23 results about "City development" patented technology

The VILLAGE BLEU is an urban development structure designed to regulate legal migration to Europe. It is characterized by the fact that - it enables legal migration and makes illegal migration unnecessary. This makes humane immigration into Europe possible. - The VILLAGE BLEU site is not located on European soil. The site is preferably located on the territory of a non-EU state (item 5) and is a plot of land, likely leased temporarily, from the European Union by a non-EU state for the construction of a city-state structure. The European Union will pay the non-EU state – essentially the lessor of the land – some form of rent. - as a city-state belonging to the European Union, with all European regulations and laws. The Village Blue is thus a kind of temporary city-state. No single EU member state has the authority to govern this territory, but rather the European Union, headquartered in Brussels. Therefore, the Village Blue is a city-state of the EU. Perhaps in some respects comparable to the status of the Hong Kong Special Administrative Region until 1997. If the VILLAGE BLEU is located on the African continent, for example, all those wishing to migrate will have the opportunity to reach the EU without having to use the dangerous sea route (e.g., the Mediterranean route). Migration will then only take place via the VILLAGE BLEU. Migrants who do not immigrate to the EU via the VILLAGE BLEU will be transferred to the VILLAGE BLEU upon identification and arrest. This is not a so-called deportation to a third country, as the VILLAGE BLEU is European territory. Illegal migrants will lose the possibility of obtaining permanent residency in the near future. This will significantly contribute to preventing those wishing to migrate from falling into the hands of smugglers. Thus, the VILLAGE BLEU essentially deprives smugglers of their business model.

The invention relates to a city development talent demand prediction method and device, and a storage medium. The method comprises the following steps: selecting city research time nodes, input elements and output elements; collecting corresponding input element data and output element data of the city at the research time node; based on the input element data and the output element data, adopting a Cobb-Douglas production function to determine the output elasticity of each input element of the city; determining marginal output data and average output data of each input element according to the output elasticity; drawing a total output curve, an element marginal output curve and an average output curve of the city according to the total output data, the marginal output data and the average output data of each research time node of the city; according to the curve position relation, the urban talent development stage is determined, and a prediction result of the talent demand is generated. According to the method, the effects of capital, labor force and technical progress factors in the production process are described from the macroscopic perspective, and the influence of the talent number and quality on urban development is quantified.

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.

The invention discloses a multi-objective optimized urban development boundary land intelligent configuration simulation method, which comprises the following steps: S1, acquiring multi-source original data of a to-be-simulated city, and preprocessing the multi-source original data; s2, based on the preprocessed data, dividing urban land basic units, extracting feature information of each unit, and constructing an urban development boundary configuration basic data set; and S3, building a city development scene generation model of a generative model architecture, and taking the basic data set as input. The invention relates to the technical field of city planning and simulation. According to the multi-objective optimized intelligent configuration simulation method for the urban development boundary land, a generative model and a deep learning technology are adopted, a virtual development boundary scheme is generated according to multi-source data, the virtual development boundary scheme and actual urban land data are compared and analyzed, a deviation value is calculated, model parameters are automatically adjusted, iterative optimization is carried out, and the intelligent configuration simulation method for the urban development boundary land is achieved. And the development scheme gradually tends to be optimal.

The application provides a riverside space vitality measurement and vitality influence factor analysis method and system, constructs a macro (city energy level / function positioning), medium (district level) and micro (site activity) three-level vitality measurement system, the macro level is connected with the city development stage such as land utilization and economic data, the medium and micro level is connected with space use dynamics such as heat data and activity annotation, and the problem of insufficient adaptability of traditional research macro region is solved; the application forms a closed-loop technical path of "collection-treatment-analysis-diagnosis-optimization", solves the problem of insufficient adaptability of riverside city space vitality measurement macro region, considers the influence of city development, riverside space flood control property, riverside space design and operation management on riverside space vitality, and provides a theoretical basis for optimization and promotion of riverside space vitality.

This invention relates to the field of urban planning technology, and more particularly to a historical and cultural-oriented spatial classification and regeneration method and system. The method includes the following steps: acquiring historical and cultural data, and performing multimodal perception on the historical and cultural data to obtain historical and cultural spatial data; extracting deep features from the historical and cultural spatial data to obtain historical and cultural element data; constructing a spatial semantic map from the historical and cultural element data to obtain spatial semantic map data; classifying the spatial semantic map data according to its chronological evolution trajectory to obtain historical and cultural spatial classification data; generating spatial regeneration data based on the historical and cultural spatial classification data to obtain spatial regeneration data; acquiring urban planning demand data, and integrating the urban planning demand data and the spatial regeneration data to obtain integrated spatial regeneration data. This invention combines urban planning with spatial regeneration, effectively achieving a dynamic balance between historical and cultural preservation and modern urban development.

The invention relates to the technical field of surveying and mapping geographic information, in particular to a surveying and mapping data asset evaluation system based on urban development prediction. Comprising a city development trend prediction unit, a data asset dynamic definition unit, an adaptive value composition and influence factor analysis unit, an intelligent feature construction and weight dynamic allocation unit, a prospective value model construction unit and an evaluation and decision support unit. According to the invention, an advanced city development trend prediction model is constructed, and the output result of the model is deeply fused to key evaluation links such as data asset identification, value composition analysis, influence factor screening, feature construction and weight distribution value model construction. Therefore, a surveying and mapping geographic information data asset evaluation system with dynamic response capability and a look-ahead judgment function is established. According to the system, full-life-cycle, multi-dimensional and high-precision evaluation of data assets can be realized, and scientific and reliable value support is provided for urban planning, modern governance and digital economic development.

The application relates to the technical field of dynamic updating of urban data bases, in particular to a dynamic updating method and system based on a smart city data base, which comprises the following steps: obtaining and preprocessing multi-source data from a digital city super-brain station and the city data base; performing feature extraction on the multi-source data to divide core interest and attention areas and construct regional comprehensive updating demand degrees of the core interest and attention areas; and arranging the order of the core interest and attention areas in the next round of incremental updating according to the regional comprehensive updating demand degrees. The application aims to timely adjust the regional priority in the dynamic incremental updating of the updating process of the city data base, improve the dynamic updating efficiency and accuracy of the increment, and timely respond to the changes in the city development.

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 relates to a roof planting system. The roof planting system comprises a soil layer laid on a roof surface layer, plants planted on the soil layer and a drainage device arranged at a drainage port of the roof surface layer. The soil layer is formed by mixing the following raw materials in percentage by weight: 55%-65% of natural soil, 15%-25% of humus soil and 15%-25% of gravel soil; the thickness of the soil layer is 3-5 cm; the plants comprise perennial creeping ground cover plants and leaf vegetables; the perennial creeping ground cover plants grow to form grass clusters, and the leaf vegetables are planted in the grass clusters. According to the roof planting system, a self-maintaining ecological system is constructed under the condition of thin soil of 3-5 cm, ecologicalization and light weight of roof planting are achieved, and the roof planting system has important practical significance in promoting resource utilization of urban idle roof space, promoting deep fusion of biological economy and urban development and relieving human-ground contradiction.

The invention provides a hub city associated feature tracking analysis method and system based on network analysis, and relates to the technical field of data analysis, and the method comprises the steps: collecting multi-source and multi-dimensional data of a hub city, and constructing a multi-dimensional database which comprises traffic flow, economic flow, information flow and population flow; with cities as nodes and inter-city flow data as edges, edge weights are set, and a multi-level network model of the hub cities is constructed; carrying out network index calculation based on a network analysis method, and establishing a city multi-dimensional interaction relationship; through time sequence analysis of historical data and real-time data, time sequence reverse tracking and time sequence forward trend prediction are carried out, and multi-dimensional feature association strength and development direction are analyzed. According to the invention, the technical problem that the prediction of the future city development trend is lack of accuracy and foresight because city association analysis is generally carried out based on a single data source and the interaction relationship of hub cities in multiple dimensions cannot be comprehensively reflected in the prior art is solved.

This invention relates to a visual generation method and system based on digital cultural tourism scenarios, belonging to the field of smart cultural tourism. The method is used in a control unit within the visual system, which controls the display unit of the visual system to display videos to visitors from other locations. The method includes: S1, obtaining corresponding tags of basic information of visitors from other locations, and corresponding tags of the original cultural tourism animation to be displayed; S2, generating a target video animation based on a set of content tags according to preset matching rules. In the process of urban development, smart cultural tourism plays an important role in external or inter-regional exchanges, requiring the presentation of the city's image or culture to visitors from other places. Based on this, the solution described in this application can realize the intelligent generation of visual results for cultural tourism scenarios, displaying reasonable visual generation results according to the specific circumstances of visitors from other locations, thereby enhancing the experience of cross-regional cultural exchange.

The application discloses a kind of multi-scale green land exposure equality evaluation methods of fusing dynamic city identification, specifically related to the technical field of city management and resource assessment, to solve the problem that existing evaluation methods cannot accurately reveal the difference of green land resource allocation efficiency inside different development mode cities due to the adoption of static city classification framework;It is through obtaining the city development power, spatial elements, road network and static background data of each evaluation unit, dynamically dividing the city development mode type based on the development power data, and then calculating the exposure opportunity gap value representing the green land resource allocation efficiency, matching based on static background data for different mode units to form cross-mode matching groups, and finally completing equality evaluation through comparison and analysis of gap value in the group to realize.

The invention relates to the technical field of urban development, and discloses a development boundary demarcation method considering urban three-dimensional morphology, which comprises the following steps: according to urban land utilization data, constructing scenes including natural development, economic priority, ecological expression and coordinated development, and utilizing a multi-objective planning model to predict land utilization requirements under different scenes; setting an evaluation unit according to the target distance, and constructing land utilization simulation driving factors including natural environment factors, human activity factors and urban form factors; on the basis of land utilization requirements and land utilization simulation driving factors, a development boundary stipulation model is constructed in combination with a PLUS model and an iterative mathematical morphology algorithm, and land utilization simulation and urban development boundary demarcation are carried out. According to the method, a PLUS model and an iterative mathematical morphology method are combined, a development boundary demarcation model integrating multi-source features is constructed, and a decision basis is provided for urban planning and management, urban sustainable development and the like.

The invention relates to the technical field of dynamic updating of city data bases, in particular to a dynamic updating method and system based on a smart city data base, and the method comprises the steps: obtaining multi-source data from a digital city super-brain platform and a city data base, and carrying out the preprocessing of the multi-source data; performing feature extraction on the multi-source data to divide a core interest attention region, and constructing a region comprehensive update demand degree of the core interest attention region; and arranging the precedence order of each core interest region in the next round of incremental updating according to the comprehensive updating demand degree of the region. According to the method and the device, the region priority during dynamic incremental updating in the urban data base updating process is adjusted in time, the dynamic incremental updating efficiency and accuracy are improved, and urban development changes are responded in time.

The invention belongs to the technical field of urban planning, and discloses an urban development planning adaptability evaluation method and system for an urban drainage system, and the method comprises the steps: obtaining a performance reduction rule of a green infrastructure under a preset minimum maintenance condition, and carrying out the correction according to an expected maintenance input level, a long-term performance prediction curve which is more practical is generated; on the basis, the effective operation period of the green infrastructure is determined in combination with the prediction curve, namely, the time length when the performance of the green infrastructure is continuously kept above the lowest standard; and finally, inputting the dynamic performance data into the overall evaluation process of the urban drainage system, and obtaining a more accurate and more timeliness evaluation result of the adaptability of the urban drainage system to the urban development planning. According to the method, the problem of evaluation deviation caused by overestimation of green infrastructure performance in the prior art is effectively solved, and a more scientific and reliable decision basis is provided for urban planners, so that the toughness and sustainability of an urban drainage system are improved.

The invention discloses an urban high-intensity development district identification and utilization efficiency detection method based on grid growth, and the method comprises the steps: obtaining urban development data, and carrying out the grid processing of the urban development data; according to the gridded city development data, utilizing a city development district identification method to identify city development districts meeting conditions; based on a district development intensity stability index, a district geometric morphology rationality index and a district spatial relationship independence index, detecting a city development district identification result, and based on a single use efficiency index or a comprehensive use efficiency index, performing use efficiency detection; and outputting identification and use efficiency detection results of the city development districts. According to the method, the high-intensity development district and the use efficiency thereof are accurately identified, a scientific basis can be provided for urban density zoning control, updating unit delimitation and public resource reconfiguration, and refined urban design optimization and governance decision are supported.

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 relates to the technical field of city development and service, in particular to a POI (Point of Interest) double-branch auto-encoder-two-stage clustering-based city functional area identification method. The method comprises the following steps: acquiring and preprocessing multi-source POI (Point of Interest) and road network data, and constructing a POI data set with a space unit; utilizing a double-branch auto-encoder network to extract POI semantic and spatial features, and fusing the POI semantic and spatial features into a deep fusion feature vector of each unit; performing pre-clustering on the feature vectors by adopting a K-Means algorithm, and performing fine clustering by applying a DBSCAN algorithm based on a result to realize urban functional area division; and finally, calculating a function mixing degree index based on the division result and the POI data set, quantifying the function mixing degree of each unit, and generating an urban functional area identification result. According to the invention, the accuracy of functional region division and the fineness of functional mixing degree quantification are effectively improved.

The invention discloses a city development simulation and planning evaluation system based on multi-source data, which belongs to the technical field of city planning simulation and comprises a multi-source data fusion module, a digital twin construction module, a planning scheme generation module, a space-time prediction module, an influence evaluation module and a scheme optimization module. The system fuses remote sensing images, POI data and mobile phone signaling data, constructs an urban digital twinborn model comprising a spatial layer, a functional layer and a dynamic layer, performs long-term dynamic simulation on a planning scheme by adopting a space-time attention network, predicts population distribution, land utilization change and traffic jam indexes of a plurality of time nodes in the future, and performs dynamic simulation on the planning scheme. According to the method, a multi-dimensional evaluation index system is established, an optimal planning scheme is determined through multi-objective optimization, scientific support can be provided for urban planning decision making, and the method has important application value.

We provide the system. [Solution] A means of collecting various urban information and analyzing population dynamics, movement patterns, and local use, A means of simulating multiple urban development scenarios based on the analysis results and predicting their impact, A means to optimize the efficient allocation of urban resources based on prediction results, A means that includes terminals for displaying information and collecting opinions so that residents can participate in urban development plans and submit proposals, A system that allows residents to submit their opinions on proposed urban planning plans, and enables the aggregation and analysis of this information using data communication technology. A system that includes this.

The application provides a hub city correlation feature tracking analysis method and system based on network analysis, relates to the technical field of data analysis, and the method comprises the following steps: collecting multi-source multi-dimensional data of a hub city, constructing a multi-dimensional database, including traffic flow, economic flow, information flow and population flow; setting edge weights to construct a multi-level network model of the hub city by taking cities as nodes and inter-city flow data as edges; performing network index calculation based on a network analysis method, establishing multi-dimensional interactive relationships among cities; and performing time sequence reverse tracking and time sequence forward trend prediction through time sequence analysis on historical data and real-time data, and analyzing multi-dimensional feature correlation strength and development direction. The application solves the technical problem in the prior art that city correlation analysis is usually based on a single data source, the interactive relationships among hub cities in multiple dimensions cannot be comprehensively reflected, and the prediction of future city development trends lacks accuracy and foresight.

The application provides a city classification method for constructing a beautiful city differentiation index system, and relates to the technical field of city classification data processing. The application takes a city unit as an object, acquires multi-source heterogeneous data of an ecological environment protection dimension and a city development and construction dimension, performs discrete probability distribution feature compression on grid data, and extracts index features from the remaining data. Based on data confidence correction of a basic weight, a city feature vector set is constructed by introducing a spatial coordinate. Binary classification results of each dimension are obtained through unsupervised clustering, and then a subdivided type and city categories of double-high type, high-low type, low-high type and double-low type are formed. The application can reduce the influence of grid high-dimensional features, low-confidence indexes and missing spatial proximity relationships on city classification results.