An intelligent analysis system for national space planning

Abstract

This invention discloses an intelligent analysis system for territorial spatial planning, relating to the field of territorial spatial planning systems. It includes a data processing module, a planning analysis module, and further includes a module for intelligent transformation and implementation matching of public demands, a module for hierarchical planning tolerance and redundancy design, a module for full-node embedded compliance and emergency dual verification, and a self-learning dynamic adaptation closed-loop module for planning implementation. This invention constructs an intelligent analysis system covering the entire process of territorial spatial planning, from preparation and implementation to optimization. Under the premise of strictly adhering to legally mandated rigid control red lines, it resolves the contradiction between the rigid constraints and dynamic adaptation of traditional planning through four core mechanisms: intelligent transformation of demands, hierarchical flexible control, full-node dual verification, and self-learning closed-loop. This fundamentally solves the industry pain points of disconnect between planning and implementation and insufficient response to dynamic demands, significantly improving the intelligence level of territorial spatial planning and greatly shortening the planning preparation and adjustment cycle.

Description

Technical Field

[0001] This invention relates to the field of land and space planning systems, specifically to an intelligent analysis system for land and space planning. Background Technology

[0002] Currently, the core problem with existing planning analysis systems in the field of territorial spatial planning is that they cannot achieve dynamic adaptation and closed-loop management of the entire process of planning preparation, implementation, and adjustment while strictly adhering to the legally mandated rigid control red lines of territorial space. Most existing systems only cover basic data processing in the planning preparation stage and single compliance verification after the plan is finalized. They cannot quantify and transform dynamic factors throughout the entire lifecycle, such as public demands, changes in project implementation, and emergency response needs for sudden disasters, into planning optimization bases that meet legal requirements. Nor have they established a hierarchical and flexible adjustment mechanism that matches control requirements. As a result, approved planning schemes cannot quickly respond to various dynamic needs during implementation, frequently resulting in pain points such as a disconnect between planning and actual implementation, high rework costs for compliance modifications, and insufficient planning adaptability in emergency scenarios. They cannot meet the actual application needs for refined and intelligent management and control throughout the entire lifecycle of territorial spatial planning. Summary of the Invention

[0003] Based on this, the purpose of this invention is to provide an intelligent analysis system for land and space planning, so as to solve the technical problems that existing land and space planning analysis systems lead to a disconnect between planning schemes and actual implementation, and insufficient response capabilities to various dynamic demands.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent analysis system for land and space planning, including a data processing module, a planning analysis module, and also including a public demand intelligent transformation and implementation matching module, a planning hierarchical fault tolerance and redundancy design module, a full-node embedded compliance and emergency dual verification module, and a planning implementation self-learning dynamic adaptation closed-loop module; The data processing module is communicatively connected to the planning and analysis module, and also unidirectionally communicates with the four newly added modules mentioned above, so as to output a unified spatiotemporally anchored basic dataset for the entire system. The public demand intelligent transformation and implementation matching module extracts implementable demands and transforms them into flexible optimization indicators, which are then transmitted synchronously to the other modules. The tolerance planning hierarchical fault-tolerant redundancy design module generates hierarchical flexible reserved space and unlocking rules, which are then transmitted synchronously to the other modules. The full-node embedded compliance and emergency dual verification module conducts dual verification synchronously at all planning nodes, and the results drive the solution iteration. The planning implementation self-learning dynamic adaptation closed-loop module realizes dynamic adjustment of the plan and self-learning optimization of the whole system model, forming a closed-loop management of the entire life cycle.

[0005] The data processing module has a built-in multi-source data unified spatiotemporal anchoring module. This module is used to collect multi-source data such as satellite remote sensing images, five-level statutory planning results, and disaster risks. After completing the coordinate and format standardization, it anchors the spatial, attribute, and temporal information of all data to the corresponding geographic entities, using the unique geographic entity code as the core. It outputs a basic dataset of unified spatiotemporal anchoring across the entire domain and transmits it synchronously to all other modules of the system.

[0006] The intelligent conversion and implementation matching module for public demands has a built-in sub-module for demand spatial matching and feasibility pre-verification. This sub-module is used to perform semantic extraction and spatial positioning of public demands collected from multiple channels, anchor the demands to corresponding geographical entities and plots, and complete feasibility verification with legal rigid constraints as the boundary. After prioritizing valid demands according to popularity and scope of impact, the demands are converted into elastic optimization indicators with corresponding weights. At the same time, the spatial positioning results of the demands are transmitted to the planning hierarchical fault tolerance and redundancy design module.

[0007] The planning and analysis module has a built-in sub-module for synchronous generation and pre-verification of multi-scenario solutions. This sub-module uses a unified spatiotemporally anchored basic dataset as its foundation, takes the rigid legal requirements of the higher level as inviolable boundaries, and combines flexible optimization indicators and hierarchical flexible reserved space parameters to automatically generate three sets of differentiated planning schemes. Each scheme corresponds to different development scenarios and flexible activation rules. During the generation process, dual verification and pre-verification are completed simultaneously. When outputting, the completion status of indicators, the degree of matching of demands, emergency adaptability and applicable scenarios are marked.

[0008] The planning-level fault-tolerant redundancy design module incorporates a rigid and flexible dynamic adaptation and level locking sub-module. This sub-module automatically calculates the area, layout, and level of flexible reserve plots, as well as the level floating threshold of rigid indicators, based on the regional rigid constraint margin, demand implementation requirements, and disaster risk level. Simultaneously, it sets differentiated unlocking rules for different levels of flexible spaces: Level 1 spaces are used for routine minor adjustments to people's livelihoods without higher-level approval; Level 2 spaces are used for major project implementation requiring verification and activation at the current level; and Level 3 spaces are used for major disasters requiring full-level verification and approval. The level unlocking rules are simultaneously transmitted to the dual-verification module.

[0009] The full-node embedded compliance and emergency dual-verification module has a built-in fixed and dynamic dual-mode verification triggering sub-module. The fixed and dynamic dual-mode verification triggering sub-module automatically triggers dual verification at four fixed nodes: basic data import for planning, generation of initial draft of the plan, modification and optimization of the plan, and finalization of the results. At the same time, a dynamic triggering mechanism is set up so that when the user modifies any content of rigid boundary, flexible space, or emergency layout, a special dual verification is triggered in real time. The verification results are synchronized to the planning analysis module in real time to complete the local correction. The verification rules are automatically adapted according to the priority of the request and the regional risk level.

[0010] The full-node embedded compliance and emergency dual-verification module incorporates a full-level traceability compliance verification sub-module. This sub-module connects to the five-level statutory planning results, verifying not only whether the current level of planning has exceeded the three control lines and rigid indicators, but also tracing back to the higher-level planning indicators to break down the entire chain and verify whether adjustments at the current level affect the implementation of rigid constraints at the higher level. It spatially locates and marks non-compliant content across the entire chain, outputs modification suggestions, and simultaneously feeds back the results of high-frequency conflict areas to the planning hierarchical fault tolerance redundancy design module to optimize the elastic parameters of the corresponding areas.

[0011] The full-node embedded compliance and emergency dual-verification module includes a multi-hazard coupling scenario simulation verification submodule. This submodule connects to regional multi-hazard risk data, simulates extreme scenarios of single-hazard and multi-hazard coupling, and verifies whether the emergency facility layout in the planning scheme meets the requirements of extreme scenarios and avoids high-risk areas. It also verifies the emergency activation feasibility of the corresponding area's flexible reserve land. The verification results are fed back to the public demand module, automatically increasing the priority of emergency-related demands in high-risk areas, and are also fed back to the planning analysis module to optimize the emergency layout.

[0012] The planning and implementation self-learning dynamic adaptation closed-loop module incorporates a full-process closed-loop self-learning optimization sub-module. This sub-module is used to connect with monitoring data, new requests, and information on sudden disasters during the planning and implementation process, and to track implementation deviations in real time. When deviations, new requests, or emergencies occur, the module automatically matches the corresponding level of elasticity space to dynamically adjust the solution without breaking rigid constraints. The adjustment process triggers dual verification simultaneously. At the same time, the full-process data of each adjustment is recorded in the self-learning database, automatically optimizing the parameters of the entire system model and updating them synchronously to all front-end modules, thereby achieving iterative upgrades of system capabilities.

[0013] The system also includes a full-link traceability visualization and interactive module. This module communicates with all other modules in the system and is used to visualize basic data, demand distribution, planning schemes, verification results, flexible spatial distribution, and implementation progress through two-dimensional maps, three-dimensional scenes, and statistical charts. It also allows users to directly adjust land parcels, modify parameters, and configure scenarios within the interface. During the adjustment process, the impact of the operation on rigid constraints, demand matching degree, and emergency response capabilities is displayed in real time. The system supports full-link traceability for any indicator or land parcel and allows for one-click export of standardized planning results that meet legal approval requirements. In summary, the present invention has the following main advantages: It constructs an intelligent analysis system covering the entire process of land and space planning, including preparation, implementation, and optimization. Under the premise of strictly adhering to legally mandated rigid control red lines, it addresses the core contradiction of the difficulty in balancing rigid constraints and dynamic adaptation in traditional planning through four core mechanisms: intelligent transformation of demands, hierarchical flexible control, dual verification at all nodes, and self-learning closed loop. This system streamlines the entire lifecycle management of planning, fundamentally solving the industry pain points of disconnect between planning and implementation and insufficient dynamic demand response. It significantly improves the intelligence level, compliance, and emergency resilience of land and space planning, greatly shortens the planning preparation and adjustment cycle, and possesses significant industry application value. Detailed Implementation

[0014] The embodiments of the present invention will now be described.

[0015] The intelligent analysis system for land and space planning of the present invention includes a data processing module, a planning analysis module, a public demand intelligent transformation and implementation matching module (hereinafter referred to as the public demand module), a planning hierarchical fault tolerance and redundancy design module (hereinafter referred to as the fault tolerance and redundancy module), a full-node embedded compliance and emergency dual verification module (hereinafter referred to as the dual verification module), a planning implementation self-learning dynamic adaptation closed-loop module (hereinafter referred to as the closed-loop module), and a full-link traceable visual interaction module.

[0016] The intelligent analysis system for this country's spatial planning uses a unified spatiotemporally anchored basic dataset output by the data processing module as its underlying foundation. It achieves intelligent transformation of people's livelihood needs through the public demand module, constructs a hierarchical and flexible management and control system through the fault tolerance and redundancy module, generates multi-scenario differentiated planning schemes through the planning analysis module, completes dual verification of compliance and emergency response capabilities throughout the entire process through the dual verification module, realizes dynamic adjustment and system self-learning optimization in the planning implementation stage through the closed-loop module, and finally realizes full-process human-computer interaction and output of results through the visualization interaction module.

[0017] The data processing module has a built-in multi-source data unified spatiotemporal anchoring module, which is the underlying data support unit of the entire system.

[0018] Multi-source data acquisition scope: The multi-source data collected by the submodule includes, but is not limited to: spatial imagery data: aerial photography images with a resolution of 0.5 meters to 2 meters, remote sensing images from domestic satellites such as GF-2 / GF-6, and oblique photogrammetric 3D real-world data; statutory planning data: statutory approval results of national, provincial, municipal, county, and township-level overall territorial spatial plans, detailed plans, and related special plans; risk management data: multi-hazard risk data such as geological disaster risk zoning, flood inundation lines, earthquake fault zones, and forest fire risk zoning, and vector control data of the three control lines (ecological protection red line, permanent basic farmland, and urban development boundary); related business data: national population census data, economic and social development statistics, land ownership data, project approval data, and historical data of government requests, etc.

[0019] Standardized processing rules: All collected data are uniformly converted to the 2000 National Geodetic Coordinate System (CGCS2000) and the 1985 National Elevation Datum. Vector data is uniformly converted to GDB / SHP format, raster data is uniformly converted to TIFF format, and attribute data is uniformly converted to GeoJSON format to eliminate coordinate deviations, format barriers, and semantic differences between multi-source data.

[0020] Unified spatiotemporal anchoring mechanism: Strictly following the Ministry of Natural Resources' "Classification and Coding Rules for Geographic Entities", a unique and permanent geographic entity code is assigned to every geographic entity (plot, building, road, municipal facility, control unit, etc.) in the entire region. With this unique code as the core, the spatial coordinate information, attribute control information, and time version information of all data are anchored to the corresponding geographic entity, constructing a unified spatiotemporal anchoring basic dataset that integrates space, attributes, and time. The dataset is divided into three sub-databases: spatial database, attribute database, and time series database, enabling one-click retrieval of full-dimensional information for any geographic entity.

[0021] Data synchronization mechanism: The basic dataset is transmitted to all other modules of the system in real time through the Kafka distributed message queue and RESTful API interface, ensuring that the data of the whole system is from the same source, standardized and updated in real time, avoiding planning deviations caused by inconsistencies in data of multiple modules.

[0022] The intelligent transformation and implementation matching module for public demands has a built-in sub-module for demand spatial matching and feasibility pre-verification. It is the core unit for realizing the people-oriented planning. Its core function is to transform scattered public demands into quantitative and flexible optimization indicators that can be incorporated into the planning process.

[0023] Multi-channel demand collection: The sub-module connects to multiple channels such as the 12345 government service hotline, the People's Daily Online leadership message board, the online and offline message system for planning publicity, the community survey questionnaire system, and the petition business system to collect all public demands related to land and space planning. It supports automatic recognition and conversion of demands in multiple formats such as text, voice, and images.

[0024] Intelligent semantic extraction and spatial positioning: Based on a finely tuned Chinese BERT large language model, semantic segmentation and core element extraction are performed on the appeal text to accurately identify the appeal type (people's livelihood support, traffic optimization, ecological protection, emergency support, industrial development, etc.), spatial location description, appeal subject, urgency level and other core information; through a self-developed address matching model and geocoding API, the text address description is converted into spatial coordinates in the CGCS2000 coordinate system, accurately anchored to the corresponding geographic entity and land use planning control unit, to achieve accurate mapping between appeal and space.

[0025] Rigid boundary verification for feasibility: The three control lines determined by the five-level statutory plan and the rigid control indicators issued by the superior are the inviolable boundaries. The feasibility of the request is automatically verified: If the spatial location corresponding to the request falls in the rigid prohibited construction zone, or if the content of the request directly exceeds the statutory rigid indicators, it is directly determined as a non-feasible request, and the reasons for non-feasibility and policy basis are output simultaneously; if the request is located in the flexible control zone and does not exceed the rigid constraints, it is determined as a valid request.

[0026] Priority ranking and flexible indicator conversion: For valid requests, a weighted algorithm is used to calculate priority weights. The weight calculation formula is: Priority Weight = 0.4 × Popularity Normalized Value + 0.4 × Impact Scope Normalized Value + 0.2 × Urgency Normalized Value. Popularity refers to the number of people making the same request and the number of repetitions; impact scope refers to the number of plots covered by the request and the number of beneficiaries; and urgency is automatically assigned based on the request type (emergency support > basic livelihood needs > routine optimization). After ranking by priority weight, the requests are converted into flexible optimization indicators with corresponding weights. For example, the request for "adding community elderly care facilities in XX community" is converted into the flexible optimization indicator "elderly care facility coverage rate within a 15-minute living circle ≥ 98%". The priority weight corresponds to the weight coefficient of the indicator.

[0027] Data synchronization mechanism: The transformed flexible optimization indicators are synchronized to the planning and analysis module in real time, and the spatial positioning results of the demands and the data of high-frequency demand areas are synchronously transmitted to the planning hierarchical fault tolerance and redundancy design module to provide a basis for flexible spatial layout.

[0028] The planning hierarchical fault tolerance redundancy design module has built-in rigid and flexible dynamic adaptation and hierarchical locking sub-modules. It is the core unit to solve the contradiction between rigid constraints and dynamic adaptation in planning. Its core function is to build a hierarchical control flexible reservation system and differentiated unlocking rules.

[0029] Core input parameters: The input parameters of the sub-module include: regional rigid constraint margin (the remaining quota of rigid indicators such as the scale of construction land and the amount of cultivated land allocated by the superior), public demand implementation needs (spatial distribution of high-frequency demands and the land use needs corresponding to the demands), and regional disaster risk level (division and spatial distribution of high, medium and low risk areas).

[0030] Automatic calculation rules for flexible reserve land parcels: The submodule automatically calculates the total size, layout, and classification of flexible reserve land parcels. Total scale: 2%-5% of the total urban construction land within the urban development boundary is reserved. The reservation ratio for high-risk areas and areas with high frequency of public concerns is increased by 0.5%-1%. The total amount of reservation shall not exceed the flexible space control requirements determined by the higher-level plan. Layout: Prioritize the layout in flexible development zones and special-purpose zones within the urban development boundary, strictly avoid the three control lines, and prioritize proximity to areas with high frequency of public demands and high-risk emergency needs to ensure the accessibility of demand implementation and emergency activation; Tiering: The flexible reserve land parcels are divided into three levels: Level 1, Level 2, and Level 3, with clear distinctions in their functional positioning, scale proportion, and unlocking rules.

[0031] Tiered flexibility and unlocking rules: Level 1 Flexible Space: The scale accounts for 30%-40% of the total scale of flexible reserve land. The land use type is urban community supporting land, small green space, and transportation micro-transformation land. The function is positioned for minor adjustments to daily livelihood demands. The unlocking rules are: only internal verification by the corresponding business department of the local natural resources authority is required, no higher-level administrative approval is required, the adjustment range does not exceed the approved area of ​​the land parcel, and does not exceed the rigid control indicators of the local level. Secondary flexible space: accounting for 40%-50% of the total flexible reserve land, the land use type is industrial supporting land and reserved land for major infrastructure, and the function is to ensure the landing of major projects; the unlocking rules are: it needs to be reviewed and approved by the planning committee at the same level, complete the dual verification of compliance and emergency response at the same level, and be filed with the superior competent department before it can be used, without having to start the full statutory approval process for planning adjustment; Level 3 Flexible Space: This area accounts for 10%-20% of the total flexible reserve land area. The land use types are reserved land for emergency shelters, reserved land for disaster prevention channels, and temporary land for post-disaster reconstruction. The layout is strictly limited to low-risk areas for geological disasters and areas above the 100-year flood inundation line. The function is positioned for emergency response to major and catastrophic disasters. The unlocking rules are as follows: It must be jointly initiated by the local government's emergency command center and the natural resources department, and complete the compliance and emergency dual verification at all levels (local, municipal, and provincial). It can be activated after being approved by the higher-level people's government. The legal procedures for planning adjustment must be completed within 6 months after the disaster ends.

[0032] Rigid Indicator Tiered Floating Thresholds: Tiered floating thresholds are set simultaneously for core rigid indicators. The first-level floating threshold is ±0.5%, corresponding to the activation of the first-level elastic space; the second-level floating threshold is ±2%, corresponding to the activation of the second-level elastic space; and the third-level floating threshold is ±5%, corresponding to the emergency activation of the third-level elastic space. The total floating amount shall not exceed the total scale of rigid indicators issued by the superior.

[0033] Data synchronization mechanism: The hierarchical flexible reserved space parameters are synchronized to the planning and analysis module in real time, and the hierarchical unlocking rules and floating thresholds are synchronously transmitted to the full-node embedded compliance and emergency dual verification module to provide a basis for verification rule adaptation.

[0034] The planning and analysis module has a built-in multi-scenario solution synchronous generation and pre-verification sub-module, which is the core solution generation unit of the system. Its core function is to generate compliant and highly adaptable differentiated planning solutions based on a unified data base, rigid constraints, flexible indicators and reserved space.

[0035] The core boundary of the solution generation is based on the unified spatiotemporal anchoring basic dataset output by the data processing module, and the three control lines and rigid control indicators determined by the higher-level statutory plan are the red line boundaries that cannot be broken. The input parameters include the elastic optimization indicators output by the public demand module and the hierarchical elastic reserved space parameters output by the fault tolerance and redundancy module.

[0036] Multi-scenario Differentiated Solution Generation Rules: Based on a multi-objective optimization algorithm, the submodule automatically generates three sets of differentiated planning schemes, each corresponding to different development scenarios and flexible activation rules. Benchmark Development Scenario: Strictly align with the rigid indicators set by higher authorities, prioritize meeting the current needs of the people, maximize the proportion of flexible space reserved at the primary level, adapt to the normal and stable development scenario of the region, and ensure the implementation of supporting facilities for people's livelihood. High-quality development scenario plan: Prioritize the implementation of major industrial projects and major infrastructure projects, maximize the proportion of secondary flexible space reservation, adapt to the scenario of rapid regional economic development and concentrated implementation of major projects, and core guarantee the space for industrial development; Safety and resilience development scenario plan: Prioritize ecological protection and disaster emergency prevention and control, maximize the proportion of three-level elastic space reservation, adapt to development scenarios in high-risk disaster areas and ecologically sensitive areas, and ensure regional safety and resilience.

[0037] Pre-verification mechanism during the generation process: During the generation of each solution, a dual verification module is simultaneously connected to complete dual pre-verification of compliance and emergency response capabilities, eliminating solutions that violate rigid constraints or pose significant security risks in advance, and ensuring that the output draft solution meets legal control requirements.

[0038] Solution output standards: When each solution is output, the completion status of core indicators (compliance rate of rigid indicators, completion rate of flexible indicators), matching degree of public demands (effective demand implementation rate, matching rate of high priority demands), emergency adaptability (emergency support capability score under multi-hazard coupling scenario, emergency facility service coverage rate), core applicable scenarios, and corresponding activation rules and procedures for flexible space.

[0039] The full-node embedded compliance and emergency dual verification module is the core compliance and security assurance unit of the system. It has built-in fixed and dynamic dual-mode verification triggering sub-module, full-level traceability compliance verification sub-module, and multi-disaster coupled scenario simulation verification sub-module. Its core function is to carry out dual verification of compliance and emergency capabilities simultaneously at all planning process nodes, and the verification results drive the iterative optimization of the solution.

[0040] Fixed and Dynamic Dual-Mode Verification Trigger Submodule Automatic Triggering of Fixed Nodes: Four mandatory fixed verification nodes are set throughout the planning process. When a node is reached, a full double verification is automatically triggered: Basic Data Import Node: When users import or update basic datasets, data compliance, coordinate consistency, and rigid boundary accuracy are verified; Draft Scheme Generation Node: After the planning analysis module outputs three draft schemes, a full double verification is triggered; Scheme Modification and Optimization Node: After users complete manual modifications to the scheme, a special double verification for the modified area is triggered; Final Result Node: When users confirm the scheme is ready to output results, a final full double verification is triggered, and a formal compliance report and emergency response capability assessment report are output.

[0041] Dynamic real-time triggering mechanism: Set dynamic triggering rules. When users modify three core contents in the visualization interface, namely rigid boundaries, flexible spatial layout and emergency facility layout, special dual verification is triggered in real time. The verification scope is the modified plot and its associated control unit. The verification results are synchronized to the planning analysis module in real time, and local correction and non-compliant content warnings are automatically completed.

[0042] Verification rules are adaptive and adaptable: Verification rules are automatically adapted based on the priority of the request and the regional risk level. In areas with a high concentration of high-priority requests, the compliance of the request implementation is guaranteed first, and in high-risk areas, the verification weight of emergency adaptation capability is increased.

[0043] Full-level traceability compliance verification submodule Full-level statutory planning integration: The sub-module has a built-in database of five levels of statutory planning results, which connects in real time with statutory planning results at the national, provincial, municipal, county and township levels, and establishes a full-link ledger for the breakdown of rigid indicators.

[0044] Dual-dimensional compliance verification logic: Local compliance verification: Verify whether the three control lines of the local plan are consistent with the higher-level plan, whether they exceed the rigid control indicators issued by the higher level, and whether the land use nature of the plots meets the statutory control requirements; Upward full-link traceability verification: Trace back to the entire chain of indicators of the higher-level plan to verify whether the adjustment of the local plan affects the overall implementation of the rigid constraints of the higher level. For example, adjustments to county-level plans need to be traced back to the municipal and provincial indicator breakdown ledgers to ensure that the adjustments do not exceed the provincial total indicators.

[0045] Handling and feedback of non-compliant content: Accurately locate non-compliant content spatially, mark it with red, yellow and green warnings on the map, simultaneously complete the full-chain source tracing, clarify the policy basis and full-chain impact of non-compliance, and output feasible modification suggestions; at the same time, the results of high-frequency conflict areas are fed back to the planning hierarchical fault tolerance redundancy design module to optimize the elastic space reservation ratio and parameters of the corresponding areas, and reduce compliance conflicts from the source.

[0046] Multi-hazard Coupling Scenario Simulation and Verification Submodule Disaster Data and Simulation Models: The sub-module connects to official disaster risk data from departments such as natural resources, emergency management, water resources, and meteorology. It includes built-in numerical models of flooding, geological disaster stability, and multi-hazard coupled simulation models, supporting simulation of extreme scenarios involving single and multiple hazards.

[0047] Multi-dimensional emergency verification content: ① Safety verification of emergency facility layout: Verify whether emergency shelters, emergency hospitals, fire stations, disaster prevention channels, and other emergency facilities in the planning scheme avoid high-risk areas and whether they can be activated normally under extreme scenarios; ② Emergency support capability verification: Verify whether the service coverage and capacity of emergency facilities under extreme scenarios meet the emergency needs of the area's permanent residents and whether disaster prevention channels remain unobstructed; ③ Emergency feasibility verification of flexible space: Verify the accessibility, safety stability, and ownership clarity of the corresponding flexible reserve land plots to confirm the feasibility of rapid activation under emergency scenarios.

[0048] Verification results are fed back in reverse: On the one hand, the verification results are fed back to the public demands module, which automatically increases the priority of emergency-related demands in high-risk areas; on the other hand, they are fed back to the planning and analysis module, which automatically optimizes the layout of emergency facilities and the flexible space configuration, thereby improving the safety and resilience of the plan.

[0049] The planning implementation self-learning dynamic adaptation closed-loop module has a built-in full-process closed-loop self-learning optimization sub-module, which is the core unit for realizing full life cycle management of planning and system capability iteration. Its core function is to realize dynamic adjustment of planning and self-learning optimization of the whole system model, forming full life cycle closed-loop management.

[0050] Implement real-time data integration: The submodule connects in real time with natural resource satellite imagery enforcement monitoring data, annual implementation monitoring data of territorial spatial planning, newly added public demand data, emergency management department information on sudden disasters, and project approval data during the planning implementation process through the government data sharing interface, so as to realize real-time perception of the planning implementation status.

[0051] Implement deviation tracking and early warning: Track the progress of the implementation of rigid planning indicators, the actual use of construction land, and the progress of the implementation of supporting facilities for people's livelihood in real time, and set deviation early warning thresholds. When the deviation between the implementation progress and the planning exceeds 10%, the deviation early warning will be automatically triggered and pushed to the relevant responsible personnel.

[0052] Dynamic adjustment and adaptation mechanism: When implementation deviations, new valid demands, or sudden disasters occur, the system automatically initiates the adaptation process: First, it verifies whether the adjustment requirement exceeds the legal rigid constraints. If it does, the adjustment is directly prohibited and the policy basis is output. If the rigid constraints are not exceeded, the corresponding level of flexibility and unlocking rules are automatically matched to complete the dynamic adjustment of the planning scheme. The adjustment process triggers dual verification of all nodes simultaneously to ensure that the adjusted scheme is compliant and safe.

[0053] A full-process self-learning optimization mechanism: A self-learning database is established to fully record the data of each solution adjustment, including the reasons for the adjustment, the content of the adjustment, the results of double verification, the implementation effect, and public feedback; Based on random forest, XGBoost machine learning models and large language models, the model parameters of the entire system are automatically optimized, including the appeal semantic extraction model, priority weight formula, elastic space calculation model, double verification rules, scenario simulation parameters, and solution generation algorithm; The optimized parameters are synchronously updated to all front-end modules of the system to achieve continuous iterative upgrades of system capabilities.

[0054] The end-to-end traceable visual interactive module communicates with all modules of the system and is the core unit of human-computer interaction in the system, realizing full-process visual display, interactive operation and output of results.

[0055] Full-dimensional visualization: Based on ArcGIS JS API, Cesium 3D engine, and ECharts visualization framework, basic data, public demand distribution heat map, planning scheme, double verification results, flexible spatial distribution map, planning implementation progress, and other content are visualized through 2D electronic maps, 3D real scene scenes, statistical charts, early warning dashboards, etc., and support 2D and 3D linkage switching.

[0056] Real-time interaction and impact prediction: Users can directly complete operations such as land plot adjustment, parameter modification, and scenario configuration in a visual interface. During the user's modification process, the system displays the quantitative impact of the operation on rigid constraints, demand matching degree, and emergency support capabilities in real time, predicting adjustment risks in advance and avoiding non-compliant operations.

[0057] Full-chain traceability function: It supports users to complete the full-chain traceability of any indicator, any plot of land, and any operation. Users can view the full-chain breakdown of the indicator's superior, the historical adjustment records of the plot, the matching status of demands, the results of dual verification, the implementation progress, and other full-process information. All operations are fully traceable and can be recorded, meeting the requirements of planning audit and compliance management.

[0058] One-click export of standardized results: Supports one-click export of standardized planning results that meet the statutory approval requirements of the Ministry of Natural Resources, including spatial data in SHP / GDB format, planning text in PDF format, planning atlas, compliance reports, emergency response capability assessment reports, public demand matching analysis reports, etc., without the need for manual secondary processing, greatly improving the efficiency of planning approval.

[0059] Example 1: Application of this system in the preparation of the overall territorial spatial planning of county-level cities This embodiment uses the overall land use plan of a county-level city in eastern my country (hereinafter referred to as "target city") as the application scenario. The target city has an administrative area of ​​1200 km². 2 The urban development boundary area is 120 km². 2 With a permanent population of 850,000, the area faces core challenges such as the risk of a once-in-a-century flood, insufficient public services in the old city, and an urgent need for major projects to be implemented in the northern industrial park.

[0060] Data processing phase: The multi-source data unified spatiotemporal anchoring module collected 23 types of multi-source data, including GF-2 satellite imagery, 0.5-meter aerial photographic imagery, five-level statutory planning results, flood / geological disaster risk data, 12345 government service request data, and land ownership data. These data were uniformly converted into the CGCS2000 coordinate system and standard format. Based on the nationally unified geographic entity coding rules, unique codes were assigned to 126,000 geographic entities across the entire region. The spatiotemporal anchoring of all data was completed, and a basic dataset for a unified spatiotemporal benchmark across the entire region was constructed. This process took 2 working days, with a data matching accuracy of 100%, and the data was synchronized to all modules of the system.

[0061] In the public appeal processing stage: the appeal spatial matching and feasibility pre-verification submodule collected 12,680 public appeals from the target city over the past two years, performed semantic extraction based on a fine-tuned BERT model, and completed spatial positioning through geocoding, anchoring to the corresponding land parcel unit; the feasibility verification was completed using three control lines and rigid indicators issued by the city as boundaries, eliminating 1,243 appeals that were not feasible, resulting in 11,437 valid appeals; the priority weights were calculated and sorted using a weighted formula, and the valid appeals were transformed into 18 elastic optimization indicators with corresponding weights. High-priority appeals included "adding community health service centers in the western part of the urban area" and "adding emergency shelters in the high-risk flood area in the south," etc. The elastic indicators were synchronized to the planning analysis module, and the spatial distribution data of the appeals were synchronized to the fault tolerance and redundancy module.

[0062] Hierarchical fault-tolerant redundancy design phase: Rigid and elastic dynamic adaptation and hierarchical locking submodules based on the remaining 8.2km² of construction land in the target city. 2 Based on the distribution of high-frequency demands and flood risk levels, the total area of ​​flexible reserve land parcels is automatically calculated to be 3.5 km². 2 (It accounts for 2.92% of the urban development boundary area, which meets the provincial control requirements), of which the primary flexible space is 1.2 km². 2 (Located in areas of high public demand in the old city), 1.6km of secondary flexible space. 2 (Located in the northern industrial park), 0.7km of three-tiered flexible space. 2 (Located in safe areas surrounding high-risk flood zones in the south), corresponding tiered unlocking rules and rigid indicator floating thresholds are set, and the parameters are synchronized to the corresponding modules.

[0063] Multi-scenario solution generation phase: The multi-scenario solution synchronous generation and pre-validation submodule automatically generates three differentiated planning schemes based on the basic dataset, rigid boundaries, elasticity indicators, and elasticity space parameters. Benchmark development scenario: 100% compliance rate of rigid indicators, 92% matching rate of high-priority demands, 88% coverage rate of emergency facilities services, and suitable for normal and stable development scenarios. High-quality development scenario solution: 100% compliance rate with rigid indicators, 100% land use guarantee rate for major projects, and adapted to scenarios of rapid industrial development; Safety and Resilience Development Scenario: 100% compliance rate with rigid indicators, 100% coverage of emergency facilities services in high-risk areas, and adapted to safety development scenarios in high-risk areas.

[0064] The solution generation process involves simultaneous double pre-verification, and the output includes complete metrics, adaptability, and applicable scenario descriptions.

[0065] The full-node dual-verification phase: The fixed and dynamic dual-mode verification triggering submodule automatically triggers full dual verification at 4 fixed nodes, and triggers dynamic verification in real time when the user makes manual adjustments; The full-level traceability compliance verification submodule completes the full-link verification of the five-level planning, confirming that none of the three schemes have broken through rigid constraints, and completes the location and modification suggestions for 3 local non-compliant contents, and feeds back the high-frequency conflict area in the old city to the fault tolerance redundancy module to optimize the first-level elastic space ratio of the area; The multi-hazard coupling scenario simulation verification submodule simulates the extreme scenario of a 100-year flood and geological disaster coupling, and finds that 2 emergency shelters in Scheme 1 are located in the flood inundation area, and automatically feeds back to the planning analysis module to complete the optimization and adjustment, and simultaneously improves the priority of emergency demands in the area.

[0066] Visualization and Output Stage: The end-to-end traceable visualization and interaction module visualizes all content through two-dimensional maps and three-dimensional real-world scenes. Planning personnel can manually optimize the plan on the interface, view the impact of the operation in real time during the adjustment process, and complete the end-to-end traceability by clicking on any plot. Finally, the safe and resilient development scenario plan is confirmed as the recommended plan, and standardized approval results that meet the requirements of the Ministry of Natural Resources can be exported with one click, including spatial data, planning text, atlas, compliance report, etc., which takes 1 working day.

[0067] Implementation of the closed-loop and self-learning phase: After the plan is approved, the system connects with implementation monitoring data in real time. In the first year of implementation, three high-priority public concerns were added in the old city area. The system automatically matched the first-level flexible space to complete the minor adjustments to the plan. The adjustment process triggered dual verification simultaneously. After the adjustment, the matching degree of the concerns increased to 94%, requiring no approval from higher authorities, and the adjustment cycle was 1 working day. In the second year of implementation, the southern part of the target city suffered a once-in-50-year flood disaster. The system automatically triggered the emergency activation process of the third-level flexible space. After completing dual verification at all levels, 0.3km was quickly activated. 2 The three-tiered flexible space serves as a temporary emergency shelter to ensure emergency response needs are met. Simultaneously, the system records each adjustment data to a self-learning database, optimizing the priority weights of requests, the flexible space calculation model, and the dual-verification rules. The optimized parameters are then synchronously updated to all modules, enabling iterative system capability iteration.

[0068] Example 2: Application of this system in the preparation of detailed land and space planning for mountainous townships This embodiment uses the detailed land use planning of a mountainous township in western my country (hereinafter referred to as "target town") as the application scenario. The target town has an administrative area of ​​86 km². 2 The urban development boundary area is 2.8 km². 2 With a permanent population of 12,000, it is located in a high-risk area for geological disasters and faces problems such as insufficient rural infrastructure, weak emergency response and disaster prevention capabilities, and land demand for rural industrial development.

[0069] The data processing module completes the collection, standardization, and unified spatiotemporal anchoring of multi-source data, including satellite imagery, statutory planning at the provincial, municipal, county, and town levels, geological disaster risk data, and homestead data. It assigns unique codes to 12,000 geographic entities across the entire region, outputs a basic dataset with a unified spatiotemporal benchmark, and synchronizes it to all modules.

[0070] The public appeal module collected 326 appeals from door-to-door surveys, village representative meetings, and online messages. After semantic extraction, spatial positioning, and feasibility verification, 298 valid appeals were obtained. These appeals were then sorted by priority and transformed into eight flexible optimization indicators, such as "full coverage of village-level elderly care service points" and "full coverage of emergency access routes to geological disaster hazard points," and synchronized to the corresponding modules.

[0071] The fault-tolerance redundancy module automatically calculates the total scale of flexible reserve land parcels (0.08 km²) based on the target town's rigid constraint margin, demand requirements, and geological disaster risk level. 2 The primary elastic space is 0.03 km. 2 (Public welfare facilities), secondary flexible space 0.025km 2 (Rural industries), three-tiered flexible space 0.025km 2 (Emergency evacuation) Set corresponding unlocking rules for different levels and synchronize the parameters to the corresponding modules.

[0072] The planning and analysis module generates three differentiated plans: prioritizing people's livelihood, developing industries, and geological safety and resilience. During the generation process, double pre-verification is completed, and the corresponding indicators and adaptation capability descriptions are output.

[0073] The dual-verification module completes dual-verification of all nodes, confirms that the scheme does not break through the rigid constraints of the superior level through full-level tracing, and performs multi-hazard coupling simulation verification of extreme scenarios such as earthquakes, landslides, and debris flows, optimizes the layout of emergency channels, and raises the priority of emergency requests in high-risk areas.

[0074] The visualization and interaction module completes the visualization display of the plan, allowing town government staff and village representatives to view the plan intuitively, make interactive adjustments, and export standardized detailed planning results with one click for planning approval and public announcement.

[0075] During the planning and implementation process, the closed-loop module connects in real time with geological disaster monitoring data, implementation progress data, and new villagers' demands to make dynamic adjustments. At the same time, it records the adjustment data to optimize the system model, forming a closed-loop management throughout the entire life cycle.

[0076] Comparative Study: Application of Traditional Planning Methods and Conventional Planning Analysis Systems This comparative example uses the same target city as Example 1 as the application scenario, adopts the traditional land and space planning method, and is equipped with a conventional planning analysis system that only has basic data processing, scheme drawing, and simple compliance verification functions. It does not have the core innovative module of this invention.

[0077] The data processing involved manual collection, manual coordinate and format conversion, and manual verification and matching, which took 20 working days. There were 8 spatial matching errors and 12 missing attribute information items. It was impossible to achieve unified spatiotemporal anchoring of all data, and there were inconsistencies in the data at multiple stages.

[0078] The public demands were manually collected and sorted, and those that could be implemented were manually selected. This method could not achieve precise spatial positioning and priority ranking. Only 12% of the demands were included in the planning considerations, and the matching rate of high-priority demands was only 42%, which is far lower than the 92% in Example 1.

[0079] The planning scheme only includes one manually drawn baseline plan, lacking differentiated scenario plans and thus unable to adapt to different development scenarios; the flexible space is estimated manually, with only 1.2km reserved. 2 A single flexible space, without a tiered design and unlocking rules, cannot achieve differentiated adaptation for minor adjustments to people's livelihoods, project implementation, and emergency response.

[0080] Compliance verification was only conducted once at the local level after the plan was finalized, without full-node embedded verification or full-link traceability. The initial draft of the plan had 8 issues that exceeded the rigid indicators of the superior authorities, and the revision took 15 working days. There was no emergency scenario simulation verification. 3 emergency shelters in the plan were located in areas that would be flooded once in 100 years, which were not discovered in time and posed a major safety hazard.

[0081] There is no real-time monitoring and dynamic adjustment mechanism during the planning and implementation phase. When deviations occur, new demands arise, or sudden disasters occur, a complete legal procedure for planning adjustment must be initiated, with an adjustment cycle of 3-6 months. This makes it impossible to respond quickly to people's livelihood and emergency needs. There is also no self-learning optimization mechanism, so the experience in planning and implementation cannot be transformed into system capabilities, and similar problems still exist in subsequent plans.

[0082] The output can only provide basic spatial data and planning text, without full-chain traceability and visualization, resulting in low public participation; the approval results require manual processing, which takes 10 working days, longer than the solution in Example 1, and the effect is worse.

[0083] Although embodiments of the present invention have been shown and described, these specific embodiments are merely explanations of the invention and are not intended to limit it. The specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. After reading this specification, those skilled in the art may make modifications, substitutions, and variations to the embodiments as needed without departing from the principles and spirit of the invention, but such modifications, substitutions, and variations are protected by patent law as long as they are within the scope of the claims of the present invention.

Claims

1. A smart analysis system for national space planning, comprising a data processing module, a planning analysis module, characterized in that, It also includes a module for intelligent transformation and implementation matching of public demands, a module for hierarchical planning and fault tolerance redundancy design, a module for full-node embedded compliance and emergency dual verification, and a module for self-learning dynamic adaptation closed-loop planning implementation. The data processing module is communicatively connected to the planning and analysis module, and is also unidirectionally communicatively connected to the intelligent transformation and implementation matching module for public demands, the planning hierarchical fault tolerance and redundancy design module, the full-node embedded compliance and emergency dual verification module, and the planning implementation self-learning dynamic adaptation closed-loop module, so as to output a unified spatiotemporally anchored basic dataset for the intelligent analysis system. The public demand intelligent conversion and implementation matching module extracts implementable demands and transforms them into flexible optimization indicators, which are then synchronously transmitted to the other modules. The planning hierarchical fault-tolerant redundancy design module generates hierarchical flexible reserved space and unlocking rules, which are synchronously transmitted to the other modules. The full-node embedded compliance and emergency dual-verification module performs dual verification synchronously at all planning nodes, and the results drive the solution iteration in reverse; the planning implementation self-learning dynamic adaptation closed-loop module realizes dynamic adjustment of planning and self-learning optimization of the whole system model, forming a closed-loop management of the whole life cycle.

2. The intelligent analysis system for land spatial planning according to claim 1, characterized in that: The data processing module has a built-in unified spatiotemporal anchoring module for multi-source data. This module is used to collect multi-source data such as satellite remote sensing images, five-level statutory planning results, and disaster risks. After completing the coordinate and format standardization, it anchors the spatial, attribute, and temporal information of all data to the corresponding geographic entities, using the unique geographic entity code as the core. It outputs a basic dataset of unified spatiotemporal anchoring across the entire domain and transmits it synchronously to all other modules of the system through the output end of the data processing module.

3. The intelligent analysis system for land spatial planning according to claim 1, characterized in that: The intelligent conversion and implementation matching module for public demands has a built-in sub-module for demand spatial matching and feasibility pre-verification. This sub-module is used to perform semantic extraction and spatial positioning of public demands collected from multiple channels, anchor the demands to corresponding geographical entities and plots, and complete feasibility verification with legal rigid constraints as the boundary. After prioritizing valid demands according to popularity and scope of impact, the demands are converted into elastic optimization indicators with corresponding weights. At the same time, the spatial positioning results of the demands are transmitted to the planning hierarchical fault tolerance and redundancy design module.

4. The intelligent analysis system for land spatial planning according to claim 1, characterized in that: The planning and analysis module has a built-in sub-module for synchronous generation and pre-verification of multi-scenario solutions. This sub-module uses a unified spatiotemporally anchored basic dataset as its foundation, takes the rigid legal requirements of the higher level as inviolable boundaries, and combines flexible optimization indicators and hierarchical flexible reserved space parameters to automatically generate three sets of differentiated planning schemes. Each scheme corresponds to different development scenarios and flexible activation rules. During the generation process, dual verification and pre-verification are completed simultaneously. When outputting, the completion status of indicators, the degree of matching of demands, emergency adaptability and applicable scenarios are marked.

5. The intelligent analysis system for land spatial planning according to claim 1, characterized in that: The planning-level fault-tolerant redundancy design module incorporates a rigid and flexible dynamic adaptation and level locking sub-module. This sub-module automatically calculates the area, layout, and level of flexible reserve plots, as well as the level floating threshold of rigid indicators, based on the regional rigid constraint margin, demand implementation requirements, and disaster risk level. Simultaneously, it sets differentiated unlocking rules for different levels of flexible spaces: Level 1 spaces are used for routine minor adjustments to people's livelihoods without higher-level approval; Level 2 spaces are used for major project implementation requiring verification and activation at the current level; and Level 3 spaces are used for major disasters requiring full-level verification and approval. The level unlocking rules are simultaneously transmitted to the dual-verification module.

6. The intelligent analysis system for land spatial planning according to claim 1, characterized in that: The full-node embedded compliance and emergency dual-verification module has a built-in fixed and dynamic dual-mode verification triggering sub-module. The fixed and dynamic dual-mode verification triggering sub-module automatically triggers dual verification at four fixed nodes: basic data import for planning, generation of initial draft of the plan, modification and optimization of the plan, and finalization of the results. At the same time, a dynamic triggering mechanism is set up so that when the user modifies any content of rigid boundary, flexible space, or emergency layout, a special dual verification is triggered in real time. The verification results are synchronized to the planning analysis module in real time to complete the local correction. The verification rules are automatically adapted according to the priority of the request and the regional risk level.

7. The intelligent analysis system for land spatial planning according to claim 6, characterized in that: The full-node embedded compliance and emergency dual-verification module incorporates a full-level traceability compliance verification sub-module. This sub-module connects to the five-level statutory planning results, verifying not only whether the current level of planning has exceeded the three control lines and rigid indicators, but also tracing back to the higher-level planning indicators to break down the entire chain and verify whether adjustments at the current level affect the implementation of rigid constraints at the higher level. It spatially locates and marks non-compliant content across the entire chain, outputs modification suggestions, and simultaneously feeds back the results of high-frequency conflict areas to the planning hierarchical fault tolerance redundancy design module to optimize the elastic parameters of the corresponding areas.

8. The intelligent analysis system for land spatial planning according to claim 6, characterized in that: The full-node embedded compliance and emergency dual verification module has a built-in multi-hazard coupling scenario simulation verification sub-module. The multi-hazard coupling scenario simulation verification sub-module is used to connect with regional multi-hazard risk data, simulate extreme scenarios of single-hazard and multi-hazard coupling, verify whether the layout of emergency facilities in the planning scheme meets the requirements of extreme scenarios and avoids high-risk areas, and at the same time verify the emergency activation feasibility of the corresponding regional flexible reserve plots. The verification results are fed back to the public demands module, automatically increasing the priority of emergency-related demands in high-risk areas, and also feeding back to the planning and analysis module to optimize emergency layout.

9. The intelligent analysis system for land spatial planning according to claim 1, characterized in that: The planning and implementation self-learning dynamic adaptation closed-loop module incorporates a full-process closed-loop self-learning optimization sub-module. This sub-module is used to connect with monitoring data, new requests, and information on sudden disasters during the planning and implementation process, and to track implementation deviations in real time. When deviations, new requests, or emergencies occur, the module automatically matches the corresponding level of elasticity space to dynamically adjust the solution without breaking rigid constraints. The adjustment process triggers dual verification simultaneously. At the same time, the full-process data of each adjustment is recorded in the self-learning database, automatically optimizing the parameters of the entire system model and updating them synchronously to all front-end modules, thereby achieving iterative upgrades of system capabilities.

10. The intelligent analysis system for territorial spatial planning according to any one of claims 1 to 9, characterized in that, The system also includes a full-link traceability visualization interaction module, which communicates with all modules of the system. This module is used to visualize basic data, demand distribution, planning schemes, verification results, flexible spatial distribution, and implementation progress through two-dimensional maps, three-dimensional scenes, and statistical charts. It also supports users to directly adjust land parcels, modify parameters, and configure scenarios on the interface. During the adjustment process, the impact of the operation on rigid constraints, demand matching degree, and emergency response capabilities is displayed in real time. It supports full-link traceability of any indicator or land parcel and supports one-click export of standardized planning results that meet the legal approval requirements.