An analysis method, device and electronic equipment for planning implementation guidance of current industrial land, and a storage medium

Abstract

The present application relates to the technical field of space planning and land use analysis, and particularly relates to a current industrial land planning implementation guidance analysis method and device, electronic equipment and storage medium, the present application obtains multiple heterogeneous original data, and obtains current industrial land vector data layer and planning implementation guidance vector data layer set through preprocessing, which overcomes the defects of limited analysis range of the prior art; through superposition analysis, data layers and attribute values corresponding to at least two implementation guidance types are formed, solving the problem of single analysis dimension and only binary judgment; through fusion, the analysis result layer and target attribute value covering the target area are obtained, realizing accurate grading identification and differential treatment of the fit degree of industrial land and planning implementation, and improving the analysis efficiency and the operability of planning implementation.

Description

Technical Field

[0001] This invention relates to the field of spatial planning and land use analysis technology, and in particular to an analysis method, apparatus, electronic device, and storage medium for guiding the implementation of current industrial land planning. Background Technology

[0002] During the previous round of rapid development of my country's real economy, provinces and cities accumulated a vast amount of existing industrial land, which effectively supported industrial expansion and upgrading. As urban development enters a new stage of intrinsic growth, the industrial structure is accelerating its transformation towards high-tech and sophisticated industries, and the urban functional layout is constantly being optimized. The functional positioning and utilization patterns of traditional existing industrial land are facing severe challenges in terms of their compatibility with current planning implementation guidelines. A large amount of existing industrial land urgently needs to be transformed, updated, and efficiently reused under the guidance of planning.

[0003] Currently, the analytical methods for addressing the implementation guidelines of current industrial land use planning have the following shortcomings: First, the scope of analysis is limited, focusing on isolated assessments of individual plots or local areas, making it difficult to cover the entire administrative region at once, resulting in low overall resource allocation efficiency; second, the analytical dimensions are singular, relying on economic indicators or single spatial characteristics, lacking a systematic integration of multiple key elements such as planning attributes, land use implementation status, and industrial innovation capabilities, making it difficult to comprehensively and accurately identify the transformation potential and suitable paths of land use; third, the classification capabilities are insufficient, only achieving a binary judgment of "whether land use conforms to the guidelines," failing to classify and categorize land use according to planning implementation requirements, and making it difficult to provide differentiated disposal guidance for land use with different levels of suitability. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide an analysis method, apparatus, electronic device, and storage medium for guiding the implementation of current industrial land use planning.

[0005] In a first aspect, embodiments of the present invention provide an analysis method for guiding the implementation of existing industrial land use planning, the method comprising: Acquire diverse and heterogeneous raw data within the same target area; the diverse and heterogeneous raw data shall include at least: land use status data, planning and control data, land use implementation status data, industrial space data, population vitality data, and enterprise economic data; The diverse and heterogeneous raw data are preprocessed to obtain a set of vector data layers of current industrial land and planning implementation guidance vector data layers within the same target area; The existing industrial land vector data layer is overlaid with the planning implementation guidance vector data layer set for analysis to form the data layer and attribute values ​​corresponding to the implementation guidance type; the implementation guidance type includes at least two of the following: relocation, conversion, upgrading and retention. The data layers and attribute values ​​of each implementation guidance type are merged to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

[0006] In conjunction with the first aspect, the steps for preprocessing diverse and heterogeneous raw data include: Data cleaning is performed on various types of diverse and heterogeneous raw data. Data cleaning includes format verification, spatial coordinate unification, topology checking and repair, and attribute field organization. By using the current land use data in the diverse and heterogeneous original data, existing industrial land use patches are filtered out to generate a vector data layer of existing industrial land use. Using the existing industrial land vector data layer as the spatial scope, other diverse and heterogeneous original data are spatially clipped to obtain clipped data within the same target area. The clipped data is then used as a set of vector data layers to guide planning implementation. Create a feature dataset in the file geodatabase, storing the current industrial land vector data layer and the planning implementation guidance vector data layer set.

[0007] In conjunction with the first aspect, the types of guidance implemented include relocation guidance; The steps involved in overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: Spatial overlay analysis is performed on the existing industrial land vector data layer and the ecological protection red line vector data and permanent farmland protection red line vector data in the planning implementation guidance vector data layer set. Existing industrial land map patches that fall completely within the range corresponding to the ecological protection red line vector data or permanent farmland protection red line vector data are identified as a type of relocation guidance. After removing the map patches corresponding to the first type of relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the ecological control zone vector data outside the development boundary in the planning implementation guidance vector data layer set. Map patches that fall completely within the range corresponding to the ecological control zone vector data are identified as the second type of relocation guidance. After removing the map patches corresponding to the first and second categories of relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the non-construction land vector data in the planning implementation guidance vector data layer set. Map patches that fall completely within the range corresponding to the non-construction land vector data are identified as the third category of relocation guidance. The map features of Category I, Category II, and Category III relocation guidance are merged to form a relocation guidance data layer, and the attribute values ​​of the relocation guidance type and guidance sub-category are filled in.

[0008] In conjunction with the first aspect, the types of guidance implemented include conversion guidance; The steps involved in overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: After removing the map patches corresponding to the relocation guidance, the remaining existing industrial land vector data layer and the planned construction land vector data in the planning implementation guidance vector data layer set are spatially overlaid and analyzed to select map patches with non-industrial land use as the basic data for the conversion guidance. Spatial overlay analysis was performed on the basic data of the conversion guidance and the vector data of the industrial park boundary. The map patches located outside the boundary of the industrial park were identified as Class I conversion guidance, and the map patches located inside the boundary of the industrial park were identified as Class II conversion guidance. Merge the map features of Class I and Class II conversion guidelines to form a conversion guide data layer, and fill in the attribute values ​​of conversion guide type and guide subclass.

[0009] In conjunction with the first aspect, the types of guidance implemented include enhancement guidance; The steps involved in overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: After removing the map patches corresponding to the relocation and conversion guidelines, the remaining existing industrial land vector data layer is spatially overlaid with the planned construction land vector data in the planning implementation guide vector data layer set to screen out map patches whose planned use is industrial land type, which serve as the basic data for the improvement guide. For the basic data of the improvement guidance located within the boundary of the industrial park in the planning implementation guidance vector data layer set, the map patches that meet the preset update conditions for land use implementation status are removed, and the remaining map patches that meet at least two inefficient use characteristic indicators are identified as a type of improvement guidance. For the basic data of the upgrading orientation located outside the boundary of the industrial park, the map patches that meet the preset update conditions in terms of land use implementation status are removed, and the remaining map patches that meet at least one inefficient use characteristic indicator are identified as the second type of upgrading orientation. Merge the type 1 and type 2 lift guidance patches to form a lift guidance data layer, and fill in the attribute values ​​of lift guidance type and guidance subclass; Among them, the inefficient utilization characteristic indicators include at least one of the following: plot ratio below the first threshold, employment population density below the second threshold, and revenue per unit area below the average level of the target area.

[0010] In conjunction with the first aspect, the types of guidance implemented include retention guidance; The steps involved in overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: After removing the map patches corresponding to the relocation, conversion, and upgrading directions, the remaining existing industrial map patches are identified as the retention directions. Based on the reserved guidance features, a reserved guidance data layer is formed, and the attribute values ​​of the reserved implementation guidance type and guidance subclass are filled in.

[0011] In conjunction with the first aspect, the steps for merging the data layers and attribute values ​​of the various implementation guidance types include: The spatial fusion tool is used to merge the vector layers corresponding to at least two implementation guidance types into a single composite layer. Repair topology errors between merged patches, including overlaps and gaps; Unify the attribute field structure of each vector layer, standardize and collect the attribute fields of implementation guidance type and guidance sub-class to form a unified target attribute system; The merged layer is validated, duplicate patches are removed and missing attributes are repaired to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

[0012] Secondly, the present invention also provides an analysis device for guiding the implementation of current industrial land use planning, comprising: The acquisition module is used to acquire diverse and heterogeneous raw data within the same target area; the diverse and heterogeneous raw data includes at least: land use status data, planning control data, land use implementation status data, industrial space data, population vitality data, and enterprise economic data; The preprocessing module is used to preprocess the diverse and heterogeneous raw data to obtain a set of vector data layers of current industrial land and planning implementation guidance vector data layers within the same target area. The analysis module is used to overlay and analyze the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type; the implementation guidance type includes at least two of the following: relocation, conversion, upgrading and retention; The fusion module is used to merge the data layers and attribute values ​​of the various implementation guidance types to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

[0013] Thirdly, this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor runs the computer program to cause the electronic device to perform the methods described above.

[0014] Fourthly, this application provides a readable storage medium storing computer program instructions, which, when read and executed by a processor, perform the above-described method.

[0015] The embodiments of the present invention bring the following beneficial effects: This application provides an analysis method, apparatus, electronic device, and storage medium for the planning implementation guidance of existing industrial land. The method includes: acquiring multi-dimensional heterogeneous raw data within the same target area; the multi-dimensional heterogeneous raw data includes at least: land use status data, planning control data, land use implementation status data, industrial space data, population vitality data, and enterprise economic data; preprocessing the multi-dimensional heterogeneous raw data to obtain a vector data layer of existing industrial land and a set of vector data layers for planning implementation guidance within the same target area; overlaying and analyzing the vector data layer of existing industrial land and the set of vector data layers for planning implementation guidance to form a data layer and attribute values ​​corresponding to the implementation guidance type; the implementation guidance type includes at least two of the following: relocation, conversion, upgrading, and retention; and fusing the data layers and attribute values ​​of each implementation guidance type to obtain an analysis result layer and target attribute values ​​for the planning implementation guidance of existing industrial land covering the target area.

[0016] This invention overcomes the limitations of existing technologies in terms of analytical scope by acquiring diverse and heterogeneous raw data and preprocessing it to obtain a vector data layer of current industrial land and a set of vector data layers for planning implementation guidance. By overlaying analysis, it forms data layers and attribute values ​​corresponding to at least two types of implementation guidance, solving the problem of single analytical dimensions and binary judgment. By fusing the data, it obtains an analytical result layer and target attribute values ​​covering the target area, achieving accurate hierarchical identification and differentiated handling of the fit between industrial land and planning implementation, thus improving analytical efficiency and the operability of planning implementation.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating the analysis method for guiding the implementation of current industrial land use planning, as provided in this embodiment of the invention; Figure 2 This is a flowchart illustrating the process of forming a relocation guidance data layer using the method provided in this embodiment of the invention; Figure 3 This is a flowchart illustrating the process of forming a transfer guide data layer using the method provided in this embodiment of the invention; Figure 4 This is a flowchart illustrating the process of forming a lift-guided data layer using the method provided in this embodiment of the invention. Figure 5 A schematic diagram of an analysis device for guiding the implementation of current industrial land use planning, provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the electronic device structure provided in an embodiment of the present invention.

[0021] Figure label: 10 - Acquisition module, 20 - Preprocessing module, 30 - Analysis module, 40 - Fusion module; 130 - Processor, 131 - Memory, 132 - Bus, 133 - Communication interface. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] To facilitate understanding of this embodiment, the application scenarios and design concepts of this application embodiment will be briefly introduced below.

[0024] Current technologies for analyzing existing industrial land use suffer from limitations in scope, single dimension, and binary judgment, making it difficult to achieve hierarchical classification and precise handling.

[0025] Based on this, this application provides an analysis method, device, electronic device, and storage medium for guiding the implementation of current industrial land planning, so as to achieve accurate identification and differentiated treatment across the entire region, multiple dimensions, and hierarchical classification.

[0026] Example 1 This application provides an analytical method for guiding the implementation of current industrial land use planning, combined with... Figure 1 As shown, the method includes: S110, acquire diverse and heterogeneous raw data within the same target area; the diverse and heterogeneous raw data shall include at least: land use status data, planning and control data, land use implementation status data, industrial space data, population vitality data, and enterprise economic data.

[0027] S120 preprocesses the diverse and heterogeneous raw data to obtain a set of vector data layers of existing industrial land and planning implementation guidance vector data layers within the same target area.

[0028] S130 involves overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type; the implementation guidance type includes at least two of the following: relocation, conversion, upgrading, and retention.

[0029] S140, the data layers and attribute values ​​of each implementation guidance type are merged to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

[0030] This invention overcomes the limitations of existing technologies in terms of analysis scope by acquiring diverse and heterogeneous raw data and preprocessing it to obtain a vector data layer of current industrial land and a set of vector data layers for planning implementation guidance. It can cover the entire target area at once. By overlaying analysis, it forms data layers and attribute values ​​corresponding to at least two implementation guidance types, solving the problem of single analysis dimension and binary judgment. By fusing the data to obtain the analysis result layer and target attribute values ​​covering the target area, it achieves accurate hierarchical identification and differentiated handling of the fit between industrial land and planning implementation, improving analysis efficiency and the operability of planning implementation.

[0031] In step S110, the target area refers to the geographical area where industrial land analysis needs to be performed, such as a complete city or development zone.

[0032] Multi-source heterogeneous raw data refers to multiple types of data that may differ in source, format, and spatial reference. In this embodiment, it includes at least seven types: land use status data (such as the current actual use of land), planning and control data (such as ecological red lines, basic farmland, and construction land planning), land use implementation status data (such as whether land has been supplied, whether it is in the reserve and project approval stage, or whether it is in an intermediate stage), industrial space data (such as industrial park boundaries and the scale of individual buildings), population vitality data (such as employment population grids), and enterprise economic data (such as enterprise registration and revenue). It may also include innovation capability data (such as the number of patents).

[0033] Taking a certain region as an example, obtain the multi-source heterogeneous raw data of that region: Land use status data: Annual change survey vector map provided by the natural resources department, including approximately 5,000 industrial land use patches; Planning and control data: Layers such as ecological protection red lines, permanent basic farmland, and urban development boundaries in the overall land use plan; Land use implementation status data: List of land parcels that have been approved for reserve, land parcels that have been supplied, and land parcels in the intermediate stage that are under construction but not yet completed, provided by the land reserve center; Industrial space data: the boundaries of approved development zones at the provincial level and above, and the plot ratio calculated from the footprint area and number of floors of individual buildings obtained through building surveys; Population vitality data: A 75m×75m grid of employment population density generated based on mobile phone signaling or census data; Enterprise economic data: Enterprise registration addresses from market regulators and enterprise revenue data from tax authorities are spatialized into point or area data. Innovation capability data: The number of enterprise patents issued by the State Intellectual Property Office is linked to the spatial location of the enterprise.

[0034] Traditional methods rely solely on land use maps or economic indicators, failing to comprehensively reflect the relationship between industrial land use and planning, implementation progress, output benefits, and innovation potential. This invention, however, systematically collects diverse and heterogeneous raw data, providing a complete foundation for subsequent multidimensional overlay analysis. This ensures that subsequent analyses can simultaneously consider different dimensions such as rigid control (red lines), flexible guidance (industrial parks, non-construction land), and vitality and efficiency (employment, revenue, patents), avoiding biased analysis due to data gaps. It also acquires all relevant data covering the entire target area at once, facilitating efficient and accurate analysis.

[0035] In conjunction with the first aspect, step S120 includes: S121, data cleaning of various diverse and heterogeneous raw data; data cleaning includes format verification, spatial coordinate unification, topology checking and repair, and attribute field organization.

[0036] S122, using the current land use data in the multi-dimensional heterogeneous original data to filter out existing industrial land use patches and generate a vector data layer of existing industrial land use.

[0037] S123 uses the existing industrial land vector data layer as the spatial range to spatially clip other diverse and heterogeneous original data to obtain clipped data within the same target area, and uses the clipped data as the planning implementation guidance vector data layer set.

[0038] S124, Create a feature dataset in the file geodatabase, storing the current industrial land vector data layer and the planning implementation guidance vector data layer set.

[0039] Understandably, raw data often has problems such as inconsistent formats, mismatched coordinates, geometric errors, and missing attributes. If these are not addressed, they will directly lead to analysis failure or incorrect results.

[0040] Step S121 first cleans the various types of heterogeneous raw data, which involves performing a series of quality checks and corrections, such as format verification, spatial coordinate unification, topology checking and repair, and attribute field organization.

[0041] The purpose of format verification is to ensure that all data files can be correctly identified and read by the geographic information system platform; spatial coordinate unification converts data from different sources (such as data using different coordinate systems) to the same spatial reference system to avoid positional misalignment during subsequent overlay; topology checking and repair corrects common geometric errors in surface features, such as gaps and self-overlap, to ensure the geometric quality of the data; attribute field organization specifically involves deleting redundant fields that are irrelevant to the analysis and verifying or supplementing missing key fields.

[0042] Taking a certain city as an example, the ecological protection red line in the original data adopts the WGS84 coordinate system, while the annual land survey data adopts the CGCS2000 coordinate system. After uniformly converting to CGCS2000, the tiny gaps in the red line patches are repaired and useless fields such as "creation time" are deleted.

[0043] Step S121 eliminates noise and errors at the data level, providing a high-quality, standardized data foundation for subsequent processing, thereby ensuring a stable analysis process and accurate and reliable analysis results.

[0044] After data cleaning, proceed to step S122: Load the land use status data from the diverse and heterogeneous original data into the ArcGIS platform. Using attribute queries, select all land parcels whose "Land Use Nature" field value is industrial land, and generate an independent vector layer, namely the current industrial land vector data layer. The land use status data typically originates from land surveys or annual change surveys and is vector data recording the actual use of each land parcel in the form of land parcels.

[0045] For example, an annual land use change survey in a certain city contains 100,000 land parcels. By filtering for "land use code = 0601", 5,000 industrial land parcels are obtained, forming a new layer. The analysis object of step S122 is limited to land currently designated as industrial; non-industrial land (such as residential, commercial, and arable land) is not considered. Its purpose is to define the scope of the study area, obtain vector datasets related to the same area, accurately extract target land, avoid interference from non-industrial land, and significantly reduce data volume while improving processing efficiency.

[0046] Next, step S123 uses the existing industrial land vector data layer as the spatial scope to spatially clip other diverse and heterogeneous original data, obtaining clipped data within the same target area. This clipped data is then used as the planning implementation guidance vector data layer set. Spatial clipping is a GIS spatial operation that uses the existing industrial land vector layer as a clipping template, strictly limiting all other original data (including ecological protection red lines, permanent basic farmland, industrial park boundaries, employment population grids, enterprise registration points, etc.) within this template, retaining only the portions that overlap with or are located within the industrial land map patches.

[0047] For example, by using 5,000 industrial land parcels as templates to cut the ecological red line layer, the red line parcels that originally covered the entire city were cut down to only fragments that intersected with industrial land; similarly, the employment population grid only retained the grids that fell within the industrial land area.

[0048] Step S123 removes non-industrial data that has no reference value to ensure that all data used for planning implementation guidance analysis are strictly consistent with the current industrial land area, thereby achieving data scope unification, avoiding interference and redundancy of data outside the scope, and reducing the burden of data storage and processing.

[0049] Finally, step S124 creates a feature dataset in the file geodatabase, storing the existing industrial land vector data layer and the planning implementation guidance vector data layer set. A file geodatabase is a container for managing spatial data such as vectors and raster data (e.g., Esri File Geodatabase). Step S124 first creates a feature dataset in the database, which stores data sets with the same spatial reference; then, it imports the existing industrial land vector data layer generated in step S122 into a designated location within this dataset, and imports all the planning implementation guidance data obtained after clipping in step S123 into the same feature dataset, forming a complete planning implementation guidance vector data layer set, and performs data backup.

[0050] For example, create a feature dataset named "StudyArea" under "D:\Project\Industrial Land Analysis.gdb", set the coordinate system to CGCS2000, and then import the "Current Industrial Land" layer as well as multiple layers such as "Ecological Red Line_Cropped", "Industrial Park Boundary_Cropped", and "Employment Grid_Cropped".

[0051] Step S124 requires efficient data organization and access methods for spatial analysis and overlay calculations. The file geodatabase supports complex queries, spatial indexes, and version management to standardize the storage of all intermediate and result data, facilitating subsequent batch processing, backtracking verification, and output of results, thereby improving data management efficiency and ensuring the repeatability of the analysis process and data security.

[0052] Steps S121-S124 are used to transform raw multi-source data into standardized analytical data.

[0053] In conjunction with the first aspect, the implementation guidance type includes relocation guidance; step S130 includes: S131 involves spatially overlaying the existing industrial land vector data layer with the ecological protection red line vector data and permanent farmland protection red line vector data in the planning implementation guidance vector data layer set. Existing industrial land map patches that fall completely within the range corresponding to the ecological protection red line vector data or the permanent farmland protection red line vector data are identified as a type of relocation guidance.

[0054] S132, after removing the map patches corresponding to the first type of relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the ecological control zone vector data outside the development boundary in the planning implementation guidance vector data layer set. Map patches that fall completely within the range corresponding to the ecological control zone vector data are identified as the second type of relocation guidance.

[0055] S133, after removing the map patches corresponding to the first and second categories of relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the non-construction land vector data in the planning implementation guidance vector data layer set. Map patches that fall completely within the range corresponding to the non-construction land vector data are identified as the third category of relocation guidance.

[0056] S134: Merge the map features of Category I, Category II, and Category III relocation guidance to form a relocation guidance data layer, and fill in the attribute values ​​of the relocation guidance type and guidance sub-category.

[0057] In step S131, spatial overlay analysis is an operation in GIS to determine the spatial relationship (such as intersection, containment, and coverage) between two or more layers. The current industrial land vector data layer is a set of map patches currently used for industry within the target area, generated during the preprocessing stage. The ecological protection red line and the permanent basic farmland protection red line are rigid control boundaries in the national land spatial planning and have legally binding force; no construction activities may encroach upon them. Complete inclusion requires that the overall geometry of the industrial map patches be located inside the red line to ensure accurate conflict determination.

[0058] This step follows the planning principles of ecological priority and protection priority, prioritizing the identification of industrial land that conflicts with the highest level of protection red lines, and treating these as the most urgent relocation targets. Its purpose is to quickly identify land parcels that must be relocated immediately, avoiding the tedious work of manually checking each red line. For example, in a city with 5,000 industrial land parcels, overlay analysis revealed that 30 were entirely within the ecological protection red line and 20 were entirely within permanent basic farmland. These 50 land parcels were marked as a Class I relocation orientation, with the "Implementation Orientation Type" filled in as "Relocation" and the "Orientation Sub-category" filled in as "Class I Relocation Orientation".

[0059] This step enables automated and accurate identification of rigidly vacated land, significantly reducing interpretation time and human error, and providing reliable data support for the subsequent formulation of priority vacating plans. Ecological protection red lines and permanent farmland protection red lines are rigid control boundaries in land planning and have the highest protection priority; no construction activities may encroach upon them.

[0060] In step S132, "removal" refers to removing the map patches that have been marked as a type of relocation from the industrial land set after the previous round of analysis, to ensure that subsequent analyses do not repeat the process; the vector data of the ecological control zone outside the development boundary comes from the area outside the urban development boundary in the national land spatial planning, which is usually dominated by ecological conservation and recreation, allowing limited human activities but not suitable for industrial use; and "complete inclusion" requires that the industrial map patches be located entirely within the boundary of the ecological control zone to avoid ambiguity caused by partial overlap.

[0061] Step S132, after completing the strictest ecological red line and basic farmland relocation, further identifies industrial land located outside the urban development boundary that has relatively important ecological functions but a protection level slightly lower than the red line. This land needs to be relocated within a specified timeframe and prioritized for ecological restoration or functional recovery. Its purpose is to clarify the second-priority relocation targets, provide guidance for time-bound relocation in planning implementation, and prevent industrial activities from continuously damaging the environmental quality of the ecological control zone.

[0062] For example, after removing 50 plots of land designated for relocation in a certain city, 4,950 industrial plots remain. By overlaying the remaining layer with the ecological control zone outside the development boundary, it was found that 80 plots are located entirely within the control zone. These plots are then marked as relocation-oriented in the second category, with "relocation" filled in for "implementation orientation type" and "second category relocation orientation" for "orientation subcategory".

[0063] This step enables the systematic identification of secondary priority land for relocation, forming a tiered arrangement of emergency relocation and time-limited relocation for the second category. This ensures both the rigidity of ecological control and the feasibility of implementation.

[0064] In step S133, non-construction land includes cultivated land, orchards, forest land, grassland, and water areas. According to land use control regulations, these lands are generally not suitable for retaining industrial functions. After removing the map patches corresponding to Category I and Category II relocation guidelines, the remaining existing industrial land vector data layer is spatially overlaid with the non-construction land vector data in the planning implementation guidance vector data layer set. Map patches that fall entirely within the range corresponding to the non-construction land vector data are identified as Category III relocation guidelines. Figure 2 As shown.

[0065] For example, after removing Category I and Category II relocation guidance areas, there are still 120 remaining industrial land parcels located entirely within non-construction land areas (such as cultivated land or forest land outside of basic farmland). These parcels are identified as Category III relocation guidance areas. This step, based on planning land use control, gradually clears out industrial land that does not conform to the planning land category. Its purpose is to identify resources that need to be gradually vacated and restored to non-construction uses during planning implementation, thereby following planning guidance, orderly guiding the withdrawal of industrial land, and reducing social conflicts and economic impacts.

[0066] Step S134 integrates the identified Category I, Category II, and Category III relocation guidance patches from three separate layers into a single layer using a spatial fusion tool. Each patch retains its original geometry and is given attribute fields: "Relocation Guidance Type" (uniformly filled in as "Relocation") and "Guidance Sub-Category" (respectively filled in as "Category I Relocation Guidance," "Category II Relocation Guidance," and "Category III Relocation Guidance"). For example, the final generated relocation guidance layer contains 250 patches: 50 Category I, 80 Category II, and 120 Category III, each with a clear classification label. This step summarizes all industrial land requiring relocation, forming a complete decision dataset. Its purpose is to provide planning managers with a clear relocation list and priorities (Category I being the most urgent, Category III the least urgent), facilitating the development of phased implementation plans. This achieves hierarchical and classified management of relocated land, providing direct data support for subsequent development of differentiated relocation compensation, timing arrangements, and land reclamation schemes.

[0067] Through steps S131 to S134, the automatic identification, hierarchical classification, and attribute assignment of the relocation orientation of all existing industrial land in the target area are realized. Compared with manual verification or single indicator evaluation, the efficiency, accuracy, and operability are greatly improved.

[0068] In conjunction with the first aspect, the implementation guidance type includes conversion guidance, and step S130 includes: S135. After removing the map patches corresponding to the relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the planned construction land vector data in the planning implementation guidance vector data layer set to screen out map patches whose planned use is non-industrial land type, which are used as the basic data for the conversion guidance.

[0069] S136. Spatial overlay analysis is performed on the basic data of the conversion guidance and the vector data of the industrial park boundary. The map patches located outside the boundary of the industrial park are identified as Class I conversion guidance, and the map patches located inside the boundary of the industrial park are identified as Class II conversion guidance.

[0070] S137, merge the map features of Class I and Class II conversion guides to form a conversion guide data layer, and fill in the attribute values ​​of conversion guide type and guide subclass.

[0071] Step S135 involves removing the land parcels corresponding to the relocation guidelines (meaning removing industrial land parcels identified as Class I, II, or III relocation sites to ensure subsequent analysis only targets land that does not require relocation for the time being), combined with... Figure 3 As shown, the remaining existing industrial land vector data layer is spatially overlaid with the planned construction land vector data in the planning implementation guidance vector data layer set to screen out the land parcels whose planned use is non-industrial land type, which serve as the basic data for the conversion guidance.

[0072] The planned construction land vector data originates from the construction land control zones in the national land spatial planning, containing the planned use attributes (such as residential, commercial, public service, industrial, etc.) of each plot. Through attribute queries, plots whose planned use field value is not industrial (e.g., codes not equal to "M" or "1001") are selected to filter out plots with non-industrial planned uses, which serve as the basis for conversion guidance. After excluding land vacated through rigid relocation, this step first identifies plots that, while currently still industrial, have been planned for other construction uses. These plots are no longer suitable for retaining industrial functions and should be converted to other construction uses, thus filtering out industrial land requiring land use conversion and providing basic data for subsequent detailed classification.

[0073] For example, after removing 250 vacated land parcels in a certain city, 4,750 industrial land parcels remained. By overlaying and filtering them with the planning and construction land use map layer, it was found that 500 of these land parcels were planned for residential or commercial use. These land parcels served as the basic data for conversion guidance.

[0074] In step S136, the industrial park boundary vector data originates from the legally defined boundaries of various development zones and industrial clusters. Industrial land located within the industrial park boundary, even if its planned use has been changed to non-industrial, may still retain some flexibility due to the overall development needs of the park; while land located outside the boundary lacks industrial agglomeration support and should be converted as soon as possible. Spatial overlay analysis is performed between the aforementioned conversion guidance data and the industrial park boundary vector data. Patches located outside the industrial park boundary are identified as having a first-class conversion guidance, while patchies located within the industrial park boundary are identified as having a second-class conversion guidance.

[0075] Step S136 combines industrial park policies to prioritize land use conversion: land outside the boundary has a more urgent need for conversion, while land inside the boundary can be converted gradually and orderly in accordance with the park's development needs. This distinguishes between two different paces: "conversion as soon as possible" and "gradual conversion," which facilitates the timing arrangement in the planning and implementation process.

[0076] For example, of the 500 map patches mentioned above, 300 are located outside the industrial park boundary and are identified as Category I redevelopment-oriented; 200 are located inside the industrial park boundary and are identified as Category II redevelopment-oriented.

[0077] Step S137 merges the aforementioned Category I and Category II land use conversion guidelines to form a conversion guidance data layer, and fills in the attribute values ​​for the conversion guidance type and guidance sub-category. Merging refers to integrating the two types of land use patches into one layer using spatial fusion tools. Each patch retains its geometric shape and adds attribute fields "Implementation Guidance Type" (uniformly filled with "Conversion") and "Guidance Sub-Category" (filled with "Category I Conversion Guidance" and "Category II Conversion Guidance" respectively). This step summarizes all industrial land requiring conversion, forming a complete conversion guidance dataset. This provides planning managers with a conversion list and priorities (Category I priority conversion, Category II conversion based on park needs), facilitating the development of implementation plans for land supply and addressing urban functional deficiencies. This achieves hierarchical and categorized management of land use conversion, combining planned use changes with industrial park policies, and improving the scientific rigor and operability of conversion decisions.

[0078] For example, the final conversion guide layer contains 500 patches, each with a clear conversion category attribute, which can be directly used for subsequent land reserve, planning control adjustment and project investment promotion.

[0079] In conjunction with the first aspect, the implementation guidance type includes enhancement guidance, step S130, which includes: S138. After removing the map patches corresponding to the relocation and conversion guidance, the remaining existing industrial land vector data layer is spatially overlaid with the planned construction land vector data in the planning implementation guidance vector data layer set to screen out map patches whose planned use is industrial land type, which are used as the basic data for the improvement guidance.

[0080] S139. For the basic data of improvement guidance located within the boundary of the industrial park in the planning implementation guidance vector data layer set, remove the land use implementation status that meets the preset update conditions, and identify the remaining land use that simultaneously meets at least two inefficient use characteristic indicators as a type of improvement guidance.

[0081] S1310, for the basic data of the upgrading orientation located outside the boundary of the industrial park, remove the land use implementation status that meets the preset update conditions, and identify the remaining land use that meets at least one inefficient use characteristic indicator as the second type of upgrading orientation.

[0082] S1311, merge the type I lift guidance and type II lift guidance polygons to form a lift guidance data layer, and fill in the attribute values ​​of lift guidance type and guidance subclass.

[0083] Among them, the inefficient utilization characteristic indicators include at least one of the following: plot ratio below the first threshold, employment population density below the second threshold, and revenue per unit area below the average level of the target area.

[0084] In steps S131-S137, the plots corresponding to the relocation and conversion guidelines are removed to ensure that subsequent analysis only targets industrial land that does not require relocation or conversion. Combined with... Figure 4 As shown, in step S138, "planned use as industrial land" refers to land parcels whose planned use field value is still "industrial" (e.g., code "M" or "1001") selected through attribute query. The planning direction for these parcels is to retain their industrial function, but they may require upgrading due to inefficient use. After excluding rigid relocation and land use change categories, step S138 identifies the remaining industrial land parcels still planned for industrial use as potential targets for upgrading. This process filters out industrial land requiring further assessment of inefficient use, providing foundational data for subsequent classification and upgrading. For example, after removing 250 relocated parcels and converting 500 parcels in a certain city, 4250 industrial parcels remain. By overlaying and filtering with the planned construction land map layer, it was found that 3000 of these parcels still have "industrial" planned use; these parcels serve as the foundational data for upgrading guidance.

[0085] Subsequently, step S139, for the basic data of the improvement orientation located within the boundary of the industrial park, first removes the land use implementation status that meets the preset update conditions, and then identifies the remaining land use that simultaneously meets at least two inefficient use characteristic indicators as a type of improvement orientation.

[0086] Specifically, industrial land within the boundaries of industrial parks typically enjoys policy support and infrastructure support, and has high potential for improvement. The pre-set conditions for renewal include land newly supplied in the past three years, land in an intermediate state (such as under construction but not yet completed), or land that has been reserved for project approval. These plots are not suitable for inclusion in the improvement guidance because they are relatively new or already have clear renewal plans.

[0087] Inefficient utilization characteristics include: building scale and plot ratio below the first threshold (e.g., between 0 and 0.2, indicating extremely low development intensity), employment population density below the second threshold (e.g., employment population per hectare between 0 and 5, indicating a lack of vitality), and revenue per unit area below the specified proportion of the target area average (e.g., one-third, indicating poor economic efficiency).

[0088] If the remaining map patches simultaneously meet at least two of the above inefficiency indicators, it indicates that their utilization efficiency is seriously insufficient, but they have the conditions for transformation within the industrial park, and efficiency improvement should be prioritized.

[0089] Step S139 combines the policy advantages and inefficiency criteria of the industrial park to identify the industrial land that is most in need of improvement and most suitable for upgrading, thereby identifying high-priority upgrade targets within the industrial park and providing a basis for implementing key upgrades and efficiency improvements. For example, in an industrial park, there are 800 basic land parcels for upgrading guidance. After removing 50 newly supplied parcels in the past three years, 30 parcels in intermediate status, and 20 parcels that have been reserved for project approval, 700 parcels remain. Among them, 150 parcels simultaneously meet the requirements of a plot ratio of less than 0.2 and fewer than 5 employees, 80 parcels simultaneously meet the requirements of a plot ratio of less than 0.2 and revenue per unit area of ​​less than one-third of the average level, and 60 parcels simultaneously meet the requirements of fewer than 5 employees and revenue per unit area of ​​less than one-third of the average level. Finally, a total of 290 parcels are identified as Category I upgrade-oriented parcels.

[0090] Step S1310, targeting the basic data for upgrading guidance located outside the industrial park boundary, first removes land parcels whose land use implementation status meets the preset update conditions, then identifies the remaining land parcels that meet at least one inefficient use characteristic indicator as Category II upgrading guidance. Unlike within the industrial park, industrial land outside the boundary lacks park policy support and infrastructure advantages, resulting in relatively insufficient upgrading conditions. Therefore, the judgment criteria are more lenient; as long as any one of the three inefficiency indicators is met, it is considered to require guidance for upgrading. This step adopts a more flexible inefficiency identification strategy in the area outside the boundary, avoiding the omission of potential upgrading targets due to overly strict standards. Its purpose is to identify industrial land that needs gradual guidance for upgrading and optimized utilization, providing support for the formulation of phased transformation plans. For example, there are 2,200 basic land parcels for upgrading guidance outside an industrial park. After removing 200 newly supplied land parcels in the past three years, 100 land parcels in the intermediate stage, and 80 land parcels that have been reserved for project approval, 1,820 land parcels remain. Among them, 500 land parcels meet the requirement of a plot ratio of less than 0.2, 600 land parcels meet the requirement of having fewer than 5 employees, and 400 land parcels meet the requirement of having a per capita revenue of less than one-third. Since meeting any one of these requirements is sufficient, after deduplication, a total of 1,200 land parcels in the second category for upgrading guidance were identified.

[0091] Subsequently, step S1311 merges the Class I and Class II improvement guidance patches to form an improvement guidance data layer, and fills in the attribute values ​​for the improvement guidance type and guidance sub-category. Merging refers to integrating the two types of patches into one layer using spatial fusion tools. Each patch retains its geometric shape and adds attribute fields "Implementation Guidance Type" (uniformly filled with "Improvement") and "Guidance Sub-category" (filled with "Class I Improvement Guidance" and "Class II Improvement Guidance" respectively). This step summarizes all industrial land requiring efficiency improvement, forming a complete improvement guidance dataset. This provides planning managers with a list and priority for improvement and transformation (Class I prioritizes key remediation, Class II is gradually guided towards improvement), facilitating the development of implementation plans for industrial land organic renewal and secondary development. This achieves hierarchical and classified management of improved land, combining inefficiency assessment with industrial park policies, highlighting key areas while considering all aspects, thus improving the scientific nature and operability of industrial land quality improvement and efficiency enhancement. For example, the final generated improvement guidance layer contains 1,490 patches (290 in category I and 1,200 in category II). Each patch has a clear improvement category and inefficiency indicator information, which can be directly used to prepare annual remediation plans, apply for renovation funds, and assess performance.

[0092] In conjunction with the first aspect, the implementation guidance type includes retention guidance; step S130 includes: S1312, after removing the map patches corresponding to the relocation, conversion, and upgrading directions, the remaining existing industrial map patches are determined as the retention directions.

[0093] S1313, Based on the reserved guidance patches, form a reserved guidance data layer, and fill in the attribute values ​​of the reserved implementation guidance type and guidance subclass.

[0094] Step S1312, after removing the map patches corresponding to the aforementioned relocation, conversion, and upgrading guidelines, identifies the remaining existing industrial land use map patches as retention guidelines. Removal refers to sequentially removing all industrial map patches identified in previous steps as belonging to categories one, two, and three of relocation guidelines, categories one and two of conversion guidelines, and categories one and two of upgrading guidelines, ensuring that retention guidelines only include plots that have undergone rigorous screening and have not been identified by any disposal rules. These remaining map patches neither touch upon rigid relocation boundaries such as ecological protection red lines and permanent basic farmland, nor are they located in ecological control zones or non-construction land outside development boundaries; their planned use remains industrial, and they have not been determined to require conversion or upgrading.

[0095] Step S1312 adopts the elimination method logic: After completing the identification of three types of orientations—rigid relocation, flexible conversion, and inefficient upgrading—the remaining industrial land is the land that best fits the current planning implementation requirements and has a relatively reasonable utilization status. Therefore, it is classified into the retention orientation to define industrial land that does not require mandatory relocation, does not require change of use, and does not require key upgrading, thus providing a basis for maintaining the status quo or partial renewal for planning implementation.

[0096] For example, a city has a total of 5,000 original industrial land parcels. After identification, 250 are classified as relocation land parcels, 500 as repurposed land parcels, and 1,490 as upgrade land parcels. The remaining 2,760 land parcels do not belong to any of the first three categories, so these land parcels are designated as retention land parcels.

[0097] Step S1313 forms a retention guidance data layer based on the aforementioned retention guidance patches, and fills in the attribute values ​​for the retention implementation guidance type and guidance sub-category. Forming a layer refers to generating an independent vector layer from the selected retention patches through data export or copying; attribute filling involves adding two fields, "Implementation Guidance Type" and "Guidance Sub-category," to the attribute table of this layer. "Implementation Guidance Type" is uniformly filled with "Retention," and "Guidance Sub-category" is filled with "Retention Guidance" (or "General Retention"). Step S1313 integrates all industrial land with retention guidance into a standardized dataset, facilitating subsequent integration with layers for relocation, conversion, and upgrading, or allowing for independent use. This provides planning managers with a clear list of retainable industrial land, supporting routine management measures such as daily supervision, partial renovation, or functional upgrades. This completes the full-coverage classification of all existing industrial land, ensuring that each piece of industrial land has a clear planning implementation guidance, avoiding problems of unclassification or omissions, and providing a complete data foundation for compiling annual plans for the implementation of territorial spatial planning and performance evaluation of industrial land. For example, the final generated retainable guide layer contains 2,760 patches, each with a "retain / retainable guide" attribute label, which can be directly used to generate industrial land protection maps or dynamic monitoring ledgers.

[0098] In conjunction with the first aspect, step S140 involves merging the data layers and attribute values ​​of each implementation guidance type, specifically including: S141, use a spatial fusion tool to merge the vector layers corresponding to at least two implementation guidance types into a single composite layer.

[0099] S142, Repair topology errors between merged patches, including overlaps and gaps.

[0100] S143 unifies the attribute field structure of each vector layer, standardizes and collects the attribute fields of implementation guidance type and guidance subclass, and forms a unified target attribute system.

[0101] S144. Perform data verification on the merged layer, remove duplicate patches and repair missing attributes to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

[0102] Step S141 first uses a spatial fusion tool to merge the vector layers corresponding to at least two implementation guidance types into a single composite layer. The spatial fusion tool is an operation in a geographic information system used to stitch, cover, or combine multiple layers according to their spatial location, such as the Union or Merge tool. Since the guidance layers for relocation, conversion, upgrading, and retention are generated separately under different filtering conditions, the patches in each layer do not overlap (because each industrial land parcel belongs to only one guidance type), but they spatially cover the existing industrial land area of ​​the entire target region. This step integrates the scattered, category-stored layers into a complete spatial dataset, facilitating unified management and subsequent processing, eliminating the inconvenience caused by data dispersion, and laying the foundation for generating a single map analysis result. For example, if four types of guide layers have been formed, namely relocation, conversion, promotion, and retention, then the relocation guide layer (250 patches), conversion guide layer (500 patches), promotion guide layer (1490 patches), and retention guide layer (2760 patches) will be merged to obtain a comprehensive layer containing 5000 patches.

[0103] Step S142 repairs topological errors between merged features. Topological errors include overlaps and gaps. Although features in each guide layer are logically mutually exclusive, slight overlaps (the same location is covered by features from two different guides) or gaps (uncovered gaps between features) may occur after merging due to differences in the accuracy of the original data, boundary digitization errors, or rounding issues in overlay analysis. Topological error repair refers to automatically or semi-automatically correcting these errors using GIS topology inspection tools. For example, the Eliminate tool can be used to delete small features in overlapping areas, or the Integrate tool can be used to merge gaps into adjacent features. This step ensures that the merged layers are geometrically seamless and non-overlapping, meeting spatial data quality requirements and avoiding duplicate counting or omissions in subsequent statistics or decision-making, thereby improving data geometric accuracy and ensuring the reliability and authority of the analysis results. For example, if a 0.1 square meter overlap is found at a boundary in the merged layer, the system automatically assigns the overlapping area to a larger guide type feature and deletes the redundant overlapping feature.

[0104] Step S143 unifies the attribute field structure of each vector layer, standardizing and aggregating the implementation guidance type and guidance sub-category attribute fields to form a unified target attribute system. Since different guidance layers may have used different field names during generation (e.g., "Relocation Guidance Type" for the vacating layer and "Transfer Guidance Type" for the conversion layer), they need to be unified to the same field names after merging. Standardization and aggregation refers to adjusting the attribute tables of all layers to a consistent set of fields, for example, setting two core fields, "Implementation Guidance Type" and "Guidance Sub-Category," and deleting other redundant or temporary auxiliary fields. The principle of this step is to establish a unified attribute data model, facilitating subsequent querying, statistics, and visualization. Its purpose is to eliminate field heterogeneity, enabling users to quickly filter different guidance patches using the same field and perform summary analysis.

[0105] For example, the previously scattered fields such as "Evacuation Guidance Type", "Transfer Guidance Type", "Improvement Guidance Type", and "Retention Implementation Guidance Type" are unified into "Implementation Guidance Type", with values ​​of "Evacuation", "Transfer", "Improvement", and "Retention" respectively; the "Guidance Sub-Category" field uniformly stores specific categories such as "Category I Evacuation Guidance", "Category II Transfer Guidance", "Category I Improvement Guidance", and "Retention Guidance".

[0106] Step S144 performs data verification on the merged layer, removes duplicate patches and repairs missing attributes, and obtains the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

[0107] Data validation includes checking for geometric errors (such as self-intersections and empty geometry), attribute integrity (such as whether core fields are null values), and logical consistency (such as whether the implementation guidance type matches the guidance subclass). For duplicate polygons (such as identical or highly overlapping polygons resulting from merging operations), a tool for deleting duplicate geometry is used to remove them; for records with missing attributes, they are completed based on adjacent polygons or default rules (if completion is not possible, they are marked as "pending verification").

[0108] The final data product in step S144 must meet quality standards suitable for planning decisions. Even minor errors can lead to misjudgments in practice. The goal is to deliver data directly applicable to planning implementation and management, supporting tasks such as visual management, task assignment, and performance evaluation. This will create an authoritative, accurate, and complete map guiding the implementation of current industrial land use planning, providing scientific decision-making support for management units at all levels, park management, and land reserve departments.

[0109] For example, the final analysis result layer contains 5,000 map patches, each with "implementation guidance type" and "guidance sub-category" attributes, and there are no overlaps, gaps, or missing attributes, which can be directly imported into the national land spatial planning map system.

[0110] Secondly, this application also provides an analysis device for guiding the implementation of current industrial land planning, combined with... Figure 5 As shown, the device includes: an acquisition module 10, a preprocessing module 20, an analysis module 30, and a fusion module 40.

[0111] The acquisition module 10 is used to acquire diverse and heterogeneous raw data within the same target area; the diverse and heterogeneous raw data includes at least: land use status data, planning control data, land use implementation status data, industrial space data, population vitality data, and enterprise economic data.

[0112] The preprocessing module 20 is used to preprocess the diverse and heterogeneous raw data to obtain a set of vector data layers of current industrial land and planning implementation guidance vector data layers within the same target area.

[0113] The analysis module 30 is used to overlay and analyze the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type; the implementation guidance type includes at least two of the following: relocation, conversion, upgrading and retention.

[0114] The fusion module 40 is used to merge the data layers and attribute values ​​of the various implementation guidance types to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

[0115] Thirdly, embodiments of this application provide an electronic device, combined with Figure 6 As shown, the electronic device includes a memory 131 and a processor 130. The memory 131 stores a computer program, and the processor 130 runs the computer program to make the electronic device perform the above-described method.

[0116] Furthermore, combined Figure 3 The electronic device shown also includes a bus 132 and a communication interface 133, with the processor 130, the communication interface 133 and the memory 131 connected via the bus 132.

[0117] The memory 131 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 133 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 132 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0118] Processor 130 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 130 or by instructions in software form. Processor 130 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 131, and processor 130 reads the information in memory 131 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0119] Fourthly, embodiments of this application provide a readable storage medium storing computer program instructions, which are read and executed by a processor to perform the above-described method.

[0120] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0121] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0122] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0123] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0124] Finally, it should be noted that the above embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An analytical method for guiding the implementation of current industrial land use planning, characterized in that, The method includes: Acquire diverse and heterogeneous raw data within the same target area; the diverse and heterogeneous raw data includes at least: land use status data, planning and control data, land use implementation status data, industrial space data, population vitality data, and enterprise economic data; The diverse and heterogeneous raw data are preprocessed to obtain a set of vector data layers of existing industrial land and planning implementation guidance vector data layers within the same target area. The existing industrial land vector data layer is overlaid and analyzed with the planning implementation guidance vector data layer set to form a data layer and attribute value corresponding to the implementation guidance type; the implementation guidance type includes at least two of the following: relocation, conversion, upgrading and retention. The data layers and attribute values ​​of each of the aforementioned implementation guidance types are merged to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

2. The method according to claim 1, characterized in that, The steps for preprocessing the aforementioned multi-variable heterogeneous raw data include: Data cleaning is performed on various types of diverse and heterogeneous raw data; the data cleaning includes format verification, spatial coordinate unification, topology checking and repair, and attribute field organization. Using the land use status data in the aforementioned multi-dimensional heterogeneous raw data, current industrial land use map patches are filtered out to generate a current industrial land use vector data layer. Using the existing industrial land vector data layer as the spatial range, other diverse and heterogeneous original data are spatially clipped to obtain clipped data within the same target area, and the clipped data is used as the planning implementation guidance vector data layer set; Create a feature dataset in the file geodatabase, and store the existing industrial land vector data layer and the planning implementation guidance vector data layer set.

3. The method according to claim 1, characterized in that, The implementation guidance types include relocation guidance; The steps of overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: Spatial overlay analysis is performed on the existing industrial land vector data layer and the ecological protection red line vector data and permanent farmland protection red line vector data in the planning implementation guidance vector data layer set. Existing industrial land map patches that fall completely within the range corresponding to the ecological protection red line vector data or the permanent farmland protection red line vector data are identified as a type of relocation guidance. After removing the map patches corresponding to the first type of relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the ecological control zone vector data outside the development boundary in the planning implementation guidance vector data layer set. Map patches that fall completely within the range corresponding to the ecological control zone vector data are identified as the second type of relocation guidance. After removing the map patches corresponding to the first and second types of relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the non-construction land vector data in the planning implementation guidance vector data layer set. Map patches that fall completely within the range corresponding to the non-construction land vector data are identified as the third type of relocation guidance. The map features of the first type of relocation guidance, the second type of relocation guidance, and the third type of relocation guidance are merged to form a relocation guidance data layer, and the attribute values ​​of the relocation guidance type and guidance sub-class are filled in.

4. The method according to claim 3, characterized in that, The implementation guidance types include repurpose guidance; The steps of overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: After removing the map patches corresponding to the relocation guidance, the remaining existing industrial land vector data layer is spatially overlaid with the planned construction land vector data in the planning implementation guidance vector data layer set to screen out map patches whose planned use is non-industrial land type, as the basic data for the conversion guidance; Spatial overlay analysis is performed on the basic data of the conversion guidance and the vector data of the industrial park boundary. The patches located outside the boundary of the industrial park are identified as Class I conversion guidance, and the patches located inside the boundary of the industrial park are identified as Class II conversion guidance. The map features of the first type of conversion guide and the second type of conversion guide are merged to form a conversion guide data layer, and the attribute values ​​of conversion guide type and guide subclass are filled in.

5. The method according to claim 4, characterized in that, The implementation guidance types include enhancement guidance; The steps of overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: After removing the map patches corresponding to the relocation guidance and the conversion guidance, the remaining existing industrial land vector data layer is spatially overlaid with the planned construction land vector data in the planning implementation guidance vector data layer set to screen out map patches with industrial land type as the basic data for the improvement guidance; For the basic data of the improvement guidance located within the industrial park boundary in the planning implementation guidance vector data layer set, the map patches that meet the preset update conditions for land use implementation status are removed, and the remaining map patches that simultaneously meet at least two inefficient use characteristic indicators are identified as a type of improvement guidance. For the basic data of the improvement guidance located outside the boundary of the industrial park, the land use implementation status that meets the preset update conditions is removed, and the remaining land use that meets at least one of the inefficient use characteristic indicators is identified as the second type of improvement guidance. The first type of lift guidance and the second type of lift guidance are merged to form a lift guidance data layer, and the attribute values ​​of lift guidance type and guidance subclass are filled in; The inefficient utilization characteristic indicators include at least one of the following: floor area ratio below a first threshold, employment population density below a second threshold, and revenue per unit area below the average level of the target area.

6. The method according to claim 5, characterized in that, The implementation guidance type includes retention guidance; The steps of overlaying and analyzing the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form the data layer and attribute values ​​corresponding to the implementation guidance type include: After removing the map patches corresponding to the relocation guidance, the conversion guidance, and the upgrading guidance, the remaining existing industrial map patches are determined as the retention guidance. Based on the reserved guidance patches, a reserved guidance data layer is formed, and the attribute values ​​of the reserved implementation guidance type and guidance sub-class are filled in.

7. The method according to any one of claims 1 to 6, characterized in that, The step of merging the data layers and attribute values ​​of the various implementation-oriented types includes: The spatial fusion tool is used to merge the vector layers corresponding to at least two implementation guidance types into a single composite layer. Repair topological errors between merged patches, including overlaps and gaps; Unify the attribute field structure of each vector layer, and standardize and collect the implementation guidance type and the guidance sub-class attribute fields to form a unified target attribute system; The merged layer is validated, duplicate patches are removed and missing attributes are repaired to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

8. An analysis device for guiding the implementation of current industrial land use planning, characterized in that, include: The acquisition module is used to acquire diverse and heterogeneous raw data within the same target area. The diverse and heterogeneous raw data includes at least: land use status data, planning and control data, land use implementation status data, industrial space data, population vitality data, and enterprise economic data; The preprocessing module is used to preprocess the diverse and heterogeneous raw data to obtain a vector data layer of current industrial land and a set of planning implementation guidance vector data layers within the same target area. The analysis module is used to overlay and analyze the existing industrial land vector data layer with the planning implementation guidance vector data layer set to form a data layer and attribute value corresponding to the implementation guidance type; the implementation guidance type includes at least two of the following: relocation, conversion, upgrading and retention; The fusion module is used to merge the data layers and attribute values ​​of the various implementation guidance types to obtain the current industrial land planning implementation guidance analysis result layer and target attribute values ​​covering the target area.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program and the processor running the computer program to cause the electronic device to perform the method of any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores computer program instructions, which, when read and executed by a processor, perform the method described in any one of claims 1 to 7.

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