154 results about "Urban space" patented technology

The invention discloses an urban flood toughness evaluation method, apparatus and device, a medium and a computer program product. The method comprises the steps of obtaining hydro meteorological data of a to-be-evaluated region and geographic information data of an urban spatial form element layer; setting boundary conditions of a plurality of flood scenes according to the hydrometeorological data, constructing a multi-scene urban flood disaster simulation model in combination with geographic information data, and respectively generating flood inundation depth data of urban spatial form element layers of the plurality of flood scenes; and calculating a first toughness index, a second toughness index and a third toughness index of each flood scene so as to calculate a flood toughness comprehensive evaluation result of each flood scene of the to-be-evaluated region. According to the method, an evaluation system of multiple composite flood disaster scenes is established, different disaster factors and interaction thereof are comprehensively considered, and the effect of key space parameters in urban flood toughness is fully considered, so that the capability of coping with flood disasters in cities can be more comprehensively and accurately evaluated.

The invention provides an urban space intelligent processing method based on multi-modal fusion, and the method comprises the steps: taking multi-modal data as input, and constructing a unified data stream processing and feature alignment mechanism; a physical space is used as a core framework, and the multi-modal data is converted into a space behavior graph with space-time position semantics; constructing an entity attribute-relation type-influence weight ternary interaction model on the basis of an interaction layer of the spatial behavior map, and analyzing a human, object and environment ternary interaction relation in the city and the park based on the ternary interaction model; designing a space intelligent engine with time sequence modeling and dynamic prediction capabilities; and constructing a task processing system. According to the invention, through deep combination of multi-modal fusion and a space intelligent technology, full-link upgrading of urban space from data perception to intelligent decision is realized, and powerful technical support is provided for fine management, efficient operation and safety guarantee of complex space scenes.

The invention discloses an urban healthy community space intelligent assessment method and system, and relates to the technical field of urban space intelligent assessment and healthy community planning, and the method introduces space grid division, street network modeling and graph theory analysis technologies, achieves the high-precision modeling and reachability simulation of an urban community space, and achieves the intelligent assessment of the urban community space. And the coverage capability and the service balance of the 15-minute walking life circle of residents can be accurately evaluated. According to the method, the reachable path network taking each grid unit as a starting point can be dynamically constructed, and the service accessibility level and the comprehensive service scoring index of each grid are quantitatively evaluated according to the quantity vector of the resident reachable service facilities. By setting dual thresholds of coverage rate and score, a'potential function blind area 'is intelligently identified, and a'cold space grid' is accurately discriminated by further combining a resident popularity activity sequence, so that scientific support and decision basis are provided for subsequent city updating, service facility layout optimization and community health space transformation.

The invention discloses an urban ventilation corridor construction method based on local climate region classification and remote sensing inversion, and belongs to the technical field of urban climate regulation and space optimization. According to the method, a multi-scale urban thermal environment analysis framework is constructed, a coupling mechanism of an urban form and a thermal effect is systematically identified from macroscopic, mesoscopic and microscopic levels, and fine modeling and regulation and control path identification of the thermal environment are realized. Meanwhile, in combination with machine learning and interpretability analysis methods, scientificity and transparency of thermal environment driving factor identification are enhanced. Through combination of remote sensing inversion, morphological factor construction and three-dimensional analogue simulation, a complete technical path of cold source identification, resistance modeling, path optimization and microclimate response evaluation is provided, and the aeration-cooling potential identification capability of blue-green infrastructures is effectively improved. The method is suitable for wind gallery planning and climate adaptation type update design of various urban spaces, and has wide popularization and application prospects.

The invention relates to the technical field of city data representation. The invention discloses an urban space general representation learning method and device based on multi-modal spatio-temporal data fusion, a terminal and a storage medium, which can improve the applicability of urban general representation and enable the urban general representation to be applicable to diversified urban analysis tasks. The method comprises the following steps: acquiring multiple modal spatio-temporal data of each space unit in a target city, and setting a corresponding view for each modal spatio-temporal data; on the basis of each modal spatio-temporal data of each space unit, generating a representation of each space unit in a single view under a view corresponding to each modal spatio-temporal data; generating a multi-view fusion representation corresponding to each space unit based on the representation of each space unit in a single view under the views corresponding to all modal spatio-temporal data, and forming a multi-view fusion representation matrix by the multi-view fusion representations corresponding to all the space units; and performing global aggregation processing on the multi-view fusion representation matrix to obtain urban general representation.

The invention relates to the field of city planning, and discloses a city spatial evolution prediction system fusing multi-modal data, and the system comprises a data preprocessing and multi-modal knowledge graph construction module which is used for configuring a knowledge graph ontology architecture and preprocessing multi-source city data; establishing a multi-modal knowledge graph based on the preprocessed multi-source city data and the knowledge graph ontology architecture; the model setting module is used for configuring a multi-modal representation learning model; the data integration module is used for a multi-modal representation learning model and performing deep integration on multi-modal data in a vector space to obtain vector representation with remote sensing and streetscape semantic information; and the knowledge reasoning and predicting module is used for performing knowledge reasoning on the missing part in the multi-modal knowledge graph based on the vector representation so as to predict the urban spatial evolution event. The urban spatial evolution event prediction can be realized, and the problem that the remote sensing image and the streetscape image are difficult to be deeply fused is effectively solved.

The invention discloses an urban space-time evolution analysis method based on multi-source historical data. The method comprises the following steps: 1) acquiring and digitally processing historical city maps, point-of-interest data and realistic paintings in multiple periods; 2) performing syntactic analysis on the urban road network and the water system by adopting a mixed model of topology and angle distance, and calculating core indexes such as integration degree and angle selection degree; 3) based on an optimization algorithm, carrying out normalization processing on the spatial syntactic index and the POI data; 4) extracting dynamic city information from the historical drawing; 5) performing statistical test on dynamic data extracted by drawing and a spatial syntactic analysis result; and 6) analyzing the space-time aggregation mode and function evolution of the public service facility by adopting a location quotient formula and kernel density estimation.By constructing a closed-loop research framework of multi-source data fusion, algorithm optimization and quantitative verification, a highly reliable scientific method is provided for deeply revealing an internal driving mechanism of urban form evolution.

The invention relates to the technical field of three-dimensional rendering, in particular to a digital city design city model visual display system which comprises a purpose calibration module, a component combination module, a path guide module, a view angle scheduling module and a rendering display module. According to the method, more accurate visual representation of urban model space purposes is realized by optimizing purpose calibration in the urban space and careful processing of geographic information, more reasonable space utilization distribution and visual display are realized by dynamically adjusting anchor points of the purpose space, more intelligent decision making in urban planning and building design is supported, and the method has the advantages of being high in practicability and easy to popularize. By extracting and combining building components with different functions, the functional semantic expression of the model is further enhanced, the information value and practicability of the model are enhanced, the interactivity and educational significance of the model are enhanced, and the model is more vivid visually and can reflect the appearance of a real city more accurately due to the improvement of rendering display. And the display quality and attraction of the model are improved.

The invention discloses a low-efficiency land use redevelopment function prediction method based on a graph neural network, and the method comprises the steps: S1, obtaining the land use benefit of each space unit in a learning region, dividing each space unit into a high land use benefit type, a middle land use benefit type and a low land use benefit type, selecting a space unit with a high land utilization benefit type as an urban land use configuration case library; s2, taking the urban land use configuration case library obtained in the step S1 as a sample set, and constructing and training a functional feature learning model based on a graph neural network according to the sample set; and S3, obtaining each space unit in the prediction area, inputting the space units into the functional feature learning model obtained in the step S2, and performing low-efficiency land use redevelopment function prediction. By simulating urban space function interaction and mechanism innovation, a traditional land utilization prediction normal form based on static rules and spatio-temporal evolution is broken through, and scientific support is provided for land benefit improvement and function replacement decision in urban updating.

The invention discloses a multi-agent collaborative urban community space planning method and device based on large model driving. The method comprises the following steps: converting original urban space data into a structured community space distribution diagram; a planning agent is constructed, the community space distribution diagram is understood and analyzed by using the planning agent, and an initial city planning scheme is output; dividing the initial city planning scheme into a plurality of community areas, and generating local optimization suggestions by a plurality of community planning reviewer agents; and fusing the community optimization suggestions by a high-level planning agent, carrying out global reasoning and coordination, and outputting a final urban space planning scheme. Through cooperative work of multiple types of agents, the intelligent level, cooperative efficiency and service fairness of urban space planning are improved, and the problems of lack of multivariate value expression in traditional generative planning, high labor cost and slow response in participative planning and the like are solved.

The invention relates to a thermal exposure risk calculation method based on urban trip people flow and built environment dynamics, and the method comprises the steps: obtaining the average radiation temperature calculation input data of an urban environment, and calculating the average radiation temperature of the urban environment according to the average radiation temperature calculation input data; calculating general thermal climate index distribution of the urban environment based on the average radiation temperature, and determining a thermal exposure time period based on the general thermal climate index distribution so as to obtain thermal exposure duration according to the thermal exposure time period; and acquiring the hourly travel pedestrian flow of the urban environment, counting the accumulated travel pedestrian flow in the thermal exposure time period based on the hourly travel pedestrian flow and the thermal exposure time period, and calculating the thermal exposure risk according to the accumulated travel pedestrian flow. Therefore, the problems that in the related technology, due to dependence on static population data, the people flow dynamic state of urban day and night travel with high temporal-spatial resolution is difficult to reflect, and a thermal risk calculation result based on the static population data cannot meet the requirements of urban space environment exposure refined analysis and early warning are solved.

The invention discloses an urban space type identification method based on a mixed density clustering algorithm, and relates to the technical fields of smart cities, urban planning, tourism planning, urban traffic and the like, and the method comprises the steps: constructing a data set for urban space type identification for a research area; based on the constructed data set, urban space division processing is carried out by using a DBSCAN density clustering algorithm, and an obtained result is marked as a clustering result D; performing unique clustering processing on each category S in the D based on a C-means clustering or Gaussian mixture model (GMM) algorithm to obtain a central point position P of each category S; counting the number of facility POIs in a local spatial range for the central point position P of each category S, and recording an obtained result as a local spatial information counting result; and determining the type of each category in the clustering result D according to a local spatial information statistical result. According to the invention, clustering of the service point space data set and identification of the urban space type can be realized based on the design of the mixed density clustering algorithm.

The invention discloses an urban planning effect evaluation method and system based on carbon emission, and the method comprises the steps: dividing urban space units, and constructing a first space unit division matrix in combination with information data; obtaining a real-time data score, and adjusting the space unit to obtain space adjustment efficiency; updating the space units based on the space adjustment efficiency to obtain a second space unit division matrix; based on the upstream and downstream industry chains, constructing a directed weighted graph, and obtaining an importance sequence through a link analysis algorithm; in combination with a multi-criterion decision analysis method, determining comprehensive weights of carbon emission indexes, and judging key nodes of an industrial chain; a low-carbon technology is introduced, the industrial chain node dependency degree is adjusted, carbon emission is optimized, and evaluation data is obtained. According to the method, the economic and carbon emission characteristics of each block of the city in different development stages are considered, the space units are flexibly allocated by using the space adjustment rate, the industrial chain layout can be automatically adjusted along with the change of data, and the implementation efficiency of the carbon reduction policy is improved.

The invention belongs to the technical field of geographic information, and discloses a low-efficiency living space studying and judging method and system based on multi-source spatio-temporal data, and the method comprises the steps: obtaining the multi-source spatio-temporal data of a target city space, and carrying out the preprocessing of the multi-source spatio-temporal data, and obtaining an index feature vector; performing feature extraction on the multi-source spatio-temporal data based on index screening and an improved deep learning algorithm to obtain index features; constructing a machine learning clustering model based on spatial constraints, and inputting the index features into the machine learning clustering model to obtain a clustering result; performing low-efficiency living space discrimination on the clustering result to obtain a low-efficiency living space in the target city space; according to the method, unified analysis and index conversion can be carried out on multi-source spatio-temporal data in a target city space, and a multi-dimensional residential land efficiency evaluation index is constructed; through index feature extraction and clustering, effective discrimination of the low-efficiency living space in the target city space is realized.

The application belongs to the technical field of urban planning, and discloses a city waterlogging resilience evaluation method and related equipment. Rainfall warning information is obtained, and rainfall event characteristic parameters are obtained by analysis. Dynamic waterlogging resilience evaluation index weights are generated according to the parameters and preset weight adjustment rules, and evaluation is performed based on the weights. Finally, the evaluation result containing weak link identification information is output, effectively solving the problem of weight static and uniform in the existing evaluation method. The evaluation index weights can be dynamically adjusted according to the rainfall event characteristics and city space heterogeneity, so as to realize accurate evaluation of city waterlogging resilience and effectively identify weak links, and provide a scientific basis for accurate scheduling of emergency resources and effective implementation of disaster prevention measures.

The application discloses a low-efficiency land dynamic monitoring management method based on real three-dimensional geographical entities, relates to the technical field of natural resource informatization management, and comprises the following steps: constructing a terrain mutation sensitivity atlas and a vertical risk guide grid, generating a weighted initial value field under the joint driving of an elevation gradient, a reflection intensity and an echo confidence, and forming vertical prior information of geographical entities; based on the vertical prior information of the geographical entities, performing spatiotemporal consistency forced registration, performing local elastic calibration on oblique photography images and laser point cloud data through a multi-scale rigid-flexible mixed constraint mechanism, and generating a vertical error field. Through the construction of the sensitivity atlas, the execution of rigid-flexible registration, the introduction of semantic reconstruction, the implementation of uncertainty propagation and dynamic resampling regulation and control, the vertical error closed-loop correction of the three-dimensional model under complex topography is realized, the accuracy and stability of low-efficiency land identification are improved, and high-credibility technical support is provided for urban space analysis and land decision-making.

The method for constructing urban ventilation corridors based on local climate zone classification and remote sensing inversion belongs to the technical field of urban climate regulation and space optimization. The present application constructs a multi-scale urban thermal environment analysis framework, from macro, meso to micro level, to identify the coupling mechanism of urban form and thermal effect, and to realize the fine modeling and regulation path identification of thermal environment. At the same time, combined with machine learning and explainable analysis method, the scientificity and transparency of thermal environment driving factor identification are enhanced. Through remote sensing inversion, form factor construction and three-dimensional simulation simulation, a complete technical path of "cold source identification-resistance modeling-path optimization-microclimate response evaluation" is put forward, which effectively improves the ventilation and cooling potential identification ability of blue-green infrastructure, and is suitable for ventilation corridor planning and climate adaptive updating design of various urban spaces, and has wide application prospect.

This invention discloses a method and system for identifying urban decline spaces, belonging to the field of urban planning technology. The method includes: S1. Acquiring population grid data and building area grid data of a target area for multiple consecutive years within a time interval; S2. Performing spatial alignment and standardization processing on the population grid data and building area grid data to form a standardized annual spatial database; S3. Removing grid units in the annual spatial database that do not possess effective urban activity characteristics to obtain a set of effective urban spatial grids; S4. Performing time series analysis on the effective urban spatial grid set to determine urban decline space grids; S5. Using a spatial clustering algorithm to cluster the determined urban decline space grids, dividing the urban decline space into continuous urban decline space and scattered urban decline space. This invention achieves automatic identification and classification of continuous and scattered urban decline spaces by analyzing the population and building area change trends over multiple consecutive years.

The invention belongs to the field of environmental protection, and particularly relates to a cold region urban space operation carbon emission measuring and calculating method based on prototype construction. The objective of the invention is to solve the problem of large result deviation when the existing carbon emission measurement method is used for measurement. According to the cold region city space operation carbon emission measuring and calculating method based on prototype construction, organic connection and deduction of building data and city data in calculation are achieved based on the calculation thought of prototype construction, the building data and the city data of the calculated cold region city space area are used for reflecting the building carbon source, and the carbon emission of the city space operation carbon emission in the cold region is calculated. Greenbelt carbon sink is reflected by urban data, and large-scale cold region urban space operation carbon emission measurement and calculation can be realized. The carbon source and the carbon sink in the urban space in the cold region do not need to be analyzed and measured one by one, and only a certain number of building sample data need to be measured, so that the measurement and calculation steps are greatly simplified, and the problem of large result deviation when a carbon emission measurement and calculation method is used for measurement and calculation is solved.

The invention discloses an extreme climate city dynamic function toughness measurement method based on mobile phone signaling data, and the method comprises the following steps: S1, determining a research region, dividing research units, and extracting an OD sample; s2, constructing a high-precision three-dimensional static city function data set based on the multi-source city space data, and obtaining a grid static function vector; s3, measuring the dynamic function toughness index of the urban space under the extreme climate; and S4, explaining the toughness mechanism under the extreme climate. Compared with the prior art, the method for measuring the dynamic function toughness of the city in the extreme climate based on the mobile phone signaling data has the advantages of being convenient to measure and use, ensuring high-precision use and providing effective data support.

The invention provides a Binjiang space vitality measurement and vitality influence factor analysis method and system, and the method comprises the steps: constructing a macroscopic (urban energy level / function positioning), mesoscopic (district level) and microscopic (site activity) three-level vitality measurement system, and enabling the macroscopic level to be in butt joint with the urban development stages such as land utilization and economic data; dynamic states such as thermodynamic data and activity annotation are used in the butt joint space of the middle and micro levels, and the problem that the adaptability of a traditional research macroscopic area is insufficient is solved; according to the method, a closed-loop technical path of collection-processing-analysis-diagnosis-optimization is formed, the problem of insufficient suitability of a Binjiang city space vitality measurement macroscopic region is solved, and the influence of city development, Binjiang space flood control attributes, Binjiang space design, operation management and the like on Binjiang space vitality is comprehensively considered; and a theoretical basis is provided for optimization and improvement of Binjiang space vitality.

The present invention relates to the field of correlation analysis between urban space and population flow. Disclosed is a method for analyzing correlation between urban spatial three-dimensional structure and population flow. The method comprises the following steps: constructing an urban construction indicator system on the basis of an urban construction dataset, and performing structure feature analysis on the urban construction indicator system to obtain three-dimensional space structure features of urban construction; using a base station to acquire mobile phone signaling data, identifying commuting behaviors of urban populations, and constructing network structure features of urban population flow; and using a LightGBM algorithm to construct and train a regression model, and performing interpretative analysis on the regression model by means of a SHAP algorithm. In the present invention, by analyzing the spatiotemporal correlation between urban spatial features and population flow, the importance of various features of urban spatial structure to population flow is investigated, and then population flow trends are effectively utilized to provide valuable references for the direction of urban development planning.

This invention discloses a method for updating the reachability of urban living circles based on spatial monitoring results, specifically relating to the fields of spatial monitoring and urban spatial computing. The method includes acquiring current monitoring results, previous monitoring results, pedestrian road networks, community entrances and exits, and service points. In edge computing nodes, each access-related element is compared according to its location correspondence. Newly added elements are recorded as new elements, and missing elements are recorded as invalid elements, generating a status change table. The status change table and pedestrian road network are read, and the access connections corresponding to the newly added elements are connected to the pedestrian road network. By comparing the current and previous monitoring results item by item, and performing localized recalculation and result write-back after generating the status change table in the edge computing nodes, locally closed areas can be promptly removed, and locally restored areas can be promptly added, thus ensuring that the dynamic reachability corresponds to the actual affected areas.

The application relates to the technical field of geographic information processing, and particularly provides a city space form identification method, device and equipment and a storage medium, aiming to solve the problem that general space form representation and classification cannot effectively formulate space planning design optimization measures. To this end, the city space form identification method comprises the following steps: acquiring a space form data set of a target region, dividing the target region into a plurality of road grid regions based on the space form data set, each road grid region comprising a plurality of first measurement indexes, calculating a variance inflation factor of each first measurement index of each road grid region based on the space form data set, determining a plurality of candidate space form types contained in the target region based on the variance inflation factors, and determining a target space form type of each road grid region based on the plurality of candidate space form types and the variance inflation factors. The application significantly improves the efficiency and stability of city space form identification.

The application discloses a sponge structure and method for expanding sidewalk tree root growth space, and the sponge structure comprises a permeation layer, a soil improvement layer, a water storage adjusting mechanism and an evaporation reduction structure, the soil improvement layer is used for filling original soil excavated on a sidewalk, the soil improvement layer is made by mixing gravel, waste wood and planting soil, and the sponge structure construction method comprises the steps of prefabricating a cement groove, pre-burying a water pipe, adjusting soil, preventing evaporation and laying the permeation layer. The soil is improved, the soil nutrition is improved, the soil is spongy, the water retention and storage performance of the soil is improved, the underground root growth space structure of the sidewalk tree is adjusted, the sidewalk tree and urban green land are connected, the sidewalk tree is really integrated into the green land, the urban heat island and waterlogging problems are solved, urban rainwater is utilized, the sidewalk tree grows healthily, and the ecological benefits of the tree are increased, and finally, the sponge city and the organicization of hard urban space are achieved.

The application provides a kind of urban dissipative space discrimination method and system based on spatial aggregation characteristics, it is related to spatial quality measure technical field.The urban dissipative space discrimination method based on spatial aggregation characteristics, comprising: obtaining city basic geographic space data and its geographic coordinates, form city space information integrated platform;According to the pre-set city dissipative space determination index library, the basic characteristic element data of city dissipative space is calculated, and the basic characteristic element data of city dissipative space is loaded into city space information integrated platform for spatial positioning calibration;Select appropriate grid scale to divide measure area;Each characteristic element data in grid unit is graded assignment;The order of city space is measured to calculate the aggregation;Establish determination rule to obtain four kinds of dissipative space characteristic element data set.The application improves the accuracy and efficiency of city dissipative space identification, and provides targeted guidance and power point for city renewal design and decision control.

The application discloses a kind of urban space layout influencing factor space-time analysis method and system. Including: obtaining the structured data set of each time section of the city space to be analyzed.Acquire the change value data set of the city space to be analyzed according to the structured data set of different time section.Each structured data set and change value data set is regressed and analyzed using geographic weighted regression model, identifies and quantifies the different effects of various influencing factors on each grid, solves the problem of spatial heterogeneity.According to the regression analysis result, construct static multivariate density value data set and dynamic multivariate density value data set.Using structural equation modeling to analyze the mediating effect of static multivariate density value data set and dynamic multivariate density value data set, generate static influence path network and dynamic influence path network.All static influence path network and dynamic influence path network are drawn as influence path diagram, show the spatial correlation and influence path of each influencing factor.

The application discloses a method for intelligently identifying the type and potential of outdoor fitness space beside a street, relates to the technical field of city planning, landscape gardening and artificial intelligence, and comprises the following steps: inputting the city space image data set of a target region into a pre-established outdoor fitness space activity type identification model to obtain an outdoor fitness space potential point corresponding to the outdoor fitness space activity type of the city space image; and inputting the city space image data set of the target region into a corresponding outdoor fitness space activity potential evaluation model to obtain the activity potential evaluation of the outdoor fitness space potential point corresponding to the outdoor fitness space activity type of the city space image; the application can analyze the city space site by means of intelligent target detection and deep learning technology, quantize the configuration relationship between the fitness behavior of the space site and the characteristics of the site elements, and establish a stable derivation relationship between the complete visual scene of the city space and the outdoor fitness activity potential.

This invention discloses a method for characterizing and measuring the disaster resilience of urban public services. The steps are as follows: A composite urban spatial network of residence, services, and transportation under normal conditions is constructed based on the urban road network; through disaster simulation, failed road sections and functional nodes under different disaster intensities are removed to construct a damaged composite urban spatial network of residence, services, and transportation; the per capita access to public services for residents at each residential node is calculated to form a performance model of the urban spatial network based on residents' access to public services; the rate of change in the per capita access to public services before and after the disaster is calculated; and the relationship curve between this rate of change and the disaster intensity is plotted to measure the disaster resilience of urban public services. This invention characterizes the dynamic evolution of the supply and demand matching performance of urban public services under multi-system collaboration by using changes in residents' access to public services, and establishes a measurement model for the disaster resilience of urban public services, providing a technical tool for enhancing urban resilience in planning practice.