44 results about "Residential land" patented technology

The invention discloses a spatial matching method and system based on natural resource monitoring and demographic data, and the method comprises the steps: obtaining residential land and house building data in regional natural resource survey monitoring data, employing a spatial position and attribute matching technology, and combining a random forest algorithm to carry out the spatial matching of the residential land and the house building, thereby achieving the spatial matching of the residential land and the house building. Extracting residential building pattern spots and attribute information thereof; establishing attribute feature mapping between a residential building pattern spot level scale and an administrative division unit scale, and converting administrative division demographic data to residential building pattern spots by using a random forest hyper-parameter search method; further integrating multi-source data in the natural resource survey monitoring data, constructing a population geographic blot index taking a water area as a mask, and correcting the population of the residential building; and finally, calculating a population distribution fitting coefficient, iteratively correcting a population distribution error, and realizing spatial accurate matching of the residential building and population distribution through a partition adjustment strategy.

The invention relates to the technical field of carbon emission monitoring, and particularly discloses a town living space carbon emission monitoring method, which comprises the following steps: firstly, checking carbon emission in energy consumption of town residents; identifying urban residential building types and geographic spaces; the residences are grouped according to the building age, and different groups are endowed with differentiated carbon emission allocation weights; building features are introduced to serve as supplementary factors of carbon emission weight distribution; then, the weight of each factor is superposed, and the total carbon emission of urban resident energy consumption of the whole city is distributed to each residence land; and finally, obtaining a carbon emission detection and simulation result of each residential land under the condition of considering photovoltaic emission reduction. By the adoption of the urban living space carbon emission monitoring method, carbon emission of residents can be monitored with high resolution on the urban scale, and a scientific and feasible technical path is provided for accurate control of urban living space carbon emission, energy-saving strategy making and photovoltaic emission reduction potential mining.

The invention discloses a cellular automaton-based land utilization and urban element collaborative simulation method. The method comprises the following steps of: calculating the development probability of each element; the method comprises the following steps of: constructing a cellular automata (CA) model of each element; space collaborative simulation calculation; and evaluating the result precision. According to the method, the urban land use change simulation precision can be effectively improved, the land use change in reality can be better simulated, the simulation precision of population and economic elements can be improved, and the interaction and synergistic effect between different urban elements are effectively revealed. By means of multi-element collaborative simulation, small changes of urban development elements can be caught more finely, and the method has good perception ability for residential land, industrial land, commercial land, public management land and the like and has important significance for simulating urban collaborative development and reasonably planning urban layout.

The invention discloses a building prototype generation method based on urban big data. The method comprises the following steps: step 1, calculating each characteristic parameter of a residential land and each characteristic parameter of a residential building; 2, deleting redundant characteristic parameters based on the correlation between the characteristic parameters of the residential land and the residential building; determining clustering characteristic parameters of the residential land and the residential building for clustering on the basis of correlation between the reserved characteristic parameters of the residential land and the residential building and the energy consumption predicted value of the residential building; step 3, performing two-stage clustering based on the determined residential land clustering center and residential building clustering center to obtain an optimal residential building clustering result focused by the optimal residential land clustering center so as to generate a building prototype set; 4, respectively calculating building energy demand indexes based on the building prototype set; and when the comprehensive value of the building energy demand index is smaller than a set threshold, repeating the step 3 to regenerate the building prototype set. And the building prototype meets urban building energy demand prediction.

The invention discloses an urban low-efficiency residential land intelligent identification method based on a convolutional neural network, and the method comprises the steps: S1, carrying out the classification of each residential land parcel, and enabling the classified residential land parcels to serve as a residential land parcel classification case library; s2, determining a neighborhood range of each living plot in the learning area according to the plot dominant type, constructing a neighborhood function combination data set of each living plot as a sample set, and training a convolutional neural network according to the sample set to obtain a classification prediction model; s3, classifying the living parcels of the identification area according to the living parcel classification case library to obtain an internal classification result, processing the living parcels of the identification area as the sample set in the S2, and inputting the classification prediction model in the S2 to obtain a neighborhood identification result; and S4, in combination with the internal classification result and the neighborhood identification result in the step S3, identifying and obtaining the low-efficiency residential land in the identification area. The urban inefficient residential land can be automatically identified, and the method has the advantages of dynamic identification, accuracy and objectivity, popularization of results, real-time adjustment and the like.

The invention discloses a community life circle delimiting method and device, equipment and a medium, and relates to the field of life circle planning, and the method comprises the steps: generating corresponding road meshes through linear ground features in a target area, and merging residential lands in the range of the road meshes to generate a residential area; constructing a hexagonal grid corresponding to the target area, and extracting the hexagonal grid to obtain a walking reachable grid; calculating a target growth origin based on the residential area and the walking reachable grid, and taking the target growth origin as a starting point to construct a target growth range so as to generate a corresponding hexagonal grid region, and obtaining a life circle initial range; and integrating the initial range of the life circle to obtain an integrated life circle, and carrying out structural division on the integrated life circle according to the activity intensity of the crowd to obtain community life circles containing areas with different densities. It can be seen from the above that the multi-source data is utilized in the method, and accurate demarcation and multi-dimensional evaluation of the community life circle of the whole province and city and other large areas are achieved.

A method for generating building prototypes based on urban big data includes the following steps: step 1: calculating characteristic parameters of residential land and residential buildings; step 2: deleting redundant characteristic parameters based on the correlation between the characteristic parameters of residential land and residential buildings; determining cluster characteristic parameters of residential land and residential buildings for clustering based on the correlation between the retained characteristic parameters of residential land and residential buildings and the predicted energy consumption values ​​of residential buildings; step 3: performing two-stage clustering based on the determined residential land cluster centers and residential building cluster centers to obtain the optimal residential building clustering results focused on the optimal residential land cluster centers to generate a building prototype set; step 4: calculating building energy demand indicators based on the building prototype set; and when the comprehensive value of the building energy demand indicators is less than a set threshold, repeating step 3 to regenerate the building prototype set. The building prototypes meet the urban building energy demand forecast.

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

The invention discloses an urban residence land price evaluation method considering data imbalance and spatial heterogeneity. The method comprises the steps of collecting historical residence land sample data of a research area and performing spatial position matching; performing hierarchical index evaluation processing on the historical residential land sample data by using a multi-hierarchical index system, and performing fusion arrangement to obtain a residential hierarchical index land price data set; the land price evaluation combination model carries out model training of residence land price prediction by using a residence level index land price data set, and a differential evolution algorithm model DE dynamically searches a hyper-parameter combination of an XGBoost model and carries out optimization processing; and obtaining residential land multi-source data of the research block to obtain indexes of all levels, inputting the indexes into the land price evaluation combination model, and outputting and obtaining a residential land price evaluation prediction result. According to the method, the double problems of unbalanced sample price data and insufficient spatial heterogeneity identification are solved, high-precision urban residential land price evaluation is realized, and the accuracy and automation level of land price evaluation are improved.

The invention relates to the technical field of spatial data processing, in particular to a method and a system for updating residential place information in a multi-mode crowd-sourced space-time vector product, which are used for preprocessing crowd-sourced space-time vector data, extracting multi-dimensional space-time characteristics of plot data of each residential place and calculating similarity among plots of each residential place; matching and aligning the land parcels of the residential areas by utilizing the similarity; training a specified heterogeneous machine learning model by taking the similarity of the surface element characteristics of the residential land parcel data and the residential land parcel matching and aligning result as training data, and constructing an integrated learning model by utilizing a machine integrated learning method so as to obtain final matching output through a voting mechanism or a stacking method in machine integrated learning; and performing matching detection on the to-be-detected residential place data by using the integrated learning model, and if a matching detection result exceeds a residential place element updating threshold value, updating the to-be-detected residential place data. The method ensures that the heterogeneous data set quickly responds to the real-time change of the geographical environment, and improves the timeliness and accuracy of the residential place data.

The invention relates to the technical field of remote sensing data analysis, and discloses a residential land building component analysis method, device and system, and the method comprises the steps: taking a reference map as a reference, referring to the concept of pixels in an image, and dividing the reference map into a plurality of pixel blocks; the method comprises the following steps of: firstly, calculating a remote sensing parameter (similar pixel value) of each pixel block through remote sensing data by matching the remote sensing data with a reference map, then setting a traversal strategy of N continuous pixel blocks, and analyzing the distribution condition of the remote sensing parameters in the N continuous pixel blocks so as to determine boundary pixel blocks. Through the method, the building component boundary calculation of the residential land can be realized through the remote sensing data with higher reliability, so that a more reliable boundary line of the building components in the residential land is obtained, and finally a more reliable analysis result of the building components of the residential land is obtained.

The invention provides a recreation facility site selection method, device and equipment and a medium, and relates to the technical field of urban planning, and the method comprises the steps: obtaining first spatial data of a recreation service blind area, second spatial data and population data of each residential land in the recreation service blind area, and road data corresponding to a research area; determining a region weight value corresponding to each residential land according to the location entropy of the residential land in the spatial dimension represented by the first spatial data, the second spatial data and the road data, and the location entropy of the residential land in the population dimension represented by the population data; generating life circle data corresponding to each residential land according to the second spatial data and the road data; and extracting the target recreation facility site selection area based on the first spatial data, the area weight value and the life circle data. According to the method, the efficiency and accuracy of recreation facility site selection can be remarkably improved, recreation service blind areas are accurately and effectively reduced, and balanced distribution of urban recreation resources is achieved.

The present invention discloses an automatic planning and layout method for residential land, an electronic device and a storage medium. The method includes extracting plot information from a residential land document and carrying out setbacks on the plot; setting the orientation of the main axis of the plot and arranging the main axis according to the position of the plot center point and the orientation of the main axis; determining the green area according to the plot area and the greening rate and generating a green area at the plot center point; using multiple points on the main axis as dividing points, perpendicular to the main axis, dividing the plot on both sides of the main axis to obtain multiple sub-plots, and using the dividing line as a secondary road; obtaining the housing building type information according to the housing type plan; carrying out housing building layout on the sub-plots according to the housing building type information; calculating the housing building height; carrying out index accounting based on the housing building height, and automatically generating a residential land layout plan when the index requirements are met. The present invention greatly improves the working efficiency and docking efficiency of planners.

The invention discloses a multi-source data analysis city production and city integration and job-housing balance city physical examination method, which belongs to the technical field of city physical examination methods, integrates city scale, traffic accessibility and terrain multi-source data, selects a proper reference radius according to a city type needing to be evaluated, considers the influence of population density, congestion index, gradient and the like on actual commuting, and provides an evaluation result for the city production and city integration and job-housing balance. Correcting the reference radius through data standardization calculation and a three-dimensional correction formula to obtain a final buffer area radius, performing buffer area analysis on industrial land and residential land data by using a GIS tool to serve as the buffer area radius, calculating an overlapping area of the industrial land and residential land buffer areas, calculating a proximity index through a formula, and obtaining a final buffer area. And quantifying the job-housing balance fluctuation degree of the space unit by calculating the proximity index standard deviation, setting a stability threshold value, and judging whether the threshold value is met or not according to whether the threshold value is met or not, or triggering a three-stage iteration mechanism.

The invention discloses a low-efficiency residential land identification method and device based on a semi-supervised generative adversarial network, a storage medium and electronic equipment. The method comprises the steps of determining a recognition object; based on the identification object, determining a corresponding index, and constructing an index system; obtaining an unlabeled data set, and constructing a labeled data set based on the index system; and training the generative adversarial model based on the unlabeled data set and the labeled data set to obtain a trained generative adversarial model, and inputting a to-be-detected sample into the trained generative adversarial model to obtain a low-efficiency land use identification result. According to the method, a comprehensive index system is established, the deep learning algorithm is introduced into low-efficiency residential land identification, the influence of subjective factors in identification is reduced, the low-efficiency residential land is accurately identified, and the field investigation cost is saved.

To provide a taxation information management device, taxation information management method and program for managing taxation information used for calculating a tax base amount with appropriate content.SOLUTION: A taxation information management device 1 for managing taxation information used for calculating a tax base amount of a real estate tax, includes a storage unit 12 that stores a plurality of pieces of taxation information including a plurality of pieces of land taxation information associated with a plurality of pieces of land specification information for specifying land and a plurality of pieces of house taxation information associated with a plurality of pieces of house specification information for specifying houses, and an update unit 133 that determines that there is an error in the land taxation information when the house taxation information stored in the storage unit 12 associated with one piece of first house specification information out of the plurality of pieces of house specification information represents that a residential house is built on the land corresponding to the first house specification information and when the special provisions for residential land are not applied in the land taxation information stored in the storage unit 12 associated with the land specification information corresponding to the first house specification information.SELECTED DRAWING: Figure 4

This product is a multipurpose retaining wall made of natural stone. First, place the lower part, then hang the upper part on top and secure it with bolts. For example, you can leave it as part of your garden and block off both ends of the bottom with stones to create a pond, or use a pump to draw water from the rear pipe and let it flow through the upper and slightly lower pipes. Or, when developing a residential area and there is a road below, the lower part can be used as a waterway, or on residential land, the lower part can be used as a flower bed, or the angle can be changed depending on the soil pressure behind, or the rear part of the base can be made longer. Or, you can use the upper part as the base of a fence, or as a flower bed for a driveway. Or, when two or three are lined up, the vertical lines disappear. Because the LD and MDH parts of the front view are sticking out for reference,

The invention discloses a residential land, public management and public service land soil pollution condition survey report form compiling system, which is characterized in that an account registration module generates a unique user account based on user information and land parcel codes, so that the uniqueness and traceability of data attribution are ensured, and data confusion is avoided; the first application module and the second application module respectively provide independent and collaborative operation ports, support single-user and multi-user data entry, management and calling, and significantly improve the working efficiency; the data storage module synchronously operates data in real time through the cloud, the delay risk of paper or offline data transmission is reduced, and human intervention links are reduced through a standardized process and an automatic verification mechanism, so that the data entry error rate is reduced, and the accuracy and reliability of a soil pollution assessment result are ensured; therefore, the technical problem that the accuracy of the evaluation result is affected due to the fact that the existing method not only consumes labor cost and time cost, but also easily causes data entry errors due to human factors is solved.

The invention belongs to the technical field of urban and rural planning, and provides a spatial special planning review analysis method, which comprises the following steps: acquiring urban population and position distribution data, dividing urban unit areas, and calculating a population aggregation index and a job-to-housing ratio; based on the classified summary, a regional imbalance group is determined, and a current pendulum type traffic judgment value is calculated to judge whether pendulum type traffic occurs or not; if not, combining a population gathering trend, and using an ARIMA model to predict an imbalance value and moment; analyzing the regional imbalance group, identifying and predicting an imbalance aggravation region, judging whether an imbalance chain reaction exists or not, and calculating an adjustment priority value if the imbalance chain reaction exists; and sequentially optimizing the planning according to the priority values, adding employment posts in the first imbalance area, adding residential lands in the second imbalance area, and optimizing the planning of the traffic network. According to the method, unbalance can be accurately pre-judged, a basis is provided for planning optimization, and the resource use efficiency is improved.

The invention discloses a multi-planning-in-one urban and rural intelligent planning auxiliary method and system. The method comprises the following steps: acquiring historical data of urban and rural land planning; according to the method, the neural network model is used for training and learning, the complex relation of land attributes can be more accurately captured, and the planning accuracy is improved; the data deduplication and filling step ensures the quality and consistency of input data, avoids the problem of inaccurate model training caused by data redundancy or missing, extracts detailed attribute features of residential land, commercial land, industrial land, agricultural land and the like from historical data, facilitates more detailed land resource planning, and improves the land utilization rate. The method is advantaged in that diversified land demands are satisfied, the VGG16 network is utilized to carry out land area detection, the network has excellent performance in the image identification field, the land area in the remote sensing image can be accurately identified, a reliable basis is provided for subsequent attribute matching, corresponding land attributes are automatically endowed, and an intelligent planning decision process is realized.

The present invention provides a method and device for obtaining the spatial carbon emissions of residents, belonging to the technical field of environmental monitoring. First, obtain the POI data and night-time light remote sensing data of the target area, divide the target area into grids, determine the importance level of each land use type in each grid according to the POI data of each land use type in each grid, and then calculate the night-time pure light value of the residential land use type under each grid based on the obtained night-time light remote sensing data; determine the carbon emissions of each grid according to the total carbon emissions of residents in the target area and the proportion of the night-time pure light value of the residential land use type in each grid in the target area. Compared with the prior art, in the present invention, through the extracted night-time pure light value of the residential land use type, a more accurate spatial distribution pattern of residents' carbon emissions is obtained, the influence of night-time lights of other land use types is reduced, the accuracy of the spatial distribution result of residents' carbon emissions is improved, and a more accurate data source is provided for subsequent low-carbon research.

The invention aims to provide the residential building with the residential land, and the residential building can meet the configuration requirements of houses with different functions and meet the requirements of continuously changing operation, such as business. The residential building comprises a plurality of floors, a plurality of basic units are arranged in the floors, each basic unit comprises a plurality of composite units, each composite unit comprises a main unit (1) with independent residential property rights and an auxiliary unit (2) with independent operating property rights, the main units are independent residential house types, and the auxiliary units are independent operating house types. The main unit has a residential space, the sub-unit has an operating space, the residential space of the main unit and the operating space of the sub-unit are partitioned in the horizontal direction and / or the vertical direction by a partition structure, the main unit is provided with an entrance which is open directly facing the public area, and the sub-unit is provided with an entrance which is open directly facing the public area. The inlet of the main unit and the inlet of the auxiliary unit are mutually independent.

The application relates to an ecological green core construction project access intelligent auditing method and system, relates to the field of text examination and approval, and comprises the following steps: extracting project red line vector data and construction content from a declaration data packet; superimposing and analyzing the red line data and a preset control factor layer set to obtain a space compliance detection conclusion and construct a space compliance characteristic parameter; selecting a rule subset from a hierarchical rule library according to a partition category and a superimposed area, assigning values to a judgment threshold according to a first difference value between a scale proportion of urban and rural construction land and a control upper limit and a second difference value between a scale proportion of residential land and the control upper limit, and obtaining a parameterized rule subset; comparing the construction content according to the parameterized rule subset, and outputting a list compliance conclusion; merging the space compliance detection conclusion and the list compliance conclusion to generate an access level conclusion, and triggering a corresponding examination and approval path and a compulsory examination and approval node. By implementing the method, the deviation between a list compliance auditing conclusion and the actual situation of land index control in a region where a project is located can be reduced.

The present invention discloses an evaluation method for land use layout based on the adjacent relationship between employment and residential land. The evaluation method includes: dividing the boundaries of three types of land, namely industrial land, residential land, and mixed land, in the target area according to a map; numbering the land with defined boundaries according to land attributes; calculating the area of each piece of land respectively; calculating the lengths of the adjacent boundaries between residential land, industrial land, and mixed land respectively; traversing and calculating the layout index of each individual piece of land; and aggregating and calculating the overall layout index of each type of land based on the layout indexes obtained through traversal calculation, which indicates the degree of layout optimization required for each type of land within the commuting circle of the target area. The present invention can provide an effective evaluation of the employment and residential land layout without relying on a large amount of additional data collection, especially user data collection, and has the advantages of fast evaluation speed, high efficiency, quantifiability, and comparability.

This invention provides a fine-scale population spatialization method that integrates geospatial and internet data. The method includes: obtaining residential building footprint data within the study area; constructing geographic grid data for the study area and determining the proportion of residential building footprint area in each geographic grid unit; obtaining the number of floors in internet-connected buildings within the study area, establishing a residential building floor estimation model, and determining the initial input values ​​for the residential building floor estimation model; calculating the estimated population for each administrative region, performing error verification with the corresponding administrative region's population statistics, iterating based on the error verification results, and optimizing and adjusting the parameters of the residential building floor estimation model. This invention constructs a population spatialization model by integrating land use (residential land), surface-covered building areas, and the number of floors in internet-connected buildings, classifying the population living in urban and rural areas to estimate the floor height of residential buildings, achieving fine-scale population spatialization with high accuracy.

The invention discloses a project range delimiting method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a planned residential land area, a planned commercial land area and a planned industrial land area of a developed region; obtaining a current residential land area, a current commercial land area and a current industrial land area; generating a current feasibility coefficient according to the planned residential land area, the planned commercial land area, the first plot ratio, the second plot ratio, the third plot ratio, the first conversion coefficient, the second conversion coefficient, the planned industrial land area, the current residential land area, the current commercial land area, the current industrial land area, the third conversion coefficient and the fourth conversion coefficient; and when the current feasibility coefficient is greater than a preset feasibility coefficient, delimiting the geographical range of the developed area as the project range of the secondary development project. The method is beneficial to improving the delimiting efficiency of the project range of the secondary development area.

The application relates to the technical field of remote sensing data analysis, and discloses a residential land building component analysis method, device and system. The residential land building component analysis method disclosed by the application takes a reference map as a reference, draws lessons from the concept of pixels in an image, divides the reference map into a plurality of pixel blocks, matches remote sensing data and the reference map, calculates remote sensing parameters (similar to pixel values) of each pixel block through the remote sensing data, sets a traversal strategy of N continuous pixel blocks, analyzes the distribution of the remote sensing parameters in the N continuous pixel blocks, and determines boundary pixel blocks. Through the above method, the boundary calculation of the building component of the residential land can be realized through more reliable remote sensing data, the boundary line of the building component in the residential land is more reliable, and finally, the analysis result of the building component of the residential land is more reliable.

The application relates to the technical field of carbon emission monitoring, and particularly discloses a kind of urban residential space carbon emission monitoring methods, including first accounting carbon emissions in urban residents' energy consumption;Urban residential building type and geographical space identification;According to the grouping of residence, different groups are given differentiated carbon emission allocation weight;Introduce building features as a supplementary factor for carbon emission weight allocation;Then superimpose each factor weight, distribute the total carbon emissions of urban residents' energy consumption to each residential land;Finally, the carbon emission detection and simulation results of each residential land under the condition of considering photovoltaic emission reduction are obtained.The application adopts the above-mentioned urban residential space carbon emission monitoring method, which can monitor the carbon emission of residents at a high resolution on a city scale, and provides a scientific and feasible technical path for the precise control of urban residential space carbon emission, the development of energy-saving strategies and the excavation of photovoltaic emission reduction potential.

The invention discloses a spatial matching method and system based on natural resource monitoring and demographic data. The method comprises the following steps: obtaining residential land and house building data in regional natural resource survey and monitoring data, using spatial position and attribute matching technology, combining with a random forest algorithm to spatially match residential land and house buildings, extracting residential house building patches and their attribute information; creating an attribute feature mapping between the residential house building patch scale and the administrative division unit scale, and using a random forest hyperparameter search method to convert administrative division demographic data to residential house building patches; further integrating multi-source data in natural resource survey and monitoring data, constructing a population geographic imprint index with a water area as a mask, and correcting the number of residential house building population; finally, calculating a population distribution fitting coefficient, iteratively correcting a population allocation error, and realizing accurate spatial matching of residential house buildings and population distribution through a zoning adjustment strategy.

The present invention provides a method, device, equipment and medium for identifying recreational service blind spots, including: obtaining recreational service resource data, residential land data and road network spatial data corresponding to a target area; determining the scale level and entry and exit point data corresponding to recreational service sources in the target area according to the recreational service resource data, and identifying the blind spot range in the target area based on the road network spatial data and the scale level and entry and exit point data corresponding to the recreational service sources; determining the living circle data corresponding to the residential land in the target area according to the residential land data and the road network spatial data, so as to extract the recreational service blind spot with the residential land as the service object from the blind spot range by using the living circle data. The present invention can quantify the recreational service blind spot in the target area, improve the accuracy of identifying the recreational service blind spot, and provide a scientific basis for the objective evaluation and planning of recreational services.