Land survey data updating method and system, product and medium

Abstract

The invention discloses a land investigation data updating method, a land investigation data updating system, a product and a medium, and relates to the field of land investigation. Superposing vector boundary data of the preset survey range on the basic geographic information layer and importing historical land information in the preset survey range to obtain a comprehensive basic information layer; acquiring actual land types, actually measured areas and ownership condition information of various lands in a preset survey range; and comparing the actual land type, the actually measured area and the ownership condition information with the comprehensive basic information layer, identifying land utilization change data, generating a land survey data updating instruction according to the land utilization change data, and sending the land survey data updating instruction and the comprehensive basic information layer to a target client. By implementing the method, the land survey data updating efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of land survey, and in particular to a land survey data updating method, system, product and medium. Background Art

[0002] With the acceleration of urbanization and the continuous changes in land use patterns, it is becoming increasingly important to accurately and timely grasp the status of land and resources utilization. As a basic work, land surveys provide important data support for land space planning, natural resource management, and ecological environmental protection.

[0003] In related technologies, investigators need to carry paper maps and survey forms to conduct field surveys on each plot of land, recording the actual use, area and ownership information of the land. After the survey is completed, this information needs to be manually entered into the computer system and compared with historical data to identify changes in land use. However, this method is time-consuming and labor-intensive, and data updating is inefficient. Summary of the invention

[0004] The present application provides a land survey data updating method and device for improving the updating efficiency of land survey data.

[0005] In the first aspect, the present application provides a land survey data updating method, which is applied to a land survey data management system, the method comprising: importing an orthophoto map of a preset survey range as a basic geographic information layer, superimposing the vector boundary data of the preset survey range on the basic geographic information layer and importing the historical land information within the preset survey range to obtain a comprehensive basic information layer; obtaining the actual land type, measured area and ownership status information of various types of land within the preset survey range; comparing the actual land type, the measured area and the ownership status information with the comprehensive basic information layer to identify land use change data, which includes land type change data, area change data and ownership status change; generating a land survey data update instruction based on the land use change data, and sending the land survey data update instruction and the comprehensive basic information layer to the target client.

[0006] By adopting the above technical solution, we first import the orthophoto map of the preset survey range as the basic geographic information layer, then superimpose vector boundary data and historical land information to obtain a comprehensive basic information layer, integrate multi-source data, and then obtain the actual land type, measured area and ownership status information and compare it with the comprehensive basic information layer. This can comprehensively and accurately identify land use change data, generate update instructions based on the change data and send them to the target client, realizing the automated update process of land survey data and improving update efficiency.

[0007] In combination with some embodiments of the first aspect, in some embodiments, the orthophoto map of the preset survey range is imported as the basic geographic information layer, the vector boundary data of the preset survey range is superimposed on the basic geographic information layer, and the historical land information within the preset survey range is imported to obtain the steps of a comprehensive basic information layer, specifically including: obtaining the orthophoto map of the preset survey range, identifying the orthophoto map based on the spectral feature library of land objects, and obtaining a preliminary land class distribution map; generating vector boundary data according to the administrative division data and terrain features of the preset survey range, and superimposing the vector boundary data on the preliminary land class distribution map to form a boundary superimposed land class map; extracting the historical land use data within the preset survey range from the land survey database, matching the spatial information in the historical land use data with the geographic entities in the boundary superimposed land class map, and forming a comprehensive basic information layer.

[0008] By adopting the above technical solution, land types are identified based on the spectral feature library of land objects, boundary data is generated by combining administrative divisions and terrain, and historical data is integrated to form a comprehensive basic information layer, which provides a more precise basis for the subsequent accurate comparison of change data and improves the reliability and accuracy of updates.

[0009] In combination with some embodiments of the first aspect, in some embodiments, the actual land type, the measured area and the ownership status information are compared with the comprehensive basic information layer to identify land use change data, and the land use change data includes the steps of: spatially superimposing and analyzing the actual land type, the measured area and the ownership status information with the historical data in the comprehensive basic information layer, identifying the patches of land type changes based on the change detection algorithm, and generating land type change data; calculating the area difference between the measured area and the historical area, and when the area difference exceeds a preset area threshold, marking it as area change data; comparing the actual ownership status with the historical ownership information, and when the actual ownership status is inconsistent with the historical ownership information, marking it as an ownership status change.

[0010] By adopting the above technical solutions, spatial overlay analysis is carried out, change detection algorithms are used to identify land type changes, area differences are calculated and ownership status is compared, land use changes are comprehensively and accurately identified, and a reliable basis is provided for data updates.

[0011] In combination with some embodiments of the first aspect, in some embodiments, after the step of generating a land survey data update instruction based on the land use change data and sending the land survey data update instruction to the target client, the method also includes: receiving the land survey data update result sent by the target client, the land survey data update result including the first land map information of a successful update and the second land map information of a failed update; analyzing the second land map information to obtain the reason for the update failure, the reason for the update failure includes data conflict, ownership dispute and change in actual situation; matching corresponding processing suggestions in a preset database based on the reason for the update failure, the processing suggestions including data verification, ownership confirmation and actual review.

[0012] By adopting the above technical solution, after receiving the update results, the failed image information is analyzed, the reasons are identified, and matching processing suggestions are made, which specifically solves the update failure problem, improves the success rate, ensures data accuracy and completeness, optimizes the update process, and reduces duplication of work and waste of resources.

[0013] In combination with some embodiments of the first aspect, in some embodiments, the corresponding processing suggestion is matched in a preset database based on the cause of the update failure, and the processing suggestion includes the steps of data verification, ownership confirmation and on-site review. The method also includes: obtaining change trend data of the second land map information, and the change trend data includes area change trend, shape change trend and attribute change trend; obtaining change trend data of adjacent spots of the second land map, and calculating the change similarity between the second land map information and the adjacent spots; if the change similarity is higher than a preset threshold, generating a warning message and sending it to the target client.

[0014] By adopting the above technical solution, after matching and processing suggestions, the change trend data is obtained and the similarity is calculated, and early warning information is sent to detect anomalies in advance and provide early warnings, so as to facilitate early measures to ensure data accuracy and effective land management.

[0015] In combination with some embodiments of the first aspect, in some embodiments, after the step of generating a land survey data update instruction based on the land use change data and sending the land survey data update instruction to the target client, the method also includes: upon receiving the land survey data update instruction sent by the target client, obtaining an update task list fed back by the target client, the update task list including spatial data correction tasks, metadata supplement tasks, attribute data update tasks and auxiliary data update tasks; formulating a database update plan based on the update task list; and updating the land survey database according to the database update plan.

[0016] By adopting the above technical solution, after receiving the instruction, the task list is obtained, the plan is formulated and the database is updated, which can ensure that the data is correctly processed and updated, improve quality and efficiency, and maintain the stability and reliability of the system.

[0017] In combination with some embodiments of the first aspect, in some embodiments, after the step of updating the land survey database according to the database update plan, the method also includes: receiving a data query request sent by the target client, the data query request including query conditions and query objects; querying the land survey database according to the query conditions to obtain a comprehensive query result, and sending the comprehensive query result to the target client; saving the query conditions, the query object and the comprehensive query result as a query template.

[0018] By adopting the above technical solution, query requests are received after the database is updated, and the results are efficiently queried and sent after analysis and verification, and saved as a template. This improves query efficiency and data utilization, provides convenient specifications for query work, and ensures efficient operation of the system.

[0019] In a second aspect, an embodiment of the present application provides a land survey data update system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the land survey data update system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0020] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the above-mentioned computer program product runs on a land survey data update system, the above-mentioned land survey data update system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on a land survey data update system, the land survey data update system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] It can be understood that the land survey data update system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, and will not be repeated here.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. This application first imports the orthophoto map of the preset survey range as the basic geographic information layer, then superimposes the vector boundary data and historical land information to obtain the comprehensive basic information layer, integrates multi-source data, and then obtains the actual land type, measured area and ownership status information and compares it with the comprehensive basic information layer. It can comprehensively and accurately identify land use change data, generate update instructions based on the change data and send them to the target client, realizing the automated update process of land survey data and improving update efficiency.

[0024] 2. This application identifies land types based on the spectral feature library of land objects, generates boundary data based on administrative divisions and terrain, and integrates historical data to form a comprehensive basic information layer, providing a more accurate basis for subsequent accurate comparison of change data and improving update reliability and accuracy.

[0025] 3. This application conducts spatial overlay analysis, uses change detection algorithms to identify land type changes, calculates area differences and compares ownership status, comprehensively and accurately identifies land use changes, and provides a reliable basis for data updates. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of a method for updating land survey data in an embodiment of the present application; Figure 2 This is another flowchart of the land survey data updating method in the embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of the land survey data update system in the embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] For ease of understanding, the following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of the land survey data updating method in the embodiment of the present application.

[0030] S101. Import an orthophoto map of a preset survey range as a basic geographic information layer, superimpose vector boundary data of the preset survey range on the basic geographic information layer, and import historical land information within the preset survey range to obtain a comprehensive basic information layer.

[0031] Among them, the preset survey scope refers to a specific geographical area that is predetermined to be surveyed. Orthophotos refer to vertical aerial or satellite remote sensing images that have been geometrically corrected and have a uniform scale and geographic coordinates. Basic geographic information layers are used to represent data layers containing basic geographic elements. Vector boundary data refers to spatial data that uses lines to represent administrative divisions or natural geographic boundaries. Historical land information refers to land use status data for a certain period in the past. Comprehensive basic information layers refer to composite data layers that integrate multiple geographic information.

[0032] This step is usually performed at the initial stage of the land survey data update process, with the aim of establishing a comprehensive basic data layer to provide a reference for subsequent data analysis and updates. Specifically, the system first retrieves and imports the latest orthophotos covering the preset survey range from the remote sensing database. These images are usually high-resolution (such as 0.5 meters or 1 meter) and can clearly display surface features. Then, the system extracts the vector boundary data of the area from the administrative division database, including multi-level administrative boundaries such as provincial boundaries, municipal boundaries, and county boundaries. The system overlays these boundary data on the orthophoto map to form a basic layer with clear geographic boundaries. Next, the system extracts the past land use data of the area from the historical land survey database, including information such as land type, area, and ownership. The system spatially matches and fuses these historical data with the basic layer to generate a comprehensive basic information layer containing multiple temporal phases and multiple elements.

[0033] In some embodiments, the creation process of this comprehensive basic information layer can be implemented in a variety of ways: Optionally, the system first uses remote sensing image processing software to pre-process the orthophoto map, including atmospheric correction, geometric correction, and image enhancement. Then, the system uses the layer overlay function of the GIS software to overlay the vector boundary data on the processed orthophoto map with a transparency of 50%. Next, the system extracts land use data from the historical database and uses spatial analysis tools to align these data with the image. Finally, the system merges all layers and optimizes colors and symbols to enhance visualization. Optionally, the system uses a cloud computing platform to first upload the orthophoto map to cloud storage. Then, the system calls the vector data processing service to convert the administrative boundary data to the same coordinate system as the image. Next, the system uses a distributed computing framework to process historical land information in parallel and convert it into a raster format. Finally, the system uses the layer synthesis service on the cloud to merge all processed data layers into a comprehensive layer and store the results in the cloud database. It is understandable that other methods can also be used to create a comprehensive basic information layer, such as using deep learning algorithms to automatically extract image features and merge them with vector data, or using blockchain technology to ensure the traceability and integrity of historical data, which is not limited here.

[0034] S102. Obtain the actual land type, measured area and ownership status information of various types of land within the preset survey scope.

[0035] The preset survey scope refers to a specific geographical area that is predetermined to be surveyed. The actual land type is used to indicate the current use type of land, such as cultivated land, forest land, construction land, etc. The measured area refers to the land area data obtained through field measurement or high-precision remote sensing interpretation. The ownership status information is used to indicate the property information such as ownership and use rights of the land, including details such as the owner and the term of use.

[0036] This step is usually performed after the basic data preparation is completed. The purpose is to obtain the latest land use status information to provide a basis for subsequent change analysis. Specifically, the system first determines the specific area to be investigated based on the preset survey scope. Then, the system uses a variety of data collection methods to obtain the actual conditions of various types of land in the area. For actual land types, the system uses high-resolution remote sensing images for automatic classification. For the measured area, the system combines GPS field measurement data and remote sensing image interpretation results. For ownership status information, the system extracts the latest land registration information by connecting to the database of the land management department. Through the integration of these multi-source data, the system generates a comprehensive attribute data set containing actual land types, measured areas and ownership status.

[0037] In some embodiments, this data acquisition process can be achieved in a variety of ways: Optionally, the system deploys a field survey team, uses GNSS equipment to measure the area, record land types, verify ownership information, and upload data in real time through a mobile application. The system performs a quality check on the uploaded data and finally integrates it into a unified dataset. Optionally, the system acquires high-resolution remote sensing images, uses deep learning algorithms for automatic classification, calculates the area, and obtains ownership data through an API interface, and finally spatially associates these data to form a comprehensive dataset. It is understandable that other methods can also be used to acquire land information, such as using Internet of Things technology to monitor land use changes in real time, or using crowdsourcing platforms to collect land use information provided by the public, which is not limited here.

[0038] S103, comparing the actual land type, the measured area and the ownership status information with the comprehensive basic information layer to identify land use change data, which includes land type change data, area change data and ownership status change data.

[0039] Among them, actual land classification refers to the actual use type of land at present, such as cultivated land, forest land, construction land, etc. Measured area refers to land area data obtained through field measurement or high-precision remote sensing interpretation. Ownership status information is used to indicate property information such as land ownership and use rights. Comprehensive basic information layer refers to a composite data layer containing historical land use data and other basic geographic information. Land use change data is used to indicate changes in land use over a certain period of time. Land classification change data refers to changes in land use, such as from agricultural land to construction land. Area change data indicates the increase or decrease in land area. Changes in ownership status refer to changes in land ownership or use rights.

[0040] This step is usually performed after obtaining the latest land survey data, with the purpose of identifying changes in land use by comparing the new and old data. Specifically, the system first spatially corresponds and attribute-matches the latest land survey data (including actual land type, measured area, and ownership status information) obtained with the generated comprehensive basic information layer. The system uses spatial analysis algorithms, such as overlay analysis, to accurately align the new and old data in space. Then, the system compares the attribute information of each plot one by one. For land type changes, the system compares the new and old land type codes, and if they are inconsistent, they are marked as land type changes. For area changes, the system calculates the difference between the new and old areas, and if it exceeds a preset threshold (such as 1% or 5 square meters), it is recorded as an area change. For changes in ownership status, the system compares the new and old owners, users, and other information, and any inconsistencies are marked as ownership changes. The system integrates all identified change information into a structured land use change dataset, including detailed information such as the type of change, the value before and after the change, and the amount of change.

[0041] In some embodiments, the identification process of land use change data can be implemented in a variety of ways: Optionally, the system first imports the new and old data into the geographic information system software to create two layers. Then, the system uses the spatial connection tool to associate the new and old data based on the geographic location. Next, the system uses the field calculator to create a new field, compares the new and old attribute values ​​through conditional statements, and marks the changes. Finally, the system uses the selection tool to extract all records with changes and export them as independent change data sets. Optionally, the system uses a distributed computing framework to split the new and old data into small blocks and distribute them to multiple computing nodes. Then, each node independently executes the comparison algorithm to identify the changes in the local data block. Then, the system collects the results of all nodes and merges and deduplicates them on the master node. Finally, the system performs a unified quality check and formatting process on the merged results to generate the final land use change data set. It can be understood that other methods can also be used to implement the identification of land use change data, which is not limited here.

[0042] S104: Generate a land survey data update instruction according to the land use change data, and send the land survey data update instruction and the comprehensive basic information layer to the target client.

[0043] Among them, land use change data refers to a collection of information reflecting changes in land use conditions, including changes in land type, area and ownership. Land survey data update instructions refer to a series of commands used to guide the client to perform data update operations. Comprehensive basic information layer refers to a composite data layer containing multiple geographic information, which is used as a reference for update operations. The target client refers to the terminal device or software system that receives the update instruction and performs the actual data update.

[0044] This step is usually performed after the land use change identification is completed. The purpose is to convert the change information into executable update instructions and send these instructions and necessary reference data to the client responsible for the actual update operation. Specifically, the system first analyzes and organizes the identified land use change data. The system converts the change data into a series of structured update instructions, each of which contains information such as the update object (such as plot identification), update type (such as land type change, area correction or ownership change), original value, update value, etc. The system also assigns a priority to each update instruction to ensure that important updates can be executed first. At the same time, the system compresses and encodes the generated comprehensive basic information layer for easy transmission. Finally, the system packages the generated update instructions and the encoded comprehensive basic information layer and sends them to the predetermined target client through a secure network protocol.

[0045] In some embodiments, the generation and sending process of the update instruction can be implemented in a variety of ways: Optionally, the system first imports the land use change data into a special instruction generation module. Then, the module uses a predefined template to convert each change record into a database update statement in a standard format. Then, the system packages these update statements into a batch script and adds transaction processing and error handling mechanisms to the script. Finally, the system uploads the batch script and the compressed comprehensive basic information layer to the server specified by the target client through an encrypted file transfer protocol. Optionally, the system uses a service architecture to first send the change data to the instruction generation service. Then, the service converts the change data into a series of application program interface calls, each call corresponding to a specific update operation. Then, the system encapsulates these application program interface calls into an instruction set in a standard format. Finally, the system pushes the instruction set and the basic layer data to the target client through a message queue. It can be understood that other methods can also be used to achieve the generation and sending of update instructions, which are not limited here.

[0046] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the land survey data updating method in the embodiment of the present application.

[0047] S201, obtaining an orthophoto map of a preset survey range, identifying the orthophoto map based on a ground feature spectral feature library, and obtaining a preliminary land type distribution map.

[0048] The preset survey scope refers to a specific geographical area that is predetermined to be surveyed, which can be an administrative unit such as a county or a natural geographical unit such as a watershed. An orthophoto is a vertical downward surface image obtained from aerial photography or satellite remote sensing, which has been geometrically corrected and has a uniform scale and geographic coordinates. The spectral feature library of land objects is a data set containing the reflectance spectral features of various land objects (such as water bodies, vegetation, buildings, etc.) in different bands. The preliminary land type distribution map is a preliminary spatial distribution map of land use types obtained by automatic image classification.

[0049] In specific implementation, the system first obtains a high-resolution orthophoto map covering the preset survey range, usually using aerial or satellite remote sensing images with a resolution of 0.5-2 meters. Then, the system calls the pre-established spectral feature library of land objects and uses supervised classification or deep learning methods to perform pixel-level land classification on the orthophoto. During the recognition process, the system matches the spectral features of each pixel with the standard spectrum in the feature library to determine its most likely land class attributes. Finally, a raster layer containing the spatial distribution of major land classes (such as cultivated land, forest land, grassland, construction land, water area, etc.) is generated, which is a preliminary land class distribution map.

[0050] S202, generating vector boundary data according to the administrative division data and terrain features of the preset survey range, and superimposing the vector boundary data on the preliminary land class distribution map to form a boundary superimposed land class map.

[0051] Administrative division data refers to the boundary information of administrative units at all levels (such as provinces, cities, counties, townships, etc.) in the study area. Topographic features refer to the undulating characteristics of the surface, including elevation, slope, and aspect. Vector boundary data is a spatial data form that uses lines to represent the boundaries of geographic elements and has precise coordinate information. The boundary overlay land class map is a comprehensive layer formed by superimposing vector data such as administrative boundaries on the land class distribution map.

[0052] In the specific implementation process, the system first calls the latest administrative division data within the preset survey scope, which usually includes multi-level administrative boundaries such as provincial boundaries, municipal boundaries, county boundaries, and township boundaries. At the same time, the system will also use the digital elevation model (DEM) to extract the main terrain feature lines of the study area, such as ridge lines, rivers and other natural boundaries. The system vectorizes these administrative boundaries and natural boundary data to generate a high-precision vector boundary data set. Subsequently, the system superimposes these vector boundary data on the preliminary land class distribution map generated in step S201. The overlay process uses the layer overlay operation in GIS spatial analysis to ensure that the boundary line and the land class distribution map correspond accurately in spatial position. The final boundary overlay land class map contains both land use type information and administrative division and natural geographical boundary information, providing an important spatial reference framework for subsequent land surveys and data updates.

[0053] S203, extracting historical land use data within a preset survey range from a land survey database, matching the spatial information in the historical land use data with the geographic entities in the boundary overlay land class map, and forming a comprehensive basic information layer.

[0054] The land survey database is a database that stores historical land survey results, including land use status data for multiple periods. Historical land use data refers to information such as land use type, area, and ownership recorded in previous land surveys. Spatial information refers to geometric features such as the location, shape, and size of geographic elements. Geographic entities refer to objective entities with spatial locations in the real world, such as plots of land and buildings. The comprehensive basic information layer is a comprehensive spatial data layer that integrates multi-source information such as images, land types, boundaries, and historical data.

[0055] The system first connects to the land survey database, and extracts the most recent land use survey data in the area according to the spatial scope of the preset survey scope. These data usually include a plot layer in vector format and an attribute data table associated with it. Subsequently, the system spatially matches the extracted historical land use data with the boundary overlay land class map generated in step S202. The matching process uses spatial relationship analysis methods, such as topological overlap analysis, to position and associate attributes of each plot in the historical data with the geographic entities (such as image classification units and administrative units) in the boundary overlay land class map. During this process, the system also performs a spatial consistency check to deal with existing boundary inconsistencies, attribute conflicts and other problems. Finally, the system generates a comprehensive basic information layer that integrates remote sensing image information, preliminary classification results, administrative boundaries, terrain features and historical survey data.

[0056] S204. Obtain the actual land type, measured area and ownership status information of various types of land within the preset survey scope.

[0057] Actual land classification refers to the actual use type of land at present, such as cultivated land, forest land, grassland, construction land, etc. The measured area is the land area data obtained through field measurement or high-precision remote sensing interpretation. Ownership status information includes property information such as ownership and use rights of land, as well as details such as land users and term of use. The preset survey scope refers to a specific geographical area that is predetermined to be subject to land survey, which can be an administrative unit such as a county or a natural geographical unit such as a watershed.

[0058] The system uses a variety of methods to obtain actual information about the land within the preset survey scope. First, the system uses high-resolution satellite images or drone aerial images, combined with advanced remote sensing interpretation technology, such as deep learning classification algorithms, to preliminarily classify the land within the survey scope and obtain actual land type information. Secondly, the system integrates field measurement data from high-precision GNSS equipment, or uses oblique photogrammetry technology to obtain accurate measured area data. For ownership status information, the system connects with the database of the land management department to extract the latest land registration book and real estate certificate information. At the same time, the system also integrates field survey data uploaded by grassroots investigators through mobile terminals, including land type verification results, area correction data, and ownership change information.

[0059] S205, spatially overlay and analyze the actual land type, measured area and ownership status information with the historical data in the comprehensive basic information layer, identify the patches where land type has changed based on a change detection algorithm, and generate land type change data.

[0060] Spatial overlay analysis refers to the process of matching the positions and comparing the attributes of two or more spatial data layers in the same coordinate system. Change detection algorithms are computational methods used to identify changes in geographic features between two periods, including various algorithms at the pixel level, object level, and feature level. A patch refers to a continuous unit of land with the same attributes. Land class change data is a data set that records the spatial location, change type, and area of ​​changes in land use types. The comprehensive basic information layer is a comprehensive spatial data layer that integrates multi-source information such as images, land classes, boundaries, and historical data.

[0061] The system first converts the actual land type, measured area and ownership status information obtained in step S204 into a vector layer format. Then, the system spatially overlays this new vector layer with the comprehensive basic information layer generated in step S203. The overlay process uses the layer overlay function in the GIS software to ensure that the two layers correspond accurately in spatial position. Next, the system starts the change detection algorithm. Commonly used algorithms include post-classification comparison method, direct classification method and feature difference analysis method. Taking the post-classification comparison method as an example, the system compares the new and old land type attributes of each spatial unit after overlay. When the attributes are inconsistent, it is marked as a changed area. For object-level change detection, the system also considers changes in the shape, size, texture and other features of the map. In addition, the system also combines time series analysis to identify gradual land use changes. Finally, the system extracts all detected change areas to form a new land type change data layer, which contains attribute information such as the spatial range of the change map, the original land type, the current land type, and the changed area.

[0062] S206: Calculate the area difference between the measured area and the historical area. When the area difference exceeds a preset area threshold, mark it as area change data.

[0063] The measured area is the current land area data obtained through field measurement or high-precision remote sensing interpretation. The historical area refers to the land area data recorded in the last land survey. The area difference refers to the numerical difference between the measured area and the historical area. The preset area threshold is the maximum range of allowable area changes preset by the system, which is usually determined based on measurement accuracy and actual management needs. Area change data is the information of plots where the land area has changed significantly, including the location of the plot, the original area, the new area, the amount of change, etc.

[0064] The system first extracts the historical area data from the measured area data obtained in step S204 and the comprehensive basic information layer in step S203. Then, the system calculates and compares the area of ​​each plot unit, subtracts the historical area from the measured area, and obtains the area difference. The system takes measurement errors into account and usually uses relative errors rather than absolute errors for judgment. For example, for small plots, a relative change threshold of 5% is set; for large plots, a relative change threshold of 2% is set. The system compares the calculated area difference with the preset area threshold. When the absolute value of the area difference is greater than the preset area threshold, the system marks the plot as area change data. The marking process includes adding an area change flag field in the attribute table and recording the amount of change and the rate of change. At the same time, the system will also generate a new area change data layer, which contains all plots that exceed the threshold, and comes with attribute information such as the original area, new area, amount of change, and rate of change.

[0065] S207. Compare the actual ownership status with the historical ownership information. When the actual ownership status is inconsistent with the historical ownership information, mark it as a change in ownership status.

[0066] The actual ownership status refers to the current ownership and use rights of the land, as well as the land users, use period and other details. The historical ownership information refers to the land ownership data recorded in the last land survey. The change of ownership status refers to the record of changes in land ownership and use rights, including the type of change, time of change, reason for change and other information.

[0067] The system first extracts historical ownership information from the actual ownership status data obtained in step S204 and the comprehensive basic information layer in step S203. The system uses database comparison technology to compare the ownership information of each plot one by one. The comparison content includes but is not limited to: owner, user, ownership nature (such as state-owned, collectively owned), use period, use restrictions, etc. The system uses a string matching algorithm to compare these fields. When any field is found to be inconsistent, it is determined that the ownership status has changed. For the changed records, the system adds a "ownership change" flag field to the attribute table and sets it to "yes". At the same time, the system also records the specific changes, such as "ownership change" and "use period extension". In addition, the system will generate a list of ownership changes, including all the changed plot numbers, change types, original ownership information, new ownership information, etc. The marking and recording of changes in ownership status provide an important basis for subsequent land management and policy formulation, which helps to timely discover and deal with land ownership disputes and protect land rights and interests.

[0068] S208: Generate a land survey data update instruction according to the land use change data, and send the land survey data update instruction and the comprehensive basic information layer to the target client.

[0069] Land use change data refers to a comprehensive data set that records changes in land use type, area, ownership, etc. Land survey data update instructions are a series of operation instructions generated by the system to guide the target client to update data. The target client refers to the terminal device or software system that receives the update instruction and performs the actual data update operation.

[0070] The system first integrates the land type change data, area change data and ownership status change data generated in steps S205, S206 and S207 to form a complete land use change data set. Based on this change data set, the system generates a series of structured land survey data update instructions. These instructions usually include fields such as update object (plot ID), update type (land type change / area correction / ownership change), original value, update value, and update reason. For example, a typical update instruction is: "Update plot ID: 10001, update type: land type change, original value: cultivated land, update value: construction land, update reason: urban expansion". The system packages these update instructions into a standard format (such as JSON or XML) for the target client to parse and execute. At the same time, the system also compresses and encodes the comprehensive basic information layer generated in step S203 as a reference base map for the update. Finally, the system sends the update instruction package and the comprehensive basic information layer to the specified target client through a preset network protocol (such as HTTP or a dedicated data transmission protocol).

[0071] S209: Receive the land survey data update result sent by the target client, where the land survey data update result includes first land spot information of successfully updated and second land spot information of failed updated.

[0072] The land survey data update result refers to the operation result fed back by the target client after executing the update command. The first land map information that is successfully updated refers to the land plot information set that has successfully completed the data update. The second land map information that fails to update refers to the land plot information set that has not been successfully updated due to various reasons. Land map refers to a continuous land unit with the same attributes, which is the basic spatial unit for land survey and management.

[0073] The system first establishes a data receiving channel with the target client, usually using technologies such as WebSocket or long-connection HTTP to ensure real-time reception of update results. When the target client completes the data update operation, it generates an update result report in a standard format and sends it back to the system through a preset network protocol. After receiving this report, the system will parse and classify it. For the first land map information that has been successfully updated, the system records it in the update log and marks these plots as "updated" in the main database. This information usually includes plot ID, update type, update time, etc. For the second land map information that failed to update, the system will extract it separately to form a pending list. This list contains detailed information for each plot that failed to update, such as plot ID, failure reason, original data, target update value, etc. The system will also preliminarily classify the reasons for the update failure, such as "data conflict", "insufficient authority", "network error", etc., to provide a basis for subsequent problem investigation and processing.

[0074] S210. Analyze the second land map information to obtain reasons for update failure, which include data conflict, ownership dispute and changes in actual conditions.

[0075] Update failure reasons refer to the specific reasons that caused the land survey data update operation to fail to execute successfully. Data conflicts refer to situations where there are inconsistencies or contradictions between old and new data, such as the same plot of land having different attributes in different data sources. Ownership disputes refer to situations where there are disputes or ambiguities about the ownership or use rights of land. Changes in field conditions refer to situations where the actual land conditions do not match the recorded data, due to natural changes or human changes.

[0076] The system first systematically analyzes the second land map information received in step S209. The system uses data mining and pattern recognition technology to conduct in-depth analysis of each plot that failed to update. For data conflicts, the system compares information from multiple data sources (such as remote sensing images, field survey data, historical records, etc.) and uses data consistency check algorithms to identify conflict points. For example, the system finds that a plot is displayed as construction land in remote sensing images, but is still marked as cultivated land in historical records. For ownership disputes, the system analyzes land registration books, property certificates, and actual usage, and identifies existing ownership issues through keyword extraction and semantic analysis technology. For example, the system detects that there are multiple entities claiming ownership of a plot. For changes in the actual situation, the system compares the latest remote sensing images or field survey data with historical records, and uses change detection algorithms to identify significant surface changes. For example, the system finds that an area originally recorded as a lake has become land in the latest image. Through these analyses, the system generates a detailed failure reason report for each plot that failed to update, including the failure type, specific description, and related evidence data.

[0077] S211. Match corresponding processing suggestions in a preset database based on the cause of the update failure. The processing suggestions include data verification, ownership confirmation and on-site review.

[0078] The preset database is a knowledge base containing solutions to various land survey problems. The treatment suggestions are solutions or next steps for specific update failure reasons. Data verification refers to the process of re-examining and verifying questionable data. Ownership confirmation is the process of clarifying the land ownership status through legal procedures or administrative means. Field review refers to the act of sending investigators to the site to re-investigate the land situation.

[0079] The system first takes the update failure reasons analyzed in step S210 as input. The system uses natural language processing (NLP) technology to perform semantic analysis and extract key information on these failure reasons. Then, the system accesses the pre-established processing suggestion knowledge base. This knowledge base is a structured database that contains various possible failure reasons and their corresponding processing suggestions. The system uses a fuzzy matching algorithm to match the extracted failure reason keywords with the entries in the knowledge base. For failures of data conflict type, the "data verification" suggestion is matched, which specifically includes cross-verification of multiple data sources and re-data collection. For failures of ownership dispute type, the "ownership confirmation" suggestion is matched, including specific operations such as consulting historical archives, convening ownership coordination meetings, and initiating legal procedures. For failures of field situation changes type, the "field review" suggestion is matched, including specific measures such as arranging a field investigation team and using drones for aerial photography. The system associates these matched processing suggestions with the corresponding failed plot information and generates a structured processing suggestion report. This report not only contains the type of suggestion, but also includes detailed information such as specific operation steps, required resources, and expected completion time.

[0080] S212. Obtain change trend data of the second land patch information, where the change trend data includes area change trend, shape change trend and attribute change trend.

[0081] Change trend data is statistical information describing the direction and degree of change of land patches over a certain period of time. Area change trend refers to the overall trend of increase or decrease in the area of ​​land patches. Shape change trend refers to the change trend of the complexity or regularity of the shape of land patch boundaries. Attribute change trend refers to the change trend of non-spatial attributes such as the use and ownership of land patches. Second, land patch information refers to the detailed information of land units that failed to update, including plot ID, location, original attributes, etc.

[0082] The system first extracts multi-period historical data related to the second land map identified in step S210 from the historical database. The system usually selects data from the past 5-10 years to ensure the effectiveness of trend analysis. For the area change trend, the system uses a time series analysis algorithm to calculate the area value at each time point and fit a trend line to determine whether the area is increasing, stable or decreasing. For example, it is found that the area of ​​an agricultural map has shown a decreasing trend year by year in the past five years. For the shape change trend, the system uses a landscape index analysis method to calculate the shape complexity index (such as fractal dimension) at each time point and analyze its change trend. For example, it is found that the shape of a city construction map tends to be regularized. For the attribute change trend, the system uses attribute change frequency analysis and Markov chain prediction models to analyze the historical change patterns and future change probabilities of attributes such as land use and ownership. For example, it is predicted that an industrial map has a high probability of being converted into commercial land. The system integrates these analysis results into a comprehensive change trend report, including quantitative trend indicators and visual trend charts.

[0083] S213, obtaining change trend data of adjacent spots of the second land spot, and calculating the change similarity between the second land spot information and the adjacent spots.

[0084] Adjacent plots refer to other land units that are directly adjacent to the target land plot in space. Change trend data is statistical information that describes the direction and degree of change of land plots over a certain period of time, including the trend of changes in area, shape and attributes. Change similarity is a measure of the similarity of the change patterns of two or more land plots, usually expressed as a value between 0 and 1, where 1 means complete similarity and 0 means complete dissimilarity. Secondary land plot information refers to detailed information on land units that failed to update, including plot ID, location, original attributes, etc.

[0085] The system first uses a spatial analysis algorithm to identify all patches directly adjacent to the second land patch. This is usually achieved through the topological analysis function of the GIS software. The system checks whether the boundary of each patch shares a boundary line with the target patch. Then, the system performs the same change trend analysis as step S212 on these adjacent patches to obtain their area change trend, shape change trend, and attribute change trend data. Next, the system uses a multidimensional similarity calculation method to compare the change trend of the second land patch with each adjacent patch. For the area change trend, the Pearson correlation coefficient is used to measure the similarity of the change curve. For the shape change trend, the Euclidean distance is used to calculate the similarity of the shape complexity index change. For the attribute change trend, the cosine similarity is used to compare the similarity of the attribute change vector. Finally, the system performs a weighted average of the similarities of these different dimensions to obtain a comprehensive change similarity index. For example, if an industrial land patch and its adjacent patches all show a trend of decreasing area, regularizing shape, and transforming attributes to commercial land, then the change similarity between them is very high.

[0086] S214: If the change similarity is higher than a preset threshold, a warning message is generated and sent to the target client.

[0087] Change similarity is an indicator that measures the degree of similarity between two or more land patches in terms of change patterns. The preset threshold is a judgment standard pre-set by the system to determine whether the change similarity has reached a level that requires attention. Early warning information is a warning message generated by the system to alert relevant personnel to potential anomalies or situations that require special attention. The target client is a terminal device or software system that receives the early warning information and performs subsequent processing.

[0088] The system first compares the change similarity calculated in step S213 with a preset threshold. This preset threshold is usually set based on historical data analysis and expert experience, for example, set to 0.8 or 0.9. When the change similarity exceeds this threshold, the system triggers the early warning mechanism. The generation process of early warning information includes the following steps: First, the system creates a structured early warning information template, including fields such as early warning level, early warning type, involved map ID, similarity value, and change trend description. Then, the system fills the specific early warning content into this template. For example, a typical early warning message is: "High warning: map ID 10086 shows a highly similar change trend (similarity 0.95) with adjacent maps, mainly manifested in a continuous reduction in area, regularization of shape, and gradual change from agricultural land to construction land". The system will also attach relevant map location maps and change trend charts to this early warning message. Next, the system packages this early warning information into a standard format (such as JSON or XML) and sends it to the target client through a preset network protocol (such as HTTPS or a dedicated secure communication protocol). During the sending process, the system will use encryption technology to ensure the security of information transmission.

[0089] S215. Upon receiving the land survey data update instruction sent by the target client, an update task list fed back by the target client is obtained, the update task list including spatial data correction tasks, metadata supplement tasks, attribute data update tasks and auxiliary data update tasks.

[0090] The land survey data update instruction is a command sent by the target client to request the system to update the data. The update task list is a list of multiple specific update tasks. The spatial data correction task refers to the work of correcting the spatial information such as the location and shape of the land map. The metadata supplement task refers to the improvement or update of the descriptive information of the data, such as the source of the data, the time of collection, etc. The attribute data update task refers to the modification or update of the non-spatial attribute information of the land map, such as land use, ownership, etc. The auxiliary data update task refers to the update of supplementary data related to the land map, such as field photos, survey reports, etc.

[0091] The system first establishes a monitoring mechanism to continuously detect data update instructions from the target client. When receiving the update instruction, the system will parse the instruction and extract the authorization information and operation scope contained therein. Then, the system sends a task list request to the target client, asking the client to provide detailed update task information. After receiving the request, the target client will generate a structured update task list and send it back to the system. After receiving this task list, the system will parse and classify it. For spatial data correction tasks, the system will extract the list of patch IDs that need to be corrected and specific spatial correction parameters, such as coordinate adjustment values ​​or shape modification instructions. For metadata supplement tasks, the system will identify the metadata fields that need to be supplemented and the corresponding new values. For attribute data update tasks, the system will extract the attribute names that need to be updated and the new attribute values. For auxiliary data update tasks, the system will record the data types that need to be updated and the corresponding file links or contents. The system stores these classified task information in a temporary task database and assigns a unique task ID to each task. At the same time, the system will generate a task execution plan, including information such as task priority, estimated execution time, and required resources. This execution plan will take into account the dependencies between tasks to ensure the order and consistency of update operations.

[0092] S216: Formulate a database update plan based on the update task list.

[0093] A database update plan is a detailed execution plan that describes how to implement each task in the update task list in the database. This plan usually includes update sequence, data validation rules, rollback mechanism, and performance optimization strategy.

[0094] The system first analyzes and classifies the update task list obtained in step S215. The system uses a task dependency analysis algorithm to determine the order and association between tasks. For example, spatial data correction usually needs to be performed before attribute data is updated to ensure the accuracy of spatial location. Then, the system formulates specific execution strategies for each type of task. For spatial data correction tasks, the system designs processes for coordinate transformation and topology checking. For metadata supplementation tasks, the system formulates rules for data integrity verification. For attribute data update tasks, the system designs a mechanism for attribute consistency checking. For auxiliary data update tasks, the system formulates a solution for file storage and link updates. Next, the system generates a detailed SQL script or NoSQL operation sequence to implement these update operations. This script includes a transaction processing mechanism to ensure the atomicity and consistency of update operations. At the same time, the system also designs data backup and rollback strategies to deal with update failures. In addition, the system also formulates performance optimization strategies, such as batch updates, index reconstruction, etc., to improve the efficiency of large-scale data updates. Finally, the system generates a complete database update plan document that includes all these strategies and scripts, and attaches execution time estimates and resource requirement assessments.

[0095] S217. Update the land survey database according to the database update plan.

[0096] Specifically, each update task is executed in sequence. For spatial data correction, the system uses specific functions of the spatial database to perform coordinate conversion and geometric operations. For metadata supplementation, the system updates the metadata table through update statements. For attribute data updates, the system performs a series of update operations and verifies the data type and value range at the same time. For auxiliary data updates, the system updates the file storage path or updates external links. During the execution process, the system monitors the progress and status of the update operation in real time and records the execution results of each step. If an error is encountered during the update process, the system triggers the preset exception handling mechanism, including partial rollback or overall rollback operations. After the update is completed, the system performs a data consistency check to ensure that all updates are applied correctly. Finally, the system commits the transaction to make all changes effective and generates a detailed update report, including the number of records successfully updated, failed operations and reasons, etc.

[0097] S218: Receive a data query request sent by the target client, where the data query request includes a query condition and a query object.

[0098] A data query request is an instruction sent by the client to retrieve specific information. Query conditions are a set of restrictions used to filter the required data, including time range, geographic location, attribute value, etc. Query objects refer to the data entities that need to be retrieved, such as land plots, ownership information, etc.

[0099] The system first establishes a secure communication channel, usually using the HTTPS protocol, to receive data query requests from the target client. When the query request is received, the system parses and verifies the request. The parsing process includes extracting the query conditions and query object information, and the verification process includes checking the correctness of the request format and the identity authentication of the sender. For example, a typical query request is in JSON format, containing the query object (such as land map), query conditions (such as area range, land use, geographic location) and the fields to be returned. The system parses this JSON object and identifies the specific query requirements. Next, the system performs a security check on the query conditions to prevent security threats such as SQL injection. The system then converts these query conditions and objects into internal query representations to prepare for subsequent database operations. At the same time, the system also records relevant information about the query request, including the request time, request source, query content, etc.

[0100] S219: Query the land survey database according to the query condition to obtain a comprehensive query result, and send the comprehensive query result to the target client.

[0101] The query condition is a set of restrictive conditions used to filter the required data. The land survey database is a structured data storage system that stores land survey related information. The comprehensive query result is a set of data that meets the requirements retrieved from the database according to the query condition.

[0102] First, a database query statement is constructed according to the query conditions parsed in step S218. For relational databases, the system usually uses SQL language; for non-relational databases, a specific query syntax is used. The system will optimize the query statement, such as using appropriate indexes, partitioning strategies, and parallel query techniques to improve query efficiency. When executing a query, the system will consider the database load and use mechanisms such as read-write separation or query queues to balance system resources.

[0103] S220: Save the query condition, the query object, and the comprehensive query result as a query template.

[0104] The system first structures the query conditions and query objects received in step S218, as well as the comprehensive query results generated in step S219. The system creates a new data structure, usually an object in JSON or XML format, which contains three main parts: query conditions, query objects, and result structures. The query condition part includes all parameters used to filter data, such as time range, geographic location, attribute values, etc. The query object part specifies the target entity of the query, such as land patches, ownership information, etc. The result structure part records the field name, data type, and formatting method of the query result. The system also generates a unique identifier for this query template and adds metadata information, such as creation time, frequency of use, etc. Next, the system stores this structured query template in a dedicated template database. The storage process includes data compression, index creation, and access permission settings. The system also establishes associations between templates, such as creating template categories based on the similarity of query objects or conditions. In addition, the system implements a template management mechanism, including version control, usage statistics, and automatic optimization functions. In this way, the system can not only quickly reuse common queries, but also optimize future query operations based on historical query patterns, improving the efficiency and user experience of the entire land survey data query system.

[0105] In some embodiments, support can also be provided for daily tasks such as backup, update, maintenance, application and reporting of the land survey database to meet the management needs of daily land management for land survey data. The system data storage and application of the database management system involve three aspects: data storage network, internal work network and the Internet. Data should be stored in the confidential network, physically isolated from other networks, and logically isolated from the work network and the Internet. The system's data analysis and application, data maintenance and other functions run on the data storage network. System data exchange passes through the data exchange area and then uses manual isolation to exchange to the internal work network.

[0106] The system can also perform data inspection interactively and in batches, supporting multi-user parallel inspection; based on the inspection content and results, it can generate inspection reports and partial statistical evaluation results with clear content, easy error location, and certain error correction guidance; The system supports direct reading and browsing of common remote sensing image data formats, and can support the reading, writing and browsing of spatial data in more data formats through customized development and expansion. The system also supports seamless browsing of remote sensing images and spatial data throughout the city, supports the storage of metadata, maintains the association between metadata and data, browses metadata, queries and statistically summarizes metadata, appends or updates relevant metadata information when data undergoes important processing, and realizes the output and printing of metadata. It supports batch or one-time conversion of data in different formats into the unified format of the national land survey database, and generates data conversion reports. It can also distribute data, mainly including identity registration, query, retrieval, browsing, application, review, download (or offline distribution), user access and other functions. It realizes data distribution services through a set of strict and standardized management processes (user registration, login, metadata query, data application, application review, review result notification, notification of offline distribution, etc.), and realizes data submission through the data exchange service area. The exchanged data content includes all the results in the land survey database, and the exchanged data content and data format can be customized.

[0107] Identity management is performed through user, role and password management, and user identity, data operation content and operation function are bound and controlled to ensure data security. The system user table is set by the system administrator when the system is initialized, and the real-name system is adopted. Only the system administrator is allowed to adjust the user table when personnel changes.

[0108] Data statistics include many forms. Statistics can be performed based on land type codes, property rights, and any area. The statistical results are presented in the form of statistical graphs and can be exported as pictures to provide convenience for users. Data analysis can also be performed, including the second and third national land survey flow analysis, which is a statistical analysis of the flow changes of the second national land survey like the third national land survey; it also includes land occupation analysis, etc., which is an analysis of the quantity of each land type occupied by graphics within a certain range.

[0109] The following describes the land survey data updating system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the structure of a physical device of the land survey data update system in an embodiment of the present application.

[0110] It should be noted that Figure 3 The structure of the land survey data updating system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0111] like Figure 3As shown, the land survey data update system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0112] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0113] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0114] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0115] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0116] Specifically, the land survey data updating system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the land survey data updating method provided in the above embodiment is implemented.

[0117] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the land survey data update system described in the above embodiment; or may exist independently without being assembled into the land survey data update system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the land survey data update system, the land survey data update system implements the land survey data update method provided in the above embodiment.

[0118] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0119] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0120] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for updating land survey data, characterized in that: Applied to a land survey data management system, the method comprises: Importing an orthophoto map of a preset survey range as a basic geographic information layer, superimposing vector boundary data of the preset survey range on the basic geographic information layer and importing historical land information within the preset survey range to obtain a comprehensive basic information layer; Obtain the actual land type, measured area and ownership status information of various types of land within the preset survey scope; Compare the actual land type, the measured area and the ownership status information with the comprehensive basic information layer to identify land use change data, which includes land type change data, area change data and ownership status change information; A land survey data update instruction is generated according to the land use change data, and the land survey data update instruction and the comprehensive basic information layer are sent to a target client.

2. The method according to claim 1, characterized in that The step of importing the orthophoto map of the preset survey range as the basic geographic information layer, superimposing the vector boundary data of the preset survey range on the basic geographic information layer and importing the historical land information within the preset survey range to obtain the comprehensive basic information layer specifically includes: Obtain an orthophoto map of a preset survey range, identify the orthophoto map based on a ground feature spectral feature library, and obtain a preliminary land type distribution map; Generate vector boundary data according to the administrative division data and terrain features of the preset survey range, and superimpose the vector boundary data on the preliminary land type distribution map to form a boundary superimposed land type map; The historical land use data within the preset survey range is extracted from the land survey database, and the spatial information in the historical land use data is matched with the geographic entities in the boundary overlay land class map to form a comprehensive basic information layer.

3. The method according to claim 1, characterized in that The step of comparing the actual land type, the measured area and the ownership status information with the comprehensive basic information layer to identify land use change data, wherein the land use change data includes land type change data, area change data and ownership status change data, specifically includes: Perform spatial overlay analysis on the actual land type, measured area and ownership status information and the historical data in the comprehensive basic information layer, identify the patches where the land type has changed based on the change detection algorithm, and generate land type change data; Calculate the area difference between the measured area and the historical area, and when the area difference exceeds a preset area threshold, mark it as area change data; Compare the actual ownership status with the historical ownership information. When the actual ownership status is inconsistent with the historical ownership information, mark it as a change in ownership status.

4. The method according to claim 1, characterized in that: After the step of generating a land survey data update instruction according to the land use change data and sending the land survey data update instruction to the target client, the method further includes: Receiving a land survey data update result sent by the target client, wherein the land survey data update result includes first land spot information that is successfully updated and second land spot information that is failed to be updated; Analyze the second land map information to obtain reasons for update failure, where the reasons for update failure include data conflict, ownership dispute, and changes in actual conditions; Based on the cause of the update failure, corresponding processing suggestions are matched in a preset database, and the processing suggestions include data verification, ownership confirmation and on-site review.

5. The method according to claim 4, characterized in that After matching the corresponding processing suggestions in the preset database based on the update failure reasons, wherein the processing suggestions include the steps of data verification, ownership confirmation and on-site review, the method further includes: Acquire change trend data of the second land patch information, wherein the change trend data includes area change trend, shape change trend and attribute change trend; Acquire change trend data of adjacent spots of the second land spot, and calculate the change similarity between the second land spot information and the adjacent spots; If the change similarity is higher than a preset threshold, a warning message is generated and sent to the target client.

6. The method according to claim 2, characterized in that After the step of generating a land survey data update instruction according to the land use change data and sending the land survey data update instruction to the target client, the method further includes: Upon receiving the land survey data update instruction sent by the target client, obtaining an update task list fed back by the target client, the update task list including a spatial data correction task, a metadata supplement task, an attribute data update task and an auxiliary data update task; Formulate a database update plan according to the update task list; The land survey database is updated according to the database update plan.

7. The method according to claim 6, characterized in that After the step of updating the land survey database according to the database update scheme, the method further includes: Receiving a data query request sent by the target client, wherein the data query request includes a query condition and a query object; Performing a query in the land survey database according to the query condition to obtain a comprehensive query result, and sending the comprehensive query result to the target client; The query condition, the query object and the comprehensive query result are saved as a query template.

8. A land survey data updating system, characterized in that: The land survey data update system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the land survey data update system to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a land survey data updating system, the land survey data updating system is caused to execute the method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product runs on a land survey data updating system, the land survey data updating system is enabled to execute the method according to any one of claims 1 to 7.

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