CN-121070899-B - Multi-source heterogeneous space-time data fusion modeling method and system

CN121070899BCN 121070899 BCN121070899 BCN 121070899BCN-121070899-B

Abstract

The application relates to a multi-source heterogeneous space-time data fusion modeling method and system, which comprises the steps of creating a root directory on a computer system as a physical address of a space data model, creating subdirectories corresponding to storage object types under the structure of the root directory as the physical address of the storage object types, wherein the storage object types comprise vector data, two-dimensional raster data and three-dimensional model data, adding related data of the storage object types in a core metadata system table, creating a database file corresponding to the storage object types under each subdirectory, initializing, generating a dedicated metadata table corresponding to the storage object types in the database file, acquiring two-dimensional three-dimensional joint data of a live-action three-dimensional scene as data to be stored, calling a corresponding data conversion tool to convert the data to be stored based on the type of the data to be stored, storing the data to the corresponding database file in a corresponding storage mode, and associating the data with the dedicated metadata table in the database file.

Inventors

WU HAO
Ma Xieqiang
CHEN JIONGBIN
Hou dongyang
YU ZHONGHAI
ZHANG JUN
WANG LU

Assignees

国家基础地理信息中心

Dates

Publication Date: 20260508
Application Date: 20250819

Claims (8)

1. The multi-source heterogeneous space-time data fusion modeling method is characterized by comprising the following steps of: Creating a root directory on a computer system as a physical address for a spatial data model; creating a core metadata system table in the root directory, and performing global management based on a database file; creating subdirectories corresponding to all storage object types under the structure of the root directory, wherein the storage object types comprise vector data, two-dimensional raster data and three-dimensional model data and are mutually independent; adding related data of each storage object type in the core metadata system table; creating a database file corresponding to the storage object type under each sub-directory, initializing, and generating a dedicated metadata table corresponding to the storage object type in the database file; Acquiring two-dimensional combined data of a live-action three-dimensional scene as data to be stored, calling a corresponding data conversion tool to convert the data to be stored based on the type of the data to be stored, storing the data to be stored under a corresponding database file in a corresponding storage mode, and associating the data with an exclusive metadata table in the database file; The storage mode corresponding to the vector data is Feature storage, the storage mode corresponding to the two-dimensional Raster data is Raster storage, and the storage mode corresponding to the three-dimensional model data is Scene storage; The database file is used for managing stored data and relations among the data; wherein different storage object types have different data storage rules; The data storage rule of the vector data includes: Storing all data through a Feature database file; the data storage rule of the two-dimensional raster data includes: storing the exclusive metadata table through a Raster database file; Creating parallel subdirectories of the Raster database file to store Raster data files or tile slice files; the data storage rule of the three-dimensional model data includes: storing the exclusive metadata table through a Scene database file; creating parallel subdirectories of the Scene database file to store the three-dimensional model file, the texture/texture file and other dependent resources, and maintaining the original directory structure of the three-dimensional model file to maintain the dependent relationship among the resources.
2. The method according to claim 1, wherein the method further comprises: Receiving a data access request, positioning target storage data according to the data access request, and obtaining the type, the physical address and the exclusive metadata table of the target storage data; and calling a corresponding driver according to the type of the target storage data, and accessing the target storage data according to the physical address of the target storage data and the exclusive metadata table.
3. The method of claim 1, wherein the core metadata system table comprises a storage definition table, a storage type definition table, a data driven table, a spatial reference system table, and a server configuration information table; The storage definition table, the storage type definition table, the data driving table, the space reference system table and the server configuration information table all comprise a plurality of fixed fields and a plurality of extensible fields; The storage definition table is used as a unified registration center of the space data model, is in an empty state initially, and is dynamically inserted into a record when a storage object is newly built, so that synchronization of storage creation and metadata registration is realized; The storage type definition table supports integration and management of novel storage types through an expansion mechanism; The data driving table provides differentiated data analysis, format conversion and service access capacity for different storage types through a dynamic registration mechanism; The space reference system table realizes fusion and cross-platform analysis of two-dimensional data and three-dimensional data under a unified space standard through multi-format compatible design; The server configuration information table supports dynamic loading and driver level differentiated configuration of service parameters according to needs through a key-value storage and driver binding mechanism.
4. The method of claim 1, wherein metadata table design rules for different storage modes are different.
5. The method of claim 4, wherein the Feature stored metadata table design rules comprise: Constructing a vector data set table as a logic management unit of vector data, and configuring a logic level of the vector data among storage, data sets and layers; Constructing a vector data set type table as a core registry of vector data, performing authority binding, and configuring a JSON dynamic expansion mechanism; constructing a vector data type table as a standard library of vector data, and realizing unified registration and standardized management of vector data of a basic type and a custom type through a JSON dynamic definition mechanism; constructing a vector layer table as a layer registration center of vector data, and carrying out layer metadata management, spatial index and version tracking of newly-put vector data through a dynamic registration mechanism; constructing a vector data list as a core metadata list of a space data model to bear standardized definition and dynamic management and control functions of a vector data layer attribute structure, wherein the vector data list realizes automatic registration, value domain consistency and business logic integration of a new warehouse-in vector data list structure through field-level atomization control, constraint linkage and semantic mapping; constructing a vector data space list as a multidimensional geometrical expression center of a space data model, wherein the vector data space list is configured with a same vector layer multi-geometrical column coexistence mechanism, a dynamic coordinate system adaptation and a mixed index strategy; Constructing a vector data space range statistical table as a dynamic range index engine of a space data model, wherein the vector data space range statistical table is configured with an automatic range calculation and dynamic update mechanism; the metadata table design rules stored by the Raster include: Constructing a raster data set table as a logic management center of two-dimensional raster data, and realizing unified registration and space-time organization of the raster data through path rules and multilevel type codes; Constructing a grid data set type table as a standard definition library of a two-dimensional grid data set; Constructing a raster data type table as a basic type library of a two-dimensional raster data model, wherein the raster data type table is configured with a JSON dynamic definition mechanism and a strong type association mechanism; The grid data set layer table is constructed as a core table of two-dimensional grid data, and uniform layer registration, standardized service release and metadata management from an original satellite image to a real-time grid product are realized through strong binding of a physical path and a space reference, service path decoupling and dynamic metadata expansion; The grid layer expansion information table is constructed to serve as a two-dimensional grid data expansion information record table, and metadata support is provided for remote sensing image analysis and digital topography application through pyramid information, accurate space range double storage and scientific statistics pre-calculation; The metadata table design rules stored by Scene include: Constructing a three-dimensional model data set table as a logic management unit of the three-dimensional scene; Constructing a three-dimensional model data set type table as a registration center of the three-dimensional model data set type; Constructing a three-dimensional model data type table to define a three-dimensional basic type system; Constructing a three-dimensional model layer table as a layer level registration center of the three-dimensional model data, and configuring a dynamic registration mechanism to realize layer level metadata management, spatial index and version tracking of the newly-put three-dimensional model data; constructing a three-dimensional model table to store a three-dimensional model of the assembled grid material and binary content thereof; Constructing a three-dimensional model material table to store three-dimensional model material data; Constructing a texture table of the three-dimensional model to store texture map contents related to materials; And constructing a three-dimensional model grid table to store three-dimensional model grid data.
6. The method of claim 5, wherein storing vector data under a corresponding database file via Feature storage comprises: Creating or associating a dataset record in the vector dataset table as first target data; Creating a layer record for the first target data in a vector layer table, storing the first target data in the vector layer table, and associating the data set ID to which the first target data belongs; Filling metadata of the layer record of the target data in a vector data list, a vector data space list and a vector data space attribute list, and associating a layer ID of the first target data in the vector layer list; Storing the two-dimensional Raster data under a corresponding database file through a Raster storage, wherein the method comprises the following steps: copying/moving the Raster file to the parallel subdirectory of the database file of the register, or migrating the complete directory structure of the slice file set to the parallel subdirectory of the database file of the register; Creating or associating a dataset record in the raster dataset table as second target data; creating a layer record for the second target data in the raster data set layer table, storing the second target data in the raster data set layer table, and associating the data set ID to which the second target data belongs; Writing parameters of the second target data in a grid layer expansion information table, and associating layer IDs of the second target data in a grid data set layer table; storing the three-dimensional model data under a corresponding database file through the Scene storage, wherein the three-dimensional model data comprises the following steps: Copying/moving the three-dimensional model resource catalog of the three-dimensional model data to a parallel subdirectory of a Scene database file, and mapping and maintaining an original file structure and a resource dependency relationship of the three-dimensional model data through a metadata table; creating or associating a dataset record in the three-dimensional scene dataset table as third target data; creating a layer record for the third target data in the three-dimensional model layer table, storing the third target data in the three-dimensional model layer table, and associating the data set ID to which the third target data belongs; adding the three-dimensional model of the third target data into a three-dimensional model table, creating a record for each model file under the data set catalog, and associating the three-dimensional layer ID to which the record belongs; adding the material information of the three-dimensional model into a three-dimensional model material table, and associating the model ID of the third target data in the three-dimensional model table; adding texture information of the three-dimensional model into a texture table of the three-dimensional model, and associating the texture ID of the third target data in a texture table of the three-dimensional model; Adding the grid information of the three-dimensional model into a three-dimensional model grid table, and associating the model ID of the third target data in the three-dimensional model table; if the binary model file is embedded in the texture, the offset in the model binary file is recorded in the three-dimensional model table.
7. The method of claim 2, wherein invoking the corresponding driver based on the type of the target storage data, accessing the target storage data based on the physical address of the target storage data and the proprietary metadata table, comprises: if the target storage data is vector data, reading a Feature database file, and positioning the target storage data by using a vector data set table and a vector layer table; if the target storage data is two-dimensional Raster data, reading a register database file, and positioning the target storage data through a Raster data set table and a Raster data set layer table; And if the target storage data is three-dimensional model data, reading a Scene database file, and positioning the target storage data through a three-dimensional model data set table and a three-dimensional model layer table.
8. A multi-source heterogeneous spatiotemporal data fusion modeling system, comprising: a processor and a memory; The processor is connected with the memory through a communication bus: The processor is used for calling and executing the program stored in the memory; the memory is used for storing a program, and the program is at least used for executing a multi-source heterogeneous spatiotemporal data fusion modeling method of any of claims 1-7.

Description

Multi-source heterogeneous space-time data fusion modeling method and system Technical Field The application relates to the technical field of data fusion, in particular to a multi-source heterogeneous space-time data fusion modeling method and system. Background Along with the rapid development of smart city and digital twin technology, multi-source heterogeneous space-time data presents explosive growth, and multi-mode data sources such as vector data, two-dimensional raster data, three-dimensional model data and the like are covered. The existing space-time data model has obvious bottleneck in cross-dimension expression and heterogeneous data fusion, wherein two-dimensional data mainly comprise planar topology, a three-dimensional model emphasizes the characteristics of a solid geometry structure, and the two have obvious differences in space-time reference, semantic expression, precision level and the like, so that the collaborative analysis capability of the fields of natural resource monitoring, urban emergency management and the like is severely restricted. The core problem of the existing space-time data model is embodied in the staticization of a dimension splitting and fusing mechanism of a storage architecture. The current mainstream storage model is designed around a single dimension, and has limited cross-mode coordination capability. Taking a two-dimensional model as an example, although standards such as OGC GeoPackage and ESRI SHAPEFILE support vectors and raster data, it is difficult to directly express three-dimensional entities, and three-dimensional grids or point clouds often need to be converted into raster slices or external expansion, so that the data integrity is damaged. In contrast, three-dimensional models such as SuperMap S3. 3M, cesium 3D Tiles optimize rendering efficiency, but lack a spatial analysis interface (e.g., S3M cannot embed buffer calculations), resulting in visualization and computation splitting. BIM-IFC has detailed semantic attributes, but lacks geographic coordinate alignment capability, and the integration of GIS data requires manual geometric registration and attribute registration, so that the integration cost is high. At the data fusion level, there is significant mismatch between the multi-level semantic structure of citysml and the oblique photography mesh model, especially in terms of lightweight expression and real-time rendering, which is not easily compatible, and usually requires manual simplification of the model. Indoor space models such as IndoorGML require repeated conversion of the coordinate system due to the lack of dynamic binding to the geographic coordinate system, resulting in unified analysis across floors or with outdoor space. In addition, although common building design data (such as IFC and CAD) are semantically complete, the common building design data are difficult to directly embed into a GIS platform, and the fusion analysis needs to manually align structural attributes and geographic references. In the whole, the current data model cannot support unified analysis and reasoning of multidimensional space-time data, and the fusion efficiency is low. Disclosure of Invention The application provides a multi-source heterogeneous space-time data fusion modeling method and system, which at least solve the problems that a data model in the related technology cannot support unified analysis and reasoning of multi-dimensional space-time data and the fusion efficiency is low to a certain extent. The scheme of the application is as follows: According to a first aspect of an embodiment of the present application, there is provided a multi-source heterogeneous spatiotemporal data fusion modeling method, including: Creating a root directory on a computer system as a physical address for a spatial data model; creating a core metadata system table in the root directory, and performing global management based on a database file; creating subdirectories corresponding to all storage object types under the structure of the root directory, wherein the storage object types comprise vector data, two-dimensional raster data and three-dimensional model data and are mutually independent; adding related data of each storage object type in the core metadata system table; creating a database file corresponding to the storage object type under each sub-directory, initializing, and generating a dedicated metadata table corresponding to the storage object type in the database file; Acquiring two-dimensional combined data of a live-action three-dimensional scene as data to be stored, calling a corresponding data conversion tool to convert the data to be stored based on the type of the data to be stored, storing the data to be stored under a corresponding database file in a corresponding storage mode, and associating the data with an exclusive metadata table in the database file; the storage mode corresponding to the vector data is Feature storage, the storage mode