A land space dynamic monitoring and conflict identification system and method

Abstract

The application discloses a land space dynamic monitoring and conflict identification system and method, which comprises a multi-source data access and processing module, a dynamic monitoring module, a conflict identification module, a conflict event tracing and checking module, a command and dispatch module, a closed-loop treatment module and an achievement output module; the multi-source data access and processing module completes format normalization, coordinate unification and noise cleaning of multi-source heterogeneous data such as satellite remote sensing, unmanned aerial vehicle aerial photography, planning base map and land account, and outputs a standard consistent basic data base; the application completes standardized processing of multi-source heterogeneous data through the multi-source data access and processing module, provides a unified data base for the whole system, solves the problems of single data source and non-uniform data format of the existing system, realizes multi-source data collaborative interpretation through an AI model, automatically extracts changed patches, greatly improves monitoring frequency and change discovery efficiency, and reduces labor cost compared with traditional manual patrol.

Description

Technical Field

[0001] This invention relates to the field of dynamic monitoring technology of national land space, and in particular to a dynamic monitoring and conflict identification system and method for national land space. Background Technology

[0002] The current development and protection of national land space needs to balance the dual demands of development and control. Frequent development and construction activities and rapid changes in land use and spatial utilization have led to a decline in the effectiveness of traditional monitoring models that rely on annual manual inspections and paper-based records. These models suffer from low monitoring frequency, untimely detection, inefficient conflict determination based on manual experience, and insufficient end-to-end tracking. They are ill-suited to the dynamic and refined management requirements of national land use control in the new era. Furthermore, existing monitoring systems often rely on single data sources, making it difficult to integrate multi-source data from satellites, drones, and ground inspections. The identification of spatial conflicts remains at a coarse-grained, overlapping level, lacking a complete closed-loop capability from monitoring and identification to handling and tracing the source. This hinders the management departments' ability to respond quickly and efficiently to changes in national land use.

[0003] In Chinese patent CN121258286B, the solution can achieve full-cycle monitoring of land space restoration projects, but it focuses on the progress supervision of approved restoration projects and does not dynamically identify and handle the normalized land space use conflicts across the entire region. It also does not realize the automatic flow of multi-source data from access to output. Therefore, this invention proposes a land space dynamic monitoring and conflict identification system and method to solve the problems existing in the prior art. Summary of the Invention

[0004] To address the aforementioned issues, the present invention aims to propose a dynamic monitoring and conflict identification system and method for national land space. This system and method standardizes multi-source heterogeneous data through a multi-source data access and processing module, providing a unified data foundation for the entire system and solving the problems of single data source and inconsistent data formats in existing systems. Furthermore, it utilizes an AI model to achieve collaborative interpretation of multi-source data and automatically extract changed map features, significantly improving monitoring frequency and change detection efficiency, while reducing labor costs compared to traditional manual inspections.

[0005] To achieve the objectives of this invention, the invention is implemented through the following technical solution: a dynamic monitoring and conflict identification system and method for territorial space, comprising a multi-source data access and processing module, a dynamic monitoring module, a conflict identification module, a conflict event tracing and verification module, a command and dispatch module, a closed-loop handling module, and a results output module;

[0006] The multi-source data access and processing module completes the format normalization, coordinate unification, and noise cleaning of multi-source heterogeneous data such as satellite remote sensing, drone aerial photography, planning base map, and land ledger, and outputs a standardized basic data base.

[0007] The dynamic monitoring module, through processing the standard image data output by the module, directly pushes the generated change patches to the downstream conflict identification module, providing core change basis for conflict determination;

[0008] The conflict identification module performs spatial overlay analysis between the dynamic monitoring output of change patches and the multi-layer planning and control base map to automatically identify various types of land space violation and conflict events.

[0009] The conflict incident tracing and verification module synchronizes the warning list output by the conflict identification module with the verified real and valid conflict incident data to the visualization scheduling module, filtering out invalid warnings that are misjudged.

[0010] The command and dispatch module and the closed-loop handling module centrally display the output results of all preceding modules, while pushing the dispatch instructions of the management personnel back to the mobile terminal of the traceability and verification module, realizing two-way information exchange between the management end and the front-line operation end.

[0011] The output module tracks and records the entire process of conflict events from case filing and rectification to acceptance, and automatically generates standardized monitoring reports and handling ledgers.

[0012] Further improvements are made in that: the multi-source data access and processing module uses an adaptive access engine to automatically import data from different sources into the system through corresponding dedicated interfaces. The engine automatically identifies the data format, spatial coordinate system, and confidentiality level, and automatically allocates the corresponding storage partition.

[0013] Further improvements include: the dynamic monitoring module automatically connects to three types of data sources: satellite imagery, drone aerial photography data, and ground monitoring video streams, and relies on a customized trained land scene AI model to complete the collaborative interpretation of all types of data.

[0014] Further improvements include: the conflict identification module is equipped with a drag-and-drop rule editor, which overlays the monitored and output change patches with permanent basic farmland, ecological red lines and planned use zones at the pixel level to accurately determine spatial matching relationships.

[0015] Further improvements include: the conflict event tracing and verification module automatically associates the conflict events identified with the corresponding land parcel's historical approval records, ownership information, and years of monitoring change trajectory, generating a complete event tracing archive with one click.

[0016] Further improvements include: the command and dispatch module and the closed-loop handling module synchronously present full-domain monitoring data, conflict distribution and real-time handling progress on the GIS map; through the handling task flow synchronized by the command and dispatch module, based on the historical conflict data accumulated by the module, the high incidence patterns of violations in different areas are automatically analyzed.

[0017] Further improvements include: the output module automatically generates standardized monitoring reports and disposal ledgers, receives disposal progress data synchronized by the visualization scheduling module, and sends the updated status data back to the upstream preprocessing module to complete the iterative update of the basic database.

[0018] Further improvements include the following steps:

[0019] Step 1: Integrate multi-source heterogeneous data from satellite remote sensing, drone aerial photography, planning base maps, and land ledgers, and complete coordinate unification, image correction, and abnormal data cleaning and completion;

[0020] Step 2: Through a three-level collaborative mode of satellite-drone-ground monitoring, a customized AI interpretation model is used to perform pixel-level comparison of images from different time periods, automatically extracting changes such as farmland conversion to non-agricultural use and illegal construction, filtering out misjudgments caused by cloud shadows, and generating an accurate list of changes.

[0021] Step 3: Customize local land space management rules through the visual rule editor, perform spatial overlay analysis on the changed map patches and multi-layer management base map, automatically determine the conflict type, classify the conflict level, and generate a standardized conflict early warning list;

[0022] Step 4: Associate the initially identified conflict events with the historical approval files, ownership information and monitoring change data of the corresponding land parcels to generate a complete traceability file and push it to the front-line verification personnel. Verify the authenticity of the conflict on-site through the mobile terminal, mark the false judgment warning and supplement the verification information, filter the invalid warnings and output the list of real and valid conflict events.

[0023] Step 5: Record all process nodes of the conflict from case filing and rectification to acceptance and cancellation, automatically summarize and organize standardized monitoring reports and handling ledgers, and at the same time, transmit and update the land space status data after rectification to the basic data base to complete the closed-loop iteration of data.

[0024] The beneficial effects of this invention are as follows: By standardizing the processing of heterogeneous multi-source data through a multi-source data access and processing module, a unified data foundation is provided for the entire system, solving the problems of single data sources and inconsistent data formats in existing systems; AI models enable collaborative interpretation of multi-source data, automatically extracting changed patches, significantly increasing monitoring frequency and change detection efficiency, and reducing labor costs compared to traditional manual inspections; A drag-and-drop rule editor adapts to the control requirements of different areas, achieving pixel-level spatial overlay analysis, improving the accuracy of conflict identification, and reducing reliance on experience in manual judgment; Through the integration of the entire link module, a closed-loop management system is achieved from identification, tracing, scheduling to disposal, supporting two-way information exchange between the management end and the front-line operation end, significantly improving the response efficiency of conflict handling; Finally, standardized results are automatically generated and basic data iteration is completed, forming a complete closed loop of data updates, continuously ensuring the timeliness of basic data. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the system modules of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Example 1

[0029] according to Figure 1As shown, this embodiment provides a land space dynamic monitoring and conflict identification system and method, including a multi-source data access and processing module, a dynamic monitoring module, a conflict identification module, a conflict event tracing and verification module, a command and dispatch module, a closed-loop handling module, and a results output module. The multi-source data access and processing module automatically identifies the format, spatial coordinate system, and confidentiality level of data from different sources through an adaptive access engine. It completes the format normalization, coordinate unification, and noise cleaning of multi-source heterogeneous data such as satellite remote sensing, UAV aerial photography, planning base maps, and land ledgers. After automatically allocating corresponding storage partitions, it outputs a standardized basic data base. The dynamic monitoring module automatically connects to three types of data sources: satellite imagery, UAV aerial photography data, and ground monitoring video streams. Relying on a customized trained land scene AI model, it completes the collaborative interpretation of all types of data. It extracts and generates change patches from the processed standard image data and directly pushes them to the downstream conflict identification module, providing core change evidence for conflict determination.

[0030] The conflict identification module is equipped with a drag-and-drop rule editor that supports custom control rules. It performs pixel-level spatial overlay analysis on the dynamic monitoring output change patches and multi-layer planning control base maps such as permanent basic farmland, ecological red lines, and planned use zones to accurately determine spatial matching relationships, automatically identify various types of land space violations and conflicts, and generate a conflict warning list after classifying the conflict levels.

[0031] After receiving the conflict warning list, the conflict incident tracing and verification module automatically corresponds to the historical approval records, ownership information, and long-term monitoring change trajectories of the conflicting land parcels, generating a complete incident tracing file with one click. This file is then pushed to frontline verification personnel for on-site verification via mobile devices. After verification, invalid warnings with false positives are filtered out, and the real and valid conflict incident data is synchronized to the command and dispatch module. The command and dispatch and closed-loop handling modules centrally display the full-area monitoring data, conflict distribution, and real-time handling progress on the GIS map. The dispatch instructions from management personnel are pushed back to the mobile terminal of the tracing and verification module, achieving two-way information exchange between the management end and the frontline operation end. The results output module tracks and records the entire process of conflict incidents from case filing, rectification to acceptance, automatically generating standardized monitoring reports and handling ledgers. At the same time, it receives handling progress data and sends the updated status data after rectification back to the upstream multi-source data access and processing module to complete the iterative update of the basic database and form a closed-loop data process.

[0032] The monitoring and identification methods of this system include the following steps: First, it integrates multi-source heterogeneous data from satellite remote sensing, drone aerial photography, planning base maps, and land ledgers. After data classification and storage through an adaptive engine, it achieves unified coordinate normalization, image correction, and abnormal data cleaning and completion, outputting a standardized basic data base. Second, it adopts a three-level collaborative mode of satellite-drone-ground monitoring, using a customized AI interpretation model to perform pixel-level comparisons of data from different time periods, automatically extracting change patches such as farmland conversion to non-agricultural uses and illegal construction, filtering out misjudgments caused by factors such as cloud shadows, and generating an accurate list of change patches. Third, it allows for the customization of land space management rules that meet local requirements through a drag-and-drop visual rule editor, performing spatial overlay analysis of change patches with multi-layered management base maps, automatically determining conflict types, and classifying conflicts. The system first ranks conflict events by generating a standardized conflict warning list. The fourth step involves automatically linking the historical approval files, ownership information, and annual monitoring change data of the corresponding land parcels to the initially identified conflict events, generating a complete traceability file and pushing it to frontline verification personnel. Verification personnel then use mobile devices to verify the authenticity of the conflict on-site, marking false warnings and supplementing on-site verification information. After filtering invalid warnings, a list of valid conflict events is output. The fifth step involves the command and dispatch module pushing down disposal tasks, recording the entire process of conflict resolution from case filing and rectification to acceptance and closure. After disposal, a standardized monitoring report and disposal ledger are automatically generated, and the completed land space status data is updated back to the basic data base, completing the closed-loop iteration of data and continuously ensuring the timeliness of the basic data. The table below shows the module information.

[0033]

[0034] Table 1 Module Information Table

[0035] Example 2

[0036] After generating a complete source tracing file, the conflict incident tracing and verification module supports automatic allocation of verification tasks according to the conflict level and the jurisdiction. It prioritizes pushing high-level conflict tasks to front-line verification personnel in the corresponding jurisdiction, avoiding the manual screening process for task allocation and further shortening the response time. The command and dispatch module supports one-click initiation of collaborative handling applications for cross-regional conflict incidents, automatically synchronizing conflict information and source tracing files to the management ports of related regions. This solves the information silo problem in cross-jurisdictional conflict handling, further improving the efficiency of collaborative handling. It is more suitable for municipal-level land space monitoring and management scenarios with large areas and complex jurisdictional divisions.

[0037] The closed-loop handling and output module in this embodiment generates a unique electronic handling file for each conflict event. It automatically tracks and records the entire process from event identification, dispatch, on-site verification, case filing and enforcement, rectification completion, and acceptance and archiving. For events exceeding the prescribed handling time limit, it automatically triggers an escalation warning and pushes it to the superior competent department for supervision, completely avoiding delays and omissions in conflict event handling. The system automatically compares the on-site images after rectification with the planning control base map, intelligently verifies whether the rectification meets the standards, and accurately identifies cases of false rectification and inadequate rectification. The module has a built-in report template library required by the natural resources department, which can quickly and automatically generate monthly dynamic monitoring reports, annual land use assessment reports, and a full ledger of conflict handling. It can directly connect to the superior land space supervision platform to complete data reporting without manual secondary formatting, saving the repetitive workload of manual sorting and secondary entry. Finally, the system back-synchronizes the latest land use status data that has passed acceptance back to the upstream multi-source data preprocessing module to complete the iterative update of the entire system's basic database, forming a complete business closed loop of "monitoring-identification-handling-updating".

[0038] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic monitoring and conflict identification system for national land space, characterized in that, It includes a multi-source data access and processing module, a dynamic monitoring module, a conflict identification module, a conflict event tracing and verification module, a command and dispatch module, a closed-loop handling module, and a results output module; The multi-source data access and processing module completes the format normalization, coordinate unification, and noise cleaning of multi-source heterogeneous data such as satellite remote sensing, drone aerial photography, planning base map, and land ledger, and outputs a standardized basic data base. The dynamic monitoring module, through processing the standard image data output by the module, directly pushes the generated change patches to the downstream conflict identification module, providing core change basis for conflict determination; The conflict identification module performs spatial overlay analysis between the dynamic monitoring output of change patches and the multi-layer planning and control base map to automatically identify various types of land space violation and conflict events. The conflict incident tracing and verification module synchronizes the warning list output by the conflict identification module with the verified real and valid conflict incident data to the visualization scheduling module, filtering out invalid warnings that are misjudged. The command and dispatch module and the closed-loop handling module centrally display the output results of all preceding modules, while pushing the dispatch instructions of the management personnel back to the mobile terminal of the traceability and verification module, realizing two-way information exchange between the management end and the front-line operation end. The output module tracks and records the entire process of conflict events from case filing and rectification to acceptance, and automatically generates standardized monitoring reports and handling ledgers.

2. The land space dynamic monitoring and conflict identification system according to claim 1, characterized in that: The multi-source data access and processing module uses an adaptive access engine to automatically import data from different sources into the system through corresponding dedicated interfaces. The engine automatically identifies the data format, spatial coordinate system, and confidentiality level, and automatically allocates the corresponding storage partition.

3. The land space dynamic monitoring and conflict identification system according to claim 1, characterized in that: The dynamic monitoring module automatically connects to three types of data sources: satellite imagery, drone aerial photography data, and ground monitoring video streams. Relying on a customized trained AI model for land and resources scenarios, it completes the collaborative interpretation of all types of data.

4. The land space dynamic monitoring and conflict identification system according to claim 1, characterized in that: The conflict identification module is equipped with a drag-and-drop rule editor, which overlays the monitored change patches with permanent basic farmland, ecological red lines and planned use zones at the pixel level to accurately determine spatial matching relationships.

5. The land space dynamic monitoring and conflict identification system according to claim 1, characterized in that: The conflict event tracing and verification module automatically associates the conflict events identified with the corresponding land parcels' historical approval records, ownership information, and years of monitoring change trajectories, generating a complete event tracing archive with a single click.

6. The land space dynamic monitoring and conflict identification system according to claim 1, characterized in that: The command and dispatch module and the closed-loop handling module simultaneously present full-domain monitoring data, conflict distribution, and real-time handling progress on the GIS map. Through the handling task flow synchronized by the command and dispatch module, and based on the historical conflict data accumulated by the module, the high incidence patterns of violations in different areas are automatically analyzed.

7. The land space dynamic monitoring and conflict identification system according to claim 1, characterized in that: The output module automatically generates standardized monitoring reports and disposal ledgers, receives disposal progress data synchronized by the visualization scheduling module, and sends the updated status data back to the upstream preprocessing module to complete the iterative update of the basic database.

8. The method for applying to a dynamic monitoring and conflict identification system for national land space according to claims 1-7, characterized in that, Includes the following steps: Step 1: Integrate multi-source heterogeneous data from satellite remote sensing, drone aerial photography, planning base maps, and land ledgers, and complete coordinate unification, image correction, and abnormal data cleaning and completion; Step 2: Through a three-level collaborative mode of satellite-drone-ground monitoring, a customized AI interpretation model is used to perform pixel-level comparison of images from different time periods, automatically extracting changes such as farmland conversion to non-agricultural use and illegal construction, filtering out misjudgments caused by cloud shadows, and generating an accurate list of changes. Step 3: Customize local land space management rules through the visual rule editor, perform spatial overlay analysis on the changed map patches and multi-layer management base map, automatically determine the conflict type, classify the conflict level, and generate a standardized conflict early warning list; Step 4: Associate the initially identified conflict events with the historical approval files, ownership information and monitoring change data of the corresponding land parcels to generate a complete traceability file and push it to the front-line verification personnel. Verify the authenticity of the conflict on-site through the mobile terminal, mark the false judgment warning and supplement the verification information, filter the invalid warnings and output the list of real and valid conflict events. Step 5: Record all process nodes of the conflict from case filing and rectification to acceptance and cancellation, automatically summarize and organize standardized monitoring reports and handling ledgers, and at the same time, transmit and update the land space status data after rectification to the basic data base to complete the closed-loop iteration of data.

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