8 results about "Residential land" patented technology

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 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.

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 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 present application belongs to the technical field of heavy metal contaminated soil environmental risk assessment, and particularly relates to an environmental risk assessment method for heavy metal contaminated soil remediation and building material recycling. The present application adopts simulated rainwater to leach the risk assessment system, calculates the diffusion coefficient of the remediated heavy metal in soil, and thereby constructs a one-dimensional heavy metal diffusion model. Then, according to the dilution and attenuation coefficient of the heavy metal in groundwater, the concentration level of the heavy metal in the building material released into the groundwater during the process of remediated soil recycling into building material is calculated. Finally, the potential drinking groundwater pollution risk possibly caused by the remediated soil recycling into the first type of land (residential land) is quantitatively evaluated. The present application has the advantages of simple method, clear process, short cycle, high efficiency, scientific rationality, and can accurately predict and evaluate the pollution risk of the local groundwater caused by the building material recycling of the remediated contaminated soil, which is beneficial to the protection of the groundwater environment, and the method provided by the present application has wide applicability.

The invention relates to the technical field of urban and rural construction, and discloses a method and system for identifying rural idle land potential, and the method comprises the steps: obtaining a high-resolution remote sensing image of a target area and a corresponding rural residence map layer, carrying out the contour marking of a roof in the remote sensing image according to a preset roof category system, generating a marking text with category information, and carrying out the recognition of the rural idle land potential. Converting the annotation file into a normalized coordinate format required by a target detection model, training a YOLO-SEG model, carrying out roof identification on cut image tiles, outputting contour and category results, carrying out statistics on the tile roof area proportion in each construction map spot, judging a land parcel of which the proportion exceeds a set proportion as an idle land potential land parcel, and carrying out the detection of the idle land potential land parcel. According to the invention, by integrating the remote sensing image and the GIS data and through the YOLO-SEG artificial intelligence model, the accuracy and consistency of the recognition result are significantly improved, the subjective deviation caused by the experience difference of personnel is avoided, and the recognition efficiency of the rural idle land potential is improved.

The invention discloses a human activity net phosphorus input measuring and calculating method based on land utilization, and relates to the technical field of regional phosphorus income and expenditure evaluation.The method comprises the steps that land utilization type data of a research area is obtained, and agricultural land and construction land are distinguished; key calculation parameters of the human activity net phosphorus input amount of the research area are collected; constructing a human activity net phosphorus input amount accounting model of a land utilization unit scale, and respectively estimating net phosphorus input amounts of the agricultural land and the construction land; summarizing the total input amount of terrestrial human activity net phosphorus according to the drainage basin or the research area based on the land utilization ratio of the agricultural land and the construction land; classification accounting is carried out according to the agricultural land and the residential land, required calculation parameters are few, the data acquisition difficulty is remarkably reduced, and the calculation simplicity and universality are improved; and meanwhile, the spatial distribution information of the net phosphorus input quantity can be directly output, and a more intuitive and reliable technical support is provided for basin phosphorus load refined evaluation and water environment management.