Intelligent investigation method for industrial land information

Abstract

The invention discloses a method for intelligently investigating industrial land information. The method comprises the following steps: 1) creating a unique association code for the industrial land information by adopting an association code identification system; 2) periodically identifying newly-built buildings and idle lands in the industrial lands; and 3) planning an optimal path of the unmanned aerial vehicle by using a Voronoi graph algorithm, carrying out evidence collection on the abnormal area through the unmanned aerial vehicle carrying a high-definition camera and a laser radar, and generating an evidence collection report associated with the land parcel according to the association code. According to the invention, an intelligent sensing network is constructed by using satellite remote sensing, the unmanned aerial vehicle and Internet of Things equipment, and 24-hour automatic monitoring and real-time monitoring and early warning are realized.

Description

Technical Field

[0001] The present invention relates to the field of land use information management, and in particular to a method for intelligent investigation of industrial land use information. Background Art

[0002] Currently, industrial land management mainly relies on manual inspections and single-department data statistics, which has the following core problems:

[0003] 1. Serious data silos: Data such as land use planning data, permit documents, corporate tax payments from the tax department, and electricity and energy consumption data from the power department are stored in scattered locations, lacking a unified coding and sharing mechanism. For example, a plot of land is planned for "industrial warehousing," but the company that actually occupies it may illegally convert it into a commercial facility. Because the data on planned land use, approvals, taxes, electricity usage, and energy consumption are disconnected, such issues are difficult to detect in a timely manner.

[0004] 2. Delayed information updates: Land use status (e.g., illegal construction, idleness) relies on quarterly or annual manual verification, with response times as long as 1-3 months, leading to management blind spots. For example, a company may expand its factory without authorization, and by the time law enforcement officers discover it, construction has already been completed, resulting in wasted resources and increased enforcement costs.

[0005] 3. Insufficient decision-making basis: The government lacks real-time data support, making it difficult to accurately identify inefficient land use. For example, long-term idle land cannot be quickly identified and targeted revitalization strategies cannot be formulated in a timely manner due to the lack of a dynamic assessment mechanism. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for intelligent investigation of industrial land information, comprising the following steps:

[0007] 1) Using an association code identification system to create a unique association code for industrial land information; the industrial land information includes land parcel, approval, tax, power company, economic and information department, electricity consumption, energy consumption, and output value;

[0008] 2) Periodically identify new buildings and idle land in industrial land. If new buildings exist, proceed to step 3); if idle land exists, proceed to step 4);

[0009] The steps for identifying new buildings in industrial land are as follows: periodically acquiring satellite remote sensing images of industrial land, and identifying the satellite remote sensing images of industrial land to determine whether there are new buildings;

[0010] The steps for identifying idle land in industrial land are as follows: using intelligent sensing equipment to collect construction information corresponding to each plot, and judging whether there is idle land based on the construction information. If so, the idle land is regarded as an abnormal area and the process proceeds to step 4);

[0011] 3) Compare the newly built buildings in the satellite remote sensing image of the industrial land with the approval association code. If the newly built buildings are illegal buildings, the area where the newly built buildings are located is regarded as an abnormal area and proceed to step 4);

[0012] 4) Use the Voronoi diagram algorithm to plan the optimal path of the drone, use the drone equipped with high-definition cameras and lidar to collect evidence in abnormal areas, and generate a forensic report associated with the plot based on the association code.

[0013] Furthermore, in the process of periodically identifying new buildings and idle land in industrial land, the land use efficiency indicators of each plot are also evaluated;

[0014] Land use efficiency indicators include tax revenue per unit area, output value per unit energy consumption, employment density, and environmental compliance rate.

[0015] Furthermore, idle land refers to land where the enterprise's electricity consumption is zero for a continuous period of T1, the enterprise's electricity consumption decreases by more than 50% week-on-week, or the number of logistics vehicles entering and leaving the land decreases by 80% for a continuous period of T2.

[0016] Furthermore, construction information includes the company’s real-time electricity consumption and the frequency of logistics vehicles entering and leaving the company;

[0017] The company’s real-time electricity consumption is monitored through smart meters;

[0018] The frequency of logistics vehicles entering and exiting is monitored by license plate recognition cameras.

[0019] Furthermore, the steps of identifying industrial land satellite remote sensing images include:

[0020] S1) extracting the outline features of buildings from the current industrial land satellite remote sensing image;

[0021] S2) comparing the outline features of buildings in current satellite remote sensing images of industrial land with the outline features of buildings in historical images to identify newly built buildings.

[0022] Furthermore, in step S1), the contour features of the buildings in the current industrial land satellite remote sensing image are extracted by a convolutional neural network;

[0023] The convolutional neural network is trained through historical data sets.

[0024] Furthermore, illegal buildings refer to new buildings that exceed the approval scope, have no corresponding permits, or the permit information is inconsistent with the actual construction purpose or does not match the scale.

[0025] Furthermore, the coding rule of the land use association code is: administrative division code + land use type code + X coordinate of the center point of the land use spatial range + Y coordinate of the center point of the land use spatial range + area + serial number, and is associated with the GIS coordinates, planned use, area, and property rights information of the land parcel;

[0026] The coding rule for the approval association code is: administrative division code + approval type code + approval document number + approval time + serial number, and is associated with the permitted use, building area, permission opinion, validity period, and scanned copy of the approval document;

[0027] The coding rules for the tax department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with the enterprise's annual tax payment and value-added tax details;

[0028] The coding rules for the power company association code are: administrative division code + department name code + enterprise unified social credit code, and are associated with the company's monthly electricity consumption and peak and valley electricity consumption data;

[0029] The coding rules for the economic and information department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with business data; business data includes enterprise output value and employment scale.

[0030] Furthermore, when creating a unique association code for industrial land information, the data source and modification history are recorded to ensure that the data is traceable and tamper-proof.

[0031] The technical benefits of this invention are undeniable. Through a unified coding system, it connects multiple sources of data, including land, approvals, and enterprises, enabling dynamic interconnection and interoperability of information and related data. This invention also utilizes satellite remote sensing, drones, and IoT devices to build an intelligent sensing network, enabling 24-hour automated monitoring, real-time monitoring, and early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Flow chart of the method. DETAILED DESCRIPTION

[0033] The present invention will be further described below with reference to the following examples, but it should not be understood that the scope of the present invention is limited to the following examples. Without departing from the above technical ideas of the present invention, various substitutions and modifications can be made according to common technical knowledge and customary means in the art, and all should be included in the scope of protection of the present invention.

[0034] Example 1:

[0035] See also Figure 1 A method for intelligent investigation of industrial land information includes the following steps:

[0036] 1) Using an association code identification system to create a unique association code for industrial land information; the industrial land information includes land parcel, approval, tax, power company, economic and information department, electricity consumption, energy consumption, and output value;

[0037] 2) Periodically identify new buildings and idle land in industrial land. If new buildings exist, proceed to step 3); if idle land exists, proceed to step 4);

[0038] The steps for identifying new buildings in industrial land are as follows: periodically acquiring satellite remote sensing images of industrial land, and identifying the satellite remote sensing images of industrial land to determine whether there are new buildings;

[0039] The steps for identifying idle land in industrial land are as follows: using intelligent sensing equipment to collect construction information corresponding to each plot, and judging whether there is idle land based on the construction information. If so, the idle land is regarded as an abnormal area and the process proceeds to step 4);

[0040] 3) Compare the newly built buildings in the satellite remote sensing image of the industrial land with the approval association code. If the newly built buildings are illegal buildings, the area where the newly built buildings are located is regarded as an abnormal area and proceed to step 4);

[0041] 4) Use the Voronoi diagram algorithm to plan the optimal path of the drone, use the drone equipped with high-definition cameras and lidar to collect evidence in abnormal areas, and generate a forensic report associated with the plot based on the association code.

[0042] During the periodic identification of new buildings and idle land in industrial land, the land efficiency indicators of each plot are also evaluated;

[0043] Land use efficiency indicators include tax revenue per unit area, output value per unit energy consumption, employment density, and environmental compliance rate.

[0044] Idle land refers to land where the enterprise's electricity consumption is zero for a continuous period of T1, the enterprise's electricity consumption decreases by more than 50% week-on-week, or the number of logistics vehicles entering and leaving the land decreases by 80% for a continuous period of T2.

[0045] Construction information includes real-time electricity consumption of enterprises and the frequency of logistics vehicles entering and leaving;

[0046] The company’s real-time electricity consumption is monitored through smart meters;

[0047] The frequency of logistics vehicles entering and exiting is monitored by license plate recognition cameras.

[0048] The steps for identifying industrial land satellite remote sensing images include:

[0049] S1) extracting the outline features of buildings from the current industrial land satellite remote sensing image;

[0050] S2) comparing the outline features of buildings in current satellite remote sensing images of industrial land with the outline features of buildings in historical images to identify newly built buildings.

[0051] In step S1), the outline features of the building in the current industrial land satellite remote sensing image are extracted through a convolutional neural network;

[0052] The convolutional neural network is trained through historical data sets.

[0053] Illegal buildings refer to new buildings that exceed the approved scope, have no corresponding permits, or whose permit information is inconsistent with the actual construction purpose or does not match the scale.

[0054] The coding rule of the land association code is: administrative division code + land type code + X coordinate of the center point of the land spatial range + Y coordinate of the center point of the land spatial range + area + serial number, and it is associated with the GIS coordinates, planned use, area, and property rights information of the land parcel;

[0055] The coding rule for the approval association code is: administrative division code + approval type code + approval document number + approval time + serial number, and is associated with the permitted use, building area, permission opinion, validity period, and scanned copy of the approval document;

[0056] The coding rules for the tax department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with the enterprise's annual tax payment and value-added tax details;

[0057] The coding rules for the power company association code are: administrative division code + department name code + enterprise unified social credit code, and are associated with the company's monthly electricity consumption and peak and valley electricity consumption data;

[0058] The coding rules for the economic and information department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with business data such as enterprise output value and employment scale.

[0059] When creating a unique association code for industrial land information, record the data source and modification history to ensure data traceability and tamper-proofing.

[0060] Example 2:

[0061] A method for intelligent investigation of industrial land information includes the following steps:

[0062] 1) Using an association code identification system to create a unique association code for industrial land information; the industrial land information includes land parcel, approval, tax, power company, economic and information department, electricity consumption, energy consumption, and output value;

[0063] 2) Periodically identify new buildings and idle land in industrial land. If new buildings exist, proceed to step 3); if idle land exists, proceed to step 4);

[0064] The steps for identifying new buildings in industrial land are as follows: periodically acquiring satellite remote sensing images of industrial land, and identifying the satellite remote sensing images of industrial land to determine whether there are new buildings;

[0065] The steps for identifying idle land in industrial land are as follows: using intelligent sensing equipment to collect construction information corresponding to each plot, and judging whether there is idle land based on the construction information. If so, the idle land is regarded as an abnormal area and the process proceeds to step 4);

[0066] 3) Compare the newly built buildings in the satellite remote sensing image of the industrial land with the approval association code. If the newly built buildings are illegal buildings, the area where the newly built buildings are located is regarded as an abnormal area and proceed to step 4);

[0067] 4) Use the Voronoi diagram algorithm to plan the optimal path of the drone, use the drone equipped with high-definition cameras and lidar to collect evidence in abnormal areas, and generate a forensic report associated with the plot based on the association code.

[0068] Example 3:

[0069] A method for intelligently investigating industrial land information, with the same technical content as Example 2, further comprising evaluating the land use efficiency indicators of each plot during the periodic identification of new buildings and idle land within the industrial land;

[0070] Land use efficiency indicators include tax revenue per unit area, output value per unit energy consumption, employment density, and environmental compliance rate.

[0071] Example 4:

[0072] A method for intelligent investigation of industrial land information, with technical content similar to any one of Examples 2-3. Furthermore, idle land refers to land where the enterprise's electricity consumption is zero for a continuous period of T1, the enterprise's electricity consumption decreases by more than 50% week-on-week, or the number of logistics vehicles entering and exiting the land decreases by 80% for a continuous period of T2.

[0073] Example 5:

[0074] A method for intelligently investigating industrial land information, with the same technical content as any one of Examples 2-4, wherein the construction information further includes the enterprise's real-time electricity consumption and the frequency of logistics vehicle entry and exit;

[0075] The company’s real-time electricity consumption is monitored through smart meters;

[0076] The frequency of logistics vehicles entering and exiting is monitored by license plate recognition cameras.

[0077] Example 6:

[0078] A method for intelligent investigation of industrial land information, with the same technical content as any one of Examples 2-5, further comprising the step of identifying satellite remote sensing images of industrial land:

[0079] S1) extracting the outline features of buildings from the current industrial land satellite remote sensing image;

[0080] S2) comparing the outline features of buildings in current satellite remote sensing images of industrial land with the outline features of buildings in historical images to identify newly built buildings.

[0081] Example 7:

[0082] A method for intelligent investigation of industrial land information, the technical content of which is the same as any one of Examples 2-6, further comprising extracting the outline features of buildings in the current industrial land satellite remote sensing image through a convolutional neural network in step S1);

[0083] The convolutional neural network is trained through historical data sets.

[0084] Example 8:

[0085] A method for intelligent investigation of industrial land information, the technical content of which is the same as any one of Examples 2-7. Furthermore, illegal buildings refer to new buildings that exceed the approval scope, have no corresponding permits, or the permit information is inconsistent with the actual construction purpose or does not match the scale.

[0086] Example 9:

[0087] A method for intelligent investigation of industrial land information, with the same technical content as any one of Examples 2-8, further comprising: a land association code comprising: administrative division code + land type code + X coordinate of the center point of the land spatial range + Y coordinate of the center point of the land spatial range + area + serial number, and associated with the land parcel's GIS coordinates, planned use, area, and property rights information;

[0088] The coding rule for the approval association code is: administrative division code + approval type code + approval document number + approval time + serial number, and is associated with the permitted use, building area, permission opinion, validity period, and scanned copy of the approval document;

[0089] The coding rules for the tax department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with the enterprise's annual tax payment and value-added tax details;

[0090] The coding rules for the power company association code are: administrative division code + department name code + enterprise unified social credit code, and are associated with the company's monthly electricity consumption and peak and valley electricity consumption data;

[0091] The coding rules for the economic and information department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with business data such as enterprise output value and employment scale.

[0092] Example 10:

[0093] A method for intelligent investigation of industrial land information, the technical content of which is the same as any one of Examples 2-9. Furthermore, when creating a unique association code for industrial land information, the data source and modification history are recorded to ensure that the data is traceable and tamper-proof.

[0094] Example 11:

[0095] A method for intelligent investigation of industrial land information, comprising the following steps:

[0096] 1. Definition and core technical characteristics of smart survey methods

[0097] 1.1 Method definition and core functions

[0098] Smart survey is an industrial land management method based on "data-driven, intelligent perception, and decision-making support". Its core functions include:

[0099] Dynamic association of all factors: Create unique association codes for data such as land parcels, approvals, taxes, electricity usage, and energy consumption, and build a comprehensive industrial land information analysis model to dynamically integrate multi-dimensional data such as land parcels, approvals, taxes, electricity usage, and energy consumption.

[0100] Full-cycle dynamic monitoring: Through the integrated perception network of "air-space-ground-network", changes in land use status (such as construction progress and corporate production activities) can be monitored in real time.

[0101] Intelligent analysis and decision-making: Build models for illegal construction identification and land use efficiency evaluation, and automatically generate early warning signals and optimization suggestions.

[0102] 1.2 Core Technical Features

[0103] A. Multi-dimensional data association system

[0104] An associated code identification system is used to create land use codes, approval codes, and enterprise codes to bind land use, approval, and enterprise relationships, provide real-time access to tax, electricity consumption, output value and other data for land use, record data sources and modification history, and ensure data traceability and tamper-proofing.

[0105] B. Intelligent Perception Technology Matrix

[0106] Satellite remote sensing monitoring: 0.5-meter resolution images are acquired quarterly, and convolutional neural networks (CNNs) are used to automatically identify anomalies such as new construction and idle land.

[0107] Dynamic drone inspection: For suspected problem areas discovered by satellites, the optimal path is planned using the Voronoi diagram algorithm, and high-definition cameras and lidar are used for close-range evidence collection.

[0108] IoT terminal deployment: Smart electricity meters and license plate recognition cameras are installed in key areas to collect real-time data such as corporate electricity consumption and the frequency of logistics vehicles entering and exiting.

[0109] C. Dynamic Analysis Model Library

[0110] Identification model for illegal construction land: Compares satellite images with approval records. If any construction without approval is found, an early warning will be automatically triggered and a forensic report will be generated.

[0111] Land use efficiency assessment model: calculates indicators such as tax per unit area and energy consumption-to-output ratio, and classifies them according to thresholds (can be divided into high-efficiency land use and low-efficiency land use) to support differentiated management and control.

[0112] D. Closed-loop management mechanism

[0113] From data collection (satellite images), analysis (model calculation), early warning (system push) to disposal (manual verification), closed-loop management of the entire process is achieved.

[0114] 2. Technical implementation process and key steps

[0115] 2.1 Data unique identification code and association system construction

[0116] A. Generate a unique land identification code

[0117] Coding rules: administrative division code + land use type code + X coordinate of the center point of the land use space range + Y coordinate of the center point of the land use space range + area + serial number

[0118] Information binding: associate the land use code with the plot’s GIS coordinates, planned use, area, and property rights information to form a digital archive.

[0119] B. Generation of unique identification code for approval process

[0120] Coding rules: administrative division code + approval type code (such as "land use permit" and "project permit") + approval document number + approval time (year and month) + serial number.

[0121] Information binding: Bind the approval code with information such as permitted use, building area, permission opinion, validity period, and scanned copies of approval documents to form a digital file.

[0122] C. Enterprise data unique identification code

[0123] Tax department: administrative division code + department name code (such as: SW) + enterprise unified social credit code, annual tax payment and value-added tax details of related enterprises.

[0124] Power company: administrative division code + department name code (such as DL) + enterprise unified social credit code, and the monthly electricity consumption and peak and valley data of the associated enterprise.

[0125] Economic and information technology departments: administrative division code + department name code (such as: JX) + enterprise unified social credit code, related enterprise output value, employment scale and other operating data.

[0126] D. Data association system:

[0127] First, by recording land use codes during the land use approval process, a table of associations between land use codes and approval codes is constructed to support the real-time association of land use and approval data. Second, accurate spatial location data for enterprises is created and their unified social credit codes are recorded. Based on the spatial relationship between land use and enterprise locations, a table of associations between new town land use codes and enterprise codes is constructed to support the real-time association of land use and enterprise data.

[0128] 2.2 Intelligent Perception Network Deployment and Operation and Maintenance

[0129] 2.2.1 Satellite Remote Sensing Monitoring Implementation Plan

[0130] Procurement of 0.5-meter resolution imagery (such as the Gaofen series of satellites) covers the entire region quarterly. By comparing the current quarter's imagery with the previous quarter's, we identify areas of change. Combined with approval data, we determine whether the changes comply with approval requirements, supporting the discovery of illegal land use. A table linking approval codes and land use codes is then used to indicate when industrial land construction status needs to be updated.

[0131] 2.2.2 Standardized UAV Inspection Operations

[0132] First, the satellite detection of suspected illegal construction areas and the occurrence of zero electricity consumption (suspected idleness) for 30 consecutive days by enterprises will be used as trigger conditions for drone inspections. Second, regular inspections will be established for key areas, with inspection results serving as basic data to support updates on industrial land construction status and identify illegal construction sites. Drone inspection results will be automatically linked to land parcels using land use codes.

[0133] 2.2.3 IoT Terminal Deployment and Data Application

[0134] By selecting and deploying intelligent sensing devices, enterprises can be aware of changes in data. Equipment selection and installation:

[0135] Smart meter: monitors the company's real-time electricity consumption, with data uploaded every minute.

[0136] License plate recognition camera: records the frequency of logistics vehicles entering and exiting, and analyzes the production activity of enterprises.

[0137] Environmental sensors: Detect air quality around industrial sites (for environmental impact assessment compliance verification).

[0138] Data application scenarios:

[0139] Electricity consumption sudden drop warning: If a company's electricity consumption drops by more than 50% week-on-week, a "suspected shutdown" warning will be triggered.

[0140] Vehicle frequency analysis: The number of logistics vehicles entering and leaving the site decreased by 80% and lasted for two weeks, indicating "production shrinkage".

[0141] 2.3 Data Analysis Model Development and Optimization

[0142] 2.3.1 Illegal Construction Identification Model

[0143] By regularly acquiring high-resolution satellite imagery, image segmentation algorithms (such as deep learning models) are used to extract the outline features of newly built buildings and compare them with historical imagery to identify areas of surface change. Spatial overlay analysis is performed between the building locations detected in the imagery and the permitted scopes in the approval records. If a newly built building exceeds the approved scope, does not have a corresponding permit, or the permit information is inconsistent with the actual construction purpose, or the scale does not match, it will be marked as an "illegal building" and a drone will be dispatched to take close-up photos of the suspected area. Building details (such as floor height and area) will be verified using 3D modeling technology to ensure accurate identification.

[0144] 2.3.2 Land Use Efficiency Evaluation Model

[0145] Establish multi-dimensional evaluation indicators, including calculations of core economic indicators such as tax revenue per unit area (corporate tax amount / land area) and output value per unit of energy consumption (output value / electricity consumption), as well as statistics on employment density (number of employees / land area) and environmental compliance rate (percentage of environmental impact assessment compliance). Indicator weights will be assigned based on policy guidance and dynamically adjusted based on actual management results to achieve a scientific grading of industrial land efficiency and provide data support for resource optimization.

Claims

1. A method for intelligent investigation of industrial land information, characterized in that: The following steps are involved: 1) Using an association code identification system to create a unique association code for industrial land information; the industrial land information includes land parcel, approval, tax, power company, economic and information department, electricity consumption, energy consumption, and output value. 2) Periodically identify new buildings and idle land in industrial land. If new buildings exist, proceed to step 3); if idle land exists, proceed to step 4); The steps for identifying new buildings in industrial land are as follows: periodically acquiring satellite remote sensing images of industrial land, and identifying the satellite remote sensing images of industrial land to determine whether there are new buildings; The steps for identifying idle land in industrial land are as follows: using intelligent sensing equipment to collect construction information corresponding to each plot, and judging whether there is idle land based on the construction information. If so, the idle land is regarded as an abnormal area and the process proceeds to step 4); 3) Compare the newly built buildings in the satellite remote sensing image of the industrial land with the approval association code. If the newly built buildings are illegal buildings, the area where the newly built buildings are located is regarded as an abnormal area and proceed to step 4); 4) Use the Voronoi diagram algorithm to plan the optimal path of the drone, use the drone equipped with high-definition cameras and lidar to collect evidence in abnormal areas, and generate a forensic report associated with the plot based on the association code.

2. The method for intelligent investigation of industrial land information according to claim 1, characterized in that: During the periodic identification of new buildings and idle land in industrial land, the land efficiency indicators of each plot are also evaluated; Land use efficiency indicators include tax revenue per unit area, output value per unit energy consumption, employment density, and environmental compliance rate.

3. The method for intelligent investigation of industrial land information according to claim 1, characterized in that: Idle land refers to land where the enterprise's electricity consumption is zero for a continuous period of T1, the enterprise's electricity consumption decreases by more than 50% week-on-week, or the number of logistics vehicles entering and leaving the land decreases by 80% for a continuous period of T2.

4. The method for intelligent investigation of industrial land information according to claim 3, characterized in that: Construction information includes real-time electricity consumption of enterprises and the frequency of logistics vehicles entering and leaving; The company’s real-time electricity consumption is monitored through smart meters; The frequency of logistics vehicles entering and exiting is monitored by license plate recognition cameras.

5. The method for intelligent investigation of industrial land information according to claim 1, characterized in that: The steps for identifying industrial land satellite remote sensing images include: S1) extracting the outline features of buildings from the current industrial land satellite remote sensing image; S2) comparing the outline features of buildings in current satellite remote sensing images of industrial land with the outline features of buildings in historical images to identify newly built buildings.

6. The method for intelligent investigation of industrial land information according to claim 5, characterized in that: In step S1), the outline features of the building in the current industrial land satellite remote sensing image are extracted through a convolutional neural network; The convolutional neural network is trained through historical data sets.

7. The method for intelligent investigation of industrial land information according to claim 1, characterized in that: Illegal buildings refer to new buildings that exceed the approved scope, have no corresponding permits, or the permit information is inconsistent with the actual construction purpose or does not match the scale.

8. The method for intelligent investigation of industrial land information according to claim 1, characterized in that: The coding rule of the land association code is: administrative division code + land type code + X coordinate of the center point of the land spatial range + Y coordinate of the center point of the land spatial range + area + serial number, and it is associated with the GIS coordinates, planned use, area, and property rights information of the land parcel; The coding rule for the approval association code is: administrative division code + approval type code + approval document number + approval time + serial number, and is associated with the permitted use, building area, permission opinion, validity period, and scanned copy of the approval document; The coding rules for the tax department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with the enterprise's annual tax payment and value-added tax details; The coding rules for the power company association code are: administrative division code + department name code + enterprise unified social credit code, and are associated with the company's monthly electricity consumption and peak and valley electricity consumption data; The coding rules for the economic and information department association code are: administrative division code + department name code + enterprise unified social credit code, and it is associated with business data; business data includes enterprise output value and employment scale.

9. The method for intelligent investigation of industrial land information according to claim 1, characterized in that: When creating a unique association code for industrial land information, record the data source and modification history to ensure data traceability and tamper-proofing.

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