A method, system and storage medium for generating a reconfigurable space unit, constructing a low-altitude resource object and hierarchical warehousing for low-altitude infrastructure planning

Abstract

The application discloses a kind of low-altitude infrastructure planning-oriented reworkable space unit generation, low-altitude resource object construction and hierarchical warehousing method, system and storage medium.The method obtains multiple-source space objects and clues in target area, generates reworkable space units through geometric normalization, space division or merging, constructs low-altitude operating envelope based on task scenario and model category and performs matching, generates low-altitude resource objects with low-altitude semantics, model adaptation, evidence reference, gap objects and warehousing levels, and realizes hierarchical warehousing of main resources, candidates, review, reserves and the like.

Description

Technical Field

[0001] The present invention relates to the technical fields of low-altitude infrastructure resource discovery, spatial data processing, geographic information systems, remote sensing and map data fusion, spatial object modeling, low-altitude operation envelope matching, resource library construction, and low-altitude infrastructure planning. In particular, it relates to a method, system, and storage medium for generating transformable space units, constructing low-altitude resource objects, and hierarchical storage for low-altitude infrastructure planning.

[0002] The low-altitude infrastructure referred to in the present invention may include low-altitude takeoff and landing facilities, drone nests, flight service stations, logistics distribution nodes, training sites, emergency support points, inspection support points, cultural and tourism low-altitude facilities, electric vertical takeoff and landing aircraft takeoff and landing facilities, and operation support resources supporting the above facilities. Background Art

[0003] The construction of low-altitude infrastructure involves both spatial resource identification and operation safety, external environment, regulatory boundaries, and commercial value judgment. Different from ordinary ground facilities, the availability of low-altitude infrastructure usually depends on the combination of multiple factors such as ground space, overlying clear airspace, approach and departure channels, mission aircraft capabilities, communication and power supply guarantees, emergency response conditions, and evidence verifiability.

[0004] In the actual planning process, public information, map points of interest, remote sensing images, manually collected forms, industry reports, and operation feedback are often scattered in different systems, with different data granularities, timeliness, and credibility. If the site selection conclusion is given only based on a single source or manual experience, problems such as misjudgment of sites, inability to trace evidence, omission of external constraints, and over-high recommendation levels are likely to occur.

[0005] Low-altitude infrastructure planning also has obvious regional network attributes. Whether a single point is excellent does not directly determine its construction priority in the regional network. Service coverage, redundant coverage, corridor connectivity, multi-scenario co-location, mission response time, construction cost, and operation support coordination between nodes will all affect the final planning result of the regional low-altitude infrastructure network.

[0006] At the same time, the results of low-altitude infrastructure planning are usually used for internal demonstration, industry reporting, demonstration area construction, controlled trial operation preparation, and subsequent project transformation. If the system output does not clearly distinguish between planning suggestions, static display, trial operation preparation, and approval permits, it is easy to cause unclear output boundaries, and even lead users to misunderstand the evaluation results as the basis for direct flight or formal operation.

[0007] Therefore, the low-altitude infrastructure planning system needs to simultaneously possess the capabilities of objectified expression, evidence-based traceability, constraint-based evaluation, networked planning, degradation control, and feedback-based update to support a more robust, interpretable, and auditable planning review process.

[0008] Existing technologies struggle to transform ordinary spatial objects into low-altitude reviewable resource objects with low-altitude operational semantics, mission / aircraft compatibility, evidence gaps, and database entry levels. Therefore, a technical solution is needed that is driven by low-altitude business scenarios, based on objects and evidence, and controlled by constraints and boundaries.

[0009] This invention does not aim to provide administrative approvals, flight permits, or airspace approvals. Instead, it provides technical support for planning review, construction sequencing, supplementary certificate verification, and controlled trial operation preparation, enabling the system output to be auditable and traceable.

[0010] The purpose of this invention is to provide a method, system, and storage medium for generating modifiable spatial units, constructing and hierarchically storing low-altitude resource objects in a database for low-altitude infrastructure planning. This addresses the problems of scattered object sources, insufficient evidence, inconsistent constraint expressions, difficulty in interpreting recommendation results, and difficulty in closing the feedback and update loop in the review of low-altitude infrastructure planning. Summary of the Invention

[0011] The core concept of this invention is to first transform multi-source inputs into a unified low-altitude object representation, then associate the object with evidence, constraints, gaps, and output boundaries, and finally generate a planning output that is degradable, verifiable, and feedback-enabled based on single-point evaluation and regional network evaluation.

[0012] To achieve the above objectives, the method provided by the present invention can be executed by a computing device, server, cloud platform, edge computing node or a combination thereof, or can be deployed in a low-altitude infrastructure planning and review system through a computer program product.

[0013] S201: Obtain multi-source spatial objects and clues. Obtain existing low-altitude facilities, building rooftops, parking lots, logistics parks, industrial parks, hospitals, schools, open areas in scenic spots, transportation hubs, emergency sites, and other spaces that can be modified.

[0014] In some implementations, obtaining multi-source spatial objects and clues can be achieved by calling object indexing, spatial calculation, semantic extraction, rule engine, or manual review interface; the processing results are saved as structured fields and associated with task identifiers, region identifiers, scene identifiers, and version identifiers.

[0015] In some implementations, the output of acquiring multi-source spatial objects and clues can be used as input for subsequent steps, while preserving the mapping relationship between the original input, the cleaned results, and the derived results.

[0016] S202: Generate modifiable spatial units. Perform geometric normalization, spatial segmentation, or spatial merging on spatial objects to generate point-like, area-like, roof-like, ground-like, corridor-related, or composite scene units.

[0017] In some implementations, generating modifiable spatial units can invoke object indexing, spatial computation, semantic extraction, rule engine, or manual review interfaces; the processing results are saved as structured fields and associated with task identifiers, region identifiers, scene identifiers, and version identifiers.

[0018] In some implementations, the output of generating modifiable spatial units can be used as input for subsequent steps, while preserving the mapping between the original input, the cleansing results, and the derived results.

[0019] S203: Construct a low-altitude operation envelope. Construct takeoff and landing space, safety buffer, arrival and departure channels, parking and maintenance, charging and battery swapping, communication support, and emergency response envelopes based on mission scenarios and aircraft types.

[0020] In some implementations, constructing the low-altitude operational envelope can involve calling object indexing, spatial computation, semantic extraction, rule engines, or manual review interfaces; the processing results are stored as structured fields and associated with task identifiers, region identifiers, scene identifiers, and version identifiers.

[0021] In some implementations, the output of constructing the low-altitude operating envelope can be used as input for subsequent steps, while preserving the mapping relationship between the original input, the cleaning result, and the derived result.

[0022] S204: Execution Unit and Envelope Matching. Match the modifiable space unit with the low-altitude operation envelope in terms of area, shape, clearance, approach and departure directions, accessibility, support conditions, and sensitive target avoidance.

[0023] In some implementations, the execution unit and envelope matching can invoke object indexing, spatial calculation, semantic extraction, rule engine, or manual review interface; the processing results are stored in structured fields and associated with task identifier, region identifier, scene identifier, and version identifier.

[0024] In some implementations, the output of the execution unit and envelope matching can be used as input for subsequent steps, while preserving the mapping relationship between the original input, the cleaning result, and the derived result.

[0025] S205: Generate low-altitude resource objects. Transform space units that meet space adaptability conditions or have the potential for supplementary certification into existing facility-type, potential modification-type, mission-specific-type, regional reserve-type, or return-to-core-type resource objects.

[0026] In some implementations, generating low-altitude resource objects can involve calling object indexing, spatial calculation, semantic extraction, rule engine, or manual review interfaces; the processing results are saved as structured fields and associated with task identifiers, region identifiers, scene identifiers, and version identifiers.

[0027] In some implementations, the output of generating low-altitude resource objects can be used as input for subsequent steps, while preserving the mapping between the original input, the cleansing results, and the derived results.

[0028] S206: Generate evidence and gap objects. Examine spatial validity, facility authenticity, feasibility of modification, operational support, mission adaptability, external constraints, and evidence quality to form gap objects.

[0029] In some implementations, generating evidence and gap objects can invoke object indexing, spatial calculation, semantic extraction, rule engine, or manual review interface; the processing results are saved as structured fields and associated with task identifier, region identifier, scene identifier, and version identifier.

[0030] In some implementations, the generated evidence and gap objects further include records of credibility, timeliness, spatial scope, verification status, and recommendation restrictions, so that subsequent modules cannot directly output high-confidence conclusions when key conditions are missing.

[0031] S207: Perform tiered data entry. Based on envelope matching results, evidence strength, gap severity, external constraint status, and verification status, determine the main resource layer, candidate layer, verification layer, reference layer, reserve layer, hidden layer, or noise layer.

[0032] In some implementations, hierarchical data entry can be performed by calling object indexing, spatial calculation, semantic extraction, rule engine, or manual review interface; the processing results are saved as structured fields and associated with task identifier, region identifier, scene identifier, and version identifier.

[0033] In some implementations, the output of the hierarchical data entry process can be used as input for subsequent steps, while preserving the mapping between the original input, the cleaned results, and the derived results.

[0034] S208: Output the subsequent review interface. Write the low-altitude resource objects into the multi-scenario resource library and output standardized object representations to the evaluation, planning, recommendation, and controlled operation modules.

[0035] In some implementations, the output follow-up review interface can call object indexing, spatial calculation, semantic extraction, rule engine or manual review interface; the processing results are saved as structured fields and associated with task identifier, region identifier, scene identifier and version identifier.

[0036] In some implementations, the output of the subsequent review interface can be used as input for subsequent steps, while preserving the mapping relationship between the original input, the cleaned results, and the derived results.

[0037] In the above method, if any key data is unavailable, unverifiable, has conflicting sources, or is not timely enough, the system preferably does not presume that the condition is met, but instead records the corresponding gap, verification action, and output restrictions.

[0038] In the above method, feedback updates can change the object status, gap status, constraint status, recommendation level, and construction sequence, but do not directly overwrite the original source citations and original evidence records, thus preserving the audit chain.

[0039] This invention also provides a system comprising the following modules: a multi-source spatial object acquisition module, a modifiable spatial unit generation module, a low-altitude operational envelope construction module, a spatial unit-operational envelope matching module, a low-altitude resource object generation module, an evidence and gap checking module, a hierarchical data entry module, and a subsequent review interface module. These modules can be deployed on the same server, or they can be deployed as microservices, plugins, or in an edge cloud collaborative manner.

[0040] The multi-source spatial object acquisition module is used to perform data processing, rule judgment, status update or result output operations corresponding to its name, and write the input, output, timestamp and version number in the processing process into the audit log.

[0041] The modifiable spatial unit generation module is used to perform data processing, rule judgment, status update or result output operations corresponding to its name, and write the input, output, timestamp and version number in the processing process into the audit log.

[0042] The low-altitude operation envelope construction module is used to perform data processing, rule judgment, status update or result output operations corresponding to its name, and write the input, output, timestamp and version number during the processing into the audit log.

[0043] The spatial unit—the running envelope matching module—is used to perform data processing, rule judgment, status update, or result output operations corresponding to its name, and writes the inputs, outputs, timestamps, and version numbers during the processing into the audit log.

[0044] The low-altitude resource object generation module is used to perform data processing, rule judgment, status update or result output operations corresponding to its name, and write the input, output, timestamp and version number in the processing process into the audit log.

[0045] The Evidence and Gap Check module is used to perform data processing, rule judgment, status update, or result output operations corresponding to its name, and writes the inputs, outputs, timestamps, and version numbers during the processing into the audit log.

[0046] The layered data entry module is used to perform data processing, rule judgment, status update, or result output operations corresponding to its name, and writes the inputs, outputs, timestamps, and version numbers during the processing into the audit log.

[0047] The subsequent review interface module is used to perform data processing, rule judgment, status update or result output operations corresponding to its name, and write the input, output, timestamp and version number in the processing process into the audit log.

[0048] The present invention also provides an electronic device, including a processor, a memory, a communication interface and a display interface, wherein a computer program stored in the memory is executed by the processor to implement any of the above method steps.

[0049] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0050] This invention unifies the objects, evidence, constraints, gaps, recommendations, and feedback in low-altitude infrastructure planning into a computable data chain, thereby improving the traceability of planning review results.

[0051] This invention performs conservative processing when external constraints are lacking or evidence is insufficient, which can reduce the risk of incorrect recommendations, over-display, and misuse of evaluation results.

[0052] This invention combines single-point suitability evaluation with regional network planning evaluation, enabling regional-level outputs such as node hierarchy, service coverage, redundant coverage, corridor connectivity, phased construction, and investment priorities.

[0053] This invention allows manual review, trial operation feedback, and environmental updates to enter a closed loop by preserving the differences between the original source and the feedback update, without destroying the original chain of evidence.

[0054] This invention is applicable to multiple business scenarios such as low-altitude logistics, inspection, emergency response, police aviation, cultural tourism, training, flight services, and comprehensive demonstration, and has good scalability. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the overall process of the method of the present invention.

[0056] Figure 2 This is a schematic diagram of the generation of modifiable spatial units according to the present invention.

[0057] Figure 3 This is a schematic diagram of the low-altitude operation envelope composition of the present invention.

[0058] Figure 4 This is a schematic diagram of the spatial unit and operational envelope matching determination process of the present invention.

[0059] Figure 5 This is a schematic diagram of the hierarchical storage of low-altitude resource objects according to the present invention. Detailed Implementation

[0060] The present invention will be further described below with reference to the accompanying drawings and embodiments. It should be understood that the embodiments described are only for explaining the present invention and are not intended to limit the scope of protection of the present invention.

[0061] In this specification, the target area can be an administrative region, a low-altitude demonstration zone, an industrial park, an area surrounding an airport, an urban cluster, a transportation corridor, a logistics network area, a scenic area, or an emergency support area. Different data access strategies and constraint configurations can be adopted for different target areas.

[0062] In this specification, low-altitude business scenarios may include logistics and distribution, inspection and patrol, emergency support, police-aviation cooperation, training and drills, cultural and tourism experiences, flight services, transportation connections, and comprehensive demonstrations. A candidate object can be bound to multiple business scenarios simultaneously.

[0063] In this specification, aircraft types may include multi-rotor, fixed-wing, compound-wing, logistics drones, inspection drones, police drones, emergency drones, and electric vertical takeoff and landing (EVTOL) aircraft. Different aircraft types have different space requirements, safety buffers, charging and battery swapping requirements, and operational windows.

[0064] See Figure 1 In step S201, the system executes "acquiring multi-source spatial objects and clues". This involves acquiring existing low-altitude facilities, building rooftops, parking lots, logistics parks, industrial parks, hospitals, schools, open areas in scenic spots, transportation hubs, emergency sites, and other spaces that can be modified.

[0065] The inputs to step S201 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, confidence fields, gap fields, or intermediate results that can be called by the next step.

[0066] In step S201, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version and processing module to facilitate subsequent traceability.

[0067] In step S201, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0068] See Figure 1In step S202, the system executes "Generate Modifiable Spatial Units". This involves geometrically normalizing, spatially segmenting, or merging spatial objects to generate point-like, area-like, rooftop, ground-like, corridor-related, or composite scene units.

[0069] The inputs to step S202 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, confidence fields, gap fields, or intermediate results that can be called by the next step.

[0070] In step S202, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version and processing module to facilitate subsequent traceability.

[0071] In step S202, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0072] See Figure 1 In step S203, the system executes "constructing a low-altitude operation envelope". Based on the mission scenario and aircraft type, it constructs an envelope encompassing takeoff and landing space, safety buffer, arrival and departure channels, parking and maintenance, charging and battery swapping, communication support, and emergency response.

[0073] The inputs to step S203 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, credibility fields, gap fields, or intermediate results that can be called by the next step.

[0074] In step S203, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version and processing module to facilitate subsequent traceability.

[0075] In step S203, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0076] See Figure 1 In step S204, the system performs "execution unit and envelope matching". The area, shape, clearance, approach and departure directions, accessibility, support conditions, and sensitive target avoidance are matched between the modifiable space unit and the low-altitude operation envelope.

[0077] The inputs to step S204 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, credibility fields, gap fields, or intermediate results that can be called by the next step.

[0078] In step S204, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version and processing module to facilitate subsequent traceability.

[0079] In step S204, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0080] See Figure 1 In step S205, the system executes "generating low-altitude resource objects". Space units that meet the space adaptability conditions or have the potential for supplementary certification are transformed into existing facility type, potential modification type, mission-specific type, regional reserve type, or return-to-core type resource objects.

[0081] The inputs to step S205 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, confidence fields, gap fields, or intermediate results that can be called by the next step.

[0082] In step S205, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version, and processing module to facilitate subsequent traceability.

[0083] In step S205, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0084] See Figure 1 In step S206, the system executes "Generate Evidence and Gap Objects". It checks spatial validity, facility authenticity, modification feasibility, operational support, task adaptability, external constraints, and evidence quality to form gap objects.

[0085] The inputs to step S206 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, confidence fields, gap fields, or intermediate results that can be called by the next step.

[0086] In step S206, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version, and processing module to facilitate subsequent traceability.

[0087] In step S206, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0088] See Figure 1 In step S207, the system performs "execution of layered data entry". Based on envelope matching results, evidence strength, gap severity, external constraint status, and verification status, the system determines the main resource layer, candidate layer, verification layer, reference layer, reserve layer, hidden layer, or noise layer.

[0089] The inputs to step S207 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, confidence fields, gap fields, or intermediate results that can be called by the next step.

[0090] In step S207, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version and processing module to facilitate subsequent traceability.

[0091] In step S207, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0092] See Figure 1 In step S208, the system executes the "output of subsequent review interface". Low-altitude resource objects are written into the multi-scenario resource library, and standardized object representations are output to the evaluation, planning, recommendation, and controlled operation modules.

[0093] The inputs to step S208 may include raw data, manual configuration, external interface return results, and historical version records; the outputs may include structured objects, status identifiers, confidence fields, gap fields, or intermediate results that can be called by the next step.

[0094] In step S208, the system can generate a unique identifier for each record and associate the identifier with the target area, business scenario, data source, processing time, processing version, and processing module to facilitate subsequent traceability.

[0095] In step S208, if the input data is missing, conflicting, expired, or has a mismatched spatial scope, the system preferably generates a verification mark or gap object instead of directly deleting the record or presuming that it meets the conditions.

[0096] See Figure 2 The system architecture of this invention can adopt a layered structure of data access, object evidence, constraint evaluation, planning recommendation, and output feedback. Data is transmitted between layers through unified object identifiers, source identifiers, constraint identifiers, and version identifiers.

[0097] In some implementations, the data access layer can receive data through file import, database connection, map service interface, manual data collection form, web page parsing service, remote sensing image processing service, or message queue.

[0098] In some implementations, the object evidence layer can merge multiple names, coordinates, images, and sources for the same candidate object, but the merging result does not delete the original source; instead, it forms an object version and an evidence version.

[0099] In some implementations, the constraint evaluation layer may use rule engines, spatial overlay analysis, buffer analysis, distance calculation, coverage analysis, path connectivity analysis, threshold discrimination, or manual review results as the basis for constraint judgment.

[0100] In some implementations, the planning recommendation layer can generate single-point recommendations, network combinations, phased construction, renovation and upgrading, priority for supplementary certification, and exit suggestions based on regional planning objectives.

[0101] In some implementations, the output feedback layer can send the results to maps, reports, dashboards, interface services, or task preparation package generation services, and include prohibited claims and audit identifiers in the output.

[0102] See Figure 3 The data relationship of the present invention preferably takes the low-altitude object as the core and associates the evidence claims, source citations, constraint objects, gap objects, output boundaries and feedback records.

[0103] For source citations, the system can record the source type, source address, source summary, collection time, credibility, timeliness, spatial scope, collector or collection system, and review status.

[0104] For evidence claims, the system can record the claim type, claim content, confidence level, strength of evidence, verification status, source of association, association constraints, scope, and generation method.

[0105] For gap objects, the system can record the gap type, gap severity, corresponding object, corresponding claim, corresponding constraint, recommended action, processing priority, and current status.

[0106] For output boundaries, the system can record allowed output, restricted output, degraded output, additional explanatory text, prohibited claims, map display method, and report display method.

[0107] See Figure 4 Regional network evaluation can abstract candidate objects into nodes, and task connections, service radii, corridor relationships or business demand connections into edges, and further calculate coverage, connectivity, redundancy and balance indicators.

[0108] In some implementations, the system can record priority construction nodes, upgrade nodes, certificate supplementation nodes, reserve nodes, and exit nodes in different states, but textual descriptions are preferred over approval conclusions in the official document output.

[0109] See Figure 5 The feedback calibration closed loop can receive feedback from manual review, trial operation records, abnormal events, external environment updates, policy and rule updates, and engineering modifications, and generate a new version status.

[0110] During feedback calibration, the system preferably uses an append-recording method to save the feedback results; if the feedback results conflict with the original evidence, the system generates a conflict record and a review task, rather than directly overwriting the original evidence.

[0111] Example 1: Identification of reconfigurable rooftop spaces.

[0112] In this embodiment, the system first establishes the target region, scene targets, and object set, and then follows... Figure 1 The process shown forms a data processing chain.

[0113] For data related to "identification of rooftop remodelable spaces", the system can read publicly available information, map objects, manually collected results, external constraint data and historical operation records to generate object representations, evidence records, constraint status and gap status.

[0114] When the relevant evidence is sufficient and the external constraints are verifiable, the system can improve the planning availability of the object; when the relevant evidence is insufficient, the constraints are not confirmed, or the scope does not match, the system restricts it to the review, static display, special demonstration, or reserve status.

[0115] This embodiment demonstrates the invention's ability to objectify, provide evidence for, constrain, and conservatively output information for low-altitude infrastructure planning review in the "identification of rooftop remodelable spaces" scenario.

[0116] Example 2: Existing helipad resources are already in the database.

[0117] In this embodiment, the system first establishes the target region, scene targets, and object set, and then follows... Figure 1 The process shown forms a data processing chain.

[0118] For data related to "existing helipad resources being entered into the database", the system can read publicly available information, map objects, manually collected results, external constraint data, and historical operation records to generate object representations, evidence records, constraint status, and gap status.

[0119] When the relevant evidence is sufficient and the external constraints are verifiable, the system can improve the planning availability of the object; when the relevant evidence is insufficient, the constraints are not confirmed, or the scope does not match, the system restricts it to the review, static display, special demonstration, or reserve status.

[0120] This embodiment demonstrates the invention's ability to objectify, provide evidence for, constrain, and conservatively output information for the planning and review of low-altitude infrastructure in the scenario of "existing helipad resources being included in the database".

[0121] Example 3: The main warehouse is not directly accessed from a flat, open area.

[0122] In this embodiment, the system first establishes the target region, scene targets, and object set, and then follows... Figure 1 The process shown forms a data processing chain.

[0123] For data related to "flat and open areas not directly entering the main database", the system can read publicly available information, map objects, manually collected results, external constraint data and historical operation records to generate object representations, evidence records, constraint status and gap status.

[0124] When the relevant evidence is sufficient and the external constraints are verifiable, the system can improve the planning availability of the object; when the relevant evidence is insufficient, the constraints are not confirmed, or the scope does not match, the system restricts it to the review, static display, special demonstration, or reserve status.

[0125] This embodiment demonstrates the invention's ability to objectify, provide evidence for, constrain, and conservatively output information for low-altitude infrastructure planning and review in scenarios where "flat, open land does not directly enter the main database".

[0126] Example 4: Construction of resources for a composite scenario in a logistics park.

[0127] In this embodiment, the system first establishes the target region, scene targets, and object set, and then follows... Figure 1 The process shown forms a data processing chain.

[0128] For data related to "composite scenario resource construction in logistics parks", the system can read publicly available information, map objects, manually collected results, external constraint data and historical operation records to generate object representations, evidence records, constraint states and gap states.

[0129] When the relevant evidence is sufficient and the external constraints are verifiable, the system can improve the planning availability of the object; when the relevant evidence is insufficient, the constraints are not confirmed, or the scope does not match, the system restricts it to the review, static display, special demonstration, or reserve status.

[0130] This embodiment demonstrates the invention's ability to objectify, provide evidence for, constrain, and conservatively output the planning and review of low-altitude infrastructure in the "logistics park complex scenario resource construction" scenario.

[0131] In another implementation, the system can be deployed on a cloud server, with low-altitude resource acquisition terminals, map display terminals, and planning review terminals accessing the server via a network. The server centrally stores records of objects, evidence, constraints, gaps, recommendations, and feedback.

[0132] In another implementation, the system can interface with existing geographic information systems, low-altitude monitoring platforms, digital twin platforms, project management platforms, or report generation platforms to output standardized interface data.

[0133] In another implementation, the system can configure different hard access rules, threshold rules, and output boundary rules according to the regulatory requirements and data availability of different regions.

[0134] In another implementation, the system can use the results of manual review as one of the sources with higher credibility, but still record the reviewer, review time, review basis and review scope to avoid manual conclusions from deviating from the chain of evidence.

[0135] In another implementation, the system can associate and save images, map screenshots, report summaries, or web page content, but the images and web page content are only used as source references or evidence materials and do not directly replace structured constraint judgments.

[0136] In another implementation, the system can generate different output templates based on the task type, such as internal review templates, planning suggestion templates, supplementary certification list templates, controlled trial operation preparation templates, and audit traceability templates.

[0137] The technical features in the above embodiments can be combined with each other without conflict. All technical solutions formed by equivalent substitution or transformation should fall within the protection scope of this invention.

[0138] Table 1 shows the key data objects that can be used in this invention and their applications. This table is only an example of data structure for ease of understanding and does not limit the field names, number of fields, or storage methods.

[0139] Modifiable Space Unit Table Used to store object identifiers, versions, statuses, sources, constraints, or output fields associated with the modifiable space cell table. Low-altitude flight envelope table Used to store object identifiers, versions, statuses, sources, constraints, or output fields associated with the low-altitude flight envelope table. Envelope matching results table Used to store object identifiers, versions, statuses, sources, constraints, or output fields associated with the envelope matching results table. Low-altitude resource object table Used to store object identifiers, versions, statuses, sources, constraints, or output fields associated with the Low Altitude Resource Object Table. Table of Evidence Citation Used to store object identifiers, versions, statuses, sources, constraints, or output fields related to the evidence citation table. Gap Object Table Used to store object identifiers, versions, statuses, sources, constraints, or output fields associated with the gap object table. Layered Inbound Status Table Used to store object identifiers, versions, statuses, sources, constraints, or output fields associated with hierarchical inbound status tables.

[0140] Those skilled in the art can expand, split, or merge the above fields according to the target area, business scenario, data availability, and regulatory requirements. As long as the objectification, evidence-based, constraint-based, degradation, and feedback processing described in this invention can be achieved, they are all equivalent implementations of this invention.

Claims

1. A method for generating modifiable spatial units, constructing low-altitude resource objects, and hierarchically storing data for low-altitude infrastructure planning, characterized in that: include: Acquire multi-source spatial object and clue data within the target area; Geometric normalization, spatial segmentation, or merging of the multi-source spatial objects are performed to generate modifiable spatial units; Construct a low-altitude operation envelope based on low-altitude mission scenarios and aircraft types; The modifiable spatial unit is matched with the low-altitude operational envelope to obtain a spatial adaptation result; a low-altitude resource object is generated based on the spatial adaptation result, evidence reference, and external constraint state. Evidence and gap checks are performed on the low-altitude resource objects; and the entry level of the low-altitude resource objects is determined based on the running envelope matching results, evidence strength, gap severity, and review status.

2. The method according to claim 1, characterized in that, The multi-source spatial objects include one or more of the following: existing low-altitude facilities, building rooftops, parking lots, logistics parks, industrial parks, hospitals, schools, open areas in scenic spots, transportation hubs, emergency sites, open areas, existing helipads, and spaces that can be modified.

3. The method according to claim 1, characterized in that, The clue data includes one or more of the following: map points of interest, building outlines, remote sensing imagery, street view images, planning data, web page text, manually collected forms, company information, external reports, and historical project data.

4. The method according to claim 1, characterized in that, The modifiable spatial units include one or more of the following: point units, surface units, roof units, ground site units, linear corridor-related units, and composite scene units.

5. The method according to claim 1, characterized in that, The low-altitude operation envelope includes one or more of the following: takeoff and landing space envelope, safety buffer envelope, arrival and departure passage envelope, parking and maintenance envelope, charging and battery swapping support envelope, communication support envelope, and emergency response envelope.

6. The method according to claim 1, characterized in that, The spatial adaptation results include one or more of the following: area adaptation results, shape adaptation results, clearance adaptation results, entry and exit direction adaptation results, ground accessibility adaptation results, protection condition adaptation results, and surrounding sensitive target avoidance adaptation results.

7. The method according to claim 1, characterized in that, The low-altitude resource objects include one or more of the following: existing facility type objects, potential transformation type objects, mission-specific type objects, regional reserve type objects, and return-to-base type objects.

8. The method according to claim 1, characterized in that, When any modifiable space unit meets some of the conditions of the low-altitude operation envelope but has gaps in space, evidence, external constraints, operational support, or ownership and use, the corresponding low-altitude resource object will be written into the review layer, reserve layer, or reference layer, but not into the main resource layer.

9. A system for generating modifiable spatial units, constructing low-altitude resource objects, and hierarchically storing data for low-altitude infrastructure planning, characterized in that: It includes a multi-source spatial object acquisition module, a modifiable spatial unit generation module, a low-altitude operational envelope construction module, a spatial unit-operational envelope matching module, a low-altitude resource object generation module, an evidence and gap checking module, a hierarchical storage module, and a subsequent review interface module, for performing the method described in any one of claims 1 to 8.

10. An electronic device or computer-readable storage medium, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores a computer program that, when executed by the processor, implements the method according to any one of claims 1 to 8; or the computer-readable storage medium stores a computer program that, when executed by the processor, implements the method according to any one of claims 1 to 8.

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