A method and system for large-scale vector data deconstruction and adaptive transmission

Abstract

Applications such as online spatiotemporal analysis, network sharing and interoperability of spatial objects in the field of geology rely on the real-time and authenticity of vector data. The present invention discloses a deconstruction and adaptive transmission method for online network access and spatial analysis of large-scale vector data, which mainly solves the problems of large-scale vector data transmission efficiency and ensures the authenticity of transmitted data. The method for vector data deconstruction and adaptive transmission disclosed in the present invention uses vector elements as processing units, and includes four sub-processes: process one: server-side vector data deconstruction, process two: storage of vector data after deconstruction, process three: on-demand adaptive transmission of deconstructed vector data, and process four: transmission of deconstructed vector data to the client for reconstruction and assembly. The present invention also provides a system for vector data deconstruction and adaptive transmission in a network environment to ensure the implementation of the above method in practical applications. The present invention has application significance in the current real-time analysis, online calculation, real-time visualization and other aspects of vector data based on the Internet and cloud computing.

Description

Technical Field

[0001] The present invention belongs to the field of online spatiotemporal calculation and visualization of geoscientific vector data, and in particular relates to a method and system for deconstructing and adaptively transmitting large-scale vector data for network spatiotemporal visualization analysis. Background Art

[0002] Vector data is an important type of spatial data in earth science. It expresses the spatial characteristics of real-world objects based on geometric models such as points, lines, and surfaces composed of geographic coordinates; at the same time, it expresses the attribute characteristics of objects (i.e., information other than spatial information) in a predefined two-dimensional table structure. Vector data is structurally composed of a series of basic units called vector elements (Features). Vector elements are further composed of two parts: geometry (Geometry) and properties (Properties).

[0003] In recent years, the development of information technologies such as cloud computing, big data, and mobile Internet has driven the transformation of information systems in the field of geoscience from the traditional static, single-machine, single-user application model to a new generation of dynamic, real-time, and networked application models. The new generation of information systems characterized by network virtualization storage, distributed computing architecture, and data stream processing technologies have put forward greater challenges and requirements for the network transmission of vector data. The online spatiotemporal computing, network sharing, and interoperability applications of the new generation of geoscience information systems are inevitably based on the network transmission of vector data. However, due to the constraints of limited network bandwidth, the network transmission of large-scale vector data inevitably has practical problems such as long data transmission time, delayed online application operations, and passive waiting of users.

[0004] The disclosed vector data transmission methods in the field of geology can be summarized into three categories: progressive transmission, compressed transmission and tile transmission. The patent with publication number CN102253947A discloses a method for clustered storage and access of vector data that can be progressively transmitted from the perspective of progressive transmission. This method embodies a storage and transmission strategy that exchanges time for details, that is, first transmitting a spatially coarse-resolution version of the vector data, and then progressively transmitting its detail increments. The patent with publication number CN110351279A discloses an encryption algorithm and watermark embedding technology based on frequency domain transformation from the perspective of progressive transmission security. This method is also based on the idea of ​​progressive transmission, but focuses more on providing a method to ensure the secure progressive transmission of vector data for the purpose of vector data copyright identification. The patent with publication number CN104899311A discloses a method for compressing geographic coordinate values ​​and then transmitting data from the perspective of data compression transmission. The compressed geographic coordinates can reduce the network transmission volume of vector data. Patent publication number CN101459901 discloses a method for transmitting vector maps based on multi-level square slices from the perspective of tile transmission, and uses mobile terminal cache to reduce the transmission volume of vector maps. Vector maps are a visual expression of symbolized vector data. Vector maps can be developed from vector data, but they are no longer original vector data.

[0005] Considering that applications such as online spatiotemporal calculation and visualization of vector data in the field of geosciences rely on the real-time and authenticity of vector data, the present invention provides a method for adaptively and efficiently transmitting original vector data according to the client's spatial range, taking into account both the efficiency of large-scale vector data transmission and the authenticity of the transmitted data. The present invention has application significance in the current real-time analysis, online calculation, and real-time visualization of vector data based on the Internet and cloud computing. Summary of the invention

[0006] The present invention aims at the application requirements of online spatiotemporal calculation and visualization of original vector data, and provides a method for deconstructing and storing the two components of vector data space and attributes using vector elements as processing units, so as to realize on-demand adaptive transmission of vector data. The method includes four sub-processes: process one: the process of deconstructing vector data on the server side, process two: the process of storing vector data after deconstruction, process three: the process of on-demand adaptive transmission of deconstructed vector data, and process four: the process of transmitting deconstructed vector data to the client for reconstruction and assembly. It is characterized in that

[0007] The process of server-side vector data deconstruction further includes:

[0008] A step of deconstructing vector data into components, for initially deconstructing the original vector data;

[0009] A step of deconstructing vector data according to grids is used to perform secondary deconstruction on the vector data after the initial deconstruction based on grid division.

[0010] The step of deconstructing the above vector data by components further includes:

[0011] A sub-step of spatial component deconstruction is used to deconstruct two components, namely spatial metadata and spatial coordinates, from the vector data. The spatial metadata component includes: geometric type information and spatial reference information in the original vector data; the spatial coordinate component includes: a complete sequence of spatial coordinates in the vector data.

[0012] A sub-step of attribute component deconstruction is used to deconstruct the attribute metadata and attribute value components from the vector data. The attribute metadata component includes: the name, data type, measurement unit and optional text description of the attribute in the vector data; the attribute value component includes: the collection of all attribute values ​​in the vector data.

[0013] The step of deconstructing the above vector data into a grid further includes:

[0014] a sub-step of vector data space division, for further dividing the spatial range covered by the vector data into a set of grids, wherein the grid division is seamless and non-overlapping, and the spatial range of any grid can be uniquely determined by two characteristic values, grid coordinates and grid scale;

[0015] a sub-step of deconstructing the vector data according to spatial division, for further deconstructing the spatial coordinate components deconstructed initially according to the spatially divided grids into spatial coordinate segment components, wherein the spatial coordinate segment components are coordinate sets divided into the grid space range, and at the same time, the order of arrangement of coordinate pairs in the spatial coordinate segment components is the same as the order of arrangement of coordinate pairs in the original spatial coordinate sequence;

[0016] A sub-step of establishing an index after deconstructing the vector data by spatial division is used to quickly retrieve the spatial coordinate fragment components by the grid after spatial division, and the index includes: a grid coordinate index and a spatial coordinate fragment index. The grid coordinate index records the association between the vector element and the grid, and the spatial coordinate fragment index records the association between the grid and the spatial coordinate fragment components.

[0017] The process of storing the vector data after deconstruction further includes:

[0018] A component-level storage step is used to store attribute metadata components, attribute value components, spatial metadata components, and spatial coordinate components in a key-value manner. The unique identifier of the vector element is used as the storage key in the component storage;

[0019] A storage step according to the spatial hierarchy is used to store the grid coordinate index, the spatial coordinate segment index and the spatial coordinate segment component in a key-value manner. The grid coordinate index storage uses the unique identifier of the vector element and the grid scale as the key, and the grid coordinate, the geometric object identifier and the geometric sub-object identifier as the value. The spatial coordinate segment index uses the grid scale, the grid coordinate, the geometric object identifier and the geometric sub-object identifier as the key, and the unique identifier of the spatial coordinate segment component as the value. The spatial coordinate segment storage uses the unique identifier of the spatial coordinate segment as the key, and the spatial coordinate segment component itself as the value.

[0020] The process of on-demand adaptive transmission of the deconstructed vector data further includes:

[0021] A spatial component transmission step is used to transmit only the spatial metadata component and spatial coordinate component of the vector data within the spatial range according to the spatial range of the client. The spatial coordinate transmission first transmits the grid coordinate index covered by the vector data, and then transmits the spatial coordinate fragment component contained in each grid space in parallel based on the grid coordinate index.

[0022] An attribute component transmission step is used to transmit only the attribute metadata component and the attribute value component of the vector data within the spatial range according to the spatial range of the client.

[0023] The process of transmitting the deconstructed vector data to the client for reconstruction and assembly further includes:

[0024] a spatial component reconstruction sub-step, for reconstructing the spatial coordinate fragment components deconstructed into different grids into the same spatial coordinate components as the original vector data, and further combining the spatial metadata components to form the spatial components of the vector data;

[0025] A vector data assembly sub-step is used to merge the attribute metadata component and the attribute value component transmitted to the client to form an attribute component, and assemble it with the reconstructed spatial component to form vector data corresponding to the original vector data structure.

[0026] In order to achieve the above object, the present invention also provides a system for vector data deconstruction and adaptive transmission. The system is composed of a server subsystem and a client subsystem to ensure the implementation of the above method in practical applications, and is characterized by including:

[0027] A server subsystem mainly realizes the deconstruction and storage of vector data, monitors requests from clients, and responds by retrieving and transmitting deconstructed vector data;

[0028] A client subsystem mainly implements sending vector data requests to the server, receiving the deconstructed vector data sent back by the server, and performing caching and data reconstruction.

[0029] The above system is characterized in that

[0030] The server terminal system further comprises:

[0031] A deconstruction module is used to deconstruct common vector data file formats such as ESRI ShapeFile, GeoJSON, and KML, and separate spatial metadata components, spatial coordinate fragment components, attribute metadata components, and attribute value components;

[0032] A storage module, used for storing the deconstructed vector data on the server side, so as to support on-demand retrieval and network transmission services of the deconstructed vector data;

[0033] a retrieval module, used for retrieving spatial metadata components, spatial coordinate fragment components, attribute metadata components, and attribute value components within a specified grid space range from the deconstructed vector data storage;

[0034] A transmission module is used to monitor the request from the client and make a transmission response to the deconstructed vector data.

[0035] The client subsystem further comprises:

[0036] A data request module, used to send a vector data request to the server, wherein the data request is divided into four sub-requests: a metadata component request, an attribute value component request, a grid coordinate index request, and a spatial coordinate segment component request according to the deconstructed vector data components;

[0037] A data receiving module, used for receiving the deconstructed vector data components sent back by the server and caching the deconstructed vector data components on the client;

[0038] a data reconstruction module, used for retrieving the deconstructed vector data components from the client cache and reconstructing them according to the inverse process of vector data deconstruction;

[0039] A data distribution and visualization module is used to publish the reconstructed vector data as data files in common vector formats such as ESRI ShapeFile, GeoJSON, KML, etc., and can perform browser-based visualization of the reconstructed vector data.

[0040] Compared with the prior art, the beneficial technical effects of the present invention are:

[0041] (1) Vector data is deconstructed into vector elements as basic units, realizing the initial decomposition of the original large-scale vector data. After the initial decomposition, the vector data can be adaptively transmitted according to the needs of different clients, supporting the vector elements required by the client, thereby avoiding the transmission of all the vector elements in the vector data at one time.

[0042] (2) The vector data is further spatially decomposed based on the grid, realizing the further decomposition of the spatial coordinate components of the vector data. The spatially decomposed vector data can adaptively transmit the spatial coordinate fragment components within the current spatial range according to the real-time changes in the spatial range required by the client, thereby avoiding the transmission of all spatial coordinates in the vector data at one time.

[0043] (3) The spatial coordinates of different geometric types are uniformly decomposed into two hierarchical organizations: geometric objects and geometric sub-objects. This unifies the rules for deconstructing, storing, and transmitting vector data of different geometric types, simplifies the steps for reconstructing vector data on the client, and shortens the time for reconstructing vector data. This can better meet the needs of time-sensitive applications such as online spatiotemporal computing and visualization rendering of vector data. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a detailed flow chart of an embodiment of the vector data deconstruction process on the server side in the present invention;

[0045] Figure 2 It is a detailed flow chart of an embodiment of the vector data storage after deconstruction on the server side in the present invention;

[0046] Figure 3 It is a detailed flow chart of an embodiment of the adaptive transmission process after vector data deconstruction in the present invention;

[0047] Figure 4 It is a schematic diagram of the grid coordinate index structure after vector data deconstruction in the present invention;

[0048] Figure 5 It is a detailed embodiment flow chart of the process of reconstructing and assembling vector data after deconstruction by the client in the present invention;

[0049] Figure 6 A structural block diagram of a vector data deconstruction and adaptive transmission system of the present invention;

[0050] Figure 7 The present invention is a flowchart of a vector data deconstruction and adaptive transmission system. DETAILED DESCRIPTION

[0051] The method and system for large-scale vector data deconstruction and adaptive transmission provided by the present invention will be further described below in conjunction with the accompanying drawings and specific implementation examples.

[0052] In the field of geoscience, vector data of different storage formats are all represented as a collection of vector elements in data structure. Therefore, the method for vector data deconstruction and adaptive transmission disclosed in the present invention uses vector elements as processing units and includes three sub-processes. Process 1: the process of vector data deconstruction on the server side, process 2: the process of storing vector data after deconstruction, process 3: the process of adaptive transmission on demand after vector data deconstruction, and process 4: the process of transmitting the deconstructed vector data to the client for reconstruction and assembly.

[0053] The server-side vector data deconstruction process only transmits the vector elements required by the client and the geometric fragments of the given spatial range in these vector elements according to different spatial and element requirements. Therefore, it is necessary to first deconstruct the vector data according to its components, and then further deconstruct the deconstructed vector elements according to the grid at the spatial level. Figure 1 The detailed flowchart of the server-side vector data deconstruction process is listed, and the specific steps are as follows:

[0054] Step S101: First, metadata and a set of all vector elements are deconstructed from vector data. The metadata of the vector data is a description of the common characteristics of the data entity, including: geometry type, spatial reference, attribute field, etc.; the set of vector elements is a set of elements with the same geometry type, such as a point element set, a line element set, and a surface element set.

[0055] Step S102: further deconstructing attribute metadata components and spatial metadata components from the metadata of the vector data. The attribute metadata component includes attribute name, data type, measurement unit and optional text description; the spatial metadata component includes geometric type information and spatial reference information. Among them, the geometric type information includes six types: point, line, surface, composite point, composite line and composite surface; the spatial reference information includes two coordinate systems: geographic coordinates and projection coordinates used by the vector data.

[0056] Step S103: Further deconstruct each vector element in the vector element set into a spatial coordinate component and an attribute value component. The spatial coordinate component is an array consisting of a set of spatial coordinates. The array structure and dimensions are described in the following table. The attribute value component is a set of attribute values ​​defined by attribute metadata.

[0057]

[0058]

[0059] Step S104: Select or define a grid division rule covering the entire world, wherein the division rule includes the definition of grid spatial range, spatial scale and grid coordinates.

[0060] Step S105: further deconstruct each vector element into one or more spatial coordinate fragment components according to the spatial range of the covered grid to form a set of spatial coordinate fragments. The spatial coordinate fragment component is an array composed of one or more points, and the array of spatial coordinate fragments is a subset of the original spatial coordinate array. The specific implementation method is as follows:

[0061] Traverse the axis of the spatial coordinate array and calculate the grid where each coordinate is located. If the grid where the coordinate is located is the same as the grid where the previous spatial coordinate is located, the current coordinate is placed in the same spatial coordinate fragment as the previous spatial coordinate. Otherwise, the current spatial coordinate is the first element of the new spatial coordinate fragment array.

[0062] Step S106: Associating the spatial coordinate fragment of each vector element with the grid, and establishing a grid coordinate index of the vector element. The grid coordinate index is an index formed by arranging the grid coordinates in the order of the spatial coordinates. The grid coordinate index has the same array structure and dimension as the original spatial coordinate array, so that the client can directly reconstruct the array structure and dimension of the original spatial coordinates based on the array structure and dimension of the grid coordinate index.

[0063] The process of storing vector data after deconstruction is stored in layers by components and space on the server side. Figure 2 The detailed flowchart of the embodiment of storing the vector data after deconstruction on the server side is listed, and the specific steps are as follows:

[0064] Step S201: Using the unique identifier of the vector data as a key, the spatial metadata component and the attribute metadata component deconstructed from the vector data are stored;

[0065] Step S202: storing the vector elements using the grid coordinates and scale as keys and the unique identifier of the vector element as a value;

[0066] Step S203: using the unique identifier of the vector element as a key and the attribute value component as a value, storing the attribute value component deconstructed from the vector element;

[0067] Step S204: using the unique identifier of the vector element and the grid scale as keys, the vector element is indexed and stored in the grid coordinates according to the grid coordinates, geometric object identifiers and sub-object identifiers after grid deconstruction as values;

[0068] Step S205: using the vector element unique identifier, grid scale, grid coordinates, geometric object identifier and geometric sub-object identifier as keys and the spatial coordinate fragment identifier as values, the spatial coordinate fragment index after grid deconstruction is stored.

[0069] Step S206: Using the spatial coordinate segment identifier as a key, the vector element is stored according to the spatial coordinate segment components after grid deconstruction.

[0070] The process of adaptive transmission after vector data deconstruction is the process of dynamically calculating and transmitting the components actually needed after deconstruction according to the client's spatial range and scale. Figure 3 The detailed flowchart of the embodiment of the adaptive transmission process after vector data deconstruction is listed, and the specific steps are as follows:

[0071] Step S301: The client converts the spatial range and scale of the requested data into grid coordinates and scales, and issues a request to transmit the vector data of the specified grid range; the server determines the set of vector elements to be transmitted based on the grid coordinates and scales, and returns the spatial metadata component, attribute metadata component and unique identification information of the vector element. The unique identification information of the vector element is used to further transmit the request parameters of other vector data components.

[0072] Step S302: The client sends a transmission request for transmitting the attribute value component and the grid coordinate index according to the unique identifier of the vector element after being transmitted back; the server retrieves and transmits the attribute value component according to the unique identifier of the vector element, and retrieves and transmits the grid coordinate index of the vector element at the same time. The grid coordinate index structure is as follows: Figure 4 shown. Figure 4 The vector element unique identifier, geometric object identifier and geometric sub-object identifier shown in the figure are associated with the vector data components deconstructed step by step according to the vector element, geometric object and sub-object, and are used for the reconstruction of the vector data on the client.

[0073] Step S303: The client parses the grid scale, grid coordinates, vector element unique identifier, geometric object identifier and geometric sub-object identifier according to the returned grid coordinate index. The five pieces of information are sent to the server as parameters for the request to transmit the spatial coordinate segment component, and are used to further retrieve and transmit the information of the spatial coordinate segment; the server retrieves the corresponding spatial coordinate segment component according to the received request parameters and transmits it back.

[0074] The deconstructed vector data is transmitted to the client and the reconstruction assembly process is responsible for reconstructing the received spatial coordinate fragment components, attribute value components and metadata components into the vector data required by the client. Figure 5 The detailed flowchart of the embodiment of the process of reconstructing and assembling the vector data after deconstruction is listed, and the specific steps are as follows:

[0075] Step S401: splicing the spatial coordinate segment components transmitted back to the client according to the grid coordinate index to form the spatial coordinate components required by the client.

[0076] Step S402: Assembling a spatial component of vector data based on the spatial metadata component and the spatial coordinate component.

[0077] Step S403: Assembling attribute components of vector data based on the attribute metadata components and the attribute value components.

[0078] refer to Figure 6 The present invention shows a vector data deconstruction and adaptive transmission system. The system consists of a server subsystem and a client subsystem.

[0079] The server terminal system 501 includes a deconstruction module 5011 , a storage module 5012 , a retrieval module 5013 and a transmission module 5014 .

[0080] The deconstruction module 5011 is mainly used to deconstruct common vector data file formats such as ESRI ShapeFile, GeoJSON, KML, etc., and separate the spatial metadata component, attribute metadata component, spatial coordinate component, and attribute value component. Then, the spatial coordinate component is further decomposed into a series of spatial coordinate fragments based on the grid.

[0081] The storage module 5012 is mainly used to store the deconstructed vector data components on the server side, so as to support on-demand retrieval and transmission services of the deconstructed vector data.

[0082] The retrieval module 5013 is mainly used to retrieve vector data components within a specified grid range from the deconstructed vector data storage. The retrieval module includes two sub-retrieval modules: component retrieval and grid retrieval.

[0083] The transmission module 5014 is mainly used to monitor the client request and make a transmission response to the deconstructed vector data. The transmission module has a daemon process that monitors the client's spatial metadata, attribute metadata, attribute value, grid coordinate index and spatial coordinate fragment transmission requests.

[0084] The client subsystem 502 includes a data request module 5021 , a data receiving module 5022 , a data reconstruction module 5023 , and a data distribution and visualization module 5024 .

[0085] The data request module 5021 is responsible for sending a vector data component request to the server. The request is divided into four sub-requests according to the vector data component: metadata component request, attribute value component request, grid coordinate index request, and spatial coordinate fragment component.

[0086] The data receiving module 5022 is responsible for receiving and caching the metadata components, attribute value components, grid coordinate index and spatial coordinate fragment components returned by the server. The cached vector data components are used for subsequent data reconstruction and avoid repeated transmission of vector data components.

[0087] The data reconstruction module 5023 is responsible for retrieving the deconstructed vector data components from the client cache and reconstructing them according to the inverse process of vector data deconstruction. When reconstructing vector data, the client first initializes the spatial coordinate array according to the structure and dimension of the grid coordinate index; then establishes the splicing order of the spatial coordinate fragment components based on the grid coordinate index and the spatial coordinate fragment index, thereby further retrieving and completing the splicing of the spatial coordinate components from the cache; finally, the spatial metadata component, the spatial coordinate component, the attribute metadata component and the attribute value component are integrated to form the vector data required by the client.

[0088] The data distribution and visualization module 5024 is responsible for publishing the stitched and reconstructed vector data as data files in common vector formats such as ESR ShareFile, GeoJSON, KML, etc. On the other hand, the reconstructed vector data can be rendered in real time based on a vector map rendering engine.

[0089] refer to Figure 7 , the present invention shows a system flow chart of vector data deconstruction and adaptive transmission, the process of which is:

[0090] Step S601, deconstructing the original vector data file into vector element components and metadata components at the server side, further deconstructing the vector element components by grid, and separating out the spatial coordinate segment components;

[0091] Step S602, storing the deconstructed vector data components in a key-value manner and hierarchical structure;

[0092] Step S603, when the client needs vector data of a specific range or element, the client first searches for metadata components and unique identifiers of vector elements in the client cache, and if the metadata components and unique identifiers of vector elements are not found, first sends a request for the metadata components and unique identifiers of vector elements to the server;

[0093] Step S604, the server retrieves the metadata component and the vector element unique identifier according to the parameters of the metadata component and the vector element unique identifier request from the client, and transmits a response;

[0094] Step S605: After receiving the metadata component and the vector element unique identifier, the client caches them, and then retrieves the attribute value component and grid coordinate index in the cache according to the vector element unique identifier. If the attribute value component and grid coordinate index are not retrieved, the client sends a request to transfer the attribute value component and grid coordinate index using the vector element unique identifier as a request parameter;

[0095] Step S606, the server retrieves the attribute value component and the grid coordinate index according to the vector element unique identification request parameter and transmits a response;

[0096] Step S607, the client caches the grid coordinate index after receiving it, and then retrieves the spatial coordinate fragment in the cache according to the grid coordinate index. If no spatial coordinate fragment component is retrieved, the client sends a spatial coordinate fragment transmission request using the grid coordinate as a request parameter.

[0097] Step S608, the server retrieves the spatial coordinate fragment according to the grid coordinate index and transmits a response;

[0098] Step S609, the client caches the received spatial coordinate segment components, and repeats this process until all spatial coordinate segment components of a vector element are transmitted and cached to the client;

[0099] Step S610: the client initializes the spatial coordinate array according to the structure and dimension of the grid coordinate index, and establishes the splicing order of the spatial coordinate segments based on the grid coordinate index and the spatial coordinate segment index, thereby completing the splicing of the spatial coordinate segments.

[0100] Step S611: based on the spliced ​​spatial coordinate components, further integrate the spatial metadata components, the attribute value components and the attribute metadata components to reconstruct the vector data required by the client.

[0101] Step S612, rendering the reconstructed vector data on the browser side and publishing it as a commonly used vector format data file such as ESRI ShapeFile, GeoJSON, KML, etc.

[0102] Although the present invention has been disclosed as above in terms of preferred embodiments, it is not intended to limit the present invention. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for large-scale vector data deconstruction and adaptive transmission, characterized in that: It includes four sub-processes: A process of vector data deconstruction on the server side; A process of storing vector data after deconstruction; A process of adaptively transmitting deconstructed vector data on demand; A process of transmitting the deconstructed vector data to the client for reconstruction and assembly; The process of deconstructing vector data on the server side further includes: A step of deconstructing vector data into components, for initially deconstructing the original vector data; A step of deconstructing vector data according to a grid, which is used to perform a secondary deconstruction on the vector data after the initial deconstruction based on the grid division; The step of deconstructing the vector data by components further comprises: A sub-step of spatial component deconstruction, for deconstructing two components, namely, spatial metadata and spatial coordinates, from vector data; A sub-step of attribute component deconstruction, for deconstructing two components, attribute metadata and attribute value, from the vector data; The step of spatially deconstructing the vector data further comprises: a sub-step of vector data space division, for further dividing the spatial range covered by the vector data into a set of grids, wherein the grid division is seamless and non-overlapping, and the spatial range of any grid can be uniquely determined by two characteristic values, grid coordinates and grid scale; a sub-step of deconstructing the vector data according to spatial division, for further deconstructing the spatial coordinate components obtained by the initial deconstruction into spatial coordinate segment components according to the grids obtained by spatial division; A sub-step of establishing an index after deconstructing the vector data according to the spatial division, for quickly retrieving the spatial coordinate fragment components according to the grid after the spatial division, wherein the index includes: a grid coordinate index and a spatial coordinate fragment index; The process of transmitting the deconstructed vector data to the client for reconstruction and assembly further includes: a spatial component reconstruction sub-step, for reconstructing the spatial coordinate fragment components deconstructed into different grids into the same spatial coordinate components as the original vector data, and further combining the spatial metadata components to form the spatial components of the vector data; A vector data assembly sub-step is used to merge the attribute metadata component and the attribute value component transmitted to the client to form an attribute component, and assemble it with the reconstructed spatial component to form vector data corresponding to the original vector data structure.

2. The method for large-scale vector data deconstruction and adaptive transmission according to claim 1, characterized in that: The process of storing the vector data after deconstruction further includes: A storage step according to the component level, for storing the attribute metadata component, the attribute value component, the spatial metadata component, and the spatial coordinate component in a key-value manner; A storage step according to the spatial hierarchy is used to store grid coordinate indexes, spatial coordinate segment indexes and spatial coordinate segment components in a key-value manner.

3. The method for large-scale vector data deconstruction and adaptive transmission according to claim 1, characterized in that: The process of on-demand adaptive transmission of the deconstructed vector data further includes: a spatial component transmission step, for transmitting only the spatial metadata component and the spatial coordinate component of the vector data within the spatial range according to the spatial range of the client; An attribute component transmission sub-step is used to transmit only the attribute metadata component and the attribute value component of the vector data within the spatial range according to the spatial range of the client.

4. A system for implementing the method described in any one of claims 1 to 3 to ensure the implementation of the method in practical applications, characterized in that: include: A server subsystem, used to realize the deconstruction and storage of vector data, and to listen to the request from the client and respond to the retrieval and transmission of the deconstructed vector data; A client subsystem is used to send vector data requests to the server, receive the deconstructed vector data sent back by the server, and perform caching and data reconstruction.

5. The system according to claim 4, characterized in that The server terminal system further comprises: A deconstruction module, used to decompose the commonly used vector data file format and separate the spatial metadata component, the spatial coordinate fragment component, the attribute metadata component, and the attribute value component; A storage module, used for storing the deconstructed vector data on the server side, so as to support on-demand retrieval and network transmission services of the deconstructed vector data; a retrieval module, used for retrieving spatial metadata components, spatial coordinate fragment components, attribute metadata components, and attribute value components within a specified grid space range from the deconstructed vector data storage; A transmission module is used to monitor the request from the client and make a transmission response to the deconstructed vector data.

6. The system according to claim 4, characterized in that The client subsystem further comprises: A data request module, used to send a vector data request to the server, wherein the data request is divided into four sub-requests according to the vector data component: a metadata component request, an attribute value component request, a grid coordinate index request, and a spatial coordinate segment component request; A data receiving module, used for receiving the deconstructed vector data components sent back by the server and caching the deconstructed vector data components on the client; a data reconstruction module, used for retrieving the deconstructed vector data components from the client cache and reconstructing them according to the inverse process of vector data deconstruction; A data distribution and visualization module is used to publish the reconstructed vector data as data files in common vector formats such as ESRI ShapeFile, GeoJSON, and KML, and can perform browser-based visualization of the reconstructed vector data.

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