Graph database-based land type pattern spot storage analysis method and system

Abstract

The invention discloses a map database-based land type map spot storage and analysis method and system. The method comprises the following steps of: acquiring and processing data; storing data; monitoring pattern spot type distribution analysis; performing annual change investigation pattern spot and land type change analysis; and reading and displaying data. According to the method, spatial analysis is carried out on land type change monitoring pattern spots and annual change investigation pattern spots, and a method based on a pattern database is designed to store analysis results; the incidence relation and important attributes of the change monitoring pattern spots and the annual change pattern spots can be expressed on a visual platform, and the monitoring type distribution condition and the annual change survey of the change conditions of different land types in a certain space range are analyzed; according to the storage and analysis method, the internal relation between the change monitoring pattern spots and the annual change pattern spots is visually presented, the effectiveness of change monitoring pattern spot analysis is improved, the data value of the monitoring pattern spots is deeply mined, natural resource data analysis and application are facilitated, and planning and decision making of related departments of the natural resource industry are supported.

Description

Technical Field

[0001] The present invention relates to the field of data analysis and application of natural resource investigation and monitoring results, and particularly to a method and system for storing and analyzing land type patches. Background Art

[0002] Natural resources are the material basis, spatial carrier and constituent elements of ecological civilization construction, and are an irreplaceable spatial support foundation for the sustainable development of the economy and society. In 2020, the Ministry of Natural Resources systematically arranged the natural resource investigation and monitoring work, and clearly put forward that analysis and evaluation is one of the main tasks of investigation and monitoring. It is required to conduct statistical summary, comprehensive analysis and systematic evaluation of the investigation and monitoring data to provide a basis for scientific decision-making and strict management. As an important part of the natural resource investigation and monitoring system, analysis and evaluation is an important tool for the transformation and leap of the original data of natural resource investigation and monitoring into information, knowledge and service management decision-making, and is a necessary means to reflect the spatial distribution law of economy, society, resources and environment. It plays a crucial role in promoting the application of natural resource investigation and monitoring results and promoting natural resource investigation and monitoring work.

[0003] In recent years, the natural resource investigation and monitoring work has been continuously carried out, accumulating a large amount of data resources. On this basis, the Ministry of Natural Resources clearly put forward that analysis and evaluation is one of the main tasks of investigation and monitoring, and requires statistical summary, comprehensive analysis and systematic evaluation of the investigation and monitoring data. Based on this, by analyzing the correlation between the change monitoring patches and the annual change survey patches, a storage and analysis method based on graph database technology is studied to intuitively present the internal relationship between the change monitoring patches and the annual change patches, and deeply explore the value of natural resource investigation and monitoring data. For example, analyzing the distribution of land type change monitoring patch types within a certain spatial range, and analyzing the land type changes of annual change survey patches within a certain spatial range, etc., is conducive to the data analysis and application of natural resources, supports the planning and decision-making of relevant departments in the natural resource industry, and provides a scientific basis for natural resource management work. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for storing and analyzing land type patches based on a graph database, which can at least analyze the distribution of land type change monitoring patch types within a certain spatial range.

[0005] According to the first aspect of the present invention, there is provided a method for storing and analyzing land type patches based on a graph database, which includes: Data acquisition and processing: Obtain the current year's land type change monitoring patches and the previous year's annual change survey patches and their information and attributes, divide the attributes into important attributes and basic attributes; perform overlay analysis on the land type change monitoring patches and the annual change survey patches to obtain the correlation and the overlapping area; Data storage: Store the land type change monitoring patches and annual change survey patches as point elements. Store the basic attributes of the patches as the attributes of the point elements, and store the important attributes of the patches as the point elements in the map database. Store the association relationships as the edge elements in the map database; Analysis of the distribution of monitoring patch types: Based on the map database, analyze the distribution of monitoring types of land type change monitoring patches within a set spatial range; Analysis of land type changes in annual change survey patches: Based on the map database, analyze the land type changes in annual change survey patches within a set spatial range.

[0006] According to the above-mentioned method for storing and analyzing land type patches based on the map database, in the steps of data acquisition and processing, obtain land type change monitoring patches and annual change survey patches and their information and attributes, and divide the attributes into important attributes and basic attributes, including: Obtain land type change monitoring patches and their attributes, and calculate the spatial position range coordinate information and spatial position center point coordinate information of the land type change monitoring patches; Obtain annual change survey patches and their attributes, and calculate the spatial position range coordinate information of the annual change survey patches; Divide the attributes of land type change monitoring patches and the attributes of annual change survey patches into important attributes and basic attributes respectively.

[0007] According to the above-mentioned method for storing and analyzing land type patches based on the map database, in the steps of data acquisition and processing, The important attributes of land type change monitoring patches include patch type, monitoring type, and center point coordinates; The basic attributes of land type change monitoring patches include patch number, administrative division code, administrative division name, patch type code, monitoring type code, monitoring area, year, and patch characteristics; The important attribute of annual change survey patches includes land type name; The basic attributes of annual change survey patches include patch number, land type code, patch area, year, ownership nature, ownership unit code, ownership unit name, location unit code, location unit name, and cultivated land slope level.

[0008] According to the above-mentioned method for storing and analyzing land type patches based on the map database, in the steps of data acquisition and processing, perform an overlay analysis of land type change monitoring patches and annual change survey patches to obtain association relationships and overlay areas, including: Overlay the land type change monitoring patches and annual change survey patches within the same spatial range; According to the superposition result, the association relationships are divided into inclusion, being included, and intersection, and the annual change survey patches associated with the land type change monitoring patches and the overlapping areas are recorded. If the land type change monitoring patch includes the annual change survey patch, the overlapping area is counted as the patch area of the annual change survey patch; if the land type change monitoring patch is included in the annual change survey patch, the overlapping area is counted as the patch area of the land type change monitoring patch; if the land type change monitoring patch intersects with the annual change survey patch, the overlapping area is counted as the overlapping area between the land type change monitoring patch and the annual change survey patch.

[0009] According to the above-mentioned land type patch storage analysis method based on the graph database, in the steps of monitoring patch type distribution analysis, based on the graph database, analyzing the monitoring type distribution of land type change monitoring patches within a set spatial range includes: Select a set spatial range, read the point features storing the central point coordinates of the land type change monitoring patches in the graph database, extract the coordinate values, with a total of m point features; Set the number of patches to be aggregated as n, and take every n point features as a group. According to the combination principle, there are a total of groups. Calculate the average distance of the central point coordinates of each group, sort each group according to the average distance of the central point coordinates, and extract all groups with an average distance less than the threshold v. There are a total of S groups, and each group is used as an analysis area; Calculate how many different monitoring types there are among all the point features in the analysis area, and respectively count the total area sum of the monitoring patches of the same monitoring type. Sort the total area sum of each monitoring type in the analysis area to obtain the monitoring type with the largest area change in the analysis area, and calculate the proportion P of the patch area of this monitoring type in the total monitoring patch area of the analysis area. If P is greater than 50%, then this monitoring type represents the change characteristics of the analysis area; Set different numbers n of aggregated patches and average distances v to ensure that the proportion P of the area of the monitoring type with the largest area change in each analysis area exceeds 50%.

[0010] According to the above-mentioned land type patch storage analysis method based on the graph database, in the steps of analyzing the land type change of the annual change survey patches, based on the graph database, analyzing the land type change situation of the annual change survey patches within a set spatial range includes: Select a set spatial range; read the point features of the land type of the annual change survey patches in the graph database, and count that the number of land type categories is a; read the point features of the patch types of the land type change monitoring patches in the graph database, and count that the number of patch types is b, and the number of change combinations is c kinds, where c = a * b; For the c kinds of combinations, respectively count the total area of each combination; Sort the areas of each of the c combinations, and analyze the areas of the changes in different land use types within this spatial range.

[0011] According to the above-mentioned method for storing and analyzing land use type patches based on a graph database, for the c combinations, the steps of respectively counting the total area of each combination include: Select one of the c combinations, where the land use type of the annual change survey patch is A and the patch type of the land use change monitoring patch is B; Query the starting point elements of all edge elements ending with B in the database, and the query result is t; query the starting point elements of all edge elements ending with A in the database, and the query result is r; Query the edge elements in the graph data, where the starting point element of the edge element is one of the t land use change monitoring patches and the ending point element is one of the r annual change survey patches, and obtain k edge elements; Among the k edge elements, read the overlapping area of the ending point elements, and calculate the total overlapping area of the k edge elements as the total area of this combination; Perform a loop operation to obtain the total area of each of the c combinations.

[0012] According to the above-mentioned method for storing and analyzing land use type patches based on a graph database, it further includes: Data reading and display: Read the spatial location range data of the land use change monitoring patches and the annual change survey patches in the graph database and display them on the geographic information data visualization platform; After clicking and selecting a land use change monitoring patch on the geographic information data visualization platform, query the associated annual change survey patches, important attributes, and association relationships from the graph database, and highlight the land use change monitoring patch and the associated annual change survey patch in different colors; Present the attributes and association relationships of the land use change monitoring patches and the annual change survey patches.

[0013] According to the second aspect of the present invention, a system is provided, which includes a processor and a memory, and the memory stores multiple instructions; the processor loads the instructions from the memory to execute the above-mentioned method for storing and analyzing land use type patches based on a graph database.

[0014] Beneficial effects: The present invention realizes the spatial analysis of land use change monitoring patches and annual change survey patches, and designs a method based on a graph database to store the analysis results; and can express the association relationships and important attributes of the change monitoring patches and the annual change patches on the visualization platform, and analyze the distribution of monitoring types within a certain spatial range and the changes in different land use types in the annual change survey; This storage and analysis method visually presents the internal relationship between the change monitoring patches and the annual change patches, improves the effectiveness of change monitoring patch analysis, deeply explores the data value of monitoring patches, is beneficial to the data analysis and application of natural resources, and supports the planning and decision-making of relevant departments in the natural resources industry.

[0015] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below in conjunction with the drawings and embodiments: Figure 1 is a data processing flow chart; Figure 2 is a schematic diagram for calculating the overlapping area; Figure 3 is a schematic diagram showing the correlation relationship and important attributes between the land type change monitoring patches and the annual change survey patches Figure 1 ; Figure 4 is a schematic diagram showing the correlation relationship and important attributes between the land type change monitoring patches and the annual change survey patches Figure 2 ; Figure 5 is a diagram expressing the correlation relationship between the land type change monitoring patches and the annual change survey patches. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] This part will describe in detail the specific embodiments of the present invention. The preferred embodiments of the present invention are shown in the drawings. The role of the drawings is to supplement the description in the text part of the specification, enabling people to visually and vividly understand each technical feature and the overall technical solution of the present invention, but it cannot be construed as a limitation on the protection scope of the present invention.

[0018] Referring to Figures 1 - 5 , the land type patch storage and analysis method based on the graph database in the embodiment of the present invention includes the following steps: Data acquisition and processing: Obtain the current year's land type change monitoring patches, the previous year's annual change survey patches and their information and attributes, divide the attributes into important attributes and basic attributes; perform overlay analysis on the land type change monitoring patches and the annual change survey patches to obtain the correlation relationship and the overlapping area; Data storage: Store the land type change monitoring patches and the annual change survey patches as point features, store the basic attributes of the patches as the attributes of the point features, and store the important attributes of the patches as the point features in the graph database; store the correlation relationship as the edge features in the graph database; Analysis of the distribution of monitoring patch types: Based on the graph database, analyze the distribution of monitoring types of land use change monitoring patches within the set spatial range; that is, analyze different analysis areas, which monitoring type is the main one, present the change characteristics of different areas, and further analyze the current situation characteristics of the area to provide decision-making support for natural resource management and local economic development. Analysis of land use change of annual change survey patches: Based on the graph database, analyze the land use change of annual change survey patches within the set spatial range; that is, analyze which type of change has the largest area of current land use change, and further predict and evaluate the land change situation to provide favorable suggestions for local economic development. Data reading and display: Display the data in the geographic information data visualization platform, and present the attributes and association relationships of land use change monitoring patches and annual change survey patches through operations such as clicking.

[0019] Among them, in the steps of data acquisition and processing, obtain land use change monitoring patches and annual change survey patches and their information and attributes, and divide the attributes into important attributes and basic attributes, which specifically include: Obtain land use change monitoring patches and their attributes, and use spatial analysis methods to calculate the spatial position range coordinate information and spatial position center point coordinate information of land use change monitoring patches, which are used as the spatial position range attribute and the center point attribute respectively. Obtain annual change survey patches and their attributes, and use spatial analysis methods to calculate the spatial position range coordinate information of annual change survey patches as the spatial position range attribute. According to the different importance, divide the attributes of land use change monitoring patches and the attributes of annual change survey patches into important attributes and basic attributes respectively.

[0020] Among them, in the steps of data acquisition and processing: The important attributes of land use change monitoring patches include patch type, monitoring type, center point coordinates, and spatial position range coordinates, etc. The basic attributes of land use change monitoring patches include patch number, administrative division code, administrative division name, patch type code, monitoring type code, monitoring area, year, and patch characteristics, etc. The important attributes of annual change survey patches include land use type name and spatial position range coordinates, etc. The basic attributes of annual change survey patches include patch number, land use code, patch area, year, ownership nature, ownership unit code, ownership unit name, located unit code, located unit name, and cultivated land slope level, etc.

[0021] Among them, in the steps of data acquisition and processing, the land use change monitoring patches and the annual change survey patches are overlaid and analyzed to obtain the correlation and the overlapping area. Specifically, it includes: Overlay the land use change monitoring patches and the annual change survey patches within the same spatial range; According to the overlay result, the correlation is divided into inclusion, being included, and intersection. Record the annual change survey patches related to the land use change monitoring patches and the overlapping area; Refer to Figure 2 As shown, if the land use change monitoring patch includes the annual change survey patch, the overlapping area is counted as the patch area of the annual change survey patch; if the land use change monitoring patch is included in the annual change survey patch, the overlapping area is counted as the patch area of the land use change monitoring patch; if the land use change monitoring patch intersects with the annual change survey patch, the overlapping area is counted as the overlapping area between the land use change monitoring patch and the annual change survey patch.

[0022] Among them, in the steps of analyzing the distribution of monitoring patch types, based on the graph database, analyze the distribution of monitoring types of land use change monitoring patches within the set spatial range. Specifically, it includes: Select the set spatial range. For example, according to the administrative division (such as town, county, city, etc.), read the point features storing the central point coordinates of the land use change monitoring patches in the graph database, extract the coordinate values, with a total of m point features; Set the number of patches to be aggregated as n. Every n point features are taken as a group. According to the combination principle, there are a total of groups. Calculate the average distance of the central point coordinates of each group (that is, in the group, first obtain the distance between any two patch central points, and then average these distances). Sort each group according to the average distance of the central point coordinates, and take out all the groups with an average distance less than the threshold v. There are a total of S groups, and each group is used as an analysis area; Calculate how many different monitoring types there are among all the point features in the analysis area, and respectively count the total area sum of the land use change monitoring patches of the same monitoring type, that is, read and sum the area attribute values of the land use change monitoring patch point features. Sort the total area sum of each monitoring type in this analysis area, and obtain the monitoring type with the largest area change in this analysis area. Calculate the proportion P of the patch area of this monitoring type in the total area sum of the land use change monitoring patches in this analysis area. If P is greater than 50%, then this monitoring type represents the change characteristics of this analysis area; Set different numbers n of aggregated patches and average distances v to ensure that the proportion P of the area of the monitoring type with the largest area change in each analysis area exceeds 50%, presenting the patch change characteristics of the land use monitoring types in different analysis areas.

[0023] Based on the above steps, analyze the distribution of the monitoring types of the land use change monitoring patches within the set spatial range, that is: analyze the monitoring types of the land use change monitoring patches representing the change characteristics of each analysis sub-region among the different analysis sub-regions divided within the set spatial range.

[0024] Among them, in the steps of analyzing the land use change of the annual change survey patches, based on the map database, analyze the land use change situation of the annual change survey patches within the set spatial range, which specifically includes: Select the set spatial range; read the point elements of the land use types of the annual change survey patches in the map database, and count the number of land use types as a (that is, there are a different land use types); read the point elements of the patch types of the land use change monitoring patches in the map database, and count the number of patch types as b (that is, there are b different patch types), and the number of change combinations is c, c = a * b; For each of the c combinations, count the total area of each combination respectively; Sort the areas of the c combinations respectively, and analyze the areas of the changes in different land use names within this spatial range.

[0025] Specifically, the specific steps of counting the total area of each combination for the c combinations respectively include: Select one of the c combinations, where the land use type of the annual change survey patch is A and the patch type of the land use change monitoring patch is B; Query the starting point elements of all the edge elements ending with B in the database, that is, the land use change monitoring patches, and the query result is t; query the starting point elements of all the edge elements ending with A in the database, that is, the annual change survey patches, and the query result is r; Query the edge elements in the map data, where the starting point element of the edge element is one of the t land use change monitoring patches and the ending point element of the edge element is one of the r annual change survey patches, and obtain k edge elements; Among the k edge elements, read the overlapping area of the ending point elements, and calculate the total overlapping area of the k edge elements as the total area of this combination; Loop the above operations to obtain the total areas of each of the c combinations.

[0026] Based on the above steps, analyze the land use change situation of the annual change survey patches within the set spatial range, that is: analyze the areas of the changes in different land use names within this spatial range.

[0027] Among them, in the steps of data reading and display, display the data in the geographic information data visualization platform, and present the attributes and association relationships of the land use change monitoring patches and the annual change survey patches through operations such as clicking, which specifically includes: Read the spatial location range data of the land type change monitoring patches and annual change survey patches in the graph database and display them in the geographic information data visualization platform; After clicking to select the land type change monitoring patches in the geographic information data visualization platform, query the associated annual change survey patches, important attributes, and association relationships from the graph database, and highlight the land type change monitoring patches and the associated annual change survey patches in different colors; Use the Web front-end D3.js rendering and expression technology to present the attributes and association relationships of the land type change monitoring patches and annual change survey patches through circles and connection direction lines, as shown in Figures 3 - 5 shown.

[0028] The present invention also discloses a system, which includes a processor and a memory, and the memory stores multiple instructions; the processor loads the instructions from the memory to execute the above-mentioned land type patch storage and analysis method based on the graph database.

[0029] Although the methods described above are illustrated and described as a series of acts for simplicity of explanation, it should be understood and appreciated that the methods are not limited by the order of the acts, since according to one or more embodiments, some acts may occur in a different order and / or concurrently with other acts not illustrated and described herein or other acts that would be understood by those skilled in the art. Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention. The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented using a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of both. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read from, and write to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal. In one or more exemplary embodiments, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer readable medium as one or more instructions or code.Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. The storage media can be any available media that can be accessed by a computer. By way of example and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable media. For example, if software is transferred from a web site, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of the medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray disc, where disk generally reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0030] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those of ordinary skill in the art.

Claims

1. A method for storing and analyzing land type patches based on a graph database, characterized in that, Including: Data acquisition and processing: Obtain the current-year land-use change monitoring patches, the previous-year annual change survey patches, as well as their information and attributes, and divide the attributes into important attributes and basic attributes; perform overlay analysis on the land-use change monitoring patches and the annual change survey patches to obtain the association relationship and the overlapping area; Data storage: Store the land-use change monitoring patches and the annual change survey patches as point features, store the basic attributes of the patches as the attributes of the point features, and store the important attributes of the patches as the point features in the graph database; store the association relationship as the edge feature in the graph database; Analysis of the distribution of monitoring patch types: Based on the graph database, analyze the distribution of monitoring types of land-use change monitoring patches within a set spatial range; Analysis of land-use changes in annual change survey patches: Based on the graph database, analyze the land-use change situation of annual change survey patches within a set spatial range.

2. The method for storing and analyzing land type patches based on a graph database according to claim 1, wherein In the steps of data acquisition and processing, obtaining the land-use change monitoring patches, the annual change survey patches, as well as their information and attributes, and dividing the attributes into important attributes and basic attributes includes: Obtain the land-use change monitoring patches and their attributes, and calculate the spatial location range coordinate information and the spatial location center point coordinate information of the land-use change monitoring patches; Obtain the annual change survey patches and their attributes, and calculate the spatial location range coordinate information of the annual change survey patches; Divide the attributes of the land-use change monitoring patches and the attributes of the annual change survey patches into important attributes and basic attributes respectively.

3. The method for storing and analyzing land type patches based on a graph database according to claim 2, wherein In the steps of data acquisition and processing, The important attributes of the land-use change monitoring patches include patch type, monitoring type, and center point coordinates; The basic attributes of the land-use change monitoring patches include patch number, administrative division code, administrative division name, patch type code, monitoring type code, monitoring area, year, and patch characteristics; The important attribute of the annual change survey patch includes land-use name; The basic attributes of the annual change survey patches include patch number, land-use code, patch area, year, ownership nature, ownership unit code, ownership unit name, location unit code, location unit name, and cultivated land slope level.

4. The method for storing and analyzing land type patches based on a graph database according to claim 1, wherein In the steps of data acquisition and processing, performing overlay analysis on the land-use change monitoring patches and the annual change survey patches to obtain the association relationship and the overlapping area includes: Overlay the land-use change monitoring patches and the annual change survey patches within the same spatial range; According to the overlay result, divide the association relationship into inclusion, being included, and intersection, and record the annual change survey patches related to the land-use change monitoring patches and the overlapping area; If the land-use change monitoring patch includes the annual change survey patch, the overlapping area is counted as the patch area of the annual change survey patch; if the land-use change monitoring patch is included in the annual change survey patch, the overlapping area is counted as the patch area of the land-use change monitoring patch; if the land-use change monitoring patch intersects with the annual change survey patch, the overlapping area is counted as the overlapping area between the land-use change monitoring patch and the annual change survey patch.

5. The method for storing and analyzing land type patches based on a graph database according to claim 1, characterized in that, In the steps of analysis of the distribution of monitoring patch types, based on the graph database, analyzing the distribution of monitoring types of land-use change monitoring patches within a set spatial range includes: Select and set the spatial range, read the point features storing the central point coordinates of the patches for monitoring land type changes in the graph database, extract the coordinate values, with a total of m point features; Set the number of aggregated patches as n, and every n point features are grouped as a set. According to the combination principle, there are a total of sets. Calculate the average distance of the central point coordinates for each set, sort the sets according to the average distance of the central point coordinates, and select all the sets whose average distance is less than the threshold v. There are a total of S sets, and each set is used as an analysis area; Calculate how many different monitoring types there are among all the point features in the analysis area, and separately count the total area of the monitoring patches of the same monitoring type. Sort the total area of each monitoring type in this analysis area to obtain the monitoring type with the largest area change in this analysis area, and calculate the proportion P of the patch area of this monitoring type in the total area of the monitoring patches in this analysis area. If P is greater than 50%, then this monitoring type represents the change characteristics of this analysis area; Set different numbers n of aggregated patches and average distances v to ensure that the proportion P of the area of the monitoring type with the largest area change in each analysis area exceeds 50%.

6. The method for storing and analyzing land type patches based on a graph database according to claim 1, wherein, In the steps of analyzing the land type changes of the patches in the annual change survey, based on the graph database, analyzing the land type changes of the patches in the set spatial range includes: Select and set the spatial range; read the point features of the land type of the patches in the annual change survey in the graph database, and count that the number of land types is a; read the point features of the patch types of the patches for monitoring land type changes in the graph database, and count that the number of patch types is b, and the number of change combinations is c kinds, where c = a * b; For the c kinds of combinations, separately count the total area of each combination; Sort the respective areas of the c kinds of combinations, and analyze the areas of the changes in different land type names within this spatial range.

7. The method for storing and analyzing land type patches based on a graph database according to claim 6, characterized in that, The steps of separately counting the total area of each combination for the c kinds of combinations include: Select one of the c kinds of combinations, where the land type of the patch in the annual change survey is A and the patch type of the patch for monitoring land type changes is B; Query the starting point features of all the edge features ending with B in the database, and the query result is t; query the starting point features of all the edge features ending with A in the database, and the query result is r; Query the edge features in the graph data, where the starting point feature of the edge feature is one of the t patches for monitoring land type changes and the ending point feature is one of the r patches in the annual change survey, and obtain k edge features; Among the k edge features, read the overlapping area of the ending point feature, and calculate the total overlapping area of the k edge features as the total area of this combination; Perform loop operations to obtain the total area of each of the c kinds of combinations.

8. The method for storing and analyzing land type patches based on a graph database according to claim 1, characterized in that, It also includes: Data reading and display: Read the spatial location range data of the patches for monitoring land type changes and the patches in the annual change survey in the graph database, and display them on the geographic information data visualization platform; After clicking and selecting the patches for monitoring land type changes on the geographic information data visualization platform, query the associated patches in the annual change survey, important attributes, and association relationships from the graph database, and highlight the patches for monitoring land type changes and the associated patches in the annual change survey in different colors; Present the attributes and association relationships between the patches for monitoring land type changes and the patches in the annual change survey.

9. The system is characterized in that, It includes a processor and a memory, and the memory stores multiple instructions; the processor loads the instructions from the memory to execute the method for storing and analyzing land type patches based on the graph database as described in any one of claims 1 - 8.

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