34 results about "City block" patented technology

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 discloses an urban block green land planning method and device based on thermal environment big data, and the method comprises the steps: obtaining the thermal environment data, vegetation coverage data and a vegetation database of a target block; constructing a thermal environment map of the target block based on the thermal environment data, and obtaining a thermal environment feature vector of each sub-block according to the thermal environment map; acquiring a microclimate influence value of each vegetation type; performing correlation analysis on the thermal environment feature vector and the microclimate influence value of each sub-block to obtain the microclimate adjustment contribution degree of each vegetation type to each sub-block; and according to the microclimate adjustment contribution degree, determining a target vegetation type to be planted in each sub-block and a planting proportion of each target vegetation type, and obtaining a vegetation configuration scheme of the target block. The microclimate adjusting capability of the urban green land can be improved.

A flow field prediction device includes: an analysis result acquisition unit that acquires an analysis result based on a first computation method of analyzing at least an influence between buildings with respect to a flow field in which a city block including a plurality of buildings is set as a target region; and a prediction processing unit that inputs a new analysis result acquired by the analysis result acquisition unit to a learning model trained using teaching data that includes an analysis result based on a second computation method that is more accurate than the first computation method, as correct answer data for input data including at least the analysis result based on the first computation method, and outputs an output from the learning model as a prediction result of the flow field.

The invention belongs to the technical field of high temperature evaluation, and particularly relates to an urban block scale local extreme high temperature remote sensing detection method, which comprises the following steps of: S1, framing a vector boundary of a research area by using a geographic information tool, and obtaining high-resolution surface temperature time sequence data in the research area; s2, processing the obtained remote sensing image to obtain the temperature value of each pixel in the research area, and calculating the average surface temperature and the surface temperature standard deviation of the research area on abnormal days day by day; and S3, calculating a deviation degree quantized value of the pixel in an abnormal day, and judging whether the pixel is a high-temperature abnormal pixel or not according to a preset standard. Based on the remote sensing pixel data, the method can accurately capture the difference of each pixel point of the block, and avoids taking the block as a whole for research; secondly, the frequency and intensity information of the extreme high temperature in the block are fused, and the method is more comprehensive than a traditional method which purely uses the number of days or the highest temperature of the extreme high temperature.

The invention discloses a collaborative improvement method for a horizontal wind speed algorithm in an urban block network model, and the method comprises the steps: enabling a high-resolution CFD wind field simulation to serve as a quasi-truth value, carrying out the comparison verification of wind speeds at different positions of the urban block network model and a quasi-truth value wind field, introducing local roughness and displacement height parameters which are combined with building features, and carrying out the calculation of a horizontal wind speed algorithm. The system evaluates the influence of the combination of the local roughness and the displacement height under different scales and the local friction speed inverted by the CFD on the wind speed simulation, selects the optimal parameter combination to replace the regional average roughness and the displacement height parameter according to the evaluation result, and optimizes the wind speed simulation capability of the urban block network model under the urban non-uniform underlying surface condition. The method has the advantages that the characteristic that the height of the underlying surface of the center of the city is not uniform can be more accurately represented by combining the local friction resistance speed, the local roughness and the displacement height parameters which are inversed by CFD simulation, so that the dragging effect of the city building is accurately simulated, and the horizontal wind speed closer to the reality can be obtained.

The invention provides an environmental data monitoring method and system based on cloud computing and spatial-temporal characteristics, and the method comprises the steps: receiving an environmental data set transmitted by environmental monitoring devices distributed at different positions of a city block, and carrying out the spatial-temporal characteristic extraction of the environmental data set; generating a space-time correlation feature set containing the time dimension change feature and the space dimension distribution feature; performing pattern recognition on the time-space correlation feature set through a pre-constructed carbon flux analysis model, and generating urban block carbon flux change features; according to the urban block carbon flux change feature, the position feature and the range feature of the carbon flux abnormal change area are identified, the accuracy of the urban block carbon flux change feature can be improved, and the position and the range of the carbon flux abnormal change area can be identified more accurately based on the accurate carbon flux change feature. And a reliable basis is provided for fine management of urban block carbon flux.

The invention relates to an urban block wind environment rapid prediction method for embedding a generative adversarial network by using physical information, and the method comprises the following steps: building an ideal model of an urban block, obtaining geometric data, and setting a monitoring point; performing wind field simulation based on the geometric data and the set monitoring points to obtain wind field data around the urban block building; based on the geometric data, extracting building features of the monitoring points; the extracted building features serve as input of a PIGAN depth generation model, wind field data serve as output of the model, the model is trained, and the PIGAN depth generation model is constructed by embedding a physical equation into a regularization item of a generative adversarial network; and utilizing the trained PIGAN depth generation model to carry out wind field distribution rapid prediction. Compared with the prior art, the method has the advantages of high prediction speed, high prediction accuracy and the like.

The invention provides a city block change detection method, system and device and a storage medium, and relates to the technical field of image processing, and the method comprises the steps: obtaining N time sequence satellite images of a target block, N > = 3, and taking one satellite image as a slice; constructing a time sequence fragment which takes the ith slice as the center and has the length of k, wherein k is greater than or equal to 3 and less than or equal to N; according to the time sequence relevance among the multiple slices in the time sequence fragment, the semantic coherence score of the ith slice is obtained through calculation, and the semantic coherence score is used for reflecting the change degree of the target block at the time point corresponding to the ith slice; and obtaining a detection result according to the semantic coherence score. According to the method, the change boundary and the change type when the target block changes are determined by analyzing the semantic coherence of the corresponding satellite image of the target block in the time period covered by the time sequence fragment.

The invention relates to an outdoor microclimate monitoring system and method for urban blocks, belongs to the technical field of urban intelligent monitoring and management, and solves the problem that in the prior art, low-cost accurate monitoring cannot be carried out on wide-area coverage outdoor microclimate. The method comprises the following specific steps: respectively acquiring microclimate data of a city block to be measured through a background observation point, a plurality of key observation points and a mobile observation point, and obtaining a background point temperature sequence, a key point temperature sequence and a mobile temperature sequence in a monitoring time period; respectively taking the temperature of each sampling time point in the background point temperature sequence as a reference, and correcting and calibrating the mobile temperature sequence by using the time difference; and inputting the key point temperature sequence into microclimate software, and performing dynamic heat source correction simulation on each temperature field distribution diagram in combination with the calibrated mobile temperature sequence of the corresponding time point to obtain an outdoor environment temperature simulation result in a monitoring time period, thereby realizing accurate output of meter-scale grid environment parameters of a 1KM2 block by less than or equal to 10 fixed sensors.

The application provides an environment data monitoring method and system based on cloud computing and space-time characteristics, which comprises the following steps: receiving a set of environment data transmitted by environment monitoring devices distributed at different positions in a city block, extracting space-time characteristics of the set of environment data, and generating a set of space-time correlation characteristics containing time dimension change characteristics and space dimension distribution characteristics; performing pattern recognition on the set of space-time correlation characteristics by using a pre-constructed carbon flux analysis model, and generating city block carbon flux change characteristics; and identifying position characteristics and range characteristics of a carbon flux abnormal change area according to the city block carbon flux change characteristics. The application can improve the accuracy of city block carbon flux change characteristics, and based on accurate carbon flux change characteristics, the position and range of the carbon flux abnormal change area can be more accurately identified, thereby providing a reliable basis for fine management of city block carbon flux.

The invention is suitable for the technical field of high-temperature monitoring, and particularly relates to a city block high-temperature adaptability monitoring method and system based on multi-source data fusion, and the method comprises the steps: delimiting a block needing to be subjected to high-temperature adaptability monitoring, drawing a plane distribution diagram of the block, constructing a temperature data collection platform, and carrying out the high-temperature adaptability monitoring of the block from registrants; the method comprises the steps of selecting a curbside node, acquiring monitoring data uploaded by the curbside node, and determining a deployment position of temperature sensing equipment, the monitoring data of each piece of video monitoring equipment at least comprising one piece of temperature sensing equipment. By determining the target route, personalized travel experience can be provided for pedestrians, people flow pressure of hot road sections can be relieved, microclimate load of urban blocks can be improved, travel experience of users can be improved, thermal environment management efficiency of the urban blocks can be improved, health risks caused by high temperature can be reduced, and the method is suitable for popularization and application. And the comprehensive goal of safe and comfortable travel is achieved.

The invention discloses an energy-saving city design-oriented building performance proxy model construction and application method, which comprises the following steps of: establishing a parameterized city block model, and defining city form design variables and building performance evaluation indexes; based on the parameterized city block model, generating a training data set comprising a plurality of groups of city form design variables and building performance evaluation indexes corresponding to the city form design variables through building performance simulation software; constructing and training a deep neural network model by using the training data set, so that the deep neural network model learns a nonlinear mapping relationship between urban form design variables and building performance evaluation indexes to obtain a building performance proxy model; and applying the trained building performance agent model to predict a corresponding building performance evaluation index according to the input urban form design variable. According to the method, real-time prediction of the building performance is realized through the constructed agent model, and an efficient and reliable decision support tool is provided for early scheme evaluation and optimization of energy-saving city design.

The invention discloses an emergency shelter site selection and responsibility area division method for coping with population fluctuation. The method comprises the following steps: screening potential emergency shelters based on open space vector data; establishing an adjacency relation matrix and a network distance matrix between the urban parcels and a spatial relation matrix between the potential emergency shelters and the urban parcels; one scheme is selected from all potential emergency shelter combination schemes, an initial responsibility area division scheme is generated according to the nearest neighbor principle, and a population fluctuation coefficient is calculated; searching an exchangeable plot corresponding to each responsibility area, randomly exchanging one urban plot as a new responsibility area division scheme, and recalculating a population fluctuation coefficient; repeatedly executing until all responsibility area division schemes meeting conditions and corresponding population fluctuation coefficients are obtained; and selecting an optimal scheme according to the population fluctuation coefficient, carrying out statistics on effective refuge area gaps, and selecting the optimal scheme with the minimum effective refuge area gap as the optimal scheme.

The invention discloses a man-machine interaction city block outdoor space efficiency diagnosis and optimization method, which is suitable for block updating and reconstruction and new development and construction projects in a high-density city environment. Aiming at the problems that the efficiency of the outdoor space in the existing urban environment is easily neglected and a special evaluation and optimization system is lacked, the method comprises the following steps: dividing the outdoor space into space units according with human behavior perception based on a convex space division method; a multi-dimensional evaluation index system including space unit depth, connectivity and accessibility and plot configuration diversity and accessibility is constructed, and a man-machine interaction measurement and calculation program is built based on a Grasshopper platform. The program can feed back dynamic changes of indexes in real time, automatically adjust according to factors such as road grades, entrance and exit positions and building layout, assist a designer in rapidly adjusting a scheme in a design stage and obtaining a real-time evaluation result, realize accurate diagnosis and optimization of outdoor space efficiency, and improve the efficiency of the outdoor space. And a scientific decision basis is provided for improving the utilization efficiency of the urban block space and promoting intensive development.

Visualize potential optimal locations for power generation equipment within a city block. [Solution] The information processing system includes a first acquisition unit that acquires the spatial distribution of solar radiation, a second acquisition unit that acquires the spatial distribution of wind speed in a time history, a calculation unit that uses the amount of power generated from solar power generation equipment and wind power generation equipment installed at predetermined locations in the city block to calculate a first power generation characteristic representing the power generation capacity of solar power generation equipment and a second power generation characteristic representing the power generation capacity of wind power generation equipment for each time period in the time history, an estimation unit that estimates the amount of solar power generation based on the spatial distribution of solar radiation and the first power generation characteristic, estimates the amount of wind power generation based on the spatial distribution of wind speed and the second power generation characteristic, estimates the total amount of power generated by solar power generation and wind power generation, and outputs the estimation result, and a presentation unit that displays the city block in map data and superimposes the estimated power generation amount, which can be switched for each time period in the time history based on the estimation result, and candidate locations for solar power generation equipment and wind power generation equipment.

The invention discloses an urban block environment livability forecasting method, which belongs to the technical field of application meteorology and comprises the following steps: acquiring meteorological element data at different typical positions to calculate urban environment livability evaluation indexes and spatial and temporal distribution of meteorological elements of the urban environment livability evaluation indexes at different typical positions in a future forecasting time period; selecting urban environment livability evaluation indexes suitable for different crowds according to seasons and weather types to which future forecast time periods belong: carrying out weighted calculation on meteorological elements according to exposure time percentages of different crowds at typical positions, judging urban environment livability, and carrying out risk grade division on different typical positions in urban blocks; and issuing early warning information to the high-risk area in the future forecasting time period. The problems that in the prior art, microscale meteorological element space-time distribution differences in the block and exposure characteristics of different crowds are ignored, so that risk assessment is not accurate, and personalized early warning cannot be achieved are solved.

The invention discloses an urban block risk assessment method and system based on spatio-temporal trajectory data. The method comprises the following steps: constructing a three-dimensional analysis unit; historical passenger flow sample data are collected and preprocessed; sorting the preprocessed historical passenger flow samples according to numerical values, and calculating passenger flow intervals between adjacent samples to form an interval sequence; calculating a clustering radius based on the interval sequence, and performing clustering grouping on the passenger flow samples according to the clustering radius; identifying a reasonable group from the clustering group, and setting a dynamic risk threshold value of the three-dimensional analysis unit based on the reasonable group; and carrying out real-time risk early warning. The system comprises a three-dimensional analysis unit construction module, a sample processing module, an interval calculation module, a clustering radius calculation module, a threshold setting module and a real-time early warning module. According to the invention, through three-dimensional unit construction and adaptive threshold calculation, accurate identification of passenger flow abnormal risks in different areas and time periods is realized, and the accuracy and adaptive capability of urban risk assessment are improved.

The present invention provides a non-line-of-sight (NLOS) unmanned aerial vehicle (UAV) positioning method based on a genetic algorithm. Based on the characteristics of millimeter-wave radar multipath echo data, the ghost position of the target is obtained through BP imaging, and the principle conforms to the multipath propagation model in a non-line-of-sight environment. Then, street width is used to characterize the building street layout information. Based on the geometric relationship between the position of the target and the ghost, an objective function including the unknown street width is established. The objective function is optimized through a genetic algorithm to obtain the accurate position and street width of the target. In other words, the present invention can realize non-line-of-sight target positioning under the condition of unknown building layout, and is an effective target positioning method with higher target positioning accuracy. The present invention is particularly suitable for a typical L-shaped urban block model, and provides technical support for target positioning under a generalized non-line-of-sight model.

The application discloses a kind of urban block dense road network three-dimensional organization planning method, system, equipment and medium, the method includes: according to the three-dimensional road network model of target block, identify different elevation layer position in the effective first layer public interface that can enter, can be penetrated and is associated with public activity;With effective first layer public interface as reference, measure effective public interface density and three-dimensional public penetration rate;Effective first layer public interface in each elevation layer position is mapped with three-dimensional road traffic network, constructs interface road network coupling topological graph to identify interface continuity breakpoint in effective first layer public interface and three-dimensional penetration weak point;According to effective public interface density, three-dimensional public penetration rate, interface continuity breakpoint and three-dimensional penetration weak point carries out dense road network organization repair simulation, obtains the dense road network organization repair strategy of target block;The application can realize the systematic identification of multiple first layer public interface, to realize the effective planning of small block dense road network three-dimensional organization and repair.

The application discloses a kind of unmanned aerial vehicle modeling is applied to the method and device of city microenvironment evaluation, belong to environmental meteorological monitoring technical field, the method includes based on unmanned aerial vehicle flight platform to city street building is tilted and is photographed, obtains topographic feature three-dimensional data;Generation area building and other topographic feature three-dimensional space layout model;Based on unmanned aerial vehicle flight platform obtains the low-altitude atmospheric environment parameter in region;Low-altitude atmospheric environment parameter is superimposed to three-dimensional space layout model, form space-time distribution assimilation data, and generate simulation region's complex boundary condition;Based on the complex boundary condition of simulation region and three-dimensional space layout model, using CFD method calculation obtains air flow field, space-time distribution of atmospheric pollutant concentration field and air quality index, complete city microenvironment evaluation;The application will unmanned aerial vehicle flight platform and corresponding technology be applied to city block scale microenvironment quantitative evaluation, convenient and fast, cost is relatively low.

The application relates to an environment performance prediction method and device based on pix2pix, wherein the method comprises the following steps: automatically parameterizing modeling of a city block to generate a three-dimensional simulation geometric model of the city block; performing environment performance simulation to generate an environment performance dataset; processing the three-dimensional simulation geometric model and the environment performance dataset based on a dimension reduction encoder to obtain training set samples for different environment performance prediction objects; performing color standardization processing on the training set samples; constructing a pix2pix generative adversarial network, wherein the pix2pix generative adversarial network comprises a generator based on a U-net and a discriminator based on a convolutional PatchGAN classifier; training the pix2pix generative adversarial network based on a TensorFlow deep learning framework and using the training set; predicting environment performance based on the trained pix2pix generative adversarial network; and performing color standardization processing on the predicted environment performance to obtain a prediction result. Compared with the prior art, the application has the advantages of fast prediction speed, high prediction accuracy and the like.

The invention provides an urban block wind field refined prediction method, and the method comprises the steps: obtaining wind field actual measurement data of a target urban block, and the wind field actual measurement data comprise wind speed data and position data; preprocessing the wind speed data to obtain target wind speed data; inputting the target wind speed data and the position data into a first wind field prediction model to obtain a wind field prediction result of the city block; and inputting the wind field prediction result into the second wind field prediction model to obtain a target wind field prediction result of the city block. Therefore, high-precision and high-efficiency dynamic prediction of the complex wind field of the urban block can be realized through a double-model series prediction framework in combination with the actually measured wind speed and related position data of the wind field.

The application provides a binocular positioning method using a known light source arrangement, and belongs to the field of computer vision positioning. The application captures the positions of three visible light feature points of a target object in a camera pixel image during movement of a binocular camera, and an inclination angle and a roll angle obtained by a six-axis inertial sensor. A unscented Kalman filter is used to integrate data of the inertial sensor and data of the binocular camera, so that visible light positioning is realized, that is, the position of a visible light feature point of the target object in a three-dimensional space and a heading angle are accurately calculated. The application has wide applicability, good stability, and can be used for positioning at a farther distance. The stability is excellent not only in an indoor environment, but also in complex outdoor environments such as urban blocks, mountains and oceans.

The invention relates to the technical field of crossing of city planning, color evaluation and computer vision, in particular to a city block building color harmony evaluation method and device, and the method comprises the steps: collecting and preprocessing data, obtaining block building color data, spatial position data and planning constraint data, converting the data into a unified color space, and removing noise; feature extraction: calculating single building color features, adjacent building color correlation features and block overall color distribution features; constructing a multi-dimensional evaluation index system including color suitability, adjacent coordination degree, overall balance degree and planning integrating degree; determining an index weight based on an analytic hierarchy process-entropy weight method; according to the method, objective and quantitative evaluation of the color harmony degree of the building is realized, the evaluation efficiency and accuracy are improved, a scientific basis is provided for urban block color planning and reconstruction, and the technical problems that traditional evaluation depends on subjective judgment and lacks a unified standard are solved.

The invention relates to a calculation method for fire spreading in an urban area, and aims to solve the technical problem that the accuracy of a calculation result is low or the calculation efficiency has a bottleneck in the prior art. The invention provides an urban area fire spreading calculation method, which comprises the steps of dividing block units based on the size and function type of an urban block, setting fire characteristic parameters, determining an initial ignition state of a city according to an accident type, and calculating fire spreading of the urban area. According to combustion airflow fields and environment wind fields caused by fire disasters of different block units, the coupling airflow speed in the area is calculated, the fire situation of the non-fire building in each block is calculated by considering heat radiation and a fire spreading mechanism, and the combustion state of the fire building in each block unit is updated based on the type of the building in each block.

This invention discloses a method for predicting and evaluating urban street light and heat human factors based on multimodal behavioral coupling, belonging to the field of urban microclimate environment and human comfort assessment technology. The method includes the following specific steps: S1 Multimodal data acquisition; S2 Data preprocessing and multimodal input fusion; S3 Light-heat-human factor coupling modeling; S4 Response prediction and deep learning modeling; S5 Exposure integral index calculation; S6 Interpretable output of results; S7 Digital twin feedback and optimization. This invention is the first to deeply couple light environment factors with thermal environment factors and human behavioral responses, overcoming the limitations of traditional thermal comfort assessments that only focus on a single thermal index. By automatically extracting complex relationships through a deep learning model, it improves the accuracy and robustness of comfort prediction. Compared with methods that simply use indices such as PMV / UTCI, this invention provides more accurate predictions of subjective thermal sensation in outdoor dynamic environments, and its prediction of behavioral responses fills a gap in existing technology.

This invention discloses a collaborative improvement method for horizontal wind speed algorithms in urban street network models. The method includes using high-resolution CFD wind field simulations as near-true values, comparing and verifying wind speeds at different locations in the urban street network model with the near-true wind fields, introducing local roughness and displacement height parameters incorporating building characteristics, and systematically evaluating the impact of combinations of local roughness and displacement height, along with CFD-derived local friction velocity, on wind speed simulation at different scales. Based on the evaluation results, the optimal parameter combination is selected to replace the regional average roughness and displacement height parameters, optimizing the wind speed simulation capability of the urban street network model under non-uniform urban underlying surface conditions. The advantages are: by combining the CFD-derived local friction velocity with local roughness and displacement height parameters, the non-uniformity of the underlying surface height in the city center can be more accurately characterized, thereby precisely simulating the drag effect of urban buildings and helping to obtain horizontal wind speeds closer to reality.

The invention provides a city block level carbon emission power density adaptive interpolation method and electronic equipment, and relates to the technical field of data processing. According to the implementation scheme, the position of a first interpolation sampling point in a sampling network of a first urban plot is determined based on the difference between gradient vectors of the building development amount of each sampling point of the first urban plot, and the building development amount of the sampling point is the ratio of the building area to the base area of the sampling point; determining the carbon emission power density of the first interpolation sampling point based on the carbon emission power density of the plurality of first adjacent sampling points of the first interpolation sampling point and the change slope of the carbon emission power density of the plurality of first adjacent sampling points; and interpolating the sampling network of the first urban plot based on the position of the first interpolation sampling point and the carbon emission power density. By adopting the scheme of the invention, the interpolation accuracy of the carbon emission data can be improved, and the sampling cost of the carbon emission data can be reduced.

This disclosure provides an adaptive interpolation method and electronic device for carbon emission power density at the city block level, relating to the field of data processing technology. The implementation scheme is as follows: Based on the differences in the gradient vectors of building development volume at various sampling points of a first urban plot, the location of a first interpolation sampling point in the sampling network of the first urban plot is determined, where the building development volume of the sampling point is the ratio of the building area to the base area of ​​the sampling point; based on the carbon emission power density of multiple first neighboring sampling points and the slope of the change in carbon emission power density of the multiple first neighboring sampling points, the carbon emission power density of the first interpolation sampling point is determined; based on the location and carbon emission power density of the first interpolation sampling point, interpolation is performed on the sampling network of the first urban plot. Using the scheme of this disclosure, the accuracy of carbon emission data interpolation can be improved, and the sampling cost of carbon emission data can be reduced.

This invention proposes a method and system for urban block morphology optimization design decision-making based on a generative large model. The method includes: collecting multimodal green performance data affecting local heat island intensity and wind environment performance at the urban block scale and preprocessing it; converting the preprocessed data into RDF triples based on entities, relations, and events to construct a multimodal knowledge graph; modularly clustering the knowledge in the multimodal knowledge graph to obtain structured subgraphs, improving knowledge retrieval efficiency based on the structured subgraphs, and obtaining a building green performance data vector database to establish an external knowledge base to enhance the large language model; using knowledge representation to enhance the large language model to provide guidance and receive feedback for the machine learning model executing urban block morphology optimization design, forming an edge-cloud collaborative architecture of large and small models. This method and system can improve the multimodal data processing capabilities of traditional single machine learning methods, and enhance the efficiency and accuracy of optimization design decisions.