60 results about "Urban land" patented technology

The invention discloses a land utilization type fine-grained remote sensing interpretation method based on a self-supervised learning framework, and relates to the technical field of hyperspectral remote sensing image processing and geographic information analysis. The advantages of satellite and unmanned aerial vehicle images are combined, the spectral characteristic difference is dynamically balanced by using a double attention mechanism, the relevance between wave bands and labels is mined based on a self-supervised learning framework, and land utilization first-level global and second-level fine-grained interpretation is realized. According to the method, the feasibility of the multi-mode hyperspectral remote sensing image in urban land utilization monitoring is provided, and the defects of the traditional method in the aspects of strong and insufficient marking dependence, obvious same-spectrum foreign matter phenomenon, inaccurate secondary class interpretation and the like are overcome.

The invention provides a simulation design method of an urban ecological corridor, which comprises the following steps: S1, collecting a multi-temporal thermal infrared remote sensing image of a city to be simulated and designed and preprocessing to obtain a core heat island node; s2, heat resistance surface construction is carried out based on different surface types, a heat transfer resistance surface is obtained, and the different surface types comprise a digital elevation model, an impervious surface index, a normalized vegetation index, a normalized building index, a normalized water body index and a gradient; s3, taking the core heat island node as a network end point, searching a communication path with the lowest resistance on a heat transmission resistance surface, and obtaining an urban heat island corridor; and S4, on the basis of the urban land utilization data, ecological lands of forests, wetlands, large parks and water bodies serve as candidate ecological source lands, ecological connection paths are constructed from the angle of ecological connectivity by adopting the S2 and the S3, and the urban ecological corridor is obtained.

The present application relates to a kind of carbon emission space refinement simulation and driving mechanism analysis method based on multi-source data and machine learning, including obtaining night light remote sensing, population density data, multi-source data such as interest point density, nonlinear spatial fitting model is constructed and trained by using information entropy weight method to carry out multi-source data fusion and construct economic energy comprehensive index, use city land use classification data as industry space restriction, combined with the total carbon emission of each industry calculated to build carbon emission space simulation base map, based on extreme gradient boosting tree, introduce SHAP framework for post-analysis, from global, local and spatial three scales, the nonlinear driving mechanism of carbon emission of multi-source city form element is analyzed, overcome the over-saturation defect of single night light data in city core area, realize the leap from pure space fitting to mechanism explanation, provide scientific basis and method support for high-density city accurate locking emission hotspot and making low-carbon policy.

The invention discloses an urban ventilation environment simulation and prediction method and system based on different planning objectives, and particularly relates to the field of urban ventilation environment simulation and prediction, and the method comprises the steps: obtaining ventilation characteristic data, land utilization data and regulation information data for many years as data sources; unifying the data sources to the same coordinate system and spatial resolution, and performing rasterization and numerical normalization processing; constructing a land utilization prediction model based on the PLUS based on the land utilization data and the regulation information data; and rasterizing the driving factors of the land utilization change. Regulation information is introduced in a land utilization prediction process, a dynamic land utilization conversion matrix is constructed, and a space-time diagram neural network and an entropy weight method are combined for calculation, so that joint modeling and quantitative evaluation of an urban land utilization pattern and a ventilation environment under a multi-level management and control condition are realized; the problem of systematic deviation between a simulation result and actual execution in the prior art is solved.

The present application relates to the technical field of geographic information system, and more particularly to a kind of city land planning analysis method and system based on GIS, by integrating remote sensing, historical planning, mobile terminal and social media data, construct multi-scale spatiotemporal cube model, generate standardized city temporary land data, adopt adaptive feature extraction to identify temporary land, establish hierarchical classification system, and monitor abnormal change through time series model, construct the association diagram of temporary land and city function network, analyze interactive relationship, finally propose differentiated city planning optimization suggestion, help city land resource efficient allocation and management, by fusing multi-source data, realize the multidimensional cognition of space, time, function and relationship, fundamentally improve the understanding depth of temporary land.

This invention discloses an urban land use classification method based on the fusion of multi-source data and deep learning, comprising: Step 1: Constructing a spatiotemporal map using Poisson disk sampling and graph neural networks, integrating the spatiotemporal heterogeneity of multi-source data, and dynamically adjusting weights using an attention mechanism; Step 2: Extracting static features from remote sensing and DEM using Swin Transformer, processing dynamic features from social media and mobile phone signaling using LSTM, fusing static and dynamic features through cross-modal attention, and optimizing data matching degree based on Grad-CAM++; Step 3: Combining the person-to-land flow of mobile phone signaling with the spatial correlation of social media activities, predicting trends using LSTM and embedding ecological indicator constraints; Step 4: Constructing a cross-departmental data sharing platform, collaboratively optimizing planning through a unified indicator system, and dynamically adjusting parameters using social media to mine public demands and POI data; Step 5: Introducing ecological footprint and carbon emission indicators to assess sustainability, establishing a monthly update mechanism, and dynamically calibrating model parameters through real-time data streams.

The invention relates to an urban land utilization recognition method based on a BERT model text classification algorithm, and the method is characterized in that the method comprises the following steps: 1, determining an urban land utilization recognition type, determining an urban land utilization recognition region range, obtaining POI data in the region range, and carrying out the data screening; step 2, establishing an urban land utilization identification unit in an urban land utilization identification model based on a BERT model text classification algorithm, and associating the screened POI data with the urban land utilization identification unit; step 3, carrying out geographic text mining on the POI data; and step 4, performing urban land utilization identification of the urban land utilization identification model based on the BERT model text classification algorithm to obtain a high-precision urban land utilization identification result. According to the method, high-precision urban land utilization identification can be timely and accurately carried out by utilizing the available POI data.

This invention discloses a method for regulating the thermal environment of urban morphology under the coupling of human and bird's-eye view perspectives. It is based on the radiative transfer equation method and Landsat-8 remote sensing imagery to retrieve land surface temperature; it integrates multimodal data for refined extraction of urban feature information; it constructs a three-dimensional comprehensive representation system of urban morphology under the coupling of bird's-eye and human perspective perspectives; it establishes urban land surface temperature prediction models at different spatial scales, integrating two-dimensional urban morphology, three-dimensional urban morphology from bird's-eye view, and three-dimensional urban morphology from human perspective; and it explores the optimal configuration method for regulating the surface thermal environment of urban morphology at both fine and coarse scales. This invention can provide a scientific basis for the quantitative regulation and spatial planning optimization of the urban thermal environment, achieving refined cooling and thermal environment improvement effects through urban spatial structure optimization and greening configuration adjustment.

This invention discloses a method for assessing urban land green efficiency based on cross-regional technology flow maps. The method acquires the technology input factors, technology output factors, and land input factors of the target city and its related cities through data collection and processing rules, forming a basic data set. Based on cross-regional technology association determination rules, it identifies the correspondence between different cities in terms of technology transfer, technology output, and technology absorption, generating a cross-regional technology flow map. Based on this map, it constructs a set of land green efficiency influencing factors. By introducing the impact of cross-regional technology flow into the correspondence between land input and output, it achieves a comprehensive assessment of the target city's land green efficiency. This invention can reflect the impact of cross-regional technology flow on urban land green utilization efficiency, improves the objectivity and comparability of assessment results, and is applicable to urban green development assessment and land resource management decision-making scenarios.

The present application relates to the technical field of energy management, and especially relates to a water, electricity and gas comprehensive energy management platform for smart city, which comprises an environment sensing module, which is used to determine a typhoon radiation influence area in a target city when the target city enters a typhoon mode; a grid re-partitioning module, which is used to divide a plurality of modified city land blocks; a function area marking module, which is used to obtain a function area mark of a dominant category of each modified city land block; an energy distribution module, which is used to obtain a typhoon day unit electricity minimum reserve benchmark value corresponding to each modified city land block; a hoarding behavior identification module, which is used to determine whether there is energy hoarding behavior, and determine a hoarding behavior category when there is; and an abnormal expansion determination module, which is used to perform abnormal expansion determination to obtain an abnormal expansion determination result when a second duration risk level is obtained. The present application realizes intelligent management of city energy distribution by hoarding analysis and abnormal expansion determination on the typhoon radiation influence area.

The application belongs to the technical field of deep learning and remote sensing image processing, and specifically discloses a city land use mapping method based on multi-modal data collaborative perception, which comprises the following steps: performing parcel division on high-resolution remote sensing images of a research area to obtain irregular city parcels and remote sensing spectral features thereof; setting street sampling points along a road network, extracting street perception features and extracting interest point semantic features; constructing a heterogeneous graph structure based on the street sampling points, the street perception features and the interest point semantic features falling into the same parcel, and then extracting parcel-level multi-source geographic features; inputting the remote sensing spectral features and the parcel-level multi-source geographic features into a full sparse topic model for semantic alignment and fusion to generate fused parcel feature representations; and performing classification based on the fused parcel feature representations to output city land use mapping results. The application can realize high-precision and high-robustness city land use recognition under the condition that multi-source data is unevenly distributed or sparse.

The application discloses a kind of urban land reserve scale prediction system and method, it is related to urban planning and land management technical field, the application is by collecting urban land reserve total, annual increase and consumption area, land structure distribution and planning target structure etc. Data, calculate the dynamic coefficient reflecting the dynamic change of reserve scale and the structure adaptation coefficient for measuring the adaptation degree of structure and historical target. After the dynamic coefficient and the structure adaptation coefficient are standardized, the comprehensive index is calculated by combining weight, according to which the annual adjustment ratio is determined, and then the benchmark forecast reserve is calculated. Combined with the historical actual adjustment ratio, generate the forecast reserve of conservative, benchmark and active three kinds of scenes, determine the final forecast reserve by comparing with the average value of history. The application comprehensively dynamic trend and structure adaptability, supports multi-scenario analysis, and can provide scientific, flexible decision-making basis for urban land reserve planning.

The application provides a kind of urban land use automatic classification method and system, method includes: based on open source crowd sourcing geographic data production wide range land use training sample;Uncertainty perception context deep learning semantic segmentation network of end-to-end is constructed, and pixel-level land use classification product is obtained;Based on the segmentation of the remote sensing image to be classified by the bottom-up multi-scale segmentation algorithm, the pixel-level land use classification result is fused with the object-level segmentation boundary based on the mode vote, and the object-level land use classification product is obtained.The application is based on deep learning to automatically classify land use types, improve the classification accuracy, and save the labor cost.

The invention discloses an urban land unit greening priority evaluation method giving consideration to benefits and fairness, and the method comprises the steps: taking a potential newly-added green land as a configurable space resource from a supply side on a unified urban land unit scale, and combining land data and population space distribution, thereby achieving the evaluation of the greening priority of the urban land unit. The method comprises the following steps of: depicting a service propagation process from a newly-added green land to surrounding residents by utilizing an exponential spatial attenuation kernel function, converting the improvement of reachable green land into population weighted welfare increment through a welfare function with a marginal income decreasing characteristic, and generating a priority index capable of being directly sorted for each land unit according to the welfare increment; according to the method, the scale of the newly-added green land, the population exposure level, the current green land service insufficiency degree and the marginal welfare decline effect are considered in the same framework at the same time, and limited greening resources can be preferentially allocated to the region which is dense in population, relatively deficient in green land service and high in greening potential under the stock-oriented city updating situation.

The application discloses a kind of urban river channeling ecological construction methods, it is related to river ecological restoration technical field, including the following steps: the hardening cement part of channeling river bottom is crushed to form channeling river crushing layer;Grid cement grid is laid on channeling river crushing layer;Submerged plant is planted in grid cement grid, according to water environment, biological is added, to create pool bottom biological diversity ecological group, along the direction of river channel, the construction of urban river channeling ecology is built.The application not only reduces the occupation of river to urban land under the premise of retaining ecological system, but also saves urban livable environment, reduces river restoration cost;Through the interaction of river bottom and groundwater, the circulation system of river water and groundwater is built, the near-natural restoration of urban channeling river is better realized, the inherent microbial population of river is protected, and the self-purification capacity of river is realized.

The invention discloses an urban land surface coverage classification system based on a multispectral remote sensing technology, and relates to the technical field of spectral spatial data calculation. The system obtains land surface temperature data of a target area and a sub-area and calculates the change rate difference of the land surface temperature data; carrying out first-level correction on the initial contribution degree by utilizing a material thermal tuning coefficient; and performing second-level space coupling correction according to the correlation coefficient of the temperature change of the marked sub-region and the adjacent region, and finally generating an accurate urban surface heat contribution report. According to the method, the transformation of the urban thermal environment contribution from static recognition to dynamic quantitative evaluation is realized, and the accuracy, fineness and practical value of an evaluation result are remarkably improved. The technical problem that the spatial correlation dynamic evaluation adjustment accuracy of urban surface classification thermal contribution is insufficient is solved.

The application relates to the technical field of fitness site construction, in particular to a construction method of a multifunctional intelligent fitness site, which comprises the following steps: S1, measuring and releasing; S2, groove excavation, excavating grooves in the middle and both sides of a badminton site; S3, sports site construction, performing construction of site base hardening, leveling layer, concrete layer and ground layer; S4, installing a sliding frame in the groove in the middle of the badminton site; S5, hingedly connecting the bottom end of a liftable net column with the sliding frame; S6, installing a locking assembly; S7, installing a volleyball court surface layer winding shaft and a tennis court surface layer winding shaft; S8, installing a volleyball court plastic layer and a tennis court plastic layer, connecting the side edges of the volleyball court plastic layer with the volleyball court surface layer winding shaft, and connecting the side edges of the tennis court plastic layer with the tennis court surface layer winding shaft; the application can reduce the occupation of urban land due to the construction of sports sites, improve the utilization rate of urban land, and enable one sports site to be used for multiple ball games.

The utility model discloses an arch bridge pier, belongs to the field of bridge engineering, and solves the problems that a traditional frame pier is cumbersome in appearance, poor in spanning capacity in the transverse bridge direction and tedious in construction. The bridge pier comprises a pier body, a bearing platform and a pile foundation which are sequentially arranged from top to bottom, the pier body comprises a middle arch rib, side arch ribs and a pier top cap beam, the side arch ribs are located on the two sides of the middle arch rib and are semi-arched cantilever beams, the pier top cap beam is located on the top of the middle arch rib and the top of the side arch ribs, and a bridge pier skewback is arranged on the top of the bearing platform. An arch foot on one side of the middle arch rib and an arch foot of the side arch rib on the same side are jointly connected to a bridge pier skewback. The advantages that an arch structure is large in spanning capacity and high in material utilization rate are fully utilized, building materials are saved, the structure size is light, and the defect that surface cracks are caused by too large concrete hydration heat of a traditional frame pier is overcome. The overpass structure has large spanning capacity, ensures that the space under the overpass is transparent, and saves urban land resources.

The invention discloses an urban land utilization planning aided decision-making method and system based on big data, and the method comprises the steps: collecting land data and monitoring data of a plurality of preset cities, carrying out the semantic segmentation of a high-resolution remote sensing image of the land data according to deep learning, and obtaining a current land use type; setting initial weights of the partitions by adopting a multi-objective optimization algorithm; performing dynamic planning analysis according to the monitoring data to obtain a land utilization planning index, and when the land utilization planning index is greater than an index threshold value, introducing a dynamic weight adjustment mechanism to adjust the initial weight and refine partitions to obtain a grid region marked with the dynamic weight; step-by-step mask fuzzy C-means clustering is adopted to carry out secondary clustering on the grid region to obtain a local fine weight region, and a satisfactory decision-making mechanism is constructed according to the local fine weight region and urban development planning; and according to the satisfaction decision-making mechanism, constructing an urban land utilization planning auxiliary decision-making model, and carrying out multi-objective optimization on the urban land utilization planning auxiliary decision-making model.

The invention belongs to the technical field of urban land utilization and urban industrial park construction, and provides an urban industrial park land utilization efficiency measurement and influence evaluation method, which comprises the steps of basic evaluation database collection, current park data calculation, variable setting, staggered double difference evaluation model construction, land utilization efficiency measurement and influence evaluation analysis. The urban industrial park net carbon emission and the urban industrial park land utilization efficiency are evaluated and compared through carbon budget accounting, the global super-efficiency-based epsilon measurement model and the staggered difference model, data information is further analyzed and mined, key factors influencing the urban industrial park land utilization efficiency are clarified, and the urban industrial park net carbon emission and the urban industrial park land utilization efficiency are further analyzed and mined. And high-precision and dynamic evaluation of the land utilization efficiency of the urban industrial park is facilitated.

The application relates to the technical field of land monitoring, in particular to an intelligent urban land space change monitoring system based on data processing, which comprises a processor and a memory, the processor executes a computer program stored in the memory to realize the following steps: acquiring a suspected land change region, screening the suspected land change region according to pixel values of pixel points in the suspected land change region and each edge section of the suspected land change region, obtaining a shadow region and a land change region on a current shadow correction image, performing shadow correction on the shadow region according to a non-shadow region adjacent to the shadow region, obtaining a current target image, and re-performing region change judgment on the current target image to obtain a land non-change region and a land change region on the current target image. The application can improve the effect of monitoring and identifying urban land space changes.

The invention discloses an urban land planning analysis method based on a neural network, and relates to the technical field of land planning, and the method comprises the steps: carrying out the risk scoring of each grid according to a risk index, and marking the grid of which the risk score is greater than a risk threshold value as a target region; acquiring a multi-source data set and disaster and toughness data of the target area, and constructing a disaster risk prediction model to output a disaster risk map; constructing a toughness correlation model, and outputting a toughness coefficient according to the disaster risk map and the disaster and toughness data; setting a plurality of objective functions according to the disaster risk map and the toughness coefficient of the target area to obtain candidate planning schemes, performing microenvironment evolution and disaster dynamic simulation on each candidate planning scheme to obtain an evaluation score, and determining a final planning scheme; the disaster risk map and the toughness coefficient are combined, the optimal balance between environmental sustainability and disaster toughness is achieved, the causal relationship between the microenvironment and the disaster risk is dynamically recognized, accurate prediction is conducted, and long-term scientific planning is achieved.

The invention relates to the technical field of urban resource management, and discloses an administrative supervision and resource management system for the whole life cycle of an urban land parcel, and the system comprises a data set collection module which is used for obtaining the life cycle data of the land parcel and generating an evidence fingerprint; the geometric identifier chaining module is used for normalizing geometric data and generating land parcel identifiers and state commitment records; the index generation module is used for calculating a progress deviation rate, a plot ratio and a purpose consistency index; the resource matching module is used for calculating the resource demand quantity, the supply quantity and the matching degree index; the constraint linkage solving module is used for generating a constraint version and executing feasible region calculation; the co-transaction solidification module is used for performing co-transaction uplink on the resource flow allocation result and the state commitment record; and the deviation write-back snapshot module is used for aggregating the deviation and generating a new-stage constraint version and a state snapshot. According to the invention, dynamic supervision, resource optimization configuration and state credible tracing of the whole process from planning to operation of the urban plot are realized.

The application discloses a kind of space building land planning system and method, it is related to building land planning technical field, including the following steps: obtaining the plot boundary data of planning area, plot is coded as functional unit, and construct plot function proportion vector;K order neighborhood structure of functional unit is constructed, and neighborhood aggregation is carried out to plot function proportion vector, obtain neighborhood function proportion vector;Based on neighborhood function proportion vector, clustering and anomaly detection are carried out to functional unit, obtain several imbalance units;The plot function proportion vector of imbalance unit is disturbed and adjusted, and several function proportion adjustment path sequences are obtained based on preset path generation algorithm;The neighborhood disturbance cost of function proportion adjustment path sequence is evaluated, and land planning album is updated according to the evaluation result, solve the problem that neighborhood relationship is ignored in traditional urban land planning to the influence of land, leading to the accuracy and rationality of planning adjustment reduce.

The invention relates to an urban land optimization configuration method based on coordination between land investment and benefit output. The method mainly comprises two parts of identification of a coordination current situation between land use input and benefit output and urban land use optimal configuration based on coordination between land use input and benefit output, and comprises the following steps: firstly, evaluating land use input and benefit output to identify the coordination current situation between the land use input and the benefit output; and then, according to the current coordination situation between land investment and benefit output, land optimization configuration under different planning targets of the city is realized. According to the method, land use optimization configuration is realized from land use input and benefit output, matching land use optimization configuration can be carried out according to urban difference development planning targets, and a reference basis can be provided for territorial space planning; and high-quality development of the region can be realized through coordination between land investment and benefit output by taking a planning target as a guide in a land space planning process.

This application discloses a method and apparatus for urban environmental thermal risk assessment and early warning based on multi-source data, relating to the field of data processing technology. The method includes: acquiring multi-source data of the study city in a target year; preprocessing the multi-source data to obtain a standardized multi-source dataset; generating a local climate zone map based on the standardized multi-source dataset, and constructing a future land use simulation model and a thermal risk assessment model; calculating the thermal risk index of different blocks in the local climate zone map and the thermal risk index under future urban land use change scenarios based on the thermal risk assessment model; dividing the study city's areas into corresponding thermal risk levels based on the thermal risk index, thereby generating a thermal risk level distribution map; and triggering a graded early warning mechanism based on a preset risk threshold and the thermal risk level distribution map. This application rapidly and completely identifies the spatial distribution of urban environmental thermal risks and provides thermal risk early warning through multi-source data, which can assist in the formulation of thermal mitigation strategies.

The invention relates to the technical field of settlement simulation, in particular to a city ground settlement simulation method and system fusing InSAR and borehole, and the method comprises the steps: obtaining historical InSAR data and borehole stratum data of a target area, and carrying out the preprocessing of the obtained historical InSAR data and borehole stratum data; generating a three-dimensional grid of the target area by using the preprocessed historical InSAR data and the borehole stratum data; obtaining a settlement curved surface of the target area based on the three-dimensional grid of the target area, and performing real-time rendering on the settlement curved surface based on the scene features of the target area; and acquiring real-time InSAR data of the target area to form an InSAR time sequence data column, and driving the settlement curved surface to dynamically deform by using the InSAR time sequence data column to generate a dynamic settlement animation.

The application discloses a precipitation prediction method and system based on a spatial non-uniform fractal urban canopy model, and the precipitation prediction method based on the spatial non-uniform fractal urban canopy model comprises the following steps: collecting meteorological data of a target urban area; inputting the collected meteorological data into a mesoscale numerical weather prediction model fused with the spatial non-uniform fractal urban canopy model, and outputting a precipitation prediction result. The spatial non-uniform fractal urban canopy model is a construction of urban land surface parameters with a spatial scale scaling law characteristic; the fractal geometry theory is used to describe the spatial scale scaling law of the urban building distribution, and the theory is introduced into numerical weather prediction, so that the numerical weather prediction has the ability to solve the non-uniformity of the city on a fine scale on the meteorological mechanism across scales, especially the local atmospheric movement process that may cause strong convection and precipitation, and thus the simulation precision and the prediction ability of strong precipitation events in the city and the surrounding area are effectively improved.

The invention discloses an urban low-efficiency land identification and analysis method and system based on multivariate data, and relates to the technical field of urban land planning, and the method comprises the steps: obtaining and preprocessing basic land data, extracting a target type of land, and carrying out the attribute association and spatial linkage of the target type of land and multi-source social economic data; constructing a qualitative and quantitative low-efficiency land identification evaluation index system, and judging whether various types of lands are low-efficiency lands or not through an expert weighting and comprehensive evaluation method to obtain a preliminary low-efficiency land identification result; carrying out multi-subject and multi-type field check on the preliminary identification result, integrating multi-source data to form a correction data set, carrying out refined screening and boundary correction on the land parcel, and generating a final low-efficiency land identification result layer; and performing standardized storage on the final affirmation result, establishing an annual data dynamic updating mechanism, and performing iterative updating on the existing final affirmation result set based on the latest multi-source data. According to the invention, personal errors can be greatly reduced, and the recognition efficiency and accuracy are improved.

The application discloses a kind of urban public transport corridor design methods based on multi-objective optimization model, this method can fuse city land use POI (Point of Interest, point of interest) data, resident trip OD (Origin-Destination, origin-destination) data and corridor construction cost, to realize the line selection and level planning of multi-angle consideration city public transport corridor.The present application is based on multi-objective optimization theory, forms the mathematical model of public transport corridor design, compared with the experience judgment method and two-step clustering method widely used at present, the method can be based on existing traffic demand and future development trend, obtain more accurate and reasonable public transport corridor design result, greatly improve the efficiency of urban public transport corridor planning, reduce the time and cost of artificial design.