28 results about "Land-use planning" patented technology

The invention relates to an AI-based planned land site selection multi-objective optimization method and system. The method comprises the following steps: constructing a city data cube; constructing a cellular automaton model and generating a land utilization potential map; constructing a game decision model, and generating a preliminary site selection scheme set; inputting the preliminary site selection scheme set into a cellular automaton model to generate an evolution simulation data set; constructing a multi-target evaluation model, and calculating the relative closeness between each scheme in the preliminary site selection scheme set and an ideal solution; generating a site selection decision report according to the relative close degree; in conclusion, the urban data cube is constructed by integrating multi-source real-time and historical data, the dynamic land potential map is generated by applying the cellular automaton model, and the multi-target scientific balance is realized by introducing the multi-agent game decision. Automatic processing and consistency guarantee of planning rules are realized, a scientific quantitative tradeoff mechanism in a multi-target conflict scene is provided, and the method has the effect of improving data timeliness and dynamic response capability of site selection decision.

The invention discloses a potential diffusion model-based building planning type plane generation method and system, and the method comprises the steps: collecting a land use planning map, and the total plan layout data and plane layout data of a building / building group, and constructing a corresponding data set; a pre-trained potential diffusion model is used as a base model, low-rank adaptation fine tuning training is carried out, and a low-rank adaptation model is obtained; and based on the pre-trained potential diffusion model, loading a low-rank adaptation model, inputting the sample data into the model, and generating a corresponding general plan layout / plane layout scheme of the building / building group. The method provided by the invention is small in data demand, flexible in data processing and high in generation speed, so that a reasonable planar graph or general graph is generated according to a newly input contour or partial content during reasoning; the problems of low design efficiency, dependence on personal experience, low flexibility, high cost, limited design result and the like of the traditional land planning, building and building group total plane layout and building plane generation method are solved.

The invention discloses a land utilization planning method based on AI driving, relates to the technical field of land planning, and solves the technical problems that it is difficult to construct a regional heterogeneous graph and calculate spatial dependence intensity by using a heterogeneous graph attention network, and it is also difficult to construct a multi-agent reinforcement learning model with a planned region as an environment. Comprising the following steps: firstly, constructing a land feature tensor containing land configuration affinity and a development pressure evaluation value; constructing a regional heterogeneous graph by taking the land feature tensor as an initial feature of each node in the graph, calculating spatial dependence intensity among the nodes by using a heterogeneous graph attention network, and generating a land unit enhanced feature vector; the method comprises the following steps: firstly, obtaining feature vectors of different planning target agents, constructing a multi-agent reinforcement learning model based on the feature vectors, simulating games among different planning target agents, generating a Pareto optimal land utilization scheme set, and finally, integrating a cellular automaton to carry out multi-scene dynamic deduction, and receiving a user interaction instruction to generate a final planning scheme.

The invention discloses a water area space land utilization function evaluation regulation and control method. The method comprises the following steps: collecting multi-source heterogeneous data of a water area space to construct a three-dimensional heterogeneous information network; inputting the three-dimensional heterogeneous information network into a pre-trained heterogeneous graph neural network to generate a node embedding vector; based on the node embedding vector, extracting a dynamic evolution characteristic tensor of a water area space land utilization function through a space-time diagram convolutional network; inputting the dynamic evolution characteristic tensor into an ecological system service value evaluation model, and outputting an ecological value matrix; and by taking the ecological value matrix as a constraint condition, calling a multi-objective optimization algorithm and performing collaborative optimization in combination with a multi-agent reinforcement learning framework, and generating a Pareto optimal solution set of water area space land utilization planning and a corresponding water area function partition configuration scheme. According to the method, scientificity, reasonability and sustainability of water area space land utilization planning are achieved, the land utilization rate is increased, and sustainable development of the water area space is promoted.

The invention discloses a land survey auxiliary device for land utilization planning, which belongs to the technical field of land survey, and comprises a shell, a manual rotating shaft arranged outside the shell, a ruler belt fixedly connected with the outer surface of the manual rotating shaft, and an annular plate fixedly connected with the front surface of a bottom cylinder arranged on the outer surface of the shell, and the lower part of the inner wall of the shell is fixedly connected with a pair of communicated screen drums. According to the device, when the ruler belt is pulled to drive the manual rotating shaft to rotate or the manual rotating shaft is rotated to wind the ruler belt, the first piston rod reciprocates on the inner wall of the piston groove, external air flows to the outside of the screen drum, and the effect of cleaning dust on the outer surface of the ruler belt is achieved under the cooperative arrangement of the first banister brush; and the conditions that due to accumulation of impurities such as dust, reading is difficult in the follow-up use process or blocking occurs in the winding process are relieved, the outer surface of the tape is automatically cleaned when the tape is stretched and wound in the device, and follow-up repeated use of the device is facilitated.

The invention relates to the technical field of three-dimensional geographic modeling, in particular to a land utilization planning auxiliary method and system based on a 3D terrain model, and the method comprises the following steps: obtaining point cloud and elevation information, converting the information into a terrain curved surface, discretizing the information into a voxel grid, analyzing a planning index, converting the planning index into a geometric constraint boundary, and traversing to construct a planning voxel field. Calculating earthwork digging and filling requirements and sunshine hours to generate an evaluation matrix, correcting the building voxel distribution and finely adjusting the terrain elevation. According to the method, terrain refined expression is realized by using an octree segmentation algorithm, indexes such as a plot ratio are converted into three-dimensional space geometric constraints, site suitability is evaluated through connectivity analysis, and building layout and earthwork balance are automatically optimized by adopting morphological operation, so that the problems of lack of space intuition and error accumulation in traditional two-dimensional planning are solved; the planning calculation precision and decision scientificity under the complex terrain are remarkably improved, and dynamic adjustment and visual expression of the scheme are achieved.

The utility model provides a geography surveying and mapping device for territorial space planning, which comprises a base, a surveying and mapping instrument, an adjusting column, a sliding seat, a limiting ring, a plurality of supporting legs and a plurality of connecting rods, the surveying and mapping instrument is arranged on the base, the adjusting column is arranged below the base, a plurality of vertical sliding grooves are formed in the peripheral side of the adjusting column, the sliding seat is slidably sleeved on the adjusting column, and a first limiting groove is formed in the outer side surface of the sliding seat; the top ends of the supporting legs are hinged to the sliding seat, second limiting grooves are formed in the outer sides of the supporting legs, one ends of the connecting rods are hinged to the supporting legs, the other ends of the connecting rods are hinged to the bottom ends of the adjusting columns, when the supporting legs are folded, the connecting rods are embedded into the vertical sliding grooves, and the supporting legs are flush with the outer side face of the sliding seat. The first limiting groove communicates with the second limiting groove, the limiting ring is slidably connected with the second limiting groove, and the technical problems that in the prior art, due to the fact that a binding rope or a cover body needs to be externally arranged to fix supporting legs of a tripod of the surveying and mapping device, the tripod storage and movement efficiency is low, and the equipment cost is increased are solved.

The application discloses a kind of regional water resource consumption spatialization method, comprising: 1) constructing research area database, integrating the grid data of water consumption data and influence factor in region;2) data is preprocessed, and eliminate dimensional difference;3) screening key influence factor;4) constructing multiple linear regression model;5) based on ArcGIS platform, in combination with the grid data of key factor, generate regional water resource demand quantity spatial distribution diagram;6) according to spatial distribution diagram, the result of rasterization is verified with original observation data, guarantee the accuracy and applicability of model.The application method integrates multiple influence factors, filters out key influence factor, uses linear regression optimization model, realizes the high-resolution spatial distribution expression of regional water resource demand quantity by means of GIS technology, solves the problem that traditional method ignores the coupling relationship of multiple influence factors, and can provide important scientific basis for water resource management, land use planning and ecosystem protection.

The invention discloses a surveying and mapping data acquisition and analysis system for a land utilization planning investigation project. The surveying and mapping data acquisition and analysis system comprises a multi-source data acquisition module, a data preprocessing module, a data fusion module, an intelligent analysis module and a result output module. According to the invention, a macroscopic spectral image is obtained through a hyperspectral satellite, local details are focused through multi-spectral photography of the unmanned aerial vehicle, soil data are monitored in real time by a ground sensor, and multi-source data complement each other, so that the comprehensiveness and accuracy of the data are greatly improved; in coastal zone monitoring, satellite remote sensing, shipborne sonar and a shore-based sensor are integrated, air-sea-shore three-dimensional monitoring is achieved, information covering the terrain, the ecological environment and the like is obtained, and compared with single coastal image collection of a common method, dynamic changes of the coastal zone can be reflected more comprehensively.

The invention relates to the technical field of multi-objective optimization algorithms and land utilization planning, and discloses an improved reference vector guided evolutionary algorithm for multi-objective land utilization optimization and application. Aiming at the problems of poor convergence and diversity, strong initial population randomness and the like of the existing algorithm technology in high-dimensional multi-objective optimization, the improvement of the method comprises the following steps: firstly, adopting Latin hypercube sampling to initialize a population, and improving the space filling property and randomness; and the convergence and diversity are dynamically balanced through an enhanced angle penalty distance function, the adaptive angle penalty factor can be attenuated from 2.0 to 0.5, and the problems of early-stage excessive development and later-stage diversity loss are avoided. According to the method, the problem of high-dimensional complex optimization of multiple targets, multiple decision variables and multiple strong constraints of land utilization optimization is solved. The method aims at supporting the national dual-carbon target, guaranteeing the drainage basin water quality safety and guaranteeing the sustainable development of the drinking water source in the Guangdong Hong Kong Australian Bay area.

The invention discloses a farmland land utilization planning method and system based on unmanned aerial vehicle images, and relates to the technical field of image processing. The method comprises the following steps: preprocessing an original to-be-registered image to obtain a to-be-registered image, extracting a direction response vector of the to-be-registered image by using a phase consistency algorithm, calculating a maximum characteristic value to obtain a main moment response diagram, and extracting pixel point coordinates of local extreme points; calculating a second-order index eigenvalue according to a position relationship between primary and secondary direction indexes in the direction response vector, and generating a second-order index mapping graph; dividing sector units according to pixel point coordinates, counting second-order index characteristic values in the sector units, performing circumferential weighted convolution processing and circumferential cyclic displacement operation according to a dominant texture direction to obtain a candidate set of image descriptors to be registered, and performing similarity calculation on the candidate set and historical image descriptors to obtain an optimal matching pair; and aligning the second-order index mapping graph by using the optimal matching pair, and performing farmland land utilization planning through the aligned second-order index mapping graph.

The invention relates to the technical field of land utilization planning, in particular to a land utilization information rapid calculation and key protection area discrimination method and system. The method comprises the following steps: acquiring multi-source remote sensing data of a forest land area and preprocessing the multi-source remote sensing data to obtain a time sequence fusion elevation data set; the method comprises the following steps: constructing crown elevation change data in a time sequence mode, analyzing and judging a crown height change trend through a time sequence elevation difference value, and carrying out classified marking on a forest land change region to obtain structure change identification data; establishing a multi-factor scoring model based on the structure change identification data and the ecological factor data, and performing ecological comprehensive scoring on the forest land areas to obtain ecological score values of different forest land areas; and according to the ecological score values of different regions, identifying the focuses-protected forest land region. According to the method, continuous change analysis of the canopy structure of the forest land area on a multi-temporal scale is realized, the rapid calculation efficiency of forest land state change is improved, and dynamic identification of a key protection forest land area is realized.

The application discloses a kind of multi-modal model city solid waste high-precision extraction methods based on multi-source data, including collecting city solid waste multi-modal data, including city solid waste remote sensing optical image, remote sensing spectral data and surrounding ground object data, the data collected are preprocessed;Based on the data after pre-processing, construct sample library, train optical recognition model, spectral recognition model and ground object recognition model respectively through sample library, the optical recognition model after training is used for the preliminary screening of solid waste area, obtains the positioning and classification result of solid waste point, the spectral recognition model after training is used for further screening to the solid waste point screened by optical recognition model, the ground object information around the solid waste point screened by optical recognition model and spectral recognition model is input into ground object recognition model, and ground object recognition model outputs solid waste category;The application is suitable for city solid waste monitoring, environmental protection and land use planning, and is suitable for solid waste information extraction in complex urban environment.

Based on hydrology-hydrodynamic model pipe network drainage capacity and land use planning method, including for the target area, build urban watershed, including collecting urban basic information, set urban rainfall scenario; Construct urban pipe network drainage capacity design and land use planning method based on hydrology-hydrodynamic integrated model, including hydrology physical model and 2D kinematic-wave hydrodynamic model; According to the historical observation data, the model parameters are calibrated and verified; Output urban pipe network drainage capacity design and land use planning.

The invention relates to the technical field of land use planning design and evaluation, and discloses a land space low-efficiency land use digital planning method based on improved comprehensive evaluation, and the method comprises the steps: carrying out the feature extraction of crowd flow time series data based on the land information of land use, and generating a land space utilization rate evaluation index; clustering by adopting a space-time clustering mode, generating clustering density information and converting the clustering density information into a space low-efficiency land use index; marking the land inefficient land, and setting adjustable design parameters of the land inefficient land; and optimizing the adjustable design parameters of the territorial low-efficiency land by using an improved particle swarm algorithm to obtain an optimal design scheme of the territorial low-efficiency land. According to the method, the space low-efficiency land index is generated based on the evaluation index and the clustering information, the land low-efficiency land is marked, the adjustable design parameters are set, the optimal design scheme is generated by constructing the fitness function and combining the improved particle swarm optimization, and efficient utilization and intelligent planning of the land low-efficiency land are achieved.

The invention provides a multi-objective land utilization optimization method based on spatial data, which integrates land surface settlement data as a key constraint variable into an optimization model, and quantifies land surface settlement by integrating land utilization, social economy and ecological data and utilizing sentry SAR data, so that the method has the advantages that the land utilization efficiency is improved, and the land utilization efficiency is improved. A multi-objective function which pursues economic benefit maximization and ecological benefit maximization at the same time is constructed; and then, carrying out multi-objective optimization by adopting an improved non-dominated genetic algorithm (NSGA-II), and realizing spatial refined distribution of the optimized land utilization structure by applying a PLUS model. According to the method, the defect that the dynamic change of the geological environment is neglected in the existing method is overcome, and the optimization result can truly reflect the ground surface settlement risk, so that a scientific decision basis is provided for making a land utilization plan considering safety, development and protection in rapid development and geological sensitive areas.

This application belongs to the field of land use planning verification technology, and discloses a method, apparatus, storage medium, and equipment for land use planning verification. It involves acquiring a planning vector map and a color block planning map of the area to be verified; inputting the color block planning map into a convolutional neural network to extract color block features, obtaining a multi-scale feature map; inputting the multi-scale feature map into a pre-trained semantic segmentation network for color block segmentation, outputting color block regions; constructing a topological structure map of the area to be verified based on the color block regions; inputting the topological structure map and the planning vector map into a graph neural network to analyze topological relationships, and obtaining a state prediction result for each target node by aggregating the features of the target node itself and the features of its neighboring nodes. The state prediction results include compliance, attribute violation, spatial violation, or combined violation; integrating the state prediction results, and generating a verification report based on a rule engine. This can improve the efficiency of land use planning verification tasks and enhance the consistency and stability of verification results.

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.

This invention relates to the field of machine learning technology, proposing a method and system for public participation planning in urban renewal using resident agent reward feedback reinforcement learning. The method includes: acquiring geospatial data of the city to be planned and constructing an adjacency topology graph model; constructing resident agents corresponding to different roles based on public participation corpora of the city to be planned using a large language model; generating land use adjustment actions based on the features of the adjacency topology graph model using a reinforcement learning policy network; inputting the land use adjustment actions into the resident agents and calculating resident satisfaction reward values ​​based on the evaluation results; iteratively training the reinforcement learning policy network with the goal of maximizing the resident satisfaction reward value; and outputting a land use planning scheme for the city to be planned through the trained reinforcement learning policy network. This invention achieves a real-time closed loop between public participation and planning optimization, significantly improving the public adaptability and implementation efficiency of urban renewal planning.

The invention discloses a power distribution network planning scheme generation and recommendation system based on machine learning, relates to the technical field of power system planning, and aims to solve the technical problems that traditional power distribution network planning is low in efficiency and poor in adaptability, and complex scene requirements of variable loads and high new energy proportion in a family innovation area are difficult to meet. Comprising the steps that a data interface module serves as an interaction entrance of a system and an external data source, receives multi-source data and carries out preprocessing and transmission, and preprocessing comprises format standardization and abnormal value elimination; and the data storage module adopts a hybrid storage architecture, safely and efficiently stores the multi-source data transmitted by the data interface module, and supports rapid query and calling of the data. According to the method, the core problems of long generation period and low adaptation degree of the planning scheme of the department innovation area are effectively solved, the data integration time is greatly shortened, the generation period of the scheme is shortened, and the adaptation degree of the initial scheme and the power utilization demand and land use planning of the department is greatly improved.

This invention relates to the field of land planning technology, specifically to a land use planning optimization method and system based on spatiotemporal big data. A land use planning optimization system based on spatiotemporal big data includes: a historical land use data sequence acquisition module, a change characteristic calculation module, and an iterative optimization module. This invention acquires multi-temporal land use remote sensing raster map sequences of the land to be planned, constructs a pixel-level land use change dataset, comprehensively characterizes the land use evolution trends and change sensitivity of each location at different historical stages, and ensures that the model can identify the spatial distribution characteristics of stable areas and high-frequency change areas. Based on land type change statistics, a global transition matrix and trend probability vector are constructed to achieve quantitative modeling of land use evolution patterns, and this is used for trend-guided construction of the initial population of a genetic algorithm, improving the directionality and convergence efficiency of the optimization.

The application belongs to the technical field of land use planning and ecological environment protection, more specifically, relates to a land use scenario simulation method and system for ecological function improvement, through obtaining land use and driving factor data of a study area, dynamically evaluating habitat quality and analyzing spatio-temporal evolution characteristics; eliminating redundant collinear factors, accurately identifying key driving factors and their influence thresholds through multi-model coupling, solving the problems of core driving selection and quantitative constraint deficiency; then converting the thresholds into spatial ecological constraints, combining with regional policies to build differentiated land use scenarios, substituting into the calibrated spatial simulation model to predict future land use patterns; finally, calculating future habitat quality, positioning ecological risk areas, coupling ecological background grade to delimit control zones and develop differentiated management strategies, forming a complete optimization scheme; perfecting the connection between simulation results and land space governance, and forming a land use pattern optimization scheme for ecological function improvement.

The invention discloses a regional water resource consumption spatialization method, which comprises the following steps of: 1) constructing a research region database, and integrating water consumption data in a region and raster data of influence factors; 2) preprocessing the data to eliminate dimensional difference; 3) screening key influence factors; 4) constructing a multiple linear regression model; 5) on the basis of an ArcGIS platform, generating a regional water resource demand spatial distribution map in combination with the raster data of the key factors; and 6) checking the rasterized result and the original observation data according to the spatial distribution diagram to ensure the accuracy and applicability of the model. According to the method, the multi-element influence factors are integrated, the key influence factors are screened out, a linear regression optimization model is utilized, high-resolution spatial distribution expression of the regional water resource demand is achieved by means of the GIS technology, and the problem that the coupling relation of the multi-element influence factors is neglected in a traditional method is solved; and an important scientific basis can be provided for water resource management, land utilization planning and ecological system protection.

The application discloses a city land use recognition method based on remote sensing images, and relates to the technical field of city land use planning.The application solves the problem of insufficient fine features of the original recognition mode, locks core boundary pixels from a complex gradient pixel point set by pixel interval quantization, feature circle construction and refined point screening, and significantly improves the contour accuracy.Compared with the traditional single line contour, the refined contour can more completely represent the feature form, is especially suitable for irregular terrains, and reduces classification errors.The pixel mean value and variance features are used as the measurement, the number of combined areas and the internal feature similarity are taken into account, the optimal combination is screened through weighted calculation, scattered division or excessive merging is avoided, and the generated optimal combined area is highly consistent with the requirements of function aggregation and land use cooperation in city planning, thereby significantly improving the planning efficiency and scientificity.

This invention discloses a method for identifying and coordinating conflicts among multiple land use plans, comprising: collecting multi-dimensional data through a land use dynamic monitoring and analysis platform; identifying potential conflict areas and types using a spatiotemporal dynamic conflict early warning and simulation model; analyzing the conflict mechanism of spatial elements using a three-dimensional spatial element collaborative optimization algorithm; classifying conflict intensity levels using an ecological land use conflict quantitative assessment model; and formulating and simulating adjustments to a coordination and control scheme based on various parameters for identifying and coordinating conflicts among multiple land use plans. This invention, through multi-model collaborative linkage and a closed-loop design throughout the entire process, accurately captures the characteristics of multi-plan conflicts in the spatiotemporal dimensions, achieving a systematic and precise approach to conflict identification and coordination. It effectively solves the problems of identification bias and insufficient scheme adaptability in traditional methods, providing technical support for the scientific implementation of land use planning.

The invention discloses an engineering construction project land argumentation and analysis system based on multi-source data. The engineering construction project land argumentation and analysis system comprises a preprocessing module, a conversion module, a partitioning module and a prediction module, the preprocessing module is used for acquiring construction land resource field survey data and generating standard construction land resource field survey data; the conversion module is used for acquiring multi-source geographic information data and generating multi-source geographic elevation data; the zoning module is used for performing topographic feature analysis on the multi-source geographic elevation data and generating regional zoning land parcels and functional zoning land parcels; the prediction module is used for performing land parcel coincidence marking on the regional partition land parcels and the functional partition land parcels, generating a planning and construction simulation model, and generating a land utilization planning scheme for display according to the planning and construction simulation model; the method and the system are used for solving the technical problem that an existing engineering construction land analysis system lacks comprehensive analysis on land planning, so that the accuracy and the operability of an engineering construction land analysis planning result are insufficient.

The invention relates to a multi-scenario simulation method based on future land utilization, and aims to provide a scientific basis for land utilization planning management. The method comprises the following steps: S1, data collection and processing: collecting and processing related data, such as administrative vector data, DEM, climate, road, population and GDP data, and ensuring data unification and consistency; s2, driving force factor analysis: evaluating the influence of each driving force through a quantitative analysis method and a spatial analysis method, such as land utilization change analysis and transfer matrix analysis, and displaying the contribution of each driving force through methods such as a geographic detector and geographic weighted regression. And S3, future land utilization simulation: based on the Markov model and the PLUS model, simulating land utilization data under different scenes in the future, including natural development, ecological protection and economic development scenes. And S4, land utilization space-time evolution analysis: analyzing time and space evolution of land utilization, providing sustainable development suggestions, providing decision support for land utilization planning, and promoting optimal configuration of land resources.