factor, and finally carrying out image re-segmentation and verifying the accuracy in combination with a plot seasonal feature and boundary recognition degree correction model; according to the method, through operations such as fine seasonal factor vector construction, latitude zoning, protection area delimiting and multi-feature fusion, the shadow area land type classification accuracy is effectively improved, the influence of seasonal variation and boundary blur in a complex earth surface scene can be reduced, and the robustness and adaptability of the model are enhanced.

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 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 land type adjustment and simulation method based on carbon neutralization constraint, and the method comprises the following steps: obtaining land data of a target region, and calculating the carbon flux of each classification space; constructing a carbon profit and loss weight function based on the carbon flux, the ecological benefit and the economic benefit as an overall constraint condition; reversely deducing each land space area corresponding to a preset time node on the basis of a Markov chain model, and taking the land space areas as stage constraint conditions; performing NSGA-III optimization solution based on the constraint condition to obtain a corresponding land use adjustment scheme; an improved PLUS model is adopted to simulate a land use adjustment scheme, the carbon cost of land conversion is incorporated into a land utilization simulation process, and a genetic algorithm is utilized to optimize model parameters to obtain a land space simulation result of a target year. According to the method, a carbon cycle mechanism, a carbon sink optimization target and a land utilization decision full process are coupled, a closed loop of carbon constraint-land simulation-policy assessment is realized, and scientific decision support is provided for regional carbon emission reduction and ecological protection.

The application belongs to the technical field of space-time data analysis, and discloses a POI data-based remote sensing image semantic label extraction method, which realizes the extraction of the semantic content label of the remote sensing image by analyzing the POI data in the coverage area of the remote sensing image from the perspectives of place names and land types. Firstly, a land type label set and a place name label set as well as a density threshold and a coverage threshold of the land type label and the place name label are preset. Then, a POI data set in the coverage range of the remote sensing image is calculated and obtained, the attributes of the POI data set are subjected to Bert semantic similarity calculation with the land type label set and the place name label set, and labels with high similarity are obtained as a pre-extracted label set of the land type and the place name. Subsequently, the coverage and the density of each label in the pre-extracted label set are calculated, and labels with the coverage and the density both greater than the density threshold and the coverage threshold are screened out as the final semantic label extraction result. The method solves the problems of high cost, great difficulty and poor effect in the extraction of the semantic label in the prior art.

The application provides a planning partition-land conduction effectiveness evaluation method and device, which has the following characteristics: step S1, constructing a planning partition-land function attribute conduction matrix; step S2, obtaining a plurality of planning land vector graph patches of the planning partition; step S3, obtaining a dominant land type; step S4, aggregating the planning land vector graph patches to obtain land aggregation graph patches; step S5, obtaining coordinate values of each vertex of the planning partition and the land aggregation graph patches; step S6, calculating a characteristic vector; step S7, calculating a characteristic vector; step S8, calculating a conduction deviation coefficient; and step S9, obtaining a conduction effectiveness evaluation result according to the conduction deviation coefficient. In summary, the method can obtain the conduction effectiveness evaluation result.

The application discloses a method for intelligent verification of land change evidence photos based on multi-source information fusion, and has the characteristics that a to-be-verified image set, a travel database and a land type database are acquired respectively; travel features are determined according to the to-be-verified image set and the travel database; whether the to-be-verified image set is abnormal is judged according to the travel features and the travel database; when the to-be-verified image set is abnormal, the to-be-verified image set is marked as wrong; when the to-be-verified image set is not abnormal, first land feature types in a to-be-verified area are determined according to the land type database; second land feature types in each photo in the to-be-verified image set are determined according to the photos; and qualified to-be-verified image sets are determined according to the first land feature types in the to-be-verified area and the second land feature types in each photo in the to-be-verified image set. The application constructs a multi-level automatic verification framework, reduces the problem of false evidence from the technical level, and effectively improves the verification efficiency of evidence photos.

The application discloses a land use status map data generation method based on large-scale topographic maps, and steps include: collecting and establishing basic databases such as large-scale topographic maps, high-resolution image maps and the like; constructing a generation path of a land use status map basic unit, deconstructing elements, structures, information and the like of the large-scale topographic maps, analyzing natural and artificial features of the land, and determining a utilization direction of geographic information elements in the land use status map data generation; constructing a basic element base map through element extraction and data integration, combining land feature status characteristics to demarcate boundaries of the land and identify land types, and optimizing overall expression of the present land use; and the like. The land use status map data generation method breaks the path of conversion from the topographic map to the land use status map data, has advantages such as fine land use classification, accurate land block space and detailed spatial expression, and can provide multi-level technical support for national space planning and natural resource management.

The application discloses a land management system and method for highway engineering projects, and relates to the field of land management.The system comprises a land project change module, which changes land types, pile numbers, quantities and land unit prices according to actual site construction conditions on the basis of land project information to obtain updated land project information; an audit module, which sends the corresponding updated land project information to each audit node according to a first process audit chain; a protocol generation module, which generates a land project protocol by calling a preset protocol template when the audit is passed; the audit module, which sends the corresponding land project protocol to each audit node according to a second process audit chain; a settlement generation module, which generates a land settlement protocol when the audit is passed; the audit module, which sends the corresponding land settlement protocol to each audit node according to a third process audit chain; and a settlement archiving module, which settles according to the land settlement protocol when the audit is passed.The application improves the efficiency of land management in highway engineering projects.

The invention discloses a land recommendation service system and method based on big data, and relates to the technical field of land recommendation, and the system comprises a land type primary selection module, a user attention degree collection module, a key element analysis module, and an adaptation degree analysis and land recommendation module, which are used for receiving the type demands of user land use, the method comprises the following steps: preliminarily screening lands in a database according to type requirements, obtaining a primarily selected land set, setting an interactive weight distribution interface, obtaining the attention degree of a user to attention elements, respectively analyzing the adaptation degree of the attention elements to the user, and comprehensively analyzing the adaptation degree of the primarily selected land to the user according to the attention degree and the adaptation degree. According to the method, the primarily-selected land is regarded as a circular area with an actual influence range, the concept of land influence distance is introduced, the convenience degree of daily commuting of the user is reflected more truly, and time and energy are saved for the user through automatic evaluation and recommendation.

The invention belongs to the technical field of remote sensing image processing, and particularly provides a land resource monitoring method and device based on a remote sensing image, and electronic equipment, and the method comprises the steps: obtaining a target remote sensing image of a to-be-monitored land resource, the target remote sensing image comprises at least one mask region, the mask region is a region which is determined to be the same land type in history; framing the target remote sensing image into a plurality of framing image blocks, and segmenting at least one pattern spot in a mask area of each framing image block; aiming at each pattern spot, a plurality of target block diagrams of different scales are determined, and the target block diagram of each scale at least comprises each pattern spot; and based on the multiple target block diagrams of different scales, identifying target land types of land resources in the target block diagrams through a pre-trained land type identification model. Through the technical scheme provided by the invention, the accuracy of land resource monitoring can be improved.

The invention relates to a territorial space land use refining method, device and equipment and a storage medium, and belongs to the technical field of geographic information systems and territorial space planning, and the method comprises the following steps: obtaining multi-source spatial data; carrying out data reclassification, and establishing a mapping relation between the original category of the POI and a land use sea classification standard for the land and the land space; performing coordinate system unified conversion and standardized preprocessing on the multi-source spatial data; generating a territorial space planning basic unit based on the business data; the AOI planar evidence and the re-classified POI punctiform evidence are fused, and the comprehensive evidence intensity of different land use types in each planning basic unit is calculated; determining the land use type of each planning basic unit by combining a multi-threshold judgment mechanism with a spatial neighborhood smoothing algorithm; and outputting a land use identification result and generating a land use thematic map for land space planning. According to the method, the accuracy of land use identification, the hybrid function identification capability and the spatial rationality of the result are effectively improved.

This application discloses a method, apparatus, and electronic device for determining land types, relating to the field of data processing technology. The method includes: determining multiple first land types and corresponding first area data for each first land type in a target area based on digital elevation data; acquiring an orthophoto map of the target area; processing the orthophoto map using a target neural network model to obtain multiple second land types and corresponding second area data for each second land type in the target area; and comparing and analyzing the multiple first land types, the corresponding first area data, the multiple second land types, and the corresponding second area data to obtain multiple target land types and corresponding target area data for each target land type in the target area. This application solves the problem of low accuracy in identifying land types and area data of target areas in related technologies.

A land use classification method based on remote sensing images, comprising the following steps: step 1: obtaining the original image of remote sensing images of urban and township land, marking the pictures after screening, and a total of four categories: cultivated land, orchard, forest and building; step 2: cutting and data enhancement are carried out on the marked pictures to make a data set; step 3: the training set in the prepared data set is put into a feature extraction network and a multi-scale fusion up-sampling structure for training to obtain a segmentation model; step 4: the remote sensing image to be classified is put into the trained segmentation model to obtain the result; the purpose of the present application is to solve the problems of low small target precision and poor edge segmentation effect when the land categories are many and the features are complex in the land classification method based on remote sensing images, and a method capable of realizing more accurate identification result of various land types in remote sensing images is proposed.

The invention relates to the technical field of carbon emission, in particular to a carbon emission evaluation method and system for land utilization change. The invention discloses a carbon emission evaluation method and system for land utilization change. The system comprises a data preprocessing module, a carbon emission evaluation module and a carbon emission evaluation correction module. According to the method, the remote sensing image of the actual area is aligned with the planning design drawing, land type labeling is carried out on the rasterized image of the actual area in combination with the land type labeling network, the land type change diagram is constructed, simulation analysis is further carried out in combination with the carbon emission variation corresponding to land type conversion in the historical record, and the real-time analysis result is obtained. Inputting a carbon emission change distribution analysis network to generate a carbon emission change distribution diagram; the carbon emission change distribution diagram is corrected by combining the spatial distribution relation on the basis of the land type transformation and aggregation area, and the carbon emission change distribution diagram is optimized by using convolution operation, so that the corrected image can more accurately reflect the carbon emission change of the planning and design area.

The invention provides a natural resource element space-time process analysis method based on land type pattern spots. According to the method, a geographic vector pattern spot is used as a minimum space unit, spatial and temporal change types (newly increased, changed and killed) of land cover plaques are defined, and a corresponding algorithm is constructed. Firstly, multi-period basic geographic information data are collected and preprocessed, pattern spots are extracted and endowed with unique codes, and a topological structure and standardized codes are checked. And then realizing a spatio-temporal variation algorithm, judging the pattern spot variation type and calculating the area variation. And storing the data into a space-time database adopting an Oracle + ArcSDE engine, and carrying out space-time process analysis and visual expression, including a plurality of modes such as time axis animation and the like. The method is high in precision, avoids precision loss, is high in space-time complexity expression capability, is good in visualization effect, can provide scientific basis and decision support for the fields of natural resource management and the like, and is wide in application prospect.

The invention discloses a differential pattern spot repairing and attribute inheriting method oriented to land class docking. The method comprises the following steps: reading a background land class pattern spot and an updated land class pattern spot from a database by using GeoPandas; a result table RES is initialized, a unified coordinate system is CGCS2000, the area and overlapping area of each pattern spot are calculated, and an overlapping sequence table BLPULP is constructed; filtering updated land class pattern spots in the BLPULP through an overlapping proportion threshold value, extracting an overlapped BLPID unique sequence from the BLPULP for subsequent iteration processing, and if the overlapping proportion of a certain background land class pattern spot and the updated land class pattern spot is greater than a preset threshold value, directly inheriting an updating attribute and storing the updating attribute into RES; if the overlapping proportion of a certain background land type pattern spot and the updated land type pattern spot is not greater than a preset threshold value, screening an internally tangent pattern spot and an edge matching pattern spot, processing the two pattern spots, and adding the processed pattern spots to RES; and transferring the final RES list into an SRI Shapefile format through the GeoPandas, so that the final RES list can be directly used. According to the method, batch repairing and updating of differential pattern spots are realized, and the efficiency and precision of land class docking are remarkably improved.

The invention relates to the technical field of land utilization optimization, and particularly discloses a land utilization multi-objective optimization method and device, equipment and a storage medium, and the method comprises the steps: obtaining target economic data, target environment data and target control constraint data; after an economic benefit function and an ecological benefit function are constructed, a multi-target genetic algorithm is utilized to determine balance benefit points of the land classes under target control constraints; inputting the target environment data and the target economic data into an FLUS model for evaluation to obtain a large-area type suitability atlas and screening out a small-area sensitive region; inputting an actual existence point corresponding to the small-area sensitive region into a MaxEnt model for evaluation to obtain a small-area type suitability atlas; and determining a land utilization space distribution result of the target area in combination with the balance benefit point. According to the scheme, the land utilization simulation precision of the small-area ecological sensitive area is improved by constructing a coordinated land utilization optimization system of control constraints, ecological benefits and economic benefits.

The application provides a remote sensing monitoring information extraction data checking method, device, equipment and medium. The method comprises the following steps: using ArcGIS to identify the original land type patch in the land type patch layer on the patch initial extraction result layer and generating a corresponding land type name field; performing logical field checking on the land type name field to determine a corresponding monitoring type field; using ArcGIS to extract the result requirement field in the patch initial extraction result layer; using ArcGIS to fuse the patches corresponding to the result requirement field and the monitoring type field with the same attribute and split the fused patches; using ArcGIS to perform topological checking on the patches; calculating the patch area and deleting the patches with small areas; numbering the patches and determining the attribute of the result requirement field; and outputting the checking result of the remote sensing monitoring information extraction data. The method improves the accuracy of remote sensing monitoring information extraction and avoids information omission and errors caused by manual checking.

The application belongs to the technical field of remote sensing image processing, and specifically provides a land resource monitoring method and device based on remote sensing images and electronic equipment. The method comprises the following steps: obtaining a target remote sensing image of a land resource to be monitored, the target remote sensing image comprising at least one mask area, the mask area being an area historically determined as a same land type; dividing the target remote sensing image into multiple sub-image blocks, and segmenting at least one map patch in the mask area of each sub-image block; determining, for each map patch, a plurality of target frame maps of different scales, wherein each target frame map of each scale comprises at least the each map patch; and identifying a target land type of a land resource in each target frame map based on the plurality of target frame maps of different scales through a pre-trained land type recognition model. The technical scheme provided by the application can improve the accuracy of land resource monitoring.

The invention discloses a forest land type differentiation data processing system and method based on a GIS (Geographic Information System). The method comprises the following steps: automatically setting an area threshold value according to a woodland type through a parameter mutual exclusion constraint mechanism of the woodland type and a data source; according to a global topology overlapping processing algorithm, the overlapping relation of different types of forest lands is processed according to priorities; historical data is fixed with a non-deduction rule; based on the spatial index of the grid division method, the size of the grid can be automatically adjusted within the range of 10-500 meters; detecting the adjacency relation through intersection of the buffer areas; the component analysis algorithm and the fusion tool are connected to execute element combination; and detecting rule keywords, and identifying classification errors according to Class values and Layer field contents. According to the method, the technical problems of parameter configuration conflict, incomplete topology overlapping processing strategy, low spatial index efficiency, inaccurate element combination and the like are solved, and the accuracy and efficiency of forest land data processing are improved.

The invention relates to the technical field of geographic information processing, in particular to a multi-modal space-time information fusion-based land type recognition method, which comprises the following steps of: constructing a multi-modal land type recognition model framework, and inputting photo data of a to-be-recognized ground feature and corresponding space-time metadata; performing feature extraction on the input photo data based on an image feature extraction sub-network to obtain image features; performing feature coding on the geographic position and the space-time metadata based on the space-time information coding sub-network to obtain a space-time feature vector; sending the image feature representation and the spatial-temporal feature vector into a multi-modal feature fusion module, and performing alignment fusion to obtain a multi-modal feature; processing the multi-modal features by adopting a dynamic fusion strategy to obtain a fusion feature vector; according to the method, a multi-modal fusion strategy is adopted, so that the model can give consideration to local details and global environment information, and the precision and stability of land class recognition are remarkably improved.

The application relates to the technical field of information management, in particular to a construction land surveying and mapping information management method and system based on the Internet of Things and a medium. The method comprises the following steps: obtaining construction land surveying and mapping data through the Internet of Things, and performing collaborative sensing fusion to obtain a construction land multi-modal sensing matrix; performing multi-source consistency correction on the construction land multi-modal sensing matrix to obtain a standardized surveying and mapping tensor; obtaining construction land soil data, and analyzing the construction land soil evolution trend based on the construction land soil data; adjusting the semantic weight of the standardized surveying and mapping tensor according to the construction land soil evolution trend and the standardized surveying and mapping tensor to obtain a surveying and mapping enhanced semantic hypergraph; performing land type adaptive sparse coding on the surveying and mapping enhanced semantic hypergraph to obtain real-time surveying and mapping flow data blocks, and uploading the real-time surveying and mapping flow data blocks to a land information management platform for information storage tasks. The application can improve the data retrieval efficiency and accuracy of surveying and mapping data.

The land space land use refinement method, device, equipment and storage medium of the present application belong to the technical field of geographic information systems and land space planning, and the method comprises the following steps: acquiring multi-source spatial data; performing data reclassification to establish a mapping relationship between POI original categories and land space land use classification standards; performing coordinate system conversion and standardization preprocessing on the multi-source spatial data; generating land space planning basic units based on business data; fusing AOI surface evidence and reclassified POI point evidence to calculate the comprehensive evidence strength of different land types in each planning basic unit; determining the land use type of each planning basic unit through a multi-threshold determination mechanism combined with a spatial neighborhood smoothing algorithm; and outputting the land use recognition result and generating a land space planning land use thematic map. The present application effectively improves the accuracy of land use recognition, mixed function recognition ability and spatial rationality of the result.

The invention discloses a satellite image quality evaluation method and system based on an image search engine. The method comprises the following steps: constructing reference image databases of different land types by adopting airborne images; constructing a CLIP model, and pre-training the CLIP model by adopting the reference image database; performing image preprocessing on the satellite images collected according to the land types, and respectively creating test sample sets of the corresponding land types; inputting the test sample sets of different land classes into the CLIP model for image search, and calculating the matching accuracy of each land class sample according to a matching result; and performing weighted fusion calculation on the matching accuracy of the different land samples to obtain an evaluation index, and performing quality evaluation on the satellite image according to the evaluation index. According to the technical scheme of the invention, the method gets rid of the errors of subjective judgment and the limitation of physical indexes of manual design, is higher in objectivity, and is more suitable for high-resolution satellite images and complex ground feature contents.

The invention provides an image recognition method based on land features, and the method comprises the steps: S11, carrying out the positioning processing of a to-be-recognized part of a land feature image, obtaining the corresponding coordinates of the to-be-recognized part of the land feature image, projecting the boundary line of a vector pattern spot to the to-be-recognized part of the land feature image, and obtaining a proof image; s12, segmenting the proof image through an SAM segmentation algorithm to obtain a to-be-identified area; s13, performing low-element identification on the to-be-identified region to obtain a corresponding land type; and S14, after the identified land type is matched with the change investigation land type, classifying the land feature image. When the change investigation land feature image is checked, automatic classification can be carried out according to the proof photo and the land feature image, and an auxiliary effect on change investigation is achieved.

The invention relates to the technical field of land area measurement, and discloses a land area information acquisition system based on territorial space planning, comprising: a data acquisition module for obtaining a digital elevation model; the terrace three-coupling perimeter gain calculation module is used for calculating and obtaining terrace three-coupling perimeter gains; the direction sensitivity coefficient calculation module is used for calculating to obtain a direction sensitivity coefficient; the equivalent external expansion radius calculation module is used for calculating to obtain an equivalent external expansion radius; the area correction module is used for calculating to obtain a corrected area; and the summarizing output module is used for summarizing the corrected area and uncertainty of each land type. According to the method, a terrace frequency band is extracted according to a digital elevation model, a terrace weight is generated, terrain noise of a non-terrace area can be filtered, and a three-coupling perimeter gain kernel is constructed by fusing slope projection zoom illumination visibility and an orthographic and elevation model error sensitive item; therefore, the high-precision and high-credibility requirements of terraced space planning on terraced field area information are met.

The invention provides a method and system for screening available land parcels of reserve land, and the method comprises the steps: constructing a remote sensing land database based on ArcGIS, integrating multi-source heterogeneous geographic space data, and carrying out the preprocessing of original remote sensing land data; a plot type deduction system is established, and deducted land is obtained; and constructing an artificial intelligence large model training data set and optimizing a large model system, and carrying out land type classification identification on the deducted land by adopting a large model. According to the invention, automatic and intelligent screening and identification of available land are realized, efficient utilization and dynamic supervision of land development are realized, and a method and system support is provided for promoting land utilization and development, layout optimization and system governance.

The invention relates to the technical field of land planning, in particular to a land utilization planning optimization method and system based on space-time big data. The invention discloses a land utilization planning optimization system based on space-time big data. The system comprises a historical land utilization data sequence acquisition module, a change feature calculation module and an iterative optimization module. According to the method, a multi-temporal land utilization remote sensing grid map sequence of a to-be-planned land is obtained, a pixel-level land utilization change data set is constructed, land type evolution trends and change sensitivities of all positions in different historical stages are comprehensively represented, and it is ensured that a model can recognize spatial distribution characteristics of a stable region and a high-frequency change region; a global transfer matrix and a trend probability vector are constructed based on land type transformation statistics, quantitative modeling of a land type evolution mode is realized, the method is used for trend-guided construction of an initial population of a genetic algorithm, and the directivity and convergence efficiency of optimization are improved.