28 results about "Building density" patented technology

The invention relates to the field of fire risk analysis, in particular to a building fire monitoring control and fire risk studying and judging method. The method comprises the following steps: collecting building personnel flow information, carrying out density distribution calculation, and constructing a building density distribution diagram; performing inter-floor personnel migration state analysis on the building density distribution diagram to obtain people flow trajectory fluctuation characteristics; obtaining multi-dimensional environment monitoring data in the building, and performing people flow density interference correction based on the people flow trajectory fluctuation characteristics to obtain corrected environment monitoring parameters; performing real-time environment condition analysis and fire propagation situation mining based on the corrected environment monitoring parameters to obtain a potential fire propagation situation path; and fire risk coefficient calculation is carried out based on the potential fire propagation situation path, dynamic evacuation planning is carried out, and collaborative fire risk control operation is executed. By accurately and efficiently predicting the fire risk, the optimal risk avoidance scheme is planned for different building floors, and the building safety is improved.

The invention discloses a street building group automatic layout and iterative optimization method based on a TFM architecture, and the method comprises the steps: constructing a structured learnable graph attention matrix through high-precision point cloud data, and coding a building unit space topological relation and economic indexes through combining a historical case library; the method comprises the following steps: dynamically modeling a space function association relationship of a building group by utilizing a multi-head graph attention Transform module, and integrating space and function constraint conditions through a hierarchical constraint injection mechanism; an autoregression graph generation model is adopted to generate a preliminary layout scheme based on land parcel features and global constraints, and multi-target iterative optimization is carried out through a genetic algorithm in combination with a fitness function; and finally outputting a three-dimensional layout scheme meeting multi-dimensional indexes such as the plot ratio, the building density and the greening rate. According to the method, the traditional artificial experience driving limitation is broken through, adaptive learning and optimization under the multi-constraint condition are supported, the design period is shortened from several weeks to several hours, and the scientificity and feasibility of the scheme are remarkably improved.

The invention relates to the technical field of optical remote sensing image application, and provides a method for extracting a rural residential area and judging the closeness of a building by using tile data, which is used for extracting the rural residential area and judging the closeness of the building by combining map tile data and a deep learning technology, and judging the closeness of the building through tile resolution characteristics and actual characteristics of the rural residential area. 14-level tile images are selected for rural residential area distribution extraction, and after the 14-level tile images are obtained, a model obtained through SegFormer-based training is used for extracting rural residential area distribution; the method comprises the following steps: selecting 18-level tile images to extract rural building distribution, extracting rural buildings by using a model obtained by training based on DeepLabV3 +, and selecting medium-resolution hierarchical images to interpret, thereby improving the precision and efficiency of rural residential area extraction and building density determination.

The invention discloses a land utilization change comprehensive feature analysis method based on multi-source heterogeneous data fusion, and relates to the technical field of remote sensing and geographic information processing. Building volume, building density, night light, surface temperature and population density are aligned under unified coordinates and resolution; constructing an average building height according to volume / density and coding and recording quality; uniform noctilucence is realized through partition three-order mapping; interpolation is carried out by adopting fractional learning under the missing measurement mask, and pixel-level uncertainty is output; uniformizing the annual temperature; extrapolation is carried out through multi-scale space-time small block coding-decoding containing flux conservation and Laplace constraint, and uncertainty is given; implementing uncertainty weighted principal components according to the five indexes to obtain a comprehensive strength index; concentric buffering, set splitting regression and partial response confidence band recognition threshold values are combined. The method has the advantages of cross-period comparability, physical consistency, traceable uncertainty and the like.

The invention relates to the technical field of construction management, in particular to an urban and rural construction data analysis optimization method and system, and the method comprises the following steps: obtaining remote sensing images, analyzing the change characteristics of land parcels, calculating the difference sorting of block land parcels, constructing a functional path chain, analyzing the coupling behaviors of the land parcels, and recognizing abrupt change and coupling double-height regions. And generating an urban and rural construction data analysis result. According to the method, the green vegetation, the building density and the road linear feature of the land parcel are quantified through the remote sensing image data, the frequency and the duration of the mutation feature are recorded, the mutation vector sequence is formed, the sensitivity capture of the dynamic change of the land parcel can be realized in the initial stage, and the excessive dependence on the original data is avoided. And in combination with vector cosine distance comparison between plots in the block, a difference intensity sequence is established, accurate sequencing of spatial disturbance conditions in the region is realized, and the scientificity of plot screening is enhanced.

The invention relates to the technical field of image simulation, in particular to a dynamic simulation method and system for smart city planning simulation, and the method comprises the following steps: obtaining remote sensing image data of a city, calculating the reflectivity of a surface wave band, analyzing the height difference of surface features based on elevation data, and calculating the building coverage rate of a unit region. And classifying the differentiated material regions by using the surface material reflection features to obtain image multi-dimensional feature data. According to the invention, by analyzing the pixel gradient change rate and the building density parameter and optimizing the urban boundary determination method, the accuracy of boundary determination and the detail processing capability of urban planning are improved, and the classification of urban functional areas is accurately analyzed by combining the building height and the surface spectral reflectance analysis. The method enhances the understanding of urban spatial distribution and function division, integrates the application of multi-source data and algorithms, not only improves the efficiency of urban planning, but also increases the practicability and scientificity of a planning result.

This application provides a method and system for monitoring the heat island mitigation function of ecological corridors. The method includes acquiring remote sensing images of a monitoring area, which includes a target ecological corridor and several buildings in a buffer zone adjacent to the target ecological corridor; calculating an openness index, an aspect ratio index, a vegetation enhancement index, and a building density index; weighting and summing these indices to obtain a comprehensive heat island mitigation function index for the target ecological corridor; and issuing an alarm when the comprehensive heat island mitigation function index is less than a preset threshold. This application, by acquiring and analyzing remote sensing images covering the target ecological corridor and its adjacent buffer zones within the monitoring area, can effectively improve the efficiency and accuracy of monitoring the heat island mitigation function of ecological corridors.

The invention relates to a building planning drawing intelligent auditing processing method, and relates to the technical field of drawing processing, and the method comprises the steps: extracting the planning plot ratio, planning building density and planning greening rate of a building planning drawing to be audited, and carrying out the same drawing retrieval in a drawing database, the method comprises the following steps: acquiring a volume abnormal coefficient, a density abnormal coefficient and a greening abnormal coefficient, calculating and adjusting the retrieval quantity of the adjacency drawings of three features to obtain the retrieval quantity of the three adjacency drawings, and respectively performing adjacency drawing retrieval and abnormal analysis to obtain a volume abnormal rate, a density abnormal rate and a greening abnormal rate; and according to the volume anomaly coefficient, the density anomaly coefficient and the greening anomaly coefficient, carrying out labeling correction on the volume anomaly rate, the density anomaly rate and the greening anomaly rate, carrying out pre-auditing labeling on the building planning drawing, and carrying out auditing processing. The problems that in the prior art, the auditing period of the building planning drawing is long, and errors are prone to occurring are solved.

The invention discloses a city update identification method, device and system, and a storage medium. The method comprises the following steps: obtaining building contour change data and POI function data of a city target area; according to the building contour change data, obtaining a reconstruction type city updating area through a building density change rate; according to the POI function data, a function replacement type city updating area is obtained through the function density change rate; and carrying out visual output on the reconstruction type city updating area and the function replacement type city updating area. By adopting the technical scheme of the invention, the updated area of reconstruction and function replacement in the city is dynamically identified, and policy setting and differentiation transformation path making are assisted.

The invention relates to the technical field of urban building planning, and discloses an urban building planning method based on machine learning, comprising the following steps: step 1, data collection and preprocessing: collecting data related to urban building planning, and cleaning, formatting and normalizing the data; step 2, feature extraction and selection: extracting population density, traffic flow, land utilization type and building density features from the preprocessed data, and selecting features having great influence on urban planning through a feature selection technology; and step 3, model selection and training: selecting a machine learning model and training the model by using the training data set. Various urban building planning schemes are evaluated through an intelligent simulation tool, and in this way, urban planning not only considers current requirements, but also can predict and adapt to future changes, so that the overall sustainability of a city is improved.

The invention relates to the technical field of city planning, in particular to a city densification mode detection method and system, and the method comprises the steps: dividing the blocks of a city based on a traffic network provided by an electronic map, taking the blocks as minimum analysis units, and recognizing the main function attributes of each block; obtaining two-dimensional structure characterization and three-dimensional height characterization of each block; the two-dimensional structure representation and the three-dimensional height representation of each block are resampled to the same resolution ratio, and the space reference is unified; different weights are given to the two-dimensional structure characterization and the three-dimensional height characterization of each block according to the main function attributes of each block; according to the two-dimensional structure characterization and the three-dimensional height characterization of each block and the weight endowed by the two-dimensional structure characterization and the three-dimensional height characterization, building a building density index as characterization of urban land densification utilization; and obtaining building density indexes of a plurality of periods, performing time sequence trend analysis on the building density indexes of the plurality of periods through a linear regression model, and judging a densification mode of the current city according to an analysis result.

The invention relates to a space resource intensive utilization evaluation method and system for a marine construction project and a medium, and the method comprises the steps: calculating a current situation value of each index in a space resource intensive utilization evaluation index system based on construction project information, and calculating an implementation degree score of each index based on the current situation value of each index; the space resource intensive utilization evaluation index system comprises the following indexes: a land construction rate, a production space ratio, an ecological space ratio, a living space ratio, a channel space ratio, a reserved space ratio, a shoreline utilization rate, an ecological shoreline recovery rate, a coast building retraction distance, a space utilization rate, a plot ratio, a building density, a space resource utilization benefit and input intensity. Output intensity and tax contribution; assigning a value to the weight of each index; and calculating a comprehensive score of intensive utilization of the space resources based on the implementation degree score and the weight of each index, and determining an intensive utilization level of the space resources according to the comprehensive score of intensive utilization of the space resources. The method effectively improves the intensive utilization evaluation precision of space resources.

The present invention belongs to the cross field of remote sensing image processing and disaster risk management, and provides an adaptive threshold optimization method and system for wildland-urban interface (WUI) zoning. The technical solution is as follows: calculate the building density according to the building segmentation result; calculate the vegetation coverage, the wildland patch area and the distance measure respectively; determine the WUI determination rule, and determine the type of WUI in combination with the determination rule; set the threshold ranges of the building density, the vegetation coverage, the wildland patch area and the buffer distance measure, and calculate the WUI areas of different types of WUI under different thresholds; combine the historical burned area data and the WUI area to define the fire exposure index, use the spatial distribution characteristics of the WUI area as the independent variable of the random forest (RF) model, and the fire exposure index under different thresholds as the dependent variable of the RF model, and fit to obtain the optimal threshold, effectively solving the technical bottlenecks such as low accuracy of element extraction, single quantification standard and strong subjectivity in threshold setting in traditional WUI identification.

The invention provides an unmanned aerial vehicle flight path planning method for building image acquisition, and the method comprises the steps: obtaining a target region for building image acquisition, and collecting a first building image in a first sub-region according to a preset flight height and a first flight path; according to the first building image, hidden building spacing distribution and hidden building height distribution of the target area are obtained through analysis, same-family building spacing distribution and same-family building height distribution are indexed, and building spacing distribution and building height distribution are obtained through processing; according to the building spacing and the building height, performing flight height path planning in the second sub-region to obtain an optimal height flight path; and according to the optimal height flight path, building image acquisition of the second sub-region is carried out, and building image acquisition is continued until acquisition of the target region is completed. The technical problem that in the prior art, an unmanned aerial vehicle is poor in building image collection quality under the complex scene that the building density is large and the height difference is remarkable is solved.

The present application relates to a kind of building planning drawing intelligent auditing processing method, it is related to drawing processing technical field, including: the planning volume rate of the building planning drawing to be carried out for auditing, planning building density and planning green rate are extracted, respectively in drawing database same drawing search is carried out, and abnormal analysis is carried out to obtain volume abnormal coefficient, density abnormal coefficient and green abnormal coefficient, the calculation adjustment of the number of adjacent drawing search of three characteristics is carried out, obtain three adjacent drawing search number, respectively adjacent drawing search and abnormal analysis are carried out, obtain volume abnormal rate, density abnormal rate and green abnormal rate;According to volume abnormal coefficient, density abnormal coefficient and green abnormal coefficient, volume abnormal rate, density abnormal rate and green abnormal rate are marked correction, mark before auditing to building planning drawing is carried out, and carries out auditing processing.The present application solves the problems, such as long auditing cycle of building planning drawing in prior art, prone to error etc.

The invention discloses a self-adaptive building layout method and system based on a dynamic weight and constraint softening genetic algorithm, and the method achieves the self-adaptive building layout through a dynamic weight adjustment mechanism, a constraint softening strategy and self-adaptive iteration control under the condition of meeting the building specification constraint conditions (building spacing, sunlight requirement, plot ratio upper limit, building density limitation and the like). The method automatically and efficiently generates and optimizes an optimization scheme of the building layout in the plot, can respond to dynamic adjustment of planning parameters in real time, and is suitable for high-frequency design change and narrow feasible region scenes under planning. The method can respond to high-frequency parameter change in real time, and after parameters such as plot ratio / plot shape are changed through a dynamic parameter response mechanism (reserving compliant individuals, locally repairing and supplementing new individuals), the optimization process does not need to be completely restarted; the response time is shortened to 1 / 5 of that of a traditional method (minute-level scheme adjustment is supported); the problem that the prior art cannot adapt to high-frequency design change is thoroughly solved.

The application discloses a kind of based on multi-source big data's city compound pollution exposure evaluation method and early warning device, the method is by building including high-precision satellite remote sensing data, ground monitoring station data and mobile phone signaling data in multi-source database, realize including personnel density, traffic capacity, land cover type, blue and green infrastructure area, building density / height and compound pollution concentration in multi-source heterogeneous data fusion analysis, on this basis, a kind of multi-factor weighted assignment city compound pollution exposure risk assessment method is proposed, the evaluation method is coded and transformed, form executable independent operation program, and develop a kind of portable device that can be used for risk real-time early warning.The application is by efficient analysis of the interactive correlation mechanism between city compound air pollution and personnel, traffic, land use, blue and green facilities, space structure and other multi-source influencing factors, to realize the accurate assessment and early warning of compound category air pollution exposure risk.

The application is a kind of method and system for urban built-up area corridor space form identification, relating to the field of spatial geography technology. It includes the linear heritage corridor composed of the Grand Canal and the natural and artificial space along the canal, involving various types of urban and rural space forms. The overall continuous form zoning is of great significance for fine management and control. Taking the urban and rural corridor space of a section of the Grand Canal as an example, based on the cross-section model of form criteria, the overall space form along the canal is identified and zoned according to local characteristics. Six space form parameters, including land use type, average building height, volume rate, building density, sky openness and style control, are selected to analyze the space form characteristics. The strip method is used to identify and classify the space form characteristics along the canal, forming six cross-section types of landscape ecological zone, innovation industrial park, urban service function zone, business center zone, core historical and cultural zone and special function zone, and the space positioning is carried out to obtain the corridor space form identification result.

The invention discloses an urban boundary demarcation method for effectively eliminating terrain and low building density interference, and overcomes errors and difficulties brought to urban boundary recognition result precision by a single middle-low resolution optical remote sensing image. According to the urban boundary delimiting method based on the fusion of the high-resolution Sentinel multi-polarization radar, the multispectral optical remote sensing image and the ALOS PALSAR digital elevation model data technology, the interference problem caused by factors such as the terrain and the low building density in the urban boundary recognition and delimiting process can be effectively eliminated, and the recognition and delimiting precision of the urban boundary of the complex terrain is improved. According to the method, the recognition and delimitation of the urban boundary by fusing the Sentinel multi-polarization radar, the multispectral optical characteristics and the digital elevation model data are efficient and accurate, the delimitation precision and credibility of the urban boundary of the complex terrain are improved, repeatability and scientificity are achieved, and the method has extremely important significance on urban sustainable development and scientific planning.

This application provides a drone flight path planning method for building image acquisition, comprising: acquiring a target area for building image acquisition, acquiring a first building image within a first sub-area according to a preset flight altitude and a first flight path; acquiring an implicit building spacing distribution and an implicit building height distribution within the target area based on analysis of the first building image, indexing the spacing distribution and height distribution of similar-family buildings, and processing the obtained building spacing distribution and building height distribution; performing flight altitude path planning within a second sub-area based on the building spacing and building height to obtain an optimal altitude flight path; acquiring building images within the second sub-area according to the optimal altitude flight path, and continuing to acquire building images until acquisition of the target area is complete. This method solves the technical problem of poor building image acquisition quality of drones in complex scenes with high building density and significant height differences in the prior art.

The invention relates to the technical field of climate monitoring, in particular to a climate adaptation city monitoring and early warning method, which comprises the following steps: S1, monitoring distribution: taking each administrative region of a city as a division standard, and according to the proportion a of the occupied area of a building in each administrative region to the occupied area of the city, determining the occupied area of the city; marking each administrative region as a first region, a second region and a third region; grids with the length-width ratio of 1: 1 are uniformly distributed in each administrative region, a plurality of circles are drawn with the building center of each administrative region as the circle center, and the intersection points of all the circles and the grids and the intersection points of the grids in the region outside the circles serve as monitoring point positions; arranging climate monitoring sensors at the monitoring points; s2, monitoring and early warning; the method is divided into three types of areas according to the building density, intersection points of grids and circles serve as monitoring points, a dual-coverage network is formed, monitoring blind areas are avoided, global coverage and key area strengthening are considered, and real climate gradient changes can be better reflected.

The invention relates to the technical field of urban planning and rainwater management, and discloses a land parcel scale low-impact development planning verification method, system and device and a medium, and the method comprises the steps: determining a comprehensive runoff coefficient threshold value which needs to be reached by a land parcel based on a given land parcel low-impact development management and control target; obtaining planning layout parameters of the land parcel and hydrological parameters corresponding to various underlying surfaces in the land parcel; according to the planning layout parameters and the hydrological parameters, calculating through a runoff coefficient synthesis model to obtain an expected comprehensive runoff coefficient of the land parcel; and comparing the expected comprehensive runoff coefficient with the comprehensive runoff coefficient threshold value, and judging whether the planning scheme of the land parcel meets the low-impact development management and control target or not according to a comparison result. According to the method, existing indexes (such as green land rate and building density) which must be declared in a planning scheme are directly used as input, extracorporeal circulation of examination is avoided, and the management efficiency is greatly improved.

The invention provides a method and device for determining building density information, electronic equipment and a program product, and the method comprises the steps: determining a building region based on boundary information corresponding to a building set, the building region being a region to which a plurality of buildings included in the building set belong; based on the pre-selected division modes, grid division is carried out on the building area to obtain a plurality of grids, and the accuracy of the grids obtained through division in different pre-selected division modes is different; for any building in the building set, determining a target grid to which the building belongs in the plurality of grids; according to the method, the building density information of the building set is determined based on the target grids corresponding to the multiple buildings and the total number of the buildings in the building set, the building density information capable of accurately representing the sparse degree of building space distribution can be obtained, and the accuracy of data analysis based on the building density information can be improved.

The invention provides an ecological corridor heat island mitigation function monitoring method and system, and the method comprises the steps: obtaining a remote sensing image of a monitoring region which comprises a target ecological corridor and a plurality of buildings in a buffer interface adjacent to the target ecological corridor; the method comprises the following steps: calculating an openness index, a height-width ratio index, an enhanced vegetation index and a building density index; respectively carrying out weighted summation on the openness index, the aspect ratio index, the enhanced vegetation index and the building density index to obtain a heat island mitigation function comprehensive index of the target ecological corridor; and when the heat island mitigation function comprehensive index is smaller than a preset heat island mitigation function comprehensive index threshold value, alarm information is sent out. By acquiring and analyzing the remote sensing image covering the target ecological corridor and the adjacent buffer interface thereof in the monitoring area, the monitoring efficiency and accuracy of the heat island mitigation function of the ecological corridor can be effectively improved.

The present application relates to the technical field of optical remote sensing image application, and proposes a method for extracting rural residential areas and determining building density by using tile data, which extracts rural residential areas and determines building density by combining map tile data and deep learning technology, selects 14-level tile images for extracting the distribution of rural residential areas through the tile resolution characteristics and the actual characteristics of rural residential areas, uses the model trained based on SegFormer to extract the distribution of rural residential areas after obtaining the 14-level tile images, selects 18-level tile images for extracting the distribution of rural buildings, uses the model trained based on DeepLabV3+ to extract rural buildings, and selects medium-resolution level images for interpretation, thereby improving the accuracy and efficiency of rural residential area extraction and building density determination.

The invention discloses an urban heat island intensity analysis method and system based on remote sensing inversion, and the method comprises the steps: collecting multispectral remote sensing image data through a satellite sensor, carrying out the geometric correction and atmospheric correction of an image, and obtaining a corrected remote sensing image for the subsequent temperature inversion; a normalized vegetation index is calculated according to the corrected remote sensing image, and a vegetation index distribution map is obtained through calculation according to the difference value and sum value ratio of the red light band and the near-infrared band to reflect the vegetation coverage density; identifying a high-density building area from the corrected remote sensing image by adopting a building extraction algorithm, and obtaining a building density distribution diagram through combination of texture features and spectral features to represent a building coverage proportion; and judging the temperature gradient change in the accurate surface temperature map, if the temperature gradient exceeds a preset threshold, marking the temperature gradient as a heat island boundary line, and smoothing the boundary through a spatial interpolation method to obtain a heat island boundary contour for intensity distribution analysis.

The application discloses a map division method and device, a computer readable storage medium and a processor. The method comprises: obtaining a predetermined map of a predetermined area, wherein the predetermined map is used to show the building contour of the predetermined area, and the predetermined map comprises a plurality of preset grids, and the grid area of each preset grid is the same; determining the building density in each preset grid according to the building contour in each preset grid, wherein the building density is the ratio of the building area in the preset grid to the grid area, and the building area is determined according to the building contour; clustering the plurality of preset grids according to the building density to obtain a grid clustering result, wherein the grid clustering result comprises a plurality of density levels, and each density level comprises at least one preset grid; and dividing the predetermined map according to the grid clustering result. The application solves the technical problem of low planning efficiency caused by manual planning of the map.

The present application relates to the field of urban planning technology, and in particular to a method and system for detecting urban densification patterns, the method comprising: dividing a city into blocks based on a traffic network provided by an electronic map, using blocks as the minimum analysis unit, and identifying the main functional attributes of each block; obtaining a two-dimensional structural representation and a three-dimensional height representation of each block; resampling the two-dimensional structural representation and the three-dimensional height representation of each block to the same resolution and unifying the spatial benchmark; assigning different weights to the two-dimensional structural representation and the three-dimensional height representation of each block according to the main functional attributes of each block; constructing a building density index as a representation of urban land densification utilization based on the two-dimensional structural representation and the three-dimensional height representation of each block and the weights assigned thereto; obtaining building density indices for multiple periods, performing time series trend analysis on the building density indices for the multiple periods through a linear regression model, and judging the current urban densification pattern based on the analysis results.