Land space planning stock land management and control early warning system based on multi-dimensional analysis

Abstract

The invention discloses a territorial space planning stock land management and control early warning system based on multi-dimensional analysis, and relates to the related field of territorial space management, and the system comprises a data association module which is used for collecting territorial space planning constraint data and regional multi-dimensional land data of a target region, and carrying out the spatial association superposition, and forming a stock land database; the partition development module is used for carrying out stock unit identification and regional aggregation analysis to obtain a partition development stock land; the multi-dimensional constraint analysis module is used for constructing a multi-dimensional constraint system, performing multi-dimensional constraint analysis on the partition development stock land, and determining a partition stock land volume threshold value; and the land use management and control early warning module is used for monitoring and obtaining stock land use development planning volume data according to a partition stock land use volume threshold value, and performing land use management and control early warning based on a grading early warning mechanism. The technical problem that existing stock land management and control early warning is insufficient in accuracy and timeliness is solved, and the technical effect of improving the stock land management and control early warning accuracy and timeliness is achieved.

Description

Technical Field

[0001] This application relates to the field of territorial space management, and particularly to a control and warning system for stock land use in territorial space planning based on multi-dimensional analysis. Background Art

[0002] In the field of territorial space planning, the reasonable control and warning of stock land use are of crucial significance for realizing the optimal allocation of land resources and promoting the sustainable development of cities. At present, the main methods to solve the problem of stock land use control and warning rely on traditional land use surveys and planning approval processes, combined with manual experience for judgment and decision-making. However, due to the reliance on manual operations, the traditional methods have low data processing and analysis efficiency, and it is difficult to comprehensively and timely grasp the multi-dimensional information of stock land use. As a result, when facing the complex and changing urban development needs, it is impossible to accurately identify the development potential and constraint conditions of stock land use, and thus it is difficult to formulate scientific and reasonable control strategies.

[0003] In the related technologies at the present stage, there are technical problems of insufficient accuracy and timeliness in the control and warning of stock land use in territorial space planning. Summary of the Invention

[0004] This application provides a control and warning system for stock land use in territorial space planning based on multi-dimensional analysis. By collecting the territorial space planning constraint data and regional multi-dimensional land use data of the target area and associating and overlaying them to form a stock land use database, identifying stock units and aggregating and analyzing regions based on this database to obtain the stock land use for sub-region development, constructing a multi-dimensional constraint system based on the territorial space planning constraint data, analyzing the stock land use for sub-region development to determine the volume threshold of stock land use for each sub-region, establishing a hierarchical warning mechanism according to the volume threshold, monitoring the planned volume data of stock land use development and carrying out control and warning of land use, etc., this application solves the technical problems of insufficient accuracy and timeliness existing in the control and warning of stock land use in the existing territorial space planning, and achieves the technical effect of improving the accuracy and timeliness of the control and warning of stock land use.

[0005] This application provides a control and warning system for stock land use in territorial space planning based on multi-dimensional analysis, including: A data association module, which is used to collect the national land space planning constraint data and regional multi-dimensional land use data of the target area, spatially associate and overlay the national land space planning constraint data and the regional multi-dimensional land use data to form a stock land database; a zoning development module, which is used to identify stock units and conduct regional aggregation analysis on the target area based on the stock land database to obtain the stock land for zoned development; a multi-dimensional constraint analysis module, which is used to construct a multi-dimensional constraint system according to the national land space planning constraint data, and conduct multi-dimensional constraint analysis on the stock land for zoned development according to the multi-dimensional constraint system to determine the volume threshold of the stock land for each zone; a land use control warning module, which is used to establish a hierarchical warning mechanism according to the volume threshold of the stock land for each zone, monitor and obtain the planned volume data of the stock land development, and conduct land use control warning on the planned volume data of the stock land development based on the hierarchical warning mechanism.

[0006] In a possible implementation manner, the data association module includes: a data preprocessing unit, which is used to identify abnormal data and perform data cleaning processing on the national land space planning constraint data and the regional multi-dimensional land use data to obtain available national land space planning constraint data and available regional multi-dimensional land use data; a standardization processing unit, which is used to perform format conversion and normalization processing on the available national land space planning constraint data and the available regional multi-dimensional land use data according to the data application standard to obtain standard national land space planning constraint data and standard regional multi-dimensional land use data; a spatial registration and alignment unit, which is used to spatially register and align the standard national land space planning constraint data and the standard regional multi-dimensional land use data to obtain registered national land space planning constraint data and registered regional multi-dimensional land use data; a spatial association and overlay unit, which is used to spatially associate and overlay the registered national land space planning constraint data and the registered regional multi-dimensional land use data to obtain a stock land database.

[0007] In a possible implementation manner, the spatial association and overlay unit includes: a spatial association rule determination subunit, which is used to determine spatial association rules according to the characteristics of land use data and analysis requirements; a spatial overlay subunit, which is used to spatially associate and overlay the registered national land space planning constraint data and the registered regional multi-dimensional land use data based on the spatial association rules to obtain land use spatial overlay data; a land use attribute label library construction subunit, which is used to construct a land use attribute label library according to the associated attributes of the stock land; a plot attribute marking subunit, which is used to mark the plot attributes of the land use spatial overlay data with the land use attribute label library and store the data in the database to obtain the stock land database.

[0008] In a possible implementation manner, the partition development module includes: a unit grid granularity setting unit, configured to set the unit grid granularity according to the scale information, complexity, and analysis requirements of the target area; a land use area division unit, configured to divide the target area into land use areas according to the unit grid granularity to obtain a set of stock land use areas; a development potential evaluation unit, configured to evaluate the development potential of the set of stock land use areas and identify stock units to obtain a set of developed stock land use units; and a regional aggregation analysis unit, configured to perform regional aggregation analysis on the set of developed stock land use units based on regional aggregation rules to determine the partitioned developed stock land.

[0009] In a possible implementation manner, the land use area division unit includes: a regional pre-segmentation subunit, configured to perform regional pre-segmentation on the target area according to the unit grid granularity to obtain a set of regional grid units; a label identification subunit, configured to perform label identification on the target area based on the stock land use database to obtain a set of regional stock land use attributes; a land use unit division line construction subunit, configured to construct land use unit division lines according to the set of regional stock land use attributes; and a regional division subunit, configured to perform land use area division on the set of regional grid units based on the land use unit division lines to obtain the set of stock land use areas.

[0010] In a possible implementation manner, the development potential evaluation unit includes: a development index extraction subunit, configured to extract development indexes from the stock land use database to establish a development index evaluation system; a weight assignment subunit, configured to assign weights to each development index in the development index evaluation system according to the development requirements of stock land use to determine development index weight factors; a development scoring subunit, configured to evaluate the development potential of the set of stock land use areas by using the development index evaluation system and the development index weight factors to obtain a set of development scores for the stock land use areas; and a stock unit identification subunit, configured to preset a development score threshold, and identify stock units according to the development score threshold for the set of development scores for the stock land use areas and the set of stock land use areas to obtain the set of developed stock land use units.

[0011] In a possible implementation manner, the regional aggregation analysis unit includes: a rule determination subunit, configured to determine a spatial continuity rule and a functional similarity rule according to the regional aggregation rules; a threshold presetting subunit, configured to preset a land use spatial distance threshold and a functional similarity threshold based on the spatial continuity rule and the functional similarity rule; and an aggregation analysis subunit, configured to perform regional aggregation analysis on the set of developed stock land use units according to the land use spatial distance threshold and the functional similarity threshold to determine the partitioned developed stock land.

[0012] In a possible implementation, the multi-dimensional constraint analysis module includes: a multi-dimensional constraint quantification index determination unit for determining a multi-dimensional constraint quantification index set according to the multi-dimensional constraint system; a constraint analysis unit for performing multi-dimensional constraint analysis on the partitioned developed stock land based on the multi-dimensional constraint quantification index set to obtain the index constraint value of the partitioned stock land; and a planned volume analysis unit for performing planned volume analysis on the partitioned developed stock land based on the index constraint value of the partitioned stock land to determine the volume threshold of the partitioned stock land.

[0013] In a possible implementation, the planned volume analysis unit includes: a regression analysis subunit for collecting the case data of the stock land in the territorial spatial plan, taking the index constraint value of the stock land as the independent variable and the plot ratio as the dependent variable, performing regression analysis on the case data of the stock land in the territorial spatial plan, and constructing a volume constraint regression model; and a volume threshold determination subunit for using the volume constraint regression model to perform planned volume analysis on the partitioned developed stock land based on the index constraint value of the partitioned stock land to determine the volume threshold of the partitioned stock land.

[0014] In a possible implementation, the land use control and early warning module includes: a comparison and trigger unit for comparing and triggering the planned volume data of the stock land development based on the hierarchical early warning mechanism to determine the early warning level of the target stock land; and a hierarchical early warning unit for performing hierarchical early warning and tracking control on the partitioned developed stock land through the early warning level of the target stock land.

[0015] It is intended to propose a territorial spatial plan stock land control and early warning system based on multi-dimensional analysis through this application. The territorial spatial plan constraint data and regional multi-dimensional land use data of the target area are collected through the data association module, and the territorial spatial plan constraint data and regional multi-dimensional land use data are spatially associated and superimposed to form a stock land database. The target area is subjected to stock unit identification and regional aggregation analysis through the partitioned development module based on the stock land database to obtain the partitioned developed stock land. The multi-dimensional constraint system is constructed according to the territorial spatial plan constraint data through the multi-dimensional constraint analysis module, and multi-dimensional constraint analysis is performed on the partitioned developed stock land according to the multi-dimensional constraint system to determine the volume threshold of the partitioned stock land. The hierarchical early warning mechanism is established through the land use control and early warning module according to the volume threshold of the partitioned stock land, the planned volume data of the stock land development is monitored and obtained, and land use control and early warning are performed on the planned volume data of the stock land development based on the hierarchical early warning mechanism. The technical effect of improving the accuracy and timeliness of the stock land control and early warning is achieved. Description of the Drawings

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly introduced below. Structure diagrams are used in this application to illustrate the operations performed by the systems according to the embodiments of this application. It should be understood that the operations described above or below do not necessarily need to be precisely executed in sequence. On the contrary, as needed, various steps can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several steps can be removed from these processes.

[0017] Figure 1 It is a schematic structural diagram of the inventory land use control and warning system for territorial space planning based on multi-dimensional analysis provided by the embodiments of this application.

[0018] Figure 2 It is a schematic structural diagram of the sub-region development module in the inventory land use control and warning system for territorial space planning based on multi-dimensional analysis provided by the embodiments of this application.

[0019] Explanation of reference numerals: data association module 10, sub-region development module 20, multi-dimensional constraint analysis module 30, land use control and warning module 40. Detailed implementation manners

[0020] The above description is only an overview of the technical solutions of this application. In order to be able to more clearly understand the technical means of this application, it can be implemented in accordance with the content of the description. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically gives the detailed implementation manners of this application.

[0021] In order to make the purpose, technical solutions and advantages of this application more clear, the following will further describe this application in detail in conjunction with the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

[0022] In the following descriptions, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application.

[0023] The embodiment of the present application provides a stock land use control warning system for territorial spatial planning based on multi-dimensional analysis, as Figure 1 shown. The system includes: A data association module 10, configured to collect territorial spatial planning constraint data and regional multi-dimensional land use data of a target area, perform spatial association and superposition on the territorial spatial planning constraint data and the regional multi-dimensional land use data, and form a stock land use database.

[0024] Specifically, the territorial spatial planning constraint data refers to the constraint conditions and requirements set for aspects such as land use, ecological protection, and urban construction in territorial spatial planning. The regional multi-dimensional land use data refers to land data containing multi-dimensional information such as the current land use situation, topography, transportation network, and population distribution. The stock land use database refers to a database formed through spatial association and superposition and containing information related to stock land use.

[0025] Obtain territorial spatial planning constraint data through a government affairs data sharing platform, including data such as land use control, ecological protection red line, and permanent basic farmland protection red line. Use satellite remote sensing technology to obtain regional multi-dimensional land use data. Store the collected data in a relational database (such as PostGIS) to ensure the structuring and queryability of the data. Use GIS software (such as ArcGIS or QGIS) to perform spatial association and superposition operations. For example, associate the current land use situation data with the land use control data through spatial overlay analysis (Spatial Join) to form a stock land use database. Regularly update the data to ensure the timeliness of the stock land use database.

[0026] In a possible implementation manner, the data association module 10 includes: a data preprocessing unit, configured to identify abnormal data and perform data cleaning processing on the territorial spatial planning constraint data and the regional multi-dimensional land use data to obtain available territorial spatial planning constraint data and available regional multi-dimensional land use data; a standardization processing unit, configured to perform format conversion and normalization processing on the available territorial spatial planning constraint data and the available regional multi-dimensional land use data according to data application standards to obtain standard territorial spatial planning constraint data and standard regional multi-dimensional land use data; a spatial registration and alignment unit, configured to perform spatial registration and alignment on the standard territorial spatial planning constraint data and the standard regional multi-dimensional land use data to obtain registered territorial spatial planning constraint data and registered regional multi-dimensional land use data; a spatial association and superposition unit, configured to perform spatial association and superposition on the registered territorial spatial planning constraint data and the registered regional multi-dimensional land use data to obtain a stock land use database.

[0027] Specifically, statistical analysis methods (such as Z-score, IQR) are used to identify abnormal data. For example, calculate the mean and standard deviation of each data field. For each data point, calculate its Z-score (standardized score). If the absolute value of the Z-score is greater than 3, then this data point is considered abnormal data. An example of abnormal data identification is shown in Table 1.

[0028] Table 1: Example of Abnormal Data Identification

[0029] Use data cleaning tools (such as the Pandas library) to clean the data, delete or correct abnormal data, and fill in missing values (such as filling with the mean or median). An example of data cleaning processing is shown in Table 2.

[0030] Table 2: Example of Data Cleaning Processing Data field Original data Data after cleaning Land area 2000 1000 Floor area Empty 500 Use GIS software (such as ArcGIS) to convert data formats, and uniformly convert different formats of data (such as CSV, Shapefile) into a format supported by GIS (such as GeoJSON). Use the Python programming language for data normalization processing. For example, use the formula: Normalized value = (data value - minimum value) / (maximum value - minimum value) to perform normalization processing on each data field so that its value range is between 0 and 1. An example of normalization processing is shown in Table 3.

[0031] Table 3: Example of Normalization Processing

[0032] Use GIS software (such as QGIS) for spatial registration and alignment. Select a reference dataset (such as high-precision current land use data), and perform spatial registration on other datasets to make their coordinate systems and resolutions consistent with those of the reference dataset. An example of spatial registration and alignment is shown in Table 4.

[0033] Table 4: Example of Spatial Registration and Alignment Dataset type Original coordinate system Coordinate system after registration Current land use situation WGS84 WGS84 Land use control UTM WGS84 Use GIS software (such as ArcGIS) for spatial association overlay. Use spatial overlay analysis tools (such as Union, Intersect) to perform association overlay on the registered data, generate a database of stock land use, and store the associated data. This implementation method ensures the accuracy and integrity of the data through abnormal data identification and data cleaning. Through format conversion and normalization processing, the data format and range are unified, improving the comparability and usability of the data. Through spatial registration alignment, the alignment and consistency of different data sets in space are ensured. Through spatial association overlay, a complete database of stock land use is formed, providing data support for subsequent stock land use control and early warning.

[0034] In a possible implementation, the spatial association overlay unit includes: a spatial association rule determination subunit, configured to determine spatial association rules according to the characteristics of land use data and analysis requirements; a spatial overlay subunit, configured to perform spatial association overlay on the registered national land space planning constraint data and the registered regional multi-dimensional land use data based on the spatial association rules to obtain land use spatial overlay data; a land use attribute tag library construction subunit, configured to construct a land use attribute tag library according to the associated attributes of stock land use; and a plot attribute marking subunit, configured to use the land use attribute tag library to perform plot attribute marking and data storage in the database on the land use spatial overlay data to obtain the database of stock land use.

[0035] Specifically, according to the characteristics of land use data and analysis requirements, determine spatial association rules through expert consultation and data analysis, such as inclusion, intersection, proximity, etc. based on spatial location. Use spatial overlay tools (such as Union, Intersect) to perform association overlay on the registered data to generate land use spatial overlay data and store the associated results. Define the associated attribute tags of stock land use, such as use type, development intensity, ecological value, etc. Use a database management system (such as PostgreSQL) to store the tags in the database to construct a land use attribute tag library for subsequent query and marking. Use GIS software to perform attribute marking on the land use spatial overlay data. Use a database management system to store the marked data in the database to form a database of stock land use. This implementation method ensures the precise association between different data sets through determining spatial association rules, improving the accuracy and reliability of the data. Constructing a land use attribute tag library provides rich attribute information for the classification and management of stock land use, facilitating subsequent analysis and decision-making. Through plot attribute marking and data storage in the database, a structured database of stock land use is formed, improving the query and management efficiency of the data.

[0036] The sub-area development module 20 is configured to perform stock unit identification and regional aggregation analysis on the target area based on the database of stock land use to obtain the stock land use for sub-area development.

[0037] Specifically, the stock unit refers to a land use unit that already exists and has development potential in the territorial spatial planning. These units include idle land, inefficiently utilized land, areas to be updated, etc. They need to be identified and integrated in the planning for effective development and utilization. Through data mining and spatial analysis techniques, identify stock land use units with development potential. Specifically, extract relevant data of the target area from the stock land use database, including information such as the current land use status, land use control, and development intensity. Define the identification rules for stock units according to the planning requirements and policy requirements. For example, the identification rules can include conditions such as low land use efficiency and idle time exceeding a certain number of years. Use GIS software and programming tools (such as Python) for data screening and analysis to identify eligible stock units. Use spatial analysis tools to aggregate the identified stock units into regions to form zoned developed stock land. Specifically, according to the geographical location and planning requirements, merge adjacent stock units into larger development areas, and integrate the attributes of the aggregated areas to calculate information such as the total development potential and area.

[0038] As Figure 2 shown, in a possible implementation manner, the zoned development module 20 includes: a unit grid granularity setting unit for setting the unit grid granularity according to the scale information, complexity, and analysis requirements of the target area; a land use area division unit for dividing the target area into land use areas according to the unit grid granularity to obtain a set of stock land use areas; a development potential evaluation unit for evaluating the development potential of the set of stock land use areas and identifying stock units to obtain a set of developed stock land units; and a regional aggregation analysis unit for performing regional aggregation analysis on the set of developed stock land units based on regional aggregation rules to determine zoned developed stock land.

[0039] Specifically, according to the scale information, complexity, and analysis requirements of the target area, use GIS software and programming tools (such as Python) to set the unit grid granularity, that is, the grid size, for dividing land use areas. Specifically, extract the scale information and complexity data of the target area from the stock land use database. Determine the appropriate unit grid granularity according to the area and complexity of the target area. For example, for the urban central area, a smaller grid granularity (such as 100m×100m) can be set, and for the suburban or rural area, a larger grid granularity (such as 500m×500m) can be set.

[0040] Use GIS tools to generate a grid covering the target area, divide the target area into multiple unit grids according to the set unit grid granularity, and each grid serves as an independent land use area. The set of multiple land use areas obtained through unit grid division is the set of stock land use areas.

[0041] Use GIS software and data analysis tools (such as Python) to evaluate the development potential of the stock land area set and identify stock units. For example, extract data such as the current land use status, development intensity, and idle time of each unit grid from the stock land database. Calculate the development potential of each unit grid according to the preset development potential evaluation model. For example, the development potential evaluation model can include factors such as land use efficiency, idle time, and traffic convenience. Identify the stock units with development potential based on the evaluation results.

[0042] Use GIS software and programming tools (such as Python) to perform regional aggregation analysis on the set of developed stock land units. Specifically, according to the planning requirements and policy requirements, define the regional aggregation rules, that is, the rules for merging adjacent stock units into one development area. For example, adjacent stock units can be merged into one development area. Use GIS tools to aggregate the eligible stock units to form partitioned developed stock land. Integrate the attributes of the aggregated area and calculate information such as the total development potential and area. This implementation method can accurately divide the target area by setting an appropriate unit grid granularity, ensuring the rationality and representativeness of each unit grid. Scientifically evaluate the development potential of each unit grid through the development potential evaluation model and identify the stock units with development potential. Through regional aggregation analysis, rationally integrate the scattered stock units to form a development area with scale effect, which is convenient for centralized management and development. The whole process is based on data mining and spatial analysis technologies, ensuring the objectivity of planning decisions and data support.

[0043] In a possible implementation manner, the land area division unit includes: a regional pre-segmentation subunit, configured to perform regional pre-segmentation on the target area according to the unit grid granularity to obtain a set of regional grid units; a label identification subunit, configured to perform label identification on the target area based on the stock land database to obtain a set of regional stock land attributes; a land unit dividing line construction subunit, configured to construct a land unit dividing line according to the set of regional stock land attributes; and a regional division subunit, configured to perform land area division on the set of regional grid units based on the land unit dividing line to obtain the set of stock land areas.

[0044] Specifically, use GIS software (such as ArcGIS or QGIS) to generate grids covering the target area according to the unit grid granularity, divide the target area into multiple unit grids, and each grid serves as an independent regional grid unit. An example of regional pre-segmentation is shown in Table 5.

[0045] Table 5: Example of Regional Pre-segmentation

[0046] Extract attribute data such as the current land use status, development intensity, and idle time of the target area from the stock land database. According to the preset labeling rules, label each regional grid cell to generate a set of attributes for the regional stock land. An example of the labeling is shown in Table 6.

[0047] Table 6: Example of Labeling

[0048] According to the planning requirements and policy requirements, define the land use unit segmentation rules. For example, the position of the segmentation line can be determined based on the current land use status and development intensity. Use GIS software and programming tools (such as Python) to generate the land use unit segmentation line to separate the regional grid cells with different attributes. According to the land use unit segmentation line, divide the set of regional grid cells into multiple stock land areas. Integrate the attributes of the divided stock land areas and calculate information such as the total area and development potential of each area. This implementation method scientifically constructs the segmentation line based on attributes such as the current land use status and development intensity, efficiently divides the set of regional grid cells, and forms a set of stock land areas with clear attributes, which is convenient for subsequent development potential evaluation and regional aggregation analysis.

[0049] In a possible implementation, the development potential evaluation unit includes: a development index extraction subunit for extracting development indexes from the stock land database and building a development index evaluation system; a weight assignment subunit for assigning weights to each development index in the development index evaluation system according to the development requirements of the stock land to determine the development index weight factors; a development scoring subunit for evaluating the development potential of the set of stock land areas using the development index evaluation system and the development index weight factors to obtain a set of development scores for the stock land areas; and a stock unit identification subunit for presetting a development score threshold and identifying stock units from the set of development scores for the stock land areas and the set of stock land areas according to the development score threshold to obtain the set of developed stock land units.

[0050] Specifically, extract data such as the current land use status, development intensity, idle time, and traffic convenience from the stock land database. According to the planning requirements and policy requirements, select appropriate development indexes, such as land use efficiency, idle time, traffic convenience, etc., to construct an index system for evaluating the development potential of the stock land areas. An example of the development index evaluation system is shown in Table 7.

[0051] Table 7: Example of Development Index Evaluation System Indicator name Indicator description Land use efficiency Actual land use degree Idle time Number of years of land idleness Traffic convenience Distance between land and main traffic network Infrastructure improvement degree Infrastructure construction situation around the land According to the development requirements of stock land, invite planning experts and experts in related fields to evaluate the importance of each development index. According to the expert opinions, assign weight factors to each development index. An example of weight assignment is shown in Table 8.

[0052] Table 8: Example of Weight Assignment Indicator name Weight factor Land use efficiency 0.3 Idle time 0.2 Traffic convenience 0.25 Infrastructure improvement degree 0.25 Extract the relevant data of each stock land area from the stock land database. According to the development index evaluation system and weight factors, calculate the development potential score of each stock land area. According to the planning requirements and policy requirements, preset the development score threshold. For example, an area with a development potential score greater than 60 is considered a stock unit with development potential. According to the development score threshold, identify the stock units with development potential. This implementation method provides a comprehensive index basis for the development potential evaluation by constructing a development index evaluation system. By reasonably assigning weight factors, the scientificity and rationality of the evaluation results are ensured. By accurately evaluating the development potential of each stock land area and according to the preset development score threshold, the stock units with development potential are effectively identified, providing a clear goal for zonal development.

[0053] In a possible implementation, the area aggregation analysis unit includes: a rule determination subunit, configured to determine the spatial continuity rule and the functional similarity rule according to the area aggregation rule; a threshold presetting subunit, configured to preset the land use spatial distance threshold and the functional similarity threshold based on the spatial continuity rule and the functional similarity rule; and an aggregation analysis subunit, configured to perform area aggregation analysis on the set of developed stock land units according to the land use spatial distance threshold and the functional similarity threshold to determine the zonal developed stock land.

[0054] Specifically, according to the planning requirements and policy requirements, invite planning experts and experts in related fields to evaluate the spatial continuity and functional similarity. According to the expert opinions, define the spatial continuity rule and the functional similarity rule. For example, the spatial continuity rule can be based on the spatial distance between land use units, and the functional similarity rule can be based on the functional attributes of land use units. According to the planning requirements and expert opinions, preset the land use spatial distance threshold and the functional similarity threshold. For example, the spatial distance threshold can be set to 500 meters, and the functional similarity threshold can be set to 0.8.

[0055] Use GIS software and programming tools (such as Python) to extract the spatial location and functional attributes of each land use unit from the stock land use unit set. Calculate the spatial distance between each land use unit and calculate the functional similarity between each land use unit. According to the spatial distance threshold and the functional similarity threshold, aggregate the eligible land use units to form the partitioned stock land for development. This implementation method ensures the scientificity and rationality of the aggregation analysis and realizes efficient aggregation analysis by defining spatial continuity rules and functional similarity rules, as well as presetting the spatial distance threshold and functional similarity threshold for land use.

[0056] The multi-dimensional constraint analysis module 30 is used to construct a multi-dimensional constraint system according to the national territorial space planning constraint data, and conduct multi-dimensional constraint analysis on the partitioned stock land for development according to the multi-dimensional constraint system to determine the volume threshold of the partitioned stock land.

[0057] Specifically, according to the national territorial space planning constraint data, define multi-dimensional constraint indicators, such as building density, green space rate, etc. The multi-dimensional constraint system refers to a comprehensive constraint system that includes multiple constraint indicators such as building density and green space rate. Use a mathematical model (such as a linear programming model) to construct the multi-dimensional constraint system. For example, the floor area ratio constraint model can be expressed as: floor area ratio = total building area / land area ≤ upper limit of floor area ratio, where the total building area is the total building area of the planned building, the land area is the area of the partitioned stock land for development, and the upper limit of floor area ratio is the upper limit value set according to the planning requirements.

[0058] Process the data of the partitioned stock land for development, and extract relevant index data. Use GIS software and programming languages (such as Python) to conduct multi-dimensional constraint analysis to determine the volume threshold of the partitioned stock land, that is, the maximum floor area ratio value of the partitioned stock land.

[0059] In a possible implementation manner, the multi-dimensional constraint analysis module 30 includes: a multi-dimensional constraint quantification index determination unit, which is used to determine a multi-dimensional constraint quantification index set according to the multi-dimensional constraint system; a constraint analysis unit, which is used to conduct multi-dimensional constraint analysis on the partitioned stock land for development based on the multi-dimensional constraint quantification index set to obtain the index constraint value of the partitioned stock land; and a planned volume analysis unit, which is used to conduct planned volume analysis on the partitioned stock land for development based on the index constraint value of the partitioned stock land to determine the volume threshold of the partitioned stock land.

[0060] Specifically, invite planning experts and experts in related fields to evaluate the multi-dimensional constraint system. According to the expert opinions and planning requirements, select appropriate quantification indicators, such as building density, green space rate, traffic carrying capacity, etc. An example of the determined multi-dimensional constraint quantification index set is shown in Table 9.

[0061] Table 9: Example of multi-dimensional constraint quantification index set

[0062] Extract the relevant data of the developed stock land in each district from the stock land database. According to the multi-dimensional constraint quantification index set, calculate the index constraint value of the developed stock land in each district. For example, normalize the value of each index to between 0 and 1 for comprehensive evaluation. The normalization formula is: Normalized value = (Index value - Minimum value) / (Maximum value - Minimum value). Assign weight factors to each index according to expert opinions and planning requirements. Calculate the comprehensive constraint value of the developed stock land in each district according to the normalized value and the weight factor. The formula is: Index constraint value of the stock land in the district = ∑(Normalized value × Weight factor).

[0063] Based on the index constraint value of the stock land in the district, establish a volume threshold model. For example, a linear regression model or a machine learning model can be used to predict the volume threshold. Determine the volume threshold of the stock land in each district according to the model results. This implementation method provides a comprehensive index basis for multi-dimensional constraint analysis by constructing a multi-dimensional constraint quantification index set. By calculating the index constraint value of the developed stock land in each district, it provides data support for the planned volume analysis.

[0064] In a possible implementation, the planned volume analysis unit includes: a regression analysis subunit, which is used to collect the case data of the stock land in the territorial spatial plan, use the index constraint value of the stock land as the independent variable, and the plot ratio as the dependent variable, and perform regression analysis on the case data of the stock land in the territorial spatial plan to construct a volume constraint regression model; a volume threshold determination subunit, which is used to use the volume constraint regression model to perform planned volume analysis on the developed stock land in the district based on the index constraint value of the stock land in the district, and determine the volume threshold of the stock land in the district.

[0065] Specifically, collect the case data of the stock land in the territorial spatial plan from channels such as the historical project database, government public data, and on-site investigations, including the data of the index constraint value of the stock land and the actual plot ratio. Clean the data, remove outliers and missing values to ensure data quality. Use statistical analysis software (such as R, scikit-learn library in Python) to perform regression analysis, select a regression model, such as linear regression, polynomial regression, etc., use the collected case data to train the regression model, and verify the accuracy and reliability of the model through methods such as cross-validation.

[0066] Extract the index constraint values for the development of stock land in each sub - district from the stock land database, and use a regression model to calculate the volume threshold for the development of stock land in each sub - district. This implementation method constructs a scientific and reasonable volume constraint regression model by collecting and analyzing historical case data, and accurately calculates the volume threshold for the development of stock land in each sub - district using the regression model, ensuring the scientificity and rationality of the plan.

[0067] The land use control warning module 40 is used to establish a hierarchical warning mechanism according to the volume threshold of the stock land in the sub - district, monitor and obtain the volume data of the stock land development plan, and conduct land use control warning on the volume data of the stock land development plan based on the hierarchical warning mechanism.

[0068] Specifically, according to the volume threshold of the stock land in the sub - district, the warning levels are divided into three levels: low, medium, and high. For example, when the floor area ratio exceeds 10% of the threshold, it is a low - level warning; when it exceeds 20%, it is a medium - level warning; when it exceeds 30%, it is a high - level warning. Specific warning rules are formulated, such as sending warning messages via text messages, emails, etc. The volume data of the stock land development plan is obtained through a real - time monitoring system, and a warning trigger mechanism is implemented using a programming language (such as Java) to monitor and warn the volume data of the stock land development plan.

[0069] In a possible implementation, the land use control warning module 40 includes: a comparison trigger unit for comparing and triggering the volume data of the stock land development plan based on the hierarchical warning mechanism to determine the warning level of the target stock land; a hierarchical warning unit for conducting hierarchical warning and tracking control on the development of the stock land in the sub - district through the warning level of the target stock land.

[0070] Specifically, extract the volume data of the stock land development plan and the volume threshold for the development of stock land in each sub - district from the stock land database. Compare the volume data of the development plan with the volume threshold to determine whether to trigger a warning. Determine the warning level of the target stock land according to the comparison result of the volume data of the development plan and the volume threshold. Conduct tracking control on the development of the stock land in the sub - district where a warning is triggered to ensure that its development activities meet the planning requirements. This implementation method can accurately determine whether the target stock land triggers a warning through comparison and triggering, ensuring the timeliness and accuracy of the warning. The warning levels are divided according to the degree to which the volume data exceeds the threshold, providing clear handling strategies for warnings of different levels. Conducting tracking control on the development of the stock land in the sub - district where a warning is triggered to ensure that its development activities meet the planning requirements improves the scientificity and rationality of the plan implementation.

[0071] In the embodiments of the present application, by collecting the territorial space planning constraint data and regional multi-dimensional land use data of the target area and associating and overlaying them to form a database of stock land, identifying stock units and aggregating and analyzing the area based on this database to obtain the stock land for sub-region development, constructing a multi-dimensional constraint system according to the territorial space planning constraint data, analyzing the stock land for sub-region development to determine the volume threshold of the stock land in the sub-region, establishing a hierarchical early warning mechanism according to the volume threshold, monitoring the planned volume data of the stock land development and carrying out early warning for land use control and other technical means, the technical problems of insufficient accuracy and timeliness existing in the existing territorial space planning stock land control and early warning are solved, and the technical effect of improving the accuracy and timeliness of the stock land control and early warning is achieved.

[0072] Although various references are made to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The various units and modules included are only divided according to the functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.

[0073] The above specific embodiments do not constitute a limitation to the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to the design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be executed in a different order from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In certain embodiments, multi-tasking and parallel processing are also possible or may be advantageous.

Claims

1. The stock land use control and early warning system for territorial spatial planning based on multi-dimensional analysis is characterized in that, The system includes: A data association module, configured to collect the land use planning constraint data and regional multi-dimensional land use data of the target area, perform spatial association and overlay on the land use planning constraint data and the regional multi-dimensional land use data, and form a stock land database; A sub-area development module, configured to perform stock unit identification and regional aggregation analysis on the target area based on the stock land database to obtain the stock land for sub-area development; A multi-dimensional constraint analysis module, configured to construct a multi-dimensional constraint system according to the land use planning constraint data, perform multi-dimensional constraint analysis on the stock land for sub-area development according to the multi-dimensional constraint system, and determine the volume threshold of the stock land for sub-areas; A land use control warning module, configured to establish a hierarchical warning mechanism according to the volume threshold of the stock land for sub-areas, monitor and obtain the volume data of the stock land development plan, and perform land use control warning on the volume data of the stock land development plan based on the hierarchical warning mechanism.

2. The early warning system for the control of stock land use in territorial spatial planning based on multi-dimensional analysis according to claim 1, wherein The data association module includes: A data preprocessing unit, configured to identify abnormal data and perform data cleaning on the land use planning constraint data and the regional multi-dimensional land use data to obtain available land use planning constraint data and available regional multi-dimensional land use data; A standardization processing unit, configured to perform format conversion and normalization on the available land use planning constraint data and the available regional multi-dimensional land use data according to the data application standard to obtain standard land use planning constraint data and standard regional multi-dimensional land use data; A spatial registration and alignment unit, configured to perform spatial registration and alignment on the standard land use planning constraint data and the standard regional multi-dimensional land use data to obtain registered land use planning constraint data and registered regional multi-dimensional land use data; A spatial association and overlay unit, configured to perform spatial association and overlay on the registered land use planning constraint data and the registered regional multi-dimensional land use data to obtain a stock land database.

3. The stock land use control and warning system for territorial spatial planning based on multi-dimensional analysis according to claim 2, characterized in that The spatial association and overlay unit includes: A spatial association rule determination subunit, configured to determine spatial association rules according to the characteristics of the land use data and the analysis requirements; A spatial overlay subunit, configured to perform spatial association and overlay on the registered land use planning constraint data and the registered regional multi-dimensional land use data based on the spatial association rules to obtain land use spatial overlay data; A land use attribute label library construction subunit, configured to construct a land use attribute label library according to the associated attributes of the stock land; A plot attribute marking subunit, configured to perform plot attribute marking and data storage in the database on the land use spatial overlay data by using the land use attribute label library to obtain the stock land database.

4. The early warning system for the control of stock land in territorial space planning based on multi-dimensional analysis according to claim 1, wherein, The sub-area development module includes: A unit grid granularity setting unit, configured to set the unit grid granularity according to the scale information, complexity and analysis requirements of the target area; A land use area division unit, configured to divide the target area according to the unit grid granularity to obtain a set of stock land use areas; A development potential evaluation unit, configured to perform development potential evaluation and stock unit identification on the set of stock land use areas to obtain a set of stock land development units; The regional aggregation analysis unit is used to perform regional aggregation analysis on the set of developed stock land use units based on regional aggregation rules to determine the zoned developed stock land.

5. The early warning system for the control of stock land in territorial spatial planning based on multi-dimensional analysis according to claim 4, characterized in that, The land use area division unit includes: The regional pre-segmentation subunit is used to perform regional pre-segmentation on the target area according to the unit grid granularity to obtain a set of regional grid units; The label identification subunit is used to perform label identification on the target area based on the stock land database to obtain a set of regional stock land use attributes; The land use unit dividing line construction subunit is used to construct a land use unit dividing line according to the set of regional stock land use attributes; The area division subunit is used to perform land use area division on the set of regional grid units based on the land use unit dividing line to obtain the set of stock land use areas.

6. The early warning system for the control of stock land use in territorial space planning based on multi-dimensional analysis according to claim 4, wherein The development potential evaluation unit includes: The development index extraction subunit is used to extract development indexes from the stock land database to build a development index evaluation system; The weight assignment subunit is used to assign weights to each development index in the development index evaluation system according to the development requirements of stock land to determine the development index weight factors; The development scoring subunit is used to evaluate the development potential of the set of stock land use areas by using the development index evaluation system and the development index weight factors to obtain a set of development scores for the stock land use areas; The stock unit identification subunit is used to preset a development score threshold and perform stock unit identification on the set of development scores for the stock land use areas and the set of stock land use areas according to the development score threshold to obtain the set of developed stock land use units.

7. The early warning system for the control of stock land use in territorial space planning based on multi-dimensional analysis according to claim 4, wherein The regional aggregation analysis unit includes: The rule determination subunit is used to determine the spatial continuity rule and the functional similarity rule according to the regional aggregation rules; The threshold presetting subunit is used to preset the land use spatial distance threshold and the functional similarity threshold based on the spatial continuity rule and the functional similarity rule; The aggregation analysis subunit is used to perform regional aggregation analysis on the set of developed stock land use units according to the land use spatial distance threshold and the functional similarity threshold to determine the zoned developed stock land.

8. The early warning system for the control of stock land use in territorial spatial planning based on multi-dimensional analysis according to claim 1, characterized in that, The multi-dimensional constraint analysis module includes: The multi-dimensional constraint quantification index determination unit is used to determine a set of multi-dimensional constraint quantification indexes according to the multi-dimensional constraint system; The constraint analysis unit is used to perform multi-dimensional constraint analysis on the zoned developed stock land based on the set of multi-dimensional constraint quantification indexes to obtain the zoned stock land index constraint values; The planned volume analysis unit is used to perform planned volume analysis on the zoned developed stock land based on the zoned stock land index constraint values to determine the zoned stock land volume threshold.

9. The early warning system for the control of stock land in territorial space planning based on multi-dimensional analysis according to claim 8, characterized in that, The planned volume analysis unit includes: The regression analysis subunit is used to collect the case data of the stock land in the national territorial space plan, use the zoned stock land index constraint value as the independent variable, and the plot ratio as the dependent variable, perform regression analysis on the case data of the stock land in the national territorial space plan, and build a volume constraint regression model; A volume threshold determination subunit, configured to perform a planned volume analysis on the developed stock land in the partition by using the volume constraint regression model based on the constraint value of the land use index in the partition stock land, and determine the volume threshold of the partition stock land.

10. The early warning system for the control of stock land use in territorial spatial planning based on multi-dimensional analysis according to claim 1, characterized in that, The land use control warning module includes: A comparison trigger unit, configured to perform a comparison trigger on the developed planned volume data of the stock land based on the hierarchical warning mechanism, and determine the warning level of the target stock land; A hierarchical warning unit, configured to perform hierarchical warning and tracking control on the developed stock land in the partition through the warning level of the target stock land.

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