324 results about "Urban space" patented technology

The invention provides a multi-level low-altitude air route network construction method in a complex urban environment, and relates to the technical field of low-altitude air route construction, and the method comprises the steps: building a low-altitude flight rule base; performing three-dimensional discretization on the urban space, and dividing the airspace into three-dimensional grids; designing a risk assessment function R; dividing a plurality of height layers, and distributing the height layers for different types of aircrafts; constructing a multi-stage air route network; constructing an airspace three-dimensional airway model; based on the airspace three-dimensional air route model, adopting a hybrid iterative algorithm to optimize the air route planning of each height layer; performing path smoothing on the discrete path points generated by the hybrid iterative algorithm by adopting a B spline curve, and performing flight performance verification on the smoothed path to obtain a continuous flight path; and generating a low-altitude air route network according to the continuous flight path. According to the method, the defects in the aspects of complex urban environment processing, multi-source data integration, multi-level airspace division, path optimization and the like in the prior art can be overcome, so that safe, efficient and flexible low-altitude flight management is realized.

The invention provides a multi-source information fusion data spatial analysis method and system based on a knowledge graph, and relates to the technical field of data analysis, and the method comprises the steps: carrying out the quality calibration and fusion of multi-source heterogeneous data, and obtaining standardized fusion data; a city system knowledge graph is constructed, the city system knowledge graph comprises city element nodes with category and hierarchical relations and association strength of the city element nodes, and city function communities are constructed and optimized through a modularity optimization method; an urban element diffusion wave equation model is constructed based on an urban system knowledge graph, an urban element state propagation rule is analyzed, urban function division is performed, an urban system coupling differential equation set model is established to predict urban element state change, an urban system vulnerability index is constructed, and urban system toughness analysis is performed. According to the method, multi-source city data can be effectively fused, the city system knowledge graph is constructed, and decision support is provided for city space planning and management.

The invention relates to the technical field of big data, and discloses a space-time big data abnormal event detection method and device and a storage medium. The method comprises the following steps: performing timestamp unification and space coordinate standardization processing on urban space-time big data to obtain a standardized space-time data set; feature vector cosine similarity between each data point in the standardized spatio-temporal data set and other data points is calculated to obtain a target similarity value, and an initial neighborhood data set is selected; performing space-time density distribution calculation on the initial neighborhood data set to obtain a core neighborhood data set; performing time sequence feature and spatial distribution feature extraction on the core neighborhood data set to obtain a fusion feature weight matrix; and inputting the fusion feature weight matrix into a support vector machine classifier to perform abnormal event recognition to obtain an abnormal event detection result, thereby improving the classification capability of high-dimensional nonlinear features, and simultaneously realizing all-directional feature description and detection of abnormal events.

Provided is a system for simulating urban spatial growth by coupling urban development with water resources environmental carrying capacity, including a dynamic evaluation module for a water resources carrying capacity configured to evaluate and predict a maximum scale of urban space, a identification module for a water ecological sensitive area configured to identify water ecological security patterns and determine spatial regions that need to be avoided during urban spatial growth, and a simulation module for urban land use change configured to predict urban spatial layout features under different water ecological sensitive area protection modes and urban spatial growth scales. The system, as a whole, can predict the trends in urban population, industry, and construction land changes by simulating coupling between water resources environmental carrying capacity as well as water ecological sensitive area protection characteristics and factors such as urban socio-economic development and urban land expansion.

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 intelligent urban municipal planning method and system based on geographic information, and relates to the technical field of data processing, and the method comprises the steps: obtaining urban spatial data of different data sources, including terrain, land utilization, building distribution, traffic network, population distribution and environment index data; and analyzing the urban spatial data, including spatial overlay analysis, buffer analysis and network analysis, and identifying key problems and potential risks in urban municipal planning to obtain a data analysis result. The urban space data can be comprehensively and accurately analyzed, the optimized municipal planning scheme is automatically generated and updated and adjusted in real time, and the urban traffic fluency, the environment quality and the public facility utilization efficiency are improved.

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 provides an urban carbon neutralization path analysis system and an analysis method thereof. The urban carbon neutralization path analysis system comprises a data acquisition module, a data arrangement module, a region division module, a carbon balance calculation module, a path setting module, a path analysis module and a result output module, according to the invention, through regular rasterization region division, fine modeling of the city space is realized; the carbon sequestration capacity is dynamically estimated by combining multiple types of carbon sources and multiple types of vegetation carbon sequestration factors with an NDVI time sequence index, so that a carbon-oxygen balance calculation result has time sensitivity and spatial resolution; meanwhile, the path analysis module supports a user to set various energy structures, traffic modes and greenbelt lifting parameter combinations to form a multi-path parallel simulation matrix, the selection space of path decision is effectively expanded, the system can realize comparable carbon neutralization evolution analysis according to regions and time periods, and the effects of improving the analysis precision and enhancing the path deduction capability are achieved.

The invention belongs to the technical field of urban planning, and discloses an urban inland inundation toughness evaluation method and related equipment, rainfall event characteristic parameters are obtained through obtaining and analyzing rainfall early warning information, dynamic inland inundation toughness evaluation index weights are generated according to the parameters and a preset weight adjustment rule, and evaluation is executed according to the dynamic inland inundation toughness evaluation index weights. And finally, outputting an evaluation result containing weak link identification information, thereby effectively solving the problems of weight staticization and homogenization in the existing evaluation method. The evaluation index weight can be dynamically adjusted according to rainfall event characteristics and urban spatial heterogeneity, so that accurate evaluation of urban waterlogging toughness is realized, weak links are effectively identified, and a scientific basis is provided for accurate scheduling of emergency resources and effective implementation of disaster prevention measures.

The invention discloses a city information model management system based on a CIM basic platform and an analysis and display method, provides an innovative city information management and display solution, takes the CIM basic platform as a core, and aims to construct a high-precision and dynamically-updated city three-dimensional information model management system through an integrated information technical means. The urban space structure, the function layout and the infrastructure state can be visually and interactively explored, so that construction and development of a smart city are promoted, and the intelligent level and the comprehensive efficiency of urban management are improved.

The invention relates to the field of city updating, and discloses a city updating decision-making method based on public participation, which comprises the following steps: acquiring city space basic data including a vector map, remote sensing image data and historical, cultural and geographic information data of a city; on the basis of the acquired spatial data, a public participation base map is constructed, and the base map comprises information of a road network, land use types and historical and cultural areas of the city; collecting opinion data of the public on facility site selection through an interactive platform on the public participation base map; and according to the collected public opinion data, constructing a multi-subject scoring model. According to the method, a decision-making method based on public participation is adopted, space basic data and public opinions of cities are combined, facility site selection is evaluated through a multi-subject scoring model, and the opinions of different subjects can be integrated by the system by setting weight values of the public, experts and the government, so that the diversity and fairness of site selection schemes are ensured.

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 urban space information processing, in particular to an urban functional area fine classification method based on multi-modal data collaboration. According to the method, POI data, AOI data, land utilization data, remote sensing images and other multi-source heterogeneous data are fused, a multi-dimensional feature system is constructed, and an urban functional area classification model covering a single functional area, a composite functional area, a mixed functional area and a non-functional area is provided. According to the method, firstly, block-level basic units are constructed based on an open street map (OSM), then coordinate transformation and function classification are carried out on POI and AOI data, features such as POI density, AOI area proportion and land utilization structure are extracted respectively, and finally, function type identification is carried out on urban block units according to set classification rules. Compared with the prior art, the method has the advantages that through multi-source information fusion and discrimination logic optimization, the accuracy and applicability of urban functional area recognition are remarkably improved, and the method is suitable for scenes such as urban planning, land utilization evaluation and urban management.

The invention provides an urban space resource optimal configuration method based on an urban information model, and relates to the field of space resource configuration, and the method comprises the steps: S1, data acquisition and preprocessing, S2, dynamic association feature extraction, S3, space-time cooperative supply and demand matching, S4, dynamic demand prediction, and S5, facility layout optimization. According to the method, on the basis of a city information model, iterative optimization of city space resources such as infrastructures in the whole life cycle of planning, construction and management is achieved, the problems that in the construction process or after the infrastructures are constructed, due to uncontrollable factors of city development, the requirements are reduced, and public resources are redundant are effectively solved, and the economic benefits of the infrastructures are improved. The utilization rate of urban space is effectively improved, and the planning and construction cost of infrastructures is reduced.

The invention discloses an intelligent management method and system for territorial space planning and a storage medium, and relates to the technical field of space planning, the method adopts a geographic information system (GIS) and multi-source information such as remote sensing data and satellite data to carry out three-dimensional modeling, and an efficient and accurate data support platform is provided for urban space planning. On the basis, environment data, traffic flow data and social influence data of urban areas are collected and integrated in real time by combining an API interface and an urban related system, and comprehensive real-time dynamic data support is provided for decision making. Through real-time simulation and data input, a planner can evaluate potential conflicts and problems among different urban space areas more visually and more accurately, a planning scheme is adjusted in time, and errors and low efficiency caused by information lag or incomplete data in traditional planning are avoided. By implementing the method, the urban planning cycle can be remarkably shortened, and the efficiency and scientificity of planning decision making are improved.

The invention belongs to the technical field of urban planning, and provides an urban park site selection decision-making method, system, equipment and medium in order to solve the problem that the existing heat island effect relieving technology faces multiple bottlenecks, and multi-dimensional indexes are endowed with combined weights based on a game theory method and subjected to hierarchical normalization processing; according to the conversion heat contribution degrees of different surface feature categories, decomposing the combined weight of the surface temperature to different surface features of the target area; enabling the normalized spatial distribution map corresponding to the surface temperature to correspond to different surface features, and obtaining a thermal contribution normalized distribution map of different surface features in the target area; the above steps are fused to generate a target area site selection suitability distribution map, and screening is performed to obtain an urban park site selection scheme, so that the sensitivity loss of existing'one-step 'weighting on a high heat source area is avoided, and it is ensured that a park site selection decision not only can alleviate a heat island core area in a targeted manner, but also can adapt to the diversity characteristics of an urban spatial pattern.

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 provides an urban space toughness full-cycle optimization regulation and control method and system based on ArcGIS Engine and SOM. The method comprises the following steps: 1) multi-dimensional attribute measurement of urban spatial toughness; (2) revealing space-time differentiation characteristics of urban space toughness full-period evolution; 3) identifying influence factors of urban space toughness full-cycle evolution; 4) constructing an urban space toughness full-cycle optimization regulation and control model based on ArcGIS Engine; and 5) searching an optimal solution of urban space toughness full-cycle optimization regulation and control based on SOM. According to the method, a quantitative analysis model and a tool for urban spatial toughness optimization regulation can be provided, and suitable value and threshold range of urban spatial toughness multi-dimensional variables can be identified, so that a full-cycle optimization regulation strategy for urban spatial toughness is supported; therefore, the ability of the planning system to regulate and control the urban space toughness is enhanced from the aspects of space-time integrity and systematicness.

The invention relates to the technical field of data processing, and particularly discloses a city management event processing method and system based on Beidou grid codes. The method comprises the steps of performing grid coding on geographic space data in a city space range based on Beidou grid codes, and generating a basic grid model; when a city management event is reported, obtaining reported event data; processing the event data to determine the event type, geographic position and attribute of the city management event; determining a Beidou grid code associated with the city management event by using the geographic position; judging whether similar events exist in the city management events or not; if the similar events exist, judging whether the events are repeated events or not; if the city management event is not the repeated event, the event type and attribute of the city management event are mapped to a space grid pointed by the Beidou grid code; and packaging each block of data in the basic grid model to provide the data for a subsequent batch processing flow. Based on the invention, data support can be provided for urban management planning.

The invention provides an unmanned aerial vehicle path implementation planning method based on rolling EKF, and the method provides a new path planning strategy for the UAV in an urban space. Firstly, environment information is sensed and acquired; secondly, performing state estimation and trajectory prediction by using an EKF (Extended Kalman Filter); and finally, the model predicts and controls the rolling optimization trajectory. According to the invention, state estimation and trajectory prediction are carried out by using extended Kalman filtering (EKF), so that noise in a trajectory observed by a sensor is reduced, and the predicted trajectory is close to an actual flight trajectory as much as possible; a time axis is introduced, on the basis of rolling optimization of model prediction control, the flight time of the unmanned aerial vehicle is divided into small time intervals, and a dynamic map is constructed based on the time intervals; and searching a feasible path by using a breadth-first search method, and obtaining an optimal path through an A * algorithm. Simulation results show that the provided obstacle avoidance method can effectively avoid static buildings and dynamic obstacles, and a safe flight path is planned for the unmanned aerial vehicle in the urban space.

This application relates to the technical field of data processing and provides a method for constructing spatial scenarios based on a blue-green-grey ratio. The method first constructs a spatial scenario classification system, dividing spatial scenarios into primary and secondary spatial scenarios. Attributes corresponding to vector patches of the secondary spatial scenarios are set as follows: type name, perimeter, area, and blue-green-grey ratio. Spatial data is then preprocessed, followed by the identification of urban functional scenarios and non-urban spatial scenarios. A perimeter and an area of each spatial scenario patch are calculated and attributes of type name, perimeter, area, and blue-green-grey ratio are assigned to each spatial scenario patch. The blue-green-grey ratio attribute is used to represent the internal heterogeneity within homogeneous functional zones or the same spatial scenario. This attribute better explains the differences in land use due to varying locations, addressing the challenge in traditional land use / cover methods.

The invention discloses a subway separation island type underground excavation station construction method. The method comprises the following steps that a vertical shaft is excavated, and a construction transverse channel connected with a pilot tunnel is excavated; pilot tunnels are constructed and supported; constructing an enclosure structure and a waterproof curtain, and constructing a top beam on the pile; an advance support and a primary support are constructed, and large arch earthwork is excavated; pouring an arch secondary lining structure; pouring the side wall and the middle plate; constructing a structural bottom plate and side walls; constructing a contact channel; and a platform plate and a rail top air duct are constructed. The method has the advantages of being safe and reliable in construction process, low in economic cost, small in environmental influence, good in passenger use attribute, high in underground space utilization rate, convenient to connect with surrounding traffic and urban space and the like, and has wide popularization prospects.

The invention relates to an urban scale carbon emission prediction method and system based on small sample data enhancement. The method comprises the following steps: firstly, acquiring urban night light data, correcting the data by using a multiple linear regression model to obtain a fitting light ratio, and calculating the carbon dioxide emission of each city by combining an urban night light data inversion calculation formula to obtain a carbon emission data set; performing data enhancement on the carbon emission data set by using an improved time sequence enhanced generative adversarial network model TimeTGAN to obtain a carbon emission enhanced data set; then training the space-time sequence prediction network model to obtain a trained space-time sequence prediction model; and finally, collecting urban spatial geographic position data, and inputting the urban spatial geographic position data into the trained space-time sequence prediction model to obtain a carbon emission prediction result. Compared with the prior art, the method has the advantages that the problem of small samples in carbon emission prediction is effectively solved, and the accuracy of a prediction result is improved.

The invention relates to the technical field of big data analysis, and particularly discloses a city update multi-dimensional dynamic supervision and analysis system based on big data, which is provided with a data quality processing module, a topology verification evaluation module, a conflict repair matching module and an interactive management feedback module. And extracting data from the city multi-source data set and performing coordinate conversion to form a unified city space data set. And then, starting a topology check engine through a data processing port, and detecting and evaluating a topology conflict degree value of the data set. And according to the conflict degree, matching and executing a corresponding repair scheme, and marking the repaired data set as a city effective data set. And finally, the effective data set is uploaded to a city updating interaction port, subsequent interaction management operation is carried out, the accuracy and availability of the data are ensured, and support is provided for a city updating project.

The invention relates to the technical field of ecological data, and discloses a method for constructing an urban spatial data set for predicting bird distribution, comprising the following steps: acquiring dominant environmental factors and urban bird point location distribution data, and processing the environmental factors and the urban bird point location distribution data; utilizing Spearman correlation analysis to calculate a correlation relationship of the environmental factors; running the MaxENT model, and screening out key environmental influence factors; carrying out normalization processing on the key environment influence factors; and taking the bird richness distribution data as a dependent variable y and the key environment influence factor data as an independent variable factor xn, constructing a generalized linear model, and finally obtaining an urban space data set formula capable of being used for predicting bird distribution. According to the method, the environmental factors which mainly influence the survival of the birds in the urban area are determined, and the method is suitable for predicting the bird richness spatial distribution in the high-density urban area under the condition of lack of bird distribution data.

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 relates to the technical field of data processing, and discloses an urban space evolution detection method and system based on machine learning. The method comprises the following steps: carrying out space-time stratified sampling on city multi-scale data to obtain block-level, district-level and city-level feature tensors; calculating a collaborative weight matrix through a multi-scale space attention mechanism; a collaborative feature vector is obtained through mapping of a collaborative order degree encoder; performing time sequence interpolation processing by using a space-time cooperation trajectory decoder to obtain a dynamic cooperation index; and performing multi-level fusion on the dynamic collaboration index to obtain a collaboration measurement result. The problem that urban spatial evolution detection is lack of multi-scale cooperative relationship quantitative analysis and dynamic evolution trajectory recognition capability is solved.

Provided are an urban digital twin platform system and a moving object information analysis and management method therefor. Through the urban digital twin platform system and the moving object information analysis and management method, a moving object such as a vehicle or a pedestrian may be detected from multimodal sensor data, data on the moving object may be generated, and a situation may be quickly determined by deriving complex actions of the moving object. The urban digital twin platform system includes a multimodal sensor data input and objectification module configured to detect a moving object and to generate objectification data, a multimodal sensor data analysis module configured to classify basic actions of the moving object, to classify complex actions of the moving object, and to generate moving object information, and an urban space data server configured to store the objectification data and the moving object information.

The invention discloses a town space three-dimensional structure and population flow correlation analysis method, and relates to the field of town space and population flow correlation analysis, and the method comprises the following steps: constructing a town construction index system based on a town construction data set, and carrying out the structural feature analysis of the town construction index system, urban construction three-dimensional space structure features are obtained; the method comprises the following steps: acquiring mobile phone signaling data by using a base station, identifying commuting behaviors of urban population, and constructing network structure characteristics of urban population flow; and constructing and training a regression model by using a LightGBM algorithm, and carrying out interpretive analysis on the regression model through an SHAP algorithm. According to the method, the importance degree of each feature of the urban spatial structure to population flow is explored by analyzing the spatial-temporal correlation between the urban spatial features and the population flow, and thus valuable reference is provided for the urban development planning direction by effectively utilizing the population flow trend.