A gis-based urban building land planning analysis method and system

Abstract

This invention provides a GIS-based urban building and land planning analysis method and system, relating to the field of urban planning and land management information technology. It includes a spatial data version management module for acquiring the GIS spatial dataset and business attribute dataset required for urban building and land planning analysis. This GIS-based urban building and land planning analysis method and system establishes a unified coordinate reference between the GIS spatial dataset and the business attribute dataset, and introduces a data version management mechanism combining baseline and incremental versions. Upon receiving data update events, it performs difference comparisons based on spatial object identifiers to generate accurate change sets. Combined with the analysis dependency graph, it performs incremental recalculation only on the affected analysis subgraphs, achieving rapid updating and traceable management of urban building and land planning analysis results. This avoids repeated calculations of the entire dataset, improving the real-time performance and computational efficiency of planning analysis.

Description

Technical Field

[0001] This invention relates to the field of information technology for urban planning and land management, specifically to a GIS-based method and system for urban building and land planning analysis. Background Technology

[0002] In existing technologies, urban construction and land planning work typically relies on GIS platforms for spatial data management and analysis. By overlaying multiple source layers such as existing land categories, planned land use, roads and pipelines, ecological red lines and protection areas, and using common spatial operators such as buffer analysis, overlay analysis, land use statistics, and accessibility analysis, a foundation is formed for calculating planning indicators, determining land suitability, and demonstrating schemes. In actual practice, tabular calculations, thematic models, or distributed software tools are also used to summarize indicators such as plot ratio, height limit, public service coverage, traffic impact, and municipal carrying capacity, in order to output planning maps, statistical reports, and review materials, providing support for planning management and decision-making.

[0003] However, the aforementioned existing technologies still have obvious shortcomings: insufficient support for dynamic data updates and multi-scenario simulations, making it difficult to support rapid iteration of planning schemes, and thus failing to meet the practical needs of refined planning management and efficient decision-making. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a GIS-based urban building and land planning analysis method and system. The technical problem this invention aims to solve is: how to address the shortcomings of existing technologies in supporting dynamic data updates and multi-scenario simulations, and the difficulty in supporting rapid iteration of planning schemes, by using incremental analysis and orchestration driven by data version management and change sets, combined with a multi-scenario deduction method and process based on scenario difference sets.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a GIS-based urban building and land planning analysis system, comprising: Spatial Data Version Management Module: Used to acquire GIS spatial datasets and business attribute datasets required for urban building and land planning analysis, associate and store the GIS spatial datasets and business attribute datasets according to a unified coordinate benchmark to obtain a unified dataset, and establish a benchmark version and incremental version for the unified dataset to form a traceable data version sequence. The GIS spatial dataset consists of multiple spatial objects, each of which has a corresponding spatial object identifier and geometric information, and is associated with the attribute fields in the business attribute dataset. Dynamic update module: used to receive data update events from at least one data source; obtain the corresponding updated data based on the spatial object identifier carried by the update event, and extract the data corresponding to the same spatial object identifier from the current valid versions of the GIS spatial dataset and the business attribute dataset as comparison data, perform difference comparison on the updated data and the comparison data, the difference comparison includes geometric information differences and attribute field differences, generate a change set containing change type, change object identifier and change content and output it to trigger subsequent incremental analysis; Incremental analysis orchestration module: It is used to pre-build analysis dependency graphs for constraint verification items and evaluation index items required for urban building and land planning analysis. When the change set is received, it determines the analysis subgraphs affected by the change set and the result items to be updated based on the analysis dependency graph. It only performs incremental recalculation on the analysis operators corresponding to the analysis subgraphs, and generates and outputs an updated result set that matches the version number corresponding to the change set. Multi-scenario simulation module: used to create planning scenarios on the baseline version or any incremental version. The planning scenarios are defined by a scenario parameter set and a scenario rule set. The scenario parameter set includes development intensity parameters, land use adjustment parameters and constraint threshold parameters. Based on the planning scenarios, the spatial objects and their corresponding attributes are derived in a scenario-based manner to form corresponding scenario data versions. It also supports branching, copying and rolling back of planning scenarios to achieve parallel simulation and rapid iteration of multiple scenarios. Scenario Evaluation Output Module: This module calls the incremental analysis and orchestration module to obtain an updated result set that matches the version number of the corresponding scenario data version as the evaluation result. It then compares and outputs the evaluation results of different planning scenarios according to preset comparison dimensions and generates a visualization layer and structured analysis results associated with GIS spatial location.

[0006] Preferably, the spatial data version management module records version metadata for each version in the data version sequence. The version metadata includes: version number, generation time, corresponding change set identifier, data source identifier, and version parent-child relationship. The unified dataset is stored in the form of base version + change set, so that any incremental version can be obtained by superimposing the corresponding change set on the corresponding parent version.

[0007] Preferably, the data update event is a structured event, which includes: event type, spatial object identifier, event timestamp, and update data payload. The event type is limited to one of addition, modification, or deletion, and the update data payload includes the geometric information or attribute field values ​​of the spatial object.

[0008] Preferably, when performing the difference comparison, the dynamic update module performs geometric signature comparison after geometric normalization for geometric information differences, and performs field-level item-by-item comparison for attribute field differences. In the change set, it records the changed field name, the value before the change and the value after the change, as well as the type identifier of the geometric information change for each changed object.

[0009] Preferably, the analysis dependency graph is a directed acyclic graph (DAG). The nodes of the DAG include data nodes, operator nodes, and result nodes. The data nodes correspond to the layers or attribute fields in the unified dataset. The operator nodes correspond to preset spatial analysis operators or index calculation operators. The result nodes correspond to the constraint verification items and evaluation index items. The directed edges in the analysis dependency graph are used to represent the dependency relationship from input dependency to output output.

[0010] Preferably, when the incremental analysis orchestration module determines the analysis subgraph affected by the change set, it locates the associated data node based on the change object identifier in the change set, and performs forward propagation along the directed edges of the analysis dependency graph to obtain a set of result items to be updated. The incremental recalculation is performed only on the operator nodes that have a path connection with the set of result items to be updated, and the updated values ​​of the result nodes corresponding to the set of result items to be updated are used to form the updated result set.

[0011] Preferably, the development intensity parameters include plot ratio parameters and building height limit parameters; the land use adjustment parameters include land use change parameters and land parcel division and merging parameters; the constraint threshold parameters include public service facility service radius thresholds and road traffic capacity thresholds; and the scenario rule set includes parameter priority rules, which determine the final effective value when scenario parameters conflict with current attributes.

[0012] Preferably, the contextualized derivation is achieved by generating a contextual difference set, which includes: geometric operation records or attribute coverage records for spatial objects. The geometric operation records include plot segmentation, plot merging, and boundary adjustment. The attribute coverage records include coverage of the plot ratio field, building height limit field, and land use nature field. The contextual data version is obtained by combining the baseline version or incremental version with the contextual difference set.

[0013] A GIS-based urban building and land planning analysis method includes: S1. Obtain the GIS spatial dataset and business attribute dataset required for urban building land planning analysis, associate and store the GIS spatial dataset and business attribute dataset according to a unified coordinate benchmark to obtain a unified dataset, and establish a benchmark version and an incremental version for the unified dataset to form a traceable data version sequence. The GIS spatial dataset consists of multiple spatial objects, each of which has a corresponding spatial object identifier and geometric information, and is associated with the attribute fields in the business attribute dataset. S2. Receive a data update event from at least one data source, obtain the corresponding updated data based on the spatial object identifier carried by the update event, and extract the data corresponding to the same spatial object identifier from the current valid versions of the GIS spatial dataset and the business attribute dataset as comparison data. Perform a difference comparison between the updated data and the comparison data. The difference comparison includes geometric information differences and attribute field differences. Generate a change set containing change type, change object identifier and change content and output it. S3. For the constraint verification items and evaluation index items required for urban building land planning analysis, an analysis dependency graph is pre-constructed; when the change set is received, the analysis subgraphs affected by the change set and the result items to be updated are determined according to the analysis dependency graph, and incremental recalculation is performed only on the analysis operators corresponding to the analysis subgraphs to generate and output an updated result set that matches the version number corresponding to the change set; S4. Create a planning scenario on the baseline version or any incremental version. The planning scenario is defined by a scenario parameter set and a scenario rule set. The scenario parameter set includes development intensity parameters, land use adjustment parameters, and constraint threshold parameters. Based on the planning scenario, the spatial object and its corresponding attributes are derived in a contextualized manner to form a corresponding scenario data version. S5. Call the analysis dependency graph for the scenario data version of each planning scenario to obtain the updated result set that matches the version number of the corresponding scenario data version as the evaluation result; perform difference comparison output on the evaluation results of different planning scenarios according to the preset comparison dimensions, and generate a visualization layer and structured analysis results associated with GIS spatial location.

[0014] This invention provides a GIS-based method and system for urban building and land planning analysis. It offers the following advantages: This GIS-based urban building and land planning analysis method and system establishes a unified coordinate benchmark association between the GIS spatial dataset and the business attribute dataset. It also introduces a data version management mechanism that combines benchmark and incremental versions. When receiving data update events, it performs difference comparison based on spatial object identifiers to generate accurate change sets. Combined with the analysis dependency graph, it performs incremental recalculation only on the affected analysis subgraphs. This enables rapid updating and traceable management of urban building and land planning analysis results, avoids repeated calculations of the entire dataset, and improves the real-time performance and computational efficiency of planning analysis.

[0015] Employing a multi-scenario simulation and scenario difference set-driven analysis approach, this system supports the parallel construction, branching, and rollback of multiple planning scenarios on the same baseline or incremental version. It also calls the incremental analysis orchestration module to generate corresponding evaluation results for each scenario, enabling intuitive comparison of different planning schemes at the spatial location and indicator levels. This is beneficial for assisting planning decisions and improving the flexibility, comparability, and decision support capabilities of urban building and land planning scheme evaluation. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system modules of the present invention; Figure 2 This is a flowchart illustrating the multi-scenario deduction process of the present invention; Figure 3 This is a flowchart of the scenario evaluation and output process of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments 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, and 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.

[0018] Example 1 like Figure 1-3 As shown, this embodiment of the invention provides a GIS-based urban building and land planning analysis system, comprising: The Spatial Data Version Management Module is used to acquire GIS spatial datasets and business attribute datasets required for urban building and land planning analysis. It associates and stores these datasets using a unified coordinate benchmark to create a unified dataset. A baseline version and incremental versions are established for this unified dataset, forming a traceable data version sequence. The GIS spatial dataset consists of multiple spatial objects, each with a corresponding spatial object identifier and geometric information, and is associated with attribute fields in the business attribute dataset. The Spatial Data Version Management Module records version metadata for each version in the data version sequence. This metadata includes: version number, generation time, corresponding changeset identifier, data source identifier, and version parent-child relationship. The unified dataset is stored as a baseline version + changeset, allowing any incremental version to be obtained by overlaying the corresponding changeset onto the corresponding parent version.

[0019] The dynamic update module receives data update events from at least one data source. Based on the spatial object identifier carried in the update event, it retrieves the corresponding updated data and extracts data with the same spatial object identifier from the current valid versions of the GIS spatial dataset and the business attribute dataset as comparison data. It performs a difference comparison between the updated data and the comparison data, including geometric information differences and attribute field differences. It generates and outputs a change set containing the change type, change object identifier, and change content to trigger subsequent incremental analysis. Data update events are structured events, including: event type, spatial object identifier, event timestamp, and update data payload. The event type is limited to one of addition, modification, or deletion. The update data payload includes the geometric information or attribute field values ​​of the spatial object. When performing the difference comparison, the dynamic update module uses geometrically normalized geometric signature comparison for geometric information differences and field-level item-by-item comparison for attribute field differences. In the change set, it records the changed field name, the value before and after the change, and the type identifier of the geometric information change for each changed object.

[0020] The incremental analysis orchestration module is used to pre-construct an analysis dependency graph for constraint verification items and evaluation index items required for urban building and land planning analysis. Upon receiving a change set, it determines the analysis subgraphs affected by the change set and the result items to be updated based on the analysis dependency graph. Incremental recalculation is performed only on the analysis operators corresponding to the analysis subgraphs, generating and outputting an updated result set that matches the version number of the change set. The analysis dependency graph is a directed acyclic graph (DAG). Nodes in the DAG include data nodes, operator nodes, and result nodes. Data nodes correspond to layers or attribute fields in the unified dataset, operator nodes correspond to preset spatial analysis operators or index calculation operators, and result nodes correspond to constraint verification items and evaluation index items. Directed edges in the analysis dependency graph represent the dependency relationship from input to output. When determining the analysis subgraph affected by the change set, the incremental analysis orchestration module locates the associated data nodes based on the change object identifier in the change set, and performs forward propagation along the directed edges of the analysis dependency graph to obtain the set of result items to be updated. Incremental recalculation is only performed on the operator nodes that have a path connection with the set of result items to be updated, and the updated values ​​of the result nodes corresponding to the set of result items to be updated are combined into an updated result set.

[0021] The multi-scenario derivation module is used to create planning scenarios on the baseline version or any incremental version. Planning scenarios are defined by a scenario parameter set and a scenario rule set. The scenario parameter set includes development intensity parameters, land use adjustment parameters, and constraint threshold parameters. Based on the planning scenario, spatial objects and their corresponding attributes are derived in a scenario-based manner to form corresponding scenario data versions. It supports branching, copying, and rolling back of planning scenarios to achieve parallel derivation and rapid iteration of multiple scenarios. Development intensity parameters include plot ratio parameters and building height limit parameters; land use adjustment parameters include land use change parameters and plot splitting / merging parameters; constraint threshold parameters include public service facility service radius thresholds and road capacity thresholds. The scenario rule set includes parameter priority rules, which determine the final effective value when scenario parameters conflict with existing attributes. Scenario derivation is achieved by generating a scenario difference set, which includes geometric operation records or attribute overlay records for spatial objects. Geometric operation records include plot splitting, plot merging, and boundary adjustments; attribute overlay records include overlays on plot ratio, building height limit, and land use fields. The scenario data version is obtained by combining the baseline version or incremental version with the scenario difference set.

[0022] Scenario Assessment Output Module: This module calls the incremental analysis and orchestration module to retrieve the scenario data versions for each planning scenario. It then obtains an updated result set that matches the version number of the corresponding scenario data version as the evaluation result. The module compares the evaluation results of different planning scenarios according to preset comparison dimensions and outputs the results. Finally, it generates a visualization layer and structured analysis results associated with the GIS spatial location.

[0023] A GIS-based urban building and land planning analysis method includes: S1. Obtain the GIS spatial dataset and business attribute dataset required for urban building and land planning analysis. Link and store the GIS spatial dataset and business attribute dataset according to a unified coordinate benchmark to obtain a unified dataset. Establish a benchmark version and an incremental version for the unified dataset to form a traceable data version sequence. The GIS spatial dataset consists of multiple spatial objects. Each spatial object has a corresponding spatial object identifier and geometric information, and is associated with the attribute fields in the business attribute dataset.

[0024] S2. Receive data update events from at least one data source, obtain the corresponding updated data based on the spatial object identifier carried by the update event, and extract the data corresponding to the same spatial object identifier from the current valid versions of the GIS spatial dataset and the business attribute dataset as comparison data. Perform a difference comparison between the updated data and the comparison data. The difference comparison includes geometric information differences and attribute field differences. Generate a change set containing change type, change object identifier and change content and output it.

[0025] S3. For the constraint verification items and evaluation index items required for urban building land planning analysis, an analysis dependency graph is pre-constructed. When a change set is received, the analysis subgraphs affected by the change set and the result items to be updated are determined based on the analysis dependency graph. Incremental recalculation is performed only on the analysis operators corresponding to the analysis subgraphs, generating and outputting an updated result set that matches the version number corresponding to the change set.

[0026] S4. Create a planning scenario on the baseline version or any incremental version. The planning scenario is defined by a scenario parameter set and a scenario rule set. The scenario parameter set includes development intensity parameters, land use adjustment parameters, and constraint threshold parameters. Based on the planning scenario, spatial objects and their corresponding attributes are derived in a contextualized manner to form corresponding scenario data versions.

[0027] S5. Analyze the dependency graph of scenario data versions for each planning scenario, and obtain the updated result set that matches the version number of the corresponding scenario data version as the evaluation result. Compare the evaluation results of different planning scenarios according to preset comparison dimensions, and generate a visualization layer and structured analysis results associated with GIS spatial location.

[0028] By implementing versioned management of GIS spatial data and business attribute data, and using change sets as the driving force for incremental analysis and multi-scenario simulation, the planning analysis process only performs recalculation on the analysis units affected by data changes or scenario differences, avoiding full duplication of calculations, reducing computing resource consumption and improving analysis response efficiency. At the same time, by establishing the correspondence between data versions, change sets, analysis results and planning scenarios, the consistency, traceability and auditability of planning analysis results are enhanced. On this basis, efficient reuse of analysis results and output of differences under multiple planning scenarios are realized, enabling the adjustment and demonstration of planning schemes to be carried out in an incremental and iterative manner, and improving the clarity of the spatial expression and decision support capabilities of planning analysis results.

[0029] Example 2 This embodiment illustrates the process by which the incremental analysis and orchestration module determines the affected analysis subgraphs based on the change set and analysis dependency graph when a local change occurs in the plot ratio, and performs incremental calculations on the relevant analysis operators to obtain the corresponding planning verification results.

[0030] 1. Baseline version data source and initial calculation This embodiment is based on the implementation of a dynamic adjustment project of the detailed control plan for the central urban area of ​​a prefecture-level city. The planning analysis area is approximately 62.4 km², and the unified dataset is sourced from the 2025 planning database of the natural resources authority.

[0031] The unified dataset contains 14 GIS spatial layers, among which the land parcel layer contains 12,836 land parcel spatial objects. Each parcel has a unique ID and is associated with attribute fields such as area, floor area ratio, and building height limit.

[0032] The system uses the control plan approved in June 2025 as the baseline version. In the baseline version, the geometric area of ​​each plot in the plot layer is recorded. The plot area is obtained through GIS geometric calculation, and the calculation method is the planar projected area, with the unit being square meters.

[0033] Taking the three plots of land involved in this embodiment as an example, the data of the baseline version is as follows: Table 1: Data table related to the benchmark version of the land parcel.

[0034] The system calculates the permitted building size of the plot according to the following rules under the baseline version: Therefore, we can conclude that: P10235: P10876: P10902: .

[0035] The above results serve as the upper limit for the benchmark building size and are used for subsequent verification of floor area ratio compliance.

[0036] 2. Data updates triggered by planning adjustments During the planning and demonstration process, the planners proposed to increase the development intensity of the above three plots based on the comprehensive development needs around the rail transit stations.

[0037] On January 18, 2026, the business system sent a structured data update event to this system. The event type was modification, and the event explicitly provided the ID and the updated floor area ratio value. Table 2: Structured data update event volume ratio value data table.

[0038] The update event did not include a geometric data payload, and the system therefore confirmed that the parcel's geometric information remained unchanged.

[0039] 3. Change set generation and analysis subgraph determination The dynamic update module performs a field-level comparison between the updated data and the data in the baseline version to confirm that only the plot ratio field has changed, and generates a changeset.

[0040] The change set records each item individually: spatial object identifier, changed field name, value before change, and value after change.

[0041] After receiving the change set, the incremental analysis orchestration module locates the associated data nodes in the analysis dependency graph based on the change fields, and determines the affected analysis subgraphs along the dependency path.

[0042] Analysis revealed that only the building scale calculation operator and the floor area ratio compliance verification operator need to be updated, without involving the analysis of public service facility coverage or road capacity.

[0043] 4. Incremental calculation process and basis The incremental analysis orchestration module only performs recalculation on the three plots involved in the change set, and the recalculation adopts the same calculation rules as the baseline version.

[0044] The updated building size calculation is as follows: P10235: P10876: P10902: .

[0045] At the same time, the system reads the planned building scale data of the corresponding plot from the business attribute dataset: Table 3: Data on the planned building scale of the land parcel.

[0046] The incremental analysis and orchestration module performs floor area ratio compliance verification according to the following judgment rules: If the planned building size is less than or equal to the permitted building size, it is considered compliant; if the planned building size is greater than or equal to the permitted building size, it is considered non-compliant.

[0047] Based on this, the verification result is as follows: P10235: 18500≤20000, deemed compliant; P10876: 15800≤16250, deemed compliant; P10902: 10300>10000, deemed non-compliant.

[0048] 5. Results Output and Version Updates The system associates the above incremental analysis results with the change set, and generates a new incremental version based on the data version number corresponding to the change set, while outputting an update result set that matches the incremental version number.

[0049] The updated results set only includes the plot ratio verification results for 3 plots; the remaining 12,833 plots that have not changed continue to use the analysis results of the baseline version.

[0050] In this embodiment, the incremental analysis orchestration module performs building scale estimation and plot ratio verification operators only on 3 plots. Compared with the full analysis, which performs the same calculations on 12,836 plots, the calculation scale is reduced, and the analysis results correspond one-to-one with the actual adjustment process of the planning business.

[0051] As can be seen from the above implementation process, in the case where only the plot ratio field of the land parcel is partially changed, the system generates corresponding planning verification results for the three land parcels included in the change set. The verification results of two land parcels are compliant, and the verification result of one land parcel is non-compliant. The verification results are associated with the corresponding data version number and output. The analysis results of the remaining land parcels that have not been changed remain unchanged.

[0052] Example 3 This embodiment illustrates how, within the influence range of rail stations, when the development intensity of local residential land is adjusted in a scenario-based manner based on a multi-scenario simulation module, the system can quantitatively analyze changes in building scale and public service facility coverage indicators while keeping the baseline data unchanged.

[0053] 1. Baseline data and initial state This embodiment uses the current control detailed planning database of a certain city's planning and resources department as the data source. The database comes from the approved planning results, and the data update time is November 18, 2023.

[0054] After loading the database into the GIS environment, a research area with a radius of 600m centered on a certain station of Metro Line 4 was selected to form a planning analysis area. The total area of ​​the area was calculated to be 1.082 km².

[0055] Within the scope of the study, a total of 327 land parcel spatial objects were extracted, and the corresponding land use, plot ratio, and building height limit fields were read from the business attribute dataset. Among them: There are 193 residential land parcels, with a total area of ​​62.14 hm². Each parcel corresponds to a land parcel spatial object with a unique spatial object identifier. There are 69 commercial and service land parcels and 65 public service facilities and other land parcels.

[0056] In the baseline version, the plot ratio field for residential land ranges from 2.4 to 2.9, with approximately 71% of the residential land having a building height limit of 80m.

[0057] 2. Planning Scenario Setting According to the technical guidelines for special planning of rail transit, the area within 300m of rail stations can be designated as a key development intensity adjustment zone.

[0058] Therefore, a 300m buffer zone was constructed in the GIS with the station entrance and exit as the center, and spatial intersection analysis was performed on the residential land spatial objects to screen out 61 residential land parcels located within the buffer zone.

[0059] According to statistics, the total area of ​​the 61 residential land parcels is 21.36 hm², and the average plot ratio of the benchmark version is 2.72.

[0060] 3. Scenario parameter setting and calculation method Create planning scenario 1 on the baseline version, and set the scenario parameter set as follows: Floor area ratio parameter: The similar implemented areas are residential areas around rail stations that have been approved for implementation. The floor area ratio of residential land in the control detailed plan is between 3.2 and 3.6, which is derived from the statistical results of approved implemented areas in the planning database.

[0061] Based on the control planning indicators of similar areas already implemented around the rail station, 3.4 was selected as the unified plot ratio adjustment value.

[0062] Building height limit parameters: In accordance with the requirements for urban skyline control, the building height limit has been adjusted from the original 80m to 100m.

[0063] Rule Explanation: When a scenario parameter conflicts with a baseline attribute, the scenario parameter shall override the original field value.

[0064] 4. Contextualized Derivation and Data Version Formation The multi-scenario simulation module generates a scenario difference set S1 corresponding to planning scenario 1 for the aforementioned 61 residential land parcels, specifically including: 61 attribute coverage records were generated for the plot ratio field and 61 attribute coverage records were generated for the building height limit field.

[0065] The scenario data version is formed by combining the baseline version and the scenario difference set S1. The remaining 266 land parcels do not participate in the derivation of this scenario and still use the baseline version data.

[0066] 5. Quantitative calculation basis for changes in building scale In the baseline version, the theoretical maximum building size for residential land within 300m of a rail station is calculated as follows: In the scenario version, the corresponding residential land building scale is calculated as follows: Therefore, the newly added residential building area under scenario 1 is approximately 145,000 m².

[0067] The above building scale is a theoretical calculation result under planning constraints, without considering the current status of existing buildings and phased construction factors.

[0068] 6. Sources of calculation for public service facility coverage results Using a service radius of 500m for primary schools as a constraint threshold, a service area buffer surface was constructed for the existing primary school locations in GIS. Spatial coverage analysis was then performed on the residential land in the baseline and scenario versions. The primary school locations were derived from the public service facilities layer in the same regulatory detailed planning database, and a total of 6 primary school locations were included within the study area.

[0069] Statistical results show that the coverage rate statistics use the number of residential land parcels as the statistical object: In the baseline version, 182 residential land parcels were covered by the service radius of the primary school, accounting for 193 of the total residential land parcels within the study area. In the scenario version, 177 residential land parcels are covered by the service radius of the primary school, accounting for [percentage missing]. .

[0070] Among them, the five residential land parcels not covered by the primary school service radius are located outside the buffer zone of the primary school service radius, but still meet the minimum control requirements for planning management.

[0071] The above scenario simulation results are output in the form of a structured analysis result set with the corresponding version number, and a building scale change layer and a public service facility coverage change layer are generated simultaneously for planning scheme demonstration and decision support.

[0072] Through the above steps, the analysis results show that the impact range and degree of change of the local development intensity adjustment on the planning indicators are accurately reflected, providing clear data support for the comparison and demonstration of planning schemes, and demonstrating the feasibility of the multi-scenario simulation module in planning adjustment scenarios.

[0073] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A GIS-based urban building and land planning analysis system, characterized in that, include: Spatial Data Version Management Module: Used to acquire GIS spatial datasets and business attribute datasets required for urban building and land planning analysis, associate and store the GIS spatial datasets and business attribute datasets according to a unified coordinate benchmark to obtain a unified dataset, and establish a benchmark version and incremental version for the unified dataset to form a traceable data version sequence. The GIS spatial dataset consists of multiple spatial objects, each of which has a corresponding spatial object identifier and geometric information, and is associated with the attribute fields in the business attribute dataset. Dynamic update module: Used to receive data update events from at least one data source; Based on the spatial object identifier carried by the update event, obtain the corresponding update data, and extract the data corresponding to the same spatial object identifier from the current valid versions of the GIS spatial dataset and the business attribute dataset as comparison data. Perform a difference comparison between the update data and the comparison data. The difference comparison includes geometric information differences and attribute field differences. Generate a change set containing change type, change object identifier and change content and output it. Incremental analysis orchestration module: It is used to pre-build analysis dependency graphs for constraint verification items and evaluation index items required for urban building and land planning analysis. When the change set is received, it determines the analysis subgraphs affected by the change set and the result items to be updated based on the analysis dependency graph. It only performs incremental recalculation on the analysis operators corresponding to the analysis subgraphs, and generates and outputs an updated result set that matches the version number corresponding to the change set. Multi-scenario simulation module: used to create planning scenarios on the baseline version or any incremental version. The planning scenarios are defined by a scenario parameter set and a scenario rule set. The scenario parameter set includes development intensity parameters, land use adjustment parameters and constraint threshold parameters. Based on the planning scenarios, the spatial objects and their corresponding attributes are derivation into scenarios to form corresponding scenario data versions. Scenario Evaluation Output Module: This module calls the incremental analysis and orchestration module to obtain an updated result set that matches the version number of the corresponding scenario data version as the evaluation result. It then compares and outputs the evaluation results of different planning scenarios according to preset comparison dimensions and generates a visualization layer and structured analysis results associated with GIS spatial location.

2. The GIS-based urban building and land planning analysis system according to claim 1, characterized in that: The spatial data version management module records version metadata for each version in the data version sequence. The version metadata includes: version number, generation time, corresponding change set identifier, data source identifier, and version parent-child relationship. The unified dataset is stored in the form of base version + change set, so that any incremental version can be obtained by superimposing the corresponding change set on the corresponding parent version.

3. The GIS-based urban building and land planning analysis system according to claim 1, characterized in that: The data update event is a structured event, which includes: event type, spatial object identifier, event timestamp, and update data payload. The event type is limited to one of addition, modification, or deletion, and the update data payload includes the geometric information or attribute field values ​​of the spatial object.

4. The GIS-based urban building and land planning analysis system according to claim 1, characterized in that: When performing the difference comparison, the dynamic update module uses geometric signature comparison after geometric normalization for geometric information differences, and uses field-level item-by-item comparison for attribute field differences. In the change set, it records the changed field name, the value before the change and the value after the change, as well as the type identifier of the geometric information change for each changed object.

5. The GIS-based urban building and land planning analysis system according to claim 1, characterized in that: The analysis dependency graph is a directed acyclic graph (DAG). The nodes of the DAG include data nodes, operator nodes, and result nodes. The data nodes correspond to the layers or attribute fields in the unified dataset. The operator nodes correspond to the preset spatial analysis operators or index calculation operators. The result nodes correspond to the constraint verification items and evaluation index items. The directed edges in the analysis dependency graph are used to represent the dependency relationship from input to output.

6. The GIS-based urban building and land planning analysis system according to claim 5, characterized in that: When determining the analysis subgraph affected by the change set, the incremental analysis orchestration module locates the associated data nodes based on the change object identifier in the change set, and performs forward propagation along the directed edges of the analysis dependency graph to obtain a set of result items to be updated. The incremental recalculation is performed only on the operator nodes that have a path connection with the set of result items to be updated, and the updated values ​​of the result nodes corresponding to the set of result items to be updated are used to form the updated result set.

7. The GIS-based urban building and land planning analysis system according to claim 1, characterized in that: The development intensity parameters include plot ratio parameters and building height limit parameters; the land use adjustment parameters include land use change parameters and land parcel division and merging parameters; the constraint threshold parameters include public service facility service radius threshold and road traffic capacity threshold; and the scenario rule set includes parameter priority rules, which determine the final effective value when scenario parameters conflict with current attributes.

8. The GIS-based urban building and land planning analysis system according to claim 1, characterized in that: The contextualized derivation is achieved by generating a contextual difference set, which includes: geometric operation records or attribute coverage records for spatial objects. The geometric operation records include plot splitting, plot merging, and boundary adjustment. The attribute coverage records include coverage of the plot ratio field, building height limit field, and land use nature field. The contextual data version is obtained by combining the baseline version or incremental version with the contextual difference set.

9. A GIS-based urban building and land planning analysis method, implemented according to the GIS-based urban building and land planning analysis system described in claim 8, characterized in that... include: S1. Obtain the GIS spatial dataset and business attribute dataset required for urban building land planning analysis, associate and store the GIS spatial dataset and business attribute dataset according to a unified coordinate benchmark to obtain a unified dataset, and establish a benchmark version and an incremental version for the unified dataset to form a traceable data version sequence. The GIS spatial dataset consists of multiple spatial objects, each of which has a corresponding spatial object identifier and geometric information, and is associated with the attribute fields in the business attribute dataset. S2. Receive a data update event from at least one data source, obtain the corresponding updated data based on the spatial object identifier carried by the update event, and extract the data corresponding to the same spatial object identifier from the current valid versions of the GIS spatial dataset and the business attribute dataset as comparison data. Perform a difference comparison between the updated data and the comparison data. The difference comparison includes geometric information differences and attribute field differences. Generate a change set containing change type, change object identifier and change content and output it. S3. Pre-construct an analysis dependency graph for the constraint verification items and evaluation index items required for urban building and land planning analysis; Upon receiving the change set, the analysis subgraphs affected by the change set and the result items to be updated are determined based on the analysis dependency graph. Incremental recalculation is performed only on the analysis operators corresponding to the analysis subgraphs, and an update result set matching the version number corresponding to the change set is generated and output. S4. Create a planning scenario on the baseline version or any incremental version. The planning scenario is defined by a scenario parameter set and a scenario rule set. The scenario parameter set includes development intensity parameters, land use adjustment parameters, and constraint threshold parameters. Based on the planning scenario, the spatial object and its corresponding attributes are derived in a contextualized manner to form a corresponding scenario data version. S5. For each of the planning scenarios, call the analysis dependency graph to obtain an updated result set that matches the version number of the corresponding scenario data version as the evaluation result; The evaluation results of different planning scenarios are compared and output according to the preset comparison dimensions, and a visualization layer and structured analysis results associated with GIS spatial location are generated.

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