A method and system for describing the spatial position of multi-granularity spatiotemporal objects

Abstract

The present invention provides a method and system for describing the spatial position of a multi-granularity spatiotemporal object, and relates to the technical field of spatial information research. The concept of the method is to define the description of the spatial position of a multi-granularity spatiotemporal object as a description of the positioning information, spatial distribution and change characteristics of the spatiotemporal object; based on this, the process of the method includes: analyzing the main features of the spatial position of the multi-granularity spatiotemporal object, classifying the spatial position of the multi-granularity spatiotemporal object, and constructing a data model of the spatial position of the multi-granularity spatiotemporal object based on the main features and the categories of the spatial position obtained by the analysis. The present invention can meet the application requirements of multi-granularity spatiotemporal objects that natively support multi-source, dynamic, multi-modal and real-time spatial positions at the data model level.

Description

Technical Field

[0001] The present invention relates to the field of spatial information research technology, and in particular to a method and system for describing the spatial position of multi-granularity spatiotemporal objects. Background Art

[0002] As the foundation of spatial information research, spatial location plays a decisive role in the positioning of geographic entities and the expression of relationships. In the field of geographic information, spatial location is the key difference between geographic information systems and traditional information management systems, and is also an important part of GIS collection, processing, management, analysis and expression. Research on basic concepts, data models and modeling methods of spatial location is of great significance for the spatiotemporal positioning, neighborhood statistics, overlay analysis, pattern discovery and other aspects of geographic entities based on ubiquitous location characteristics.

[0003] The full-space information system starts from the perspective of GIS spatial thinking, expands the spatial dimension, information content and system functions of GIS, and builds an omnipresent GIS world. In order to adapt to the new opportunities and challenges faced by the development of GIS and realize the concept of ubiquitous GIS, the full-space information system changes the data organization mode of horizontal block and vertical layer in traditional GIS, directly abstracts and simplifies the objects in the real world, and describes them as multi-granular spatiotemporal objects in the digital world, thus forming the basic organizational unit of the full-space information system. As a data complex in the digital world, multi-granular spatiotemporal objects need to be described from eight aspects: spatiotemporal reference, spatial position, spatial form, association, composition structure, cognitive ability, behavioral ability and attribute characteristics (Hua Yixin, Zhou Chenghu. Multi-granular spatiotemporal object data model description framework for full-space information system [J]. Journal of Geo-Information Science, 2017, 19(9): 1142-1149.). Among them, spatial position describes the location information of things and phenomena, which is the essential feature of multi-granular spatiotemporal objects and the basis for spatial positioning, spatial analysis and comprehensive application of other feature information.

[0004] Traditional GIS uses vector, raster and surface models to express the spatial location of discrete or continuous geographic phenomena, and has achieved fruitful results. However, with the development of computer and sensor technology, the application field of GIS has gradually expanded, and traditional data models are increasingly difficult to adapt to the multi-source, dynamic, multi-modal and real-time application requirements of spatial location in complex scenarios. This is mainly manifested in: in terms of spatial location acquisition, it is difficult to meet the access of multi-source location data, such as the inability to effectively adapt and access dynamic data of different types, formats and protocols acquired by sensors in real time (Yang Fei, Hua Yixin, Li Xiang, etc. Urban infrastructure modeling and management based on multi-granularity spatiotemporal object data model [J]. Geo-Information Science); in terms of spatial location management, it is difficult to meet the organization of dynamic location data, such as the storage of temporal changes in the location of geographic entities (Gong Jianya, Li Xiao Long, Wu Huayi. Real-time GIS spatiotemporal data model [J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(03): 226-232+275.); In terms of spatial location fusion, it is unable to support multi-modal processing of location data, such as a building will present vector points, vector surfaces, two-dimensional icons, three-dimensional models and other spatial forms as the cognitive scale changes (Zhu Qing, Fu Xiao. A review of visual analysis methods for multimodal spatiotemporal big data [J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1672-1677.); In spatial location-based analysis applications, it is difficult to simultaneously take into account the temporal characteristics of location data, such as the screening of spatiotemporal companions in epidemiological survey analysis (Chen Yunhai, Jiang Nan, Cao Yibing, Yang Zhenkai, Zhao Xinke. Visual method of analyzing COVID-19 case information using spatio-temporal objects with multi-granularity[J]. Journal of Geographical Sciences, 2022, 31(7).); In terms of spatial location visualization, it is difficult to continuously express and interact with the location change process in real time. For example, although temporal GIS adds a time dimension to the data model, the time dimension is only used as a benchmark for the rigid movement of geographic elements (Cao Yibing, Zhang Jiangshui, Hua Yixin, et al. Design and implementation of a full-space spatiotemporal object visualization tool[J]. Journal of Surveying and Mapping Science and Technology, 2021, 38(02): 173-180). Summary of the invention

[0005] In response to the problems existing in traditional GIS in spatial location acquisition, management, fusion, analysis and visualization, the present invention provides a method and system for describing the spatial location of multi-granularity spatiotemporal objects, which can meet the application requirements of multi-granularity spatiotemporal objects natively supporting multi-source, dynamic, multi-modal and real-time spatial locations at the data model level.

[0006] On the one hand, the present invention provides a method for describing the spatial position of a multi-granularity spatiotemporal object, and defines the description of the spatial position of a multi-granularity spatiotemporal object as a description of the positioning information, spatial distribution and changing characteristics of the spatiotemporal object; the method comprises: analyzing the main features of the spatial position of the multi-granularity spatiotemporal object, classifying the spatial position of the multi-granularity spatiotemporal object, and constructing a data model of the spatial position of the multi-granularity spatiotemporal object based on the main features and the categories of the spatial positions obtained by the analysis.

[0007] Furthermore, the main features specifically include: one or more of multi-source features, dynamic time-varying features, virtual-to-real mapping features, multi-scale features and multi-space references.

[0008] Furthermore, the classification of the spatial positions of multi-granularity spatiotemporal objects specifically includes:

[0009] The spatial positions of multi-granularity spatiotemporal objects are classified based on data state changes, data recording methods and data generation methods.

[0010] Furthermore, according to whether the data state changes, the spatial position is divided into static position and dynamic position; according to different data recording methods, the spatial position is divided into vector form position and point set position; according to different data generation methods, the spatial position is divided into data storage position, real-time access position, function simulation position and periodic motion position.

[0011] Furthermore, a data model of the spatial position of a multi-granularity spatiotemporal object is constructed based on the main features and categories of spatial positions obtained through analysis, specifically including: determining the description content of the spatial position of the multi-granularity spatiotemporal object, formally expressing the target spatial object according to the description content, and constructing a data model of the spatial position of a multi-granularity spatiotemporal object according to a preset modeling process based on the formal expression result.

[0012] Furthermore, the description content includes cognitive scale, location type, spatial reference, spatial posture, location data and location format.

[0013] Furthermore, the target space object is formally expressed according to the description content, specifically:

[0014] Pos(A)={[P]}

[0015] Among them, A represents the target space object, P represents the spatial position of a certain position type, the set of P represents the spatial position of object A, P = {Scale, Type, SRS, Attitude, Data, Format}, Scale = {MinScale, MaxScale} represents the cognitive scale of the spatial position, MinScale and MaxScale represent the minimum cognitive scale and the maximum cognitive scale respectively; Type represents the position type, different position types have different position formats and position data; SRS represents the spatial reference used by the position data; Attitude = {pitch, yaw, roll} represents the spatial attitude of the space-time object, pitch, yaw and roll represent the pitch angle, yaw angle and roll angle respectively; Format represents the position format; Data represents the position data, and its format is determined by Type and Format.

[0016] Furthermore, based on the formal expression results, a data model of the spatial location of multi-granularity spatiotemporal objects is constructed according to the preset modeling process, which specifically includes:

[0017] Constructing different spatial position templates according to different position types; the spatial position templates contain parameters and constraint information of different types of spatial positions;

[0018] Associating the spatial location template with the spatiotemporal object class;

[0019] Instantiate the spatial locations of multi-granular spatiotemporal objects;

[0020] Dynamically model the spatial positions of instantiated multi-granularity spatiotemporal objects.

[0021] Furthermore, associating the spatial position template with the spatiotemporal object class specifically includes:

[0022] According to the different location types of the spatiotemporal object class, a suitable location template is selected and bound to the spatiotemporal object class template to realize the association between the location template and the spatiotemporal object class. The spatiotemporal object class template and the location template together constitute an abstract description of a class of spatiotemporal objects.

[0023] On the other hand, the present invention provides a system for describing the spatial position of a multi-granularity spatiotemporal object, wherein the description of the spatial position of a multi-granularity spatiotemporal object is defined as a description of the location information, spatial distribution and change characteristics of the spatiotemporal object, and the system comprises:

[0024] Feature analysis module, used to analyze the main features of the spatial position of multi-granularity spatiotemporal objects;

[0025] A spatial position classification module is used to classify the spatial positions of multi-granularity spatiotemporal objects;

[0026] The data model building module is used to build a data model of the spatial position of multi-granularity spatiotemporal objects based on the main features and spatial position categories obtained through analysis.

[0027] Beneficial effects of the present invention:

[0028] The description method and system provided by the present invention define the description of the spatial position of a multi-granularity spatiotemporal object as a description of the location information, spatial distribution and change characteristics of the spatiotemporal object. Based on the concept definition, the main characteristics of the spatial position of a multi-granularity spatiotemporal object are first analyzed, and a classification method for different classification standards is proposed, laying a theoretical foundation for the spatial position of a multi-granularity spatiotemporal object; secondly, from the perspective of a data model, a description framework and a formal expression method for the spatial position of a multi-granularity spatiotemporal object are proposed, and a modeling process for the spatial position of a multi-granularity spatiotemporal object is designed, forming a generation method for the spatial position of a multi-granularity spatiotemporal object. methodological foundation; finally, relying on the full-space information system platform, demonstration scenarios were designed for different experimental data to verify the scientificity, effectiveness and universality of the theory and method of the invention, as well as the multi-source characteristics, dynamic time-varying characteristics, virtual-reality mapping characteristics and multi-scale characteristics of the spatial position of multi-granularity spatiotemporal objects; in the full-space information system, the spatial position was given a new connotation and extension, so that the multi-granularity spatiotemporal objects natively support the multi-source, dynamic, multi-modal and real-time application requirements of the spatial position at the data model level, laying the foundation for the subsequent spatial position modeling of multi-granularity spatiotemporal objects in the full-space digital world. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The spatial position of the same spatiotemporal object at different times provided by the embodiment of the present invention;

[0030] Figure 2 A schematic flow chart of a method for describing the spatial position of a multi-granularity spatiotemporal object provided by an embodiment of the present invention;

[0031] Figure 3 A description framework for the spatial position of multi-granularity spatiotemporal objects provided by an embodiment of the present invention;

[0032] Figure 4 A modeling process for the spatial position of multi-granularity spatiotemporal objects provided by an embodiment of the present invention;

[0033] Figure 5 The full-space information system platform software system provided by the embodiment of the present invention;

[0034] Figure 6 The computational access and expression of the spatial position of the satellite spatiotemporal object provided by the embodiment of the present invention;

[0035] Figure 7A multi-scale expression of the spatial position of urban spatiotemporal objects provided by an embodiment of the present invention;

[0036] Figure 8 Real-time access and expression of the spatial location of facility spatiotemporal objects provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] In response to the problems existing in traditional GIS in spatial location acquisition, management, fusion, analysis and visualization, the present invention proposes a method and system for describing the spatial location of multi-granularity spatiotemporal objects, which natively solves the application requirements of multi-source, dynamic, multi-modal and real-time spatial locations in complex scenes.

[0039] The concept of the method for describing the spatial position of a multi-granularity spatiotemporal object provided by the present invention is to provide a basic concept of the spatial position of a multi-granularity spatiotemporal object, that is, the spatial position of a multi-granularity spatiotemporal object refers to the description of the positioning information, spatial distribution and changing characteristics of the spatiotemporal object under a certain spatiotemporal reference framework; and then realize the description of the spatial position of the multi-granularity spatiotemporal object based on this concept.

[0040] Conceptually, the spatial location of any spatiotemporal object is the spatial positioning information described under a specific spatiotemporal reference, which covers the research content of spatial location in traditional GIS. At the same time, the spatial location of multi-granular spatiotemporal objects emphasizes the spatial distribution and change characteristics of the location. Its research scope is more comprehensive and more in line with people's cognitive way of spatial location in the real world.

[0041] The spatial position of multi-granularity spatiotemporal objects describes the spatial distribution of spatiotemporal objects. Spatial distribution indicates the distribution range and distribution state (discrete or continuous) of spatiotemporal objects based on spatial positioning. That is, the spatial distribution of spatiotemporal objects can be described using vector forms such as two-dimensional coordinates and three-dimensional coordinates. For example, for train objects, three-dimensional lines formed by the geometric center of each carriage are used to describe their spatial distribution. The spatial distribution of spatiotemporal objects can also be described using point sets such as flow fields and images, such as the spatial distribution of spatiotemporal objects such as global wind fields and regional plots.

[0042] Positioning information and spatial distribution are descriptions of different angles of spatial position. For example, for an image object, only four position points are needed to realize the spatial positioning of the image object, but the range and state of the image object also need to be supplemented by the spatial distribution description. The spatial distribution of the image object is described by the continuous distribution of all pixel points; for a train object, the point set composed of the geometric center points of each carriage can realize the spatial positioning of the train object, but the spatial position of the train object should also clarify the composition of these discrete points, that is, it is a three-dimensional vector line composed of a point set to describe the distribution range and distribution state of the train object.

[0043] The spatial position of multi-granularity spatiotemporal objects includes the changing characteristics of spatiotemporal objects. The spatial position of the same spatiotemporal object will change over time, that is, the spatial position of the spatiotemporal object is dynamic. For example, in different historical periods, although the spatial position of a city is a vector surface, the spatial position of the vector surface will change. Figure 1 shown.

[0044] In summary, the spatial position of a multi-granularity spatiotemporal object is no longer a description of position data, but a collection of spatial positions of a spatiotemporal object at different change times under a certain spatiotemporal reference. In practical applications, the corresponding spatial position needs to be automatically selected according to the scene time. The same spatiotemporal object can only have a unique spatial position at the same time; however, the same spatiotemporal object in different scenes may have different spatial positions at the same time due to different cognitive scales. For example, in distributed multi-terminal applications, each window sets a different observation scale, and the spatial position of the same spatiotemporal object at the same time may be different.

[0045] When describing the spatial position of a spatiotemporal object, the coordinate value of the origin of its self-reference system in other reference systems such as the parent reference system can be used as the spatial position data. However, sometimes it is not enough to describe the spatial position information with only a three-dimensional coordinate (X, Y, Z). It is also necessary to describe the directional relationship between the self-reference system of the spatiotemporal object and the parent reference system, that is, the posture information of the spatiotemporal object. In addition, for the continuously changing spatial position of a spatiotemporal object, a spatiotemporal trajectory can be used to describe it and associate it with the spatiotemporal object through an object identifier.

[0046] Based on the above basic concepts of the spatial location of multi-granularity spatiotemporal objects, such as Figure 2 As shown, the description method specifically includes the following steps:

[0047] S101: Analyze the main features of the spatial position of multi-granular spatiotemporal objects;

[0048] S102: Classifying the spatial positions of multi-granularity spatiotemporal objects;

[0049] S103: constructing a data model of the spatial position of a multi-granularity spatiotemporal object based on the main features and categories of the spatial position obtained by analysis.

[0050] The description method provided in the embodiment of the present invention first analyzes the main characteristics of the spatial position of multi-granularity spatiotemporal objects, proposes a classification method for different classification standards, and lays a theoretical foundation for the spatial position of multi-granularity spatiotemporal objects; secondly, from the perspective of the data model, a modeling process for the spatial position of multi-granularity spatiotemporal objects is designed, forming a methodological basis for generating the spatial position of multi-granularity spatiotemporal objects, which can meet the multi-granularity spatiotemporal objects at the data model level. Natively support multi-source, dynamic, multi-modal and real-time application requirements of spatial location.

[0051] In one embodiment, the main features of the spatial position of the multi-granularity spatiotemporal object specifically include multi-source features, dynamic time-varying features, virtual-to-real mapping features, multi-scale features and multi-space references.

[0052] (1) Multi-source characteristics. The spatial location of multi-granularity spatiotemporal objects can come from historical data in a database or file system, or from real-time transmission from sensor devices such as GPS or real-time data published by network services. It also includes various forms such as function simulation data and periodic motion data, and has significant multi-source characteristics. Therefore, when expressing spatial location, it is necessary to fully consider the access and access methods of location information from different sources, so as to use a unified data model to abstract the spatial location of spatiotemporal objects.

[0053] (2) Dynamic time-varying characteristics. The spatial position of multi-granular spatiotemporal objects is not static. Over time, their spatial positions will change. According to the different change cycles, they can be divided into long-term (crustal movement), medium-term (urban construction), short-term (weather changes) and real-time (vehicle movement). Therefore, the data model needs to support the expression of discrete or continuous changes in spatial positions.

[0054] (3) Virtual-real mapping features. The spatiotemporal scope of the full-space information system has expanded from the surface space to the macroscopic and microscopic human-machine-object space and virtual space. Multi-granular spatiotemporal objects can not only describe the spatiotemporal entities in the real world, but also the spatiotemporal entities in the virtual world. For example, social accounts, post comments, IP addresses, routing nodes, etc. In the expression of virtual entities, it is often necessary to assign spatial locations to virtual entities based on the mapping relationship between virtual entities and real entities, thereby realizing virtual-real linkage and fusion expression based on spatial locations.

[0055] (4) Multi-scale features. Multi-granularity spatiotemporal objects often have different spatial positions at different cognitive scales. For example, at a small scale, a house is represented by a vector point; however, as the scale changes, the spatial position of the vector surface will be shown at a larger scale. At this time, the expression of spatial position needs to adopt a unified description method to be compatible with this change in position type. At the same time, the multi-scale position data of spatiotemporal objects need to be stored and updated synchronously.

[0056] (5) Multiple spatial datums. In terms of spatial datums, as the scale changes, multi-granularity spatiotemporal objects will present different spatial positions. Different spatial datums can be used to describe the spatial positions of spatiotemporal objects at different scales. This approach can maximize compatibility with existing data. In practical applications, the spatial datum can be quickly transformed according to different needs.

[0057] The scientific classification of the spatial position of multi-granularity spatiotemporal objects helps to clarify the research content and research boundaries of the spatial position of multi-granularity spatiotemporal objects, and helps to establish a data model of the spatial position of multi-granularity spatiotemporal objects. However, the data sources of the spatial position of multi-granularity spatiotemporal objects are complex, the data recording methods are different, and the data generation methods vary greatly. It is difficult to scientifically and effectively divide the spatial position according to a unified classification standard and classification basis in general. Therefore, in one embodiment, the present invention classifies the spatial position of multi-granularity spatiotemporal objects from three aspects: data state change, data recording method, and data generation method according to different classification standards. As shown in Table 1.

[0058] Table 1 Classification system of spatial position

[0059]

[0060] According to whether the position data status changes, the spatial position of multi-granularity spatiotemporal objects can be divided into static position and dynamic position. Static position means that the spatial position of spatiotemporal objects does not change over time, such as measurement control points, mountain peaks and other spatiotemporal objects. Dynamic position means that the spatial position of spatiotemporal objects will change over time, such as the outline of urban objects, the trajectory of vehicle objects, etc. According to the speed of spatial position change, dynamic position can be divided into discrete change dynamic position and continuous change dynamic position.

[0061] According to the different ways of recording position data, the spatial position of multi-granularity spatiotemporal objects can be divided into vector position and point set position. Vector position uses vector data such as points, lines, surfaces, multi-points, multi-lines, and multi-surfaces to represent the spatial position of spatiotemporal objects. Its position information is recorded through the nodes or node sets that constitute the vector data, such as the spatial position of spatiotemporal objects such as plots, roads, and moving vehicles. According to application requirements, vector position can be further subdivided, such as vector point position, vector line position, and so on. Point set position uses the point information contained in the file itself to represent the spatial position of spatiotemporal objects, such as the spatial position of spatiotemporal objects such as DEM, TIN, point cloud, and image.

[0062] According to the different ways of generating position data, the spatial position of multi-granularity spatiotemporal objects can be divided into data storage position, real-time access position, function simulation position, and periodic motion position. Data storage position indicates the spatial position of spatiotemporal objects that have been generated, which is stored in media such as databases, files, and network servers. Real-time access position indicates the spatial position of spatiotemporal objects obtained in real time through dynamic sensor access technology, such as GPS receivers and position simulation software that can continuously obtain real-time position data at a certain time frequency. Function simulation position indicates the spatial position of spatiotemporal objects calculated by model functions based on their own parameters and external conditions, such as missile flight trajectories, drone flight trajectories, etc. Periodic motion position indicates a periodically changing spatial position, which often only needs to store data within one cycle, and then repeats the movement according to time and characteristic parameters, such as the orbit of a satellite.

[0063] In one embodiment, the process of constructing a data model of the spatial position of a multi-granularity spatiotemporal object mainly includes the following three key steps: determining the description content of the spatial position of the multi-granularity spatiotemporal object, formally expressing the target spatial object according to the description content, and constructing a data model of the spatial position of the multi-granularity spatiotemporal object based on the formal expression result according to a preset modeling process.

[0064] How to systematically and normatively abstract and express the spatial position of spatiotemporal objects in a form that can be directly understood by computers is a basic problem in object modeling of the full-space information system. The key to solving the problem lies in how to organically combine the computer problem-solving method with the needs of multi-granularity spatiotemporal object modeling. Spatial position is the essential feature of multi-granularity spatiotemporal objects. Abstracting and formalizing its description content is the premise of spatial positioning of spatiotemporal objects. Formal language provides a formal tool for abstractly expressing things and their connections. The formal expression of spatial position is to formally describe its components using formal language, so as to achieve the purpose of studying the essence of the spatial position of spatiotemporal objects through "form". The formally expressed spatial position can be directly processed and handled by computers through certain calculation models and algorithms.

[0065] S201: Design a framework for describing the spatial location of multi-granular spatiotemporal objects

[0066] To describe the spatial position of multi-granularity spatiotemporal objects, it is necessary to consider the dynamic characteristics, multi-source characteristics, virtual-reality mapping characteristics, multi-scale characteristics and multi-space references of the spatiotemporal objects, as well as the category of the spatial position and other auxiliary information. Therefore, the description of the spatial position of multi-granularity spatiotemporal objects includes: cognitive scale, position type, spatial reference, spatial attitude, position data and position format. Figure 3 shown.

[0067] The cognitive scale describes the scale information of the spatiotemporal objects in the application scenario. The cognitive scale is divided into 22 levels using the Google Maps grading method in multi-granular spatiotemporal objects. Spatiotemporal objects often have different spatial location types in different scale ranges. For example, a certain plot object uses a vector surface position at level 14-22, and a vector point position at level 1-13. In addition, spatiotemporal objects can also use different spatial location types in the same scale range. For example, a certain plot object can use both a vector surface position and a point set position (point cloud, image, etc.) at level 14-22. The type of expression needs to be determined by the user according to application requirements.

[0068] The position type describes what type of position classification the spatial position of a space-time object belongs to, including vector position, point set position, real-time access position, function simulation position, periodic motion position, etc.

[0069] The spatial reference describes the coordinate system used by the spatial position of spatiotemporal objects. It can be a geographic coordinate system, a projected coordinate system, a relative coordinate system, etc. Different coordinate systems correspond to different position formats and position data.

[0070] The spatial attitude describes the attitude information of a space-time object in space, that is, the directional relationship between the self-reference system of the space-time object and the parent reference system. The three Euler angles of yaw, pitch and roll are used to define the change of the attitude of the space-time object. In practical applications, the spatial attitude needs to be described while describing the spatial position. In general, the self-reference system and the parent reference system of the space-time object remain parallel or identical without rotation. The spatial attitude is recorded as (0,0,0).

[0071] The position data describes the positioning data of a specific position type. For vector positions, such as points, lines, surfaces, multi-points, multi-lines, and multi-surfaces, each position data type is described using a different data structure. For real-time access positions, the position data records information such as the sensor's protocol, format, and access address. For function simulation positions, the position data records information such as the address and parameters of the function service. For periodic motion positions, the position data records information such as the address and motion parameters of the position service.

[0072] The location format describes the format information used by the location data, including two-dimensional coordinates (X, Y) or (L, B), three-dimensional coordinates (X, Y, Z) or (L, B, H), three-dimensional coordinates with time information (T, X, Y, Z) or (T, L, B, H), etc.

[0073] S202: Based on the above description framework, the spatial position of the multi-granularity spatiotemporal object is formally expressed;

[0074] The formal expression of the spatial position of multi-granularity spatiotemporal objects, namely spatial position modeling, is to explore an expression model that can cover all position types of spatiotemporal objects as much as possible, which is used to uniformly express spatial positions and lay the foundation for the subsequent logical structure design and physical storage of spatial positions.

[0075] The spatial position of a multi-granularity spatiotemporal object is not simply a temporal description of a certain type of spatial position. There are often different types of spatial positions according to different cognitive scales and actual application requirements. Therefore, the spatial position itself is a set of positions, including the spatial position expressions of spatiotemporal objects in different scale ranges and different application scenarios.

[0076] As an implementable method, the spatial position of a space-time object A is formally expressed as:

[0077] Pos(A)={[P]}

[0078] In the formula, P represents the spatial position of a certain position type, and the set of P represents the spatial position of object A. According to the description framework of the spatial position of multi-granular spatiotemporal objects, P = {Scale, Type, SRS, Attitude, Data, Format}, Scale = {MinScale, MaxScale} represents the cognitive scale of the spatial position, and MinScale and MaxScale together constitute the scale range applicable to the spatial position; Type represents the type of spatial position, corresponding to different categories in the position classification, and provides selection in the form of enumeration. Different position types have different position formats and position data; SRS represents the spatial reference used by the position; Attitude = {pitch, yaw, roll} represents the spatial attitude of the spatiotemporal object, which is composed of pitch angle pitch, yaw angle yaw and roll angle roll; Format represents the format of the spatial position, which is provided in the form of enumeration; Data represents the position data, and its format is determined by Type and Format. It is the specific data information of the spatial position. The expression form of the position data is shown in Table 2.

[0079] Table 2 Expression of spatial data

[0080]

[0081] S203: Designing a modeling process for the spatial location of multi-granular spatiotemporal objects

[0082] The modeling process of the spatial location of multi-granularity spatiotemporal objects is as follows: Figure 4 As shown, it mainly includes four steps: constructing spatial position template, associating position template with spatiotemporal object class, instantiating spatial position and dynamic position modeling, and finally realizing the addition of spatial position data of spatiotemporal object.

[0083] S2031: spatial position template construction;

[0084] Different location templates are designed according to different types of spatial locations in the real world. The location templates contain parameters and constraint information of different types of spatial locations. By separating the location templates from the location data, the location templates can be made more flexible, reusable and extensible. Location templates are generally aggregated as subcomponents of spatiotemporal object class templates.

[0085] S2032: Associating the location template with the spatiotemporal object class;

[0086] In the design process of the spatiotemporal object class template, each part of the multi-granularity spatiotemporal object octet feature needs to be added separately, including the spatial position. According to the different types of spatial positions of the spatiotemporal object class, a suitable position template is selected and bound to the spatiotemporal object class template to realize the association between the position template and the spatiotemporal object class. The spatiotemporal object class template and the position template together constitute an abstract description of a class of spatiotemporal objects. The same spatiotemporal object class may have spatial positions with different generation methods, cognitive scales, and forms of expression. In this case, multiple position templates will be included in the spatiotemporal object class template.

[0087] S2033: Spatial Position Instantiation

[0088] Based on the spatiotemporal object class template, the spatial position of multi-granular spatiotemporal objects is instantiated through various modeling methods such as human-computer interaction and automatic conversion. This process is actually to fill in the parameters of the position template in the spatiotemporal object class and instantiate multi-granular spatiotemporal objects with various specific position information. In position modeling, the same spatiotemporal object class has the same set of position templates, but when the spatiotemporal object is instantiated, different spatiotemporal objects often have different spatial positions.

[0089] S2034: Dynamic Position Modeling

[0090] The spatial position instantiated by the spatiotemporal object class template is only the position information of the spatiotemporal object at a certain moment. The spatial position of the spatiotemporal entity in the real world will change over time. Therefore, it is necessary to dynamically model the spatial position of multi-granular spatiotemporal objects, including operations such as adding, deleting, and modifying spatial positions. Finally, the position change information of the multi-granular spatiotemporal object throughout its life cycle is constructed to provide a data basis for subsequent dynamic position analysis and expression based on spatiotemporal processes.

[0091] Corresponding to the above-mentioned description method, an embodiment of the present invention also provides a description system for the spatial position of a multi-granularity spatiotemporal object. The concept of this system defines the description of the spatial position of a multi-granularity spatiotemporal object as a description of the positioning information, spatial distribution and changing characteristics of the spatiotemporal object. The system includes: a feature analysis module, a spatial position classification module and a data model construction module.

[0092] Among them, the feature analysis module is used to analyze the main features of the spatial position of multi-granularity spatiotemporal objects; the spatial position classification module is used to classify the spatial position of multi-granularity spatiotemporal objects; and the data model construction module is used to construct a data model of the spatial position of multi-granularity spatiotemporal objects based on the main features and spatial position categories obtained by analysis.

[0093] It should be noted that the multi-granularity spatiotemporal object spatial position description system provided in the embodiment of the present invention is for implementing the above method. Its specific functions can be referred to the above method embodiment and will not be repeated here.

[0094] In order to verify the effectiveness of the method and system of the present invention, the present invention also provides experimental verification data of the spatial position of multi-granularity spatiotemporal objects.

[0095] (I) Experimental environment

[0096] In order to realize the multi-source, dynamic, multi-modal and real-time description, modeling and expression requirements of spatial locations in complex scenes, this paper completes the experiment of related functions based on the full-space information system platform. The full-space information system platform adopts a "cloud + terminal" software system. The "cloud software" mainly realizes the access, storage, management, access, analysis and calculation functions of multi-granularity spatiotemporal objects, and is the core and hub of the full-space information system platform. The "client software" realizes the creation, management, visualization, data exchange and application of multi-granularity spatiotemporal objects through a variety of multi-terminal application systems and multi-granularity spatiotemporal object modeling tools, which is the key to reflecting the capabilities of the full-space information system platform. The platform software system is such as Figure 5 shown.

[0097] (II) Experimental data

[0098] The experimental data are stored in the full-space database using the spatiotemporal object class template design tool and the spatiotemporal object general conversion tool, providing a data basis for the abstraction, description, modeling and expression of the spatial location of multi-granular spatiotemporal objects. According to the different data thematic types, acquisition methods and functional expressions, the original experimental data mainly include the following types, as shown in Table 3.

[0099] Table 3 Experimental data overview

[0100]

[0101]

[0102] 3. Description and expression of the spatial position of multi-granularity spatiotemporal objects

[0103] According to the different types of spatial locations, four demonstration scenarios were designed in the experiment, and different thematic data were used for modeling. The multi-source characteristics, dynamic time-varying characteristics, virtual-reality mapping characteristics and multi-scale characteristics of the spatial location of multi-granularity spatiotemporal objects were verified. The experimental results show that the multi-granularity spatiotemporal object spatial location description framework, formal expression model and modeling process proposed in the present invention are correct and reasonable, and have good versatility.

[0104] 1. Multi-source features of spatial locations of multi-granular spatiotemporal objects

[0105] There are many ways to generate spatial position data of multi-granularity spatiotemporal objects, including data storage location, real-time access location, function simulation location, periodic motion location, etc., with significant multi-source characteristics. In the access and expression of the spatial position of satellite spatiotemporal objects, their position information is not pre-stored in the database or file system, but is calculated in real time based on orbital parameters using a specific orbital model (such as SGP4, Simplified General Perturbations). It is a periodic motion position, such as Figure 6 shown.

[0106] 2. Dynamic time-varying characteristics of the spatial position of multi-granularity spatiotemporal objects

[0107] Traditional GIS can achieve dynamic expression of spatial location through attribute extension plug-in, but in essence, this plug-in method is independent of the data model. Multi-granular spatiotemporal objects in the full spatial information system natively support dynamic expression of spatial location. In the expression of the spatial location of ship and flight spatiotemporal objects, their location information is composed of vector point data at different times, which has typical dynamic time-varying characteristics.

[0108] 3. Multi-scale features of spatial locations of multi-granular spatiotemporal objects

[0109] In the full-space information system, the same spatiotemporal object can have different spatial positions according to different cognitive scales. For example, the spatial position of urban spatiotemporal objects in large scenes is represented by vector points. As the cognitive scale changes, the spatial position of urban spatiotemporal objects in small scenes is represented by vector surfaces or images composed of point sets, which have typical multi-scale characteristics, such as Figure 7 shown.

[0110] 4. Virtual-Real Mapping Features of Multi-Grained Spatiotemporal Object Spatial Positions

[0111] Multi-granularity spatiotemporal objects can realize virtual-real linkage and fusion expression based on spatial position. In the application scenario of facility spatiotemporal objects, the smart car and its carried position sensors are modeled, such as Figure 8 As shown, the small window in the upper right corner is a proportional Chigua Reef sand table built indoors. The main scene is the digital world in the full-space information system. Through the facility access tool, the spatial position of the smart car in the real world will be mapped to the digital world in real time. At the same time, by manipulating the space-time objects of the smart car in the digital world, the movement state of the smart car in the real world (such as moving forward, backward, etc.) can also be controlled, thereby realizing the virtual-real interaction of the scene.

[0112] The present invention describes the location characteristics of multi-granularity spatiotemporal objects from the aspects of the basic concepts, main features and classification methods of the spatial location of multi-granularity spatiotemporal objects, which helps to further understand and recognize the extension and role of spatial location in multi-granularity spatiotemporal objects. On this basis, a description framework and formal expression method of the spatial location of multi-granularity spatiotemporal objects are proposed, a modeling process of the spatial location of multi-granularity spatiotemporal objects is designed, and the basic theory and modeling method of the spatial location of multi-granularity spatiotemporal objects are verified through experimental scenarios, which can provide a basic idea for the location modeling of multi-granularity spatiotemporal objects in the full-space digital world.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for describing the spatial position of a multi-granularity spatiotemporal object, characterized in that: The description of the spatial position of multi-granularity spatiotemporal objects is defined as the description of the spatiotemporal object location information, spatial distribution and its change characteristics; The method comprises: analyzing main features of the spatial positions of multi-granularity spatiotemporal objects, classifying the spatial positions of the multi-granularity spatiotemporal objects, and constructing a data model of the spatial positions of the multi-granularity spatiotemporal objects according to the main features and categories of the spatial positions obtained by the analysis.

2. A method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 1, characterized in that: The main features specifically include: one or more of multi-source features, dynamic time-varying features, virtual-to-real mapping features, multi-scale features and multi-space references.

3. A method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 1, characterized in that: The classification of the spatial positions of multi-granularity spatiotemporal objects specifically includes: The spatial positions of multi-granularity spatiotemporal objects are classified based on data state changes, data recording methods and data generation methods.

4. A method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 3, characterized in that: According to whether the data state changes, the spatial position is divided into static position and dynamic position; according to the different data recording methods, the spatial position is divided into vector position and point set position; according to the different data generation methods, the spatial position is divided into data storage position, real-time access position, function simulation position and periodic motion position.

5. The method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 1, characterized in that: A data model of the spatial position of a multi-granularity spatiotemporal object is constructed based on the main features and spatial position categories obtained by analysis, specifically including: determining the description content of the spatial position of the multi-granularity spatiotemporal object, formally expressing the target spatial object according to the description content, and constructing a data model of the spatial position of a multi-granularity spatiotemporal object according to a preset modeling process based on the formal expression result.

6. A method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 5, characterized in that: The description content includes cognitive scale, location type, spatial reference, spatial posture, location data and location format.

7. A method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 6, characterized in that: The target space object is formally expressed according to the description content, specifically: Pos(A)={[P]} Among them, A represents the target space object, P represents the spatial position of a certain position type, the set of P represents the spatial position of object A, P = {Scale, Type, SRS, Attitude, Data, Format}, Scale = {MinScale, MaxScale} represents the cognitive scale of the spatial position, MinScale and MaxScale represent the minimum cognitive scale and the maximum cognitive scale respectively; Type represents the position type, different position types have different position formats and position data; SRS represents the spatial reference used by the position data; Attitude = {pitch, yaw, roll} represents the spatial attitude of the space-time object, pitch, yaw and roll represent the pitch angle, yaw angle and roll angle respectively; Format represents the position format; Data represents the position data, and its format is determined by Type and Format.

8. A method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 6, characterized in that: Based on the formal expression results, a data model of the spatial location of multi-granularity spatiotemporal objects is constructed according to the preset modeling process, including: Constructing different spatial position templates according to different position types; the spatial position templates contain parameters and constraint information of different types of spatial positions; Associating the spatial location template with the spatiotemporal object class; Instantiate the spatial locations of multi-granular spatiotemporal objects; Dynamically model the spatial positions of instantiated multi-granularity spatiotemporal objects.

9. The method for describing the spatial position of a multi-granularity spatiotemporal object according to claim 1, characterized in that: The associating the spatial position template with the spatiotemporal object class specifically includes: According to the different location types of the spatiotemporal object class, a suitable location template is selected and bound to the spatiotemporal object class template to realize the association between the location template and the spatiotemporal object class. The spatiotemporal object class template and the location template together constitute an abstract description of a class of spatiotemporal objects.

10. A system for describing the spatial position of a multi-granularity spatiotemporal object, characterized in that: The description of the spatial position of a multi-granularity spatiotemporal object is defined as the description of the spatiotemporal object positioning information, spatial distribution and its change characteristics. The system includes: Feature analysis module, used to analyze the main features of the spatial position of multi-granularity spatiotemporal objects; A spatial position classification module is used to classify the spatial positions of multi-granularity spatiotemporal objects; The data model building module is used to build a data model of the spatial position of multi-granularity spatiotemporal objects based on the main features and spatial position categories obtained through analysis.

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