Method and device for constructing temporal geographic data model based on hierarchical compression linear referencing technology, and method for constructing index structure

Abstract

The present invention discloses a method and device for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, as well as a method for constructing an index structure. The method for constructing the temporal geographic data model includes: step 1, establishing a hierarchical road network structure and establishing a hierarchical linear referencing system based on the hierarchical road network structure; step 2, using compressed linear referencing technology to perform spatiotemporal dimensionality reduction on temporal geographic objects and their spatiotemporal relationships; step 3, storing the temporal geographic objects in a relational database based on the OpenGIS specification; and step 4, using hierarchical compressed linear referencing technology to establish a temporal geographic data model. The method of the present invention can solve the problem of efficient storage, management, and query of massive temporal geographic entities with complex spatiotemporal characteristics and spatiotemporal relationships, and has superior computing performance to existing spatiotemporal data models and spatiotemporal index structures, thus having promising business and application prospects.

Description

Technical Field

[0001] The present invention relates to the technical field of spatiotemporal data management, and in particular to a method and device for constructing a temporal geographic data model based on hierarchical compression linear referencing technology, and a method for constructing an index structure. Background Art

[0002] Time geography is a powerful spatiotemporal analytical framework for understanding individual-level activity-travel behavior under various constraints. It provides a set of classical spatiotemporal entity concepts and spatiotemporal relations to represent and analyze the movement and activities of individuals within space and time. For example, space-time paths are used to represent the historical trajectory of individuals within space and time; space-time prisms are used to delineate the spatiotemporal regions where individuals can flexibly arrange activities between two fixed activities; and the spatiotemporal intersection of space-time prisms between individuals indicates the feasibility of arranging joint activities. This comprehensive time geography framework has been widely used in various applications, such as transportation demand modeling, urban planning, social differentiation, and public health research.

[0003] In recent years, time geography research has flourished with the rise of spatiotemporal big data on human activity. The widespread use of location-aware technologies such as the Global Positioning System (GPS) and mobile radio frequency identification (RFID) in daily life has greatly expanded our ability to collect large-scale, individual-level movement data at fine spatiotemporal resolution, breaking the long-standing bottleneck of time geography research, which has been limited by the lack of such data. However, effectively conducting time geography research based on this spatiotemporal big data presents significant challenges for contemporary static GIS platforms. Summary of the Invention

[0004] The present invention provides a method and device for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, and a method for constructing an index structure, so as to solve or at least partially solve the technical problems of low management efficiency and inconvenient query in the prior art.

[0005] In order to solve the above technical problems, the first aspect of the present invention provides a method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, comprising:

[0006] S1: Load the bottom-level segment-based road network and the upper-level path-based road network, build the subordinate relationship between segments and paths, establish a hierarchical road network structure, and establish a hierarchical linear reference system based on the hierarchical road network structure. The hierarchical linear reference system consists of the bottom-level segment-based reference system and the upper-level path-based reference system.

[0007] S2: Using the hierarchical linear reference system as the positioning benchmark, compressed linear reference technology is used to perform spatiotemporal dimension reduction on temporal geographic objects and their spatiotemporal relationships;

[0008] S3: Uses a hierarchical linear referencing system based on the OpenGIS specification to store temporal geographic objects in a relational database;

[0009] S4: Based on the hierarchical linear referencing system, hierarchical compressed linear referencing technology is used to establish a temporal geographic data model to manage all-time geographic objects on the hierarchical road network.

[0010] In one embodiment, the temporal geographic objects include 3D network space-time points, 3D network space-time paths, and 3D network space-time prisms, and S2 includes:

[0011] Using compressed linear referencing technology, network location points The unique identifier of the path b v and path-based linear referencing values Compress the integration into a single real number

[0012]

[0013] Using compressed linear reference technology, (x O ,y O , t) 3D network space-time point in space Equivalent conversion to path-based (z R , 2D spacetime point in time space

[0014] (x O ,y O , t) 3D network spatiotemporal path in space and time Equivalent conversion to path-based (z R , t) in time space, expressed as:

[0015]

[0016] in, for (z R , t) in the 2D polyline segment in the space, representing the individual along the path r v The motion of a spacetime segment along a path Composition, each space-time segment Represents two points in space and time and Uniform motion between space-time segments Speed ​​V v，ij The calculation method is:

[0017]

[0018] Among them, f v For path r v The length of the trajectory segment At any time t k ∈(t i , t j )'s space-time position Its network location is calculated as:

[0019]

[0020] (x O ,y O , t) 3D network space-time prism in space-time Equivalent conversion to path-based (z R , t) in time space, expressed as:

[0021]

[0022] in, for (z R , 2D polygon in space at time t), representing the path r v All the spatiotemporal locations on the network where flexible activities can be arranged, for any network location Its height in the time dimension represents the maximum duration of activities that can be participated in at this location, and is represented by the corresponding time and space point and Decision, among which and They represent the latest departure time and earliest arrival time of the network location, respectively. In z R The projection on the dimension is a potential network region consisting of a set of disjoint linear regions;

[0023] Using the above-mentioned compressed linear referencing technology, 3D network space-time points, 3D network space-time paths and 3D network space-time prisms are equivalently converted to segment-based (z L , t) in space and time.

[0024] In one embodiment, step S3 includes:

[0025] Define ClrSpaceTimePoint, ClrSpaceTimeStation, ClrSpaceTimePath, ClrSpaceTimePrism and ClrSpaceTimeLifeLine objects to represent (z R , t) or (zL , t) spacetime points, spacetime baselines, spacetime paths, spacetime prisms and spacetime lifelines in spacetime;

[0026] Based on OpenGIS specifications, all (z R , t) or (z L , t) All temporal geographic entity classes in spacetime inherit from the Geometry class, among which the spacetime point ClrSpaceTimePoint class inherits from the spacepoint Point class, the spacetime baseline ClrSpaceTimeStation class and the spacetime path ClrSpaceTimePath class inherit from the MultiLineString class, and the spacetime prism ClrSpaceTimePrism class and the spacetime lifeline ClrSpaceTimeLifeLine class inherit from the MultiPolygon class;

[0027] Based on the above data model design, the equivalent converted temporal geographic entities are stored in the spatial database.

[0028] In one embodiment, step S4 includes:

[0029] Organize the same type of temporal geographic entities based on the same linear reference system into one layer to establish a temporal geographic data model;

[0030] The semantic information of temporal geographic entity elements is uniformly managed within the layer.

[0031] Based on the same inventive concept, the second aspect of the present invention provides a device for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, comprising:

[0032] The hierarchical linear reference system construction module is used to load the bottom-level segment-based road network and the upper-level path-based road network, build the subordinate relationship between segments and paths, establish the current hierarchical road network structure, and establish a hierarchical linear reference system based on the hierarchical road network structure. The hierarchical linear reference system is composed of the bottom-level segment-based reference system and the upper-level path-based reference system.

[0033] The spatiotemporal dimensionality reduction module is used to reduce the spatiotemporal dimensionality of temporal geographic objects and their spatiotemporal relationships using a hierarchical linear reference system as a positioning benchmark and compressed linear reference technology;

[0034] Storage module, used to store temporal geographic objects in a relational database using a hierarchical linear referencing system based on the OpenGIS specification;

[0035] The temporal geographic data model construction module is used to establish a temporal geographic data model based on a hierarchical linear reference system and adopt hierarchical compressed linear reference technology to manage all-time geographic objects on a hierarchical road network.

[0036] Based on the same inventive concept, a third aspect of the present invention provides a method for constructing an index structure based on hierarchical compressed linear referencing technology, comprising:

[0037] Based on the temporal geographic data model constructed by the method described in the first aspect, a spatiotemporal index structure based on a linear reference system is established to support queries on temporal geographic entities.

[0038] In one embodiment, based on the temporal geographic data model, a spatiotemporal index structure based on a linear reference system is established, including:

[0039] Define a TopoNet object to express the segment-based road network G L , using the adjacency table data structure to store the topological relationship between the road network nodes and the road network edges; defining the Node object and the Link object to express the road network nodes and the road network edges respectively, using the hash table data structure to store the network nodes in the TopoNet object; using the linked list structure to store the road edge associated with each node in each network node object, giving the Link object the LineString class shape attribute shape to store the road geometry, which is used to realize the temporal geographic entity on the road edge (x O ,y O , t) time-space and segment-based (z L , t) the equivalent conversion between time and space; give the TopoNet object index mechanism linkIndex to use the minimum bounding box of the road segment edge as the road network G L All road segment edges construct an R-tree index, where the leaf nodes of the road segment edge R-tree point to the corresponding road segment network edge Link object;

[0040] Define a RouteNet object to express a path-based road network G R , to store the path set; define the Route object to express the path, and use the linked list structure to store the road network G covered by the Route object L The continuous road segments in the Route object; the shape attribute of the LineString class is given to store the path geometry, which is used to realize the time geographic entity on the path (x O ,y O , t) time-space and path-based (z R, t) the equivalent conversion between time and space; give the RouteNet object index mechanism routeIndex to the path network G according to the minimum bounding box of the space of the path edge R An R-tree index is constructed for all paths, where the leaf nodes of the path R-tree point to the corresponding Route object. Path semantic attributes are assigned to Route objects to support path-based semantic queries. The RouteNet attribute linkInRoute is assigned. The linkInRoute attribute uses a hash table data structure to store the path corresponding to a road segment and its position in the path, which is used to retrieve the correspondence between the road segment and the path.

[0041] Based on the design of the TopoNet and RouteNet objects mentioned above, the hierarchical road network is stored in memory to support the index construction of temporal geographic entities on the hierarchical road network and the rapid conversion of temporal geographic entities between different road networks;

[0042] Define multiple MultiLineString layers and multiple MultiPolygon layers for the TopoNet object to store multiple spatiotemporal path layers and multiple spatiotemporal prism layers on the road segment network, and build a separate index for each layer, give the TopoNet object the attribute pathLayerSet, which uses a dynamic array data structure to store the independent index structure of each spatiotemporal path layer; give the TopoNet object the attribute prismLayerSet, which uses a dynamic array data structure to store the independent index structure of each spatiotemporal prism layer; give the Link object the attribute pathIndexSet, which uses a dynamic array data structure to store the R-tree index of all MultiLineString layers on the Link object; give the Link object the attribute p rismIndexSet, this property uses a dynamic array data structure to store the R-tree index of all MultiPolygon layers on the Link object; build a set of 2-dimensional R-trees for a single spatiotemporal path layer on the TopoNet object as an independent index structure for the layer, each R-tree corresponds to the R-tree index structure built for all spatiotemporal sub-paths in the layer on each Link object instance, and the leaf nodes of the R-tree point to the corresponding spatiotemporal sub-paths and their order within the spatiotemporal path; build a set of 2-dimensional R-trees for a single spatiotemporal prism layer on the TopoNet object as an independent index structure for the layer, each R-tree corresponds to the R-tree index structure built for all spatiotemporal sub-prisms in the layer on each Link object instance, and the leaf nodes of the R-tree point to the corresponding spatiotemporal sub-prisms and their order within the spatiotemporal prism;

[0043] Define multiple MultiLineString layers and multiple MultiPolygon layers for the RouteNet object to store multiple space-time path layers and multiple space-time prism layers on the path network, and build a separate index for each layer in the same way.

[0044] Based on the same inventive concept, the fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the method described in the first aspect when the program is executed.

[0045] Based on the same inventive concept, the fifth aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0046] Compared with the prior art, the advantages and beneficial technical effects of the present invention are as follows:

[0047] In response to the lack of efficient storage, management and query methods for massive temporal geographic entities in modern GIS platforms, this paper proposes a method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology. The constructed temporal geographic data model not only supports the expression of all temporal geographic entities, such as space-time lines and space-time volumes, but also supports the efficient storage and management of temporal geographic entities on different transportation network linear referencing systems.

[0048] Based on the temporal geographic data model constructed above, an index structure was further constructed. The spatiotemporal indexing mechanism based on this index structure can simultaneously index temporal geographic entities and their corresponding hierarchical networks, support the conversion of temporal geographic entities between different transportation network linear reference systems, and support efficient query of massive temporal geographic entities, meeting the needs of data processing and analysis in the big data era. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 A schematic diagram of a spatiotemporal path on a hierarchical LRS proposed in an embodiment of the present invention;

[0051] Figure 2 A schematic diagram of a space-time prism on a hierarchical LRS proposed in an embodiment of the present invention;

[0052] Figure 3 A schematic diagram of spatiotemporal dimensionality reduction using the path-based LRS proposed in an embodiment of the present invention for a spatiotemporal path;

[0053] Figure 4 Schematic diagram of space-time dimensionality reduction using the path-based LRS proposed in an embodiment of the present invention for a space-time prism;

[0054] Figure 5 A schematic diagram of spatiotemporal dimension reduction using the path-based LRS proposed in an embodiment of the present invention for spatiotemporal relationships;

[0055] Figure 6 A model design diagram for expressing temporal geographic entities using a hierarchical linear referencing system proposed in an embodiment of the present invention;

[0056] Figure 7 A conceptual diagram of a temporal geographic data model based on hierarchical compressed linear referencing technology proposed in an embodiment of the present invention;

[0057] Figure 8 This is a conceptual diagram of the spatiotemporal index structure based on the hierarchical compression linear referencing technology proposed in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The first aspect of the present invention discloses a method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, comprising: step 1, loading a bottom-level segment-based road network and a top-level path-based road network, constructing a subordinate relationship between segments and paths, establishing a hierarchical road network structure, and establishing a hierarchical linear referencing system based on the hierarchical road network structure; step 2, using the hierarchical linear referencing system as a positioning reference, using compressed linear referencing technology to perform spatiotemporal dimensionality reduction on temporal geographic objects and their spatiotemporal relationships; step 3, using the hierarchical linear referencing system to implement storage of temporal geographic objects in a relational database based on the OpenGIS specification; step 4, based on the hierarchical linear referencing system, using hierarchical compressed linear referencing technology, establishing a temporal geographic data model for managing all temporal geographic objects on the hierarchical road network. The second aspect discloses a method for constructing an index structure based on hierarchical compressed linear referencing technology, establishing a spatiotemporal index structure based on the linear referencing system based on the temporal geographic data model constructed in the first aspect, to support queries on temporal geographic entities.

[0059] The method of the present invention can solve the efficient storage, management and query of massive temporal geographic entities with complex spatiotemporal characteristics and spatiotemporal relationships. It is superior to existing spatiotemporal data models and spatiotemporal index structures in computing performance and has prospects for business and promotion applications.

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0061] Example 1

[0062] The embodiment of the present invention provides a method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, comprising:

[0063] S1: Load the bottom-level segment-based road network and the upper-level path-based road network, build the subordinate relationship between segments and paths, establish a hierarchical road network structure, and establish a hierarchical linear reference system based on the hierarchical road network structure. The hierarchical linear reference system consists of the bottom-level segment-based reference system and the upper-level path-based reference system.

[0064] S2: Using the hierarchical linear reference system as the positioning benchmark, compressed linear reference technology is used to perform spatiotemporal dimension reduction on temporal geographic objects and their spatiotemporal relationships;

[0065] S3: Uses a hierarchical linear referencing system based on the OpenGIS specification to store temporal geographic objects in a relational database;

[0066] S4: Based on the hierarchical linear referencing system, hierarchical compressed linear referencing technology is used to establish a temporal geographic data model to manage all-time geographic objects on the hierarchical road network.

[0067] Specifically, the "hierarchical road network structure" serves as a reference framework for the hierarchical CLR data model and is required to implement dimensionality reduction of the 3D network spatiotemporal object in step S2, for example, for converting the network spatiotemporal position in 3D (x, y, t) space-time to 2D (z, t) space-time.

[0068] The processing object of the present invention is large-scale temporal geographic entity objects in urban traffic road networks; the storage, management and query of large-scale temporal geographic entities on different linear reference systems can be realized.

[0069] The embodiment of the present invention first introduces the hierarchical linear referencing system (Hierarchical LRS) and temporal geographic entities.

[0070] Individuals’ activities in cities are usually restricted by the road network structure and cannot move freely like in the (x, y, t) plane space. The urban road network is composed of multiple layers of transportation networks, such as Figure 1 As shown in Figure 2. Each layer of the network has its own independent LRS to support the positioning of individual movement in the network. LRSs at different layers constitute a hierarchical LRS. This hierarchical LRS supports not only link-based LRSs but also multiple route-based LRSs. Figure 1 The lower layer represents the segment-based LRS, and the upper layer represents the path-based LRS. In this embodiment, the superscript L is used to represent the positioning of an individual's movement on the segment LRS; the superscript R is used to represent the positioning on the path LRS; and the superscript O is used to represent the positioning in the plane space. The segment-based LRS is represented by a segment-based network, which consists of complete network edges and network nodes in the traffic network. At the same time, the segment-based LRS is also used as the basic linear datum (Linear datum) for all path-based LRS. Each path-based LRS uses a path-based network composed of a set of segments, and each path covers a set of continuous segments in the segment-based network.

[0071] Define the segment-based network as a directed graph G L =(N, L), where N is the node set and L is the edge set. u The starting node of ∈L is n u，s ∈N, the terminal node is n u，e ∈N, ID is l u , with a length of d u On section a u Network location on It can be expressed as segment-based LRS: in is a linear measurement value, indicating that the road segment a u The relative position on represents the middle position of the road segment, and and Represent the starting point and end point of the road segment, respectively, where ε is a very small tolerance (such as ε = 10 -8 ).

[0072] Define a street-based path network as a directed graph G R =(J, R), where J is the intersection set and R is the path set. Each path r in the path network v ∈R represents a street and covers the underlying segment-based network G L A set of continuous road segments in Figure 1Path r3 consists of continuous segments<a6,a5> The path has the following characteristics: the path has a direction, such as the south side and the north side of a street are considered as two independent paths; the paths do not overlap, that is, any road segment a u ∈L belongs to at most one path; the path does not loop, that is, the path does not pass through any road segment twice; the path does not need to cover the underlying segment-based network G L The complete set of road segments in . The path has the following properties: The path has a unique path identifier b v 、Path name θ v , path length f v , starting intersection j v，s ∈J and terminate at intersection j v，e ∈J; all the links on a path belong to the road network G R The node sets of are considered as the remaining intersections, and the linear measurements of these intersections along the path are recorded as attributes.

[0073] On the path r v Network location on It can be expressed as path-based LRS in represents the linear measurement along the path, b v Is the path identifier. Linear measurement value based on the path You can use the following formula to get the network location Road section a u ∈r v Segment-based linear measurements on Sure:

[0074]

[0075] in and are the starting nodes n of the road segment u，s and terminal node n u，e , on the path r v Path-based linear measurements in . Vice versa, path-based LRS coordinates It can also be converted into LRS coordinates based on road sections according to the following formula

[0076]

[0077] For example, Figure 1 Network location points Located on segment a5. Path r3 covers segment a5 and another segment a6 of the same length as a5. Therefore, the starting node n of segment a5 is obtained. 5，s and terminal node n 5，eThe linear measurements on path r3 are and According to the above formula, the network location point n can be obtained 5，i Linear measurement value of path r3 Therefore, the network location n 5，i The path-based LRS coordinates can be determined as

[0078] The aforementioned bottom-level segment-based LRS and the multiple upper-level path-based LRSs together form a hierarchical LRS within the transportation network. This hierarchical LRS serves as a linear benchmark for individual movement within urban space. Individual movement within urban space is represented by four types of temporal geographic entities: spacetime paths, spacetime baselines, spacetime prisms, and spacetime lifelines.

[0079] Time and space points are the basis of all the above-mentioned time and space entities. When individuals move in geographic space, they can usually only collect discrete time and space points. These discrete time and space points are called control points. Generally, these control points are collected by positioning devices such as GPS. Each control point By plane space coordinates and time point t i express:

[0080]

[0081] Based on the traffic network, the above control points can also use the segment-based LRS, which is expressed as Or using path-based LRS, expressed as In addition to the above-mentioned spatiotemporal position points collected by positioning devices such as GPS, the control points of individual movement in the road network space also include the spatiotemporal position points at the road network node positions and the road network edge shape node positions.

[0082] A space-time path represents the historical movement of an individual, also known as the space-time trajectory of individual movement. Figure 1 As shown, the space-time path Yes (x O ,y O , t) in space, a continuous three-dimensional polyline (LineString) can be represented by a set of straight line segments as follows:

[0083]

[0084] Each straight line segment Indicates that on section a u At a constant speed from arrive Linear motion. Space-time path All the spatiotemporal points at which the individual changes its movement speed or direction are recorded, e.g. Figure 1 in Space-time path The projection in the segment-based network space is a set of continuous segments, such as Figure 1 in<a1,a3,a5> ; The projection in the path-based network space goes through a set of paths, such as Figure 1 in<r1,r3> A spatiotemporal baseline It is a space-time path perpendicular to the plane space, representing the activity participation of an individual in a facility. It is composed of a group of people in the same geographical location. It is composed of vertical line segments on it, which is expressed as:

[0085]

[0086] A spacetime prism represents the individual potential movement of an individual under various spacetime constraints. Figure 2 As shown, given two fixed space-time points and A space-time prism All accessible spatiotemporal locations are delineated Expressed as:

[0087]

[0088] Among them, t oi From the starting point Arrival point The shortest travel time. id From the reachable point To destination The shortest travel time can be calculated by the shortest path algorithm. The maximum activity time of any reachable point is the latest departure time of the point. and earliest arrival time The projection of the space-time prism in the network space is the potential network activity area. Figure 2 As shown, the space-time prism in the road network It can be represented by a set of three-dimensional polygons:

[0089]

[0090] Taking the road segment-based network as an example, each 3D polygon Representative road section a u All accessible spacetime locations on the network, and a set of spacetime points Composition, of which The earliest arrival time The space-time location of The latest departure time The space-time position of the space-time lifeline Represents a spacetime motion with both a fixed movement trajectory and a potential activity space. It can be represented as a combination of a spacetime path and a spacetime prism, expressed as:

[0091]

[0092] During step S1, the segment-based road network data is first preloaded into the main memory, and the road network topology is constructed, typically recorded as a topological connection table between segments and nodes. In specific implementations, this can be pre-constructed, and the pre-constructed topological connection table between segments and nodes is also loaded into the main memory simultaneously with the loading of the segment-based road network data. Then, using the segment-based road network data as the underlying reference, segments with identical street names are identified, and a street-based path network is constructed on the segment-based network. The street-based path network data is also loaded into the main memory simultaneously, and the affiliation between paths and the covered segments is constructed, typically recorded as a segment-path affiliation table. In specific implementations, this can be pre-constructed, and the pre-constructed affiliation table between segments and paths is also loaded into the main memory simultaneously with the loading of the path network data. Using the segment-based road network data as the underlying linear reference, multiple path-based road networks can be constructed and loaded. On the constructed hierarchical road network, using the corresponding hierarchical linear reference system as the positioning reference, temporal geographic entities are modeled and indexed.

[0093] In one embodiment, the temporal geographic objects include 3D network space-time points, 3D network space-time paths, and 3D network space-time prisms, and S2 includes:

[0094] Taking the path-based linear referencing system as an example, the network location points are converted to The unique identifier of the path b v and path-based linear referencing values Compress the integration into a single real number

[0095]

[0096] Using compressed linear reference technology, (x O ,y O , t) 3D network space-time point in space Equivalent conversion to path-based (z R , 2D spacetime point in time space

[0097] (x O ,y O , t) 3D network spatiotemporal path in space and time Equivalent conversion to path-based (z R , t) in time space, expressed as:

[0098]

[0099] in, for (z R , t) in the 2D polyline segment in the space, representing the individual along the path r v Movement, such as Figure 3 As shown, it consists of a set of space-time segments along the path Composition, each space-time segment Represents two points in space and time and Uniform motion between space-time segments Speed ​​V v，ij The calculation method is:

[0100]

[0101] trajectory segment At any time t k ∈(t i , t j )'s space-time position Its network location is calculated as:

[0102]

[0103] will be like Figure 2 As shown (x O ,y O , t) 3D network space-time prism in space-time Equivalent conversion to path-based (z R , t) in time space, expressed as:

[0104]

[0105] in, for (z R , 2D polygon in space at time t), representing the path r v All the spatiotemporal locations where flexible activities can be arranged, such as Figure 4 For any network location Its height in the time dimension represents the maximum duration of activities that can be participated in at this location, and is represented by the corresponding time and space point and Decision, among which and They represent the latest departure time and earliest arrival time of the network location respectively. In z RThe projection onto a dimension is a potential network region consisting of a set of disjoint linear regions.

[0106] Specifically, the compressed linear reference technology includes the path-based compressed linear reference technology and the segment-based compressed linear reference technology. Based on the above path-based compressed linear reference technology, all (x O ,y O , t) time space 3D temporal geographic entity equivalent conversion to path-based (z R , t) in the 2D space; at the same time, the original 3D (x O ,y O , t) time and space relationship between temporal and geographical entities, and 2D (z R , t) The spatiotemporal relationships between corresponding temporal and geographical entities in the time and space are consistent, e.g. Figure 5 As shown, the original 3D (x O ,y O The 3D space-time intersection relationship between the space-time prism and the space-time path in the time space can be equivalently expressed as 2D(z R ,t) is the 2D space-time intersection relationship between the space-time prism and the space-time path in the time space. Because a road segment is a special case of a path, that is, a road segment is a path that only covers one road segment, the segment-based compressed linear referencing technology is similar to the path-based compressed linear referencing technology mentioned above. You can refer to the path-based compressed linear referencing technology and convert all (x O ,y O , t) time space 3D temporal geographic entity equivalent conversion to segment-based (z L , 2D entity in time space; (z L , t) time and geographic entities in space and time (x O ,y O , t) The corresponding entities in the time and space have the same time and space relationship.

[0107] In one embodiment, step S3 includes:

[0108] Define ClrSpaceTimePoint, ClrSpaceTimeStation, ClrSpaceTimePath, ClrSpaceTimePrism and ClrSpaceTimeLifeLine objects to represent (z R , t) or (z L , t) spacetime points, spacetime baselines, spacetime paths, spacetime prisms and spacetime lifelines in spacetime;

[0109] Based on OpenGIS specifications, all (z R , t) or (z L, t) All temporal geographic entity classes in spacetime inherit from the Geometry class, among which the spacetime point ClrSpaceTimePoint class inherits from the spacepoint Point class, the spacetime baseline ClrSpaceTimeStation class and the spacetime path ClrSpaceTimePath class inherit from the MultiLineString class, and the spacetime prism ClrSpaceTimePrism class and the spacetime lifeline ClrSpaceTimeLifeLine class inherit from the MultiPolygon class;

[0110] Based on the above data model design, the equivalent converted temporal geographic entities are stored in the spatial database.

[0111] In the specific implementation process, the spatial database can be selected according to the actual situation, such as Oracle spatial database. Figure 6 The figure shows the design diagram of the temporal geographic entity expression model.

[0112] In one embodiment, step S4 includes:

[0113] Organize the same type of temporal geographic entities based on the same linear reference system into one layer to establish a temporal geographic data model;

[0114] The semantic information of temporal geographic entity elements is uniformly managed within the layer.

[0115] like Figure 7 As shown in the conceptual diagram of the hierarchical compressed linear reference data model, during the specific implementation process, the spatiotemporal path set based on the street LRS can be organized into a separate layer, and the semantic information of the temporal geographic entity elements, such as personal age, gender, income, marital status and other semantic attributes, can be uniformly managed within the layer. According to actual conditions, multiple temporal geographic entity layers can be defined on a single linear reference system. By utilizing the mature and complete spatial operators of the existing GIS platform, such as intersection, containment, overlap and other spatial operations, the temporal and spatial relationship judgment of temporal geographic entities within the layer can be equivalently realized; at the same time, based on the hierarchical LRS, the temporal and spatial relationship judgment of temporal geographic entities between different LRSs can be equivalently realized. In addition to the storage and management of temporal geographic entities, the mature and complete network analysis module of the GIS platform can be used to store and manage hierarchical road networks and corresponding hierarchical LRS.

[0116] Example 2

[0117] Based on the same inventive concept, this embodiment provides a device for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, including:

[0118] The hierarchical linear reference system construction module is used to load the bottom-level segment-based road network and the upper-level path-based road network, build the subordinate relationship between segments and paths, establish the current hierarchical road network structure, and establish a hierarchical linear reference system based on the hierarchical road network structure. The hierarchical linear reference system is composed of the bottom-level segment-based reference system and the upper-level path-based reference system.

[0119] The spatiotemporal dimensionality reduction module is used to reduce the spatiotemporal dimensionality of temporal geographic objects and their spatiotemporal relationships using a hierarchical linear reference system as a positioning benchmark and compressed linear reference technology;

[0120] Storage module, used to store temporal geographic objects in a relational database using a hierarchical linear referencing system based on the OpenGIS specification;

[0121] The temporal geographic data model construction module is used to establish a temporal geographic data model based on a hierarchical linear reference system and adopt hierarchical compressed linear reference technology to manage all-time geographic objects on a hierarchical road network.

[0122] Since the device described in Example 2 of the present invention is used to implement the method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology in Example 1 of the present invention, those skilled in the art will be able to understand the specific structure and variations of the device based on the method described in Example 1 of the present invention, and therefore will not be described in detail here. All devices used in the method of Example 1 of the present invention are within the scope of protection of the present invention.

[0123] Example 3

[0124] Based on the same inventive concept, this embodiment provides a method for constructing an index structure based on hierarchical compressed linear referencing technology, including:

[0125] Based on the temporal geographic data model constructed by the method described in the first aspect, a spatiotemporal index structure based on a linear reference system is established to support queries on temporal geographic entities.

[0126] In one embodiment, based on the temporal geographic data model, a spatiotemporal index structure based on a linear reference system is established, including:

[0127] Define a TopoNet object to express the segment-based road network G L, using the adjacency table data structure to store the topological relationship between the road network nodes and the road network edges; defining the Node object and the Link object to express the road network nodes and the road network edges respectively, using the hash table data structure to store the network nodes in the TopoNet object; using the linked list structure to store the road edge associated with each node in each network node object, giving the Link object the LineString class shape attribute shape to store the road geometry, which is used to realize the temporal geographic entity on the road edge (x O ,y O , t) time-space and segment-based (z L , t) the equivalent conversion between time and space; give the TopoNet object index mechanism linkIndex to use the minimum bounding box of the road segment edge as the road network G L All road segment edges construct an R-tree index, where the leaf nodes of the road segment edge R-tree point to the corresponding road segment network edge Link object;

[0128] Define a RouteNet object to express a path-based road network G R , to store the path set; define the Route object to express the path, and use the linked list structure to store the road network G covered by the Route object L The continuous road segments in the Route object; the shape attribute of the LineString class is given to store the path geometry, which is used to realize the time geographic entity on the path (x O ,y O , t) time-space and path-based (z R , t) the equivalent conversion between time and space; give the RouteNet object index mechanism routeIndex to the path network G according to the minimum bounding box of the space of the path edge R An R-tree index is constructed for all paths, where the leaf nodes of the path R-tree point to the corresponding Route object. Path semantic attributes are assigned to Route objects to support path-based semantic queries. The RouteNet attribute linkInRoute is assigned. The linkInRoute attribute uses a hash table data structure to store the path corresponding to a road segment and its position in the path, which is used to retrieve the correspondence between the road segment and the path.

[0129] Based on the design of the TopoNet and RouteNet objects mentioned above, the hierarchical road network is stored in memory to support the index construction of temporal geographic entities on the hierarchical road network and the rapid conversion of temporal geographic entities between different road networks;

[0130] Define multiple MultiLineString layers and multiple MultiPolygon layers for the TopoNet object to store multiple spatiotemporal path layers and multiple spatiotemporal prism layers on the road segment network, and build a separate index for each layer, give the TopoNet object the attribute pathLayerSet, which uses a dynamic array data structure to store the independent index structure of each spatiotemporal path layer; give the TopoNet object the attribute prismLayerSet, which uses a dynamic array data structure to store the independent index structure of each spatiotemporal prism layer; give the Link object the attribute pathIndexSet, which uses a dynamic array data structure to store the R-tree index of all MultiLineString layers on the Link object; give the Link object the attribute p rismIndexSet, this property uses a dynamic array data structure to store the R-tree index of all MultiPolygon layers on the Link object; build a set of 2-dimensional R-trees for a single spatiotemporal path layer on the TopoNet object as an independent index structure for the layer, each R-tree corresponds to the R-tree index structure built for all spatiotemporal sub-paths in the layer on each Link object instance, and the leaf nodes of the R-tree point to the corresponding spatiotemporal sub-paths and their order within the spatiotemporal path; build a set of 2-dimensional R-trees for a single spatiotemporal prism layer on the TopoNet object as an independent index structure for the layer, each R-tree corresponds to the R-tree index structure built for all spatiotemporal sub-prisms in the layer on each Link object instance, and the leaf nodes of the R-tree point to the corresponding spatiotemporal sub-prisms and their order within the spatiotemporal prism;

[0131] Define multiple MultiLineString layers and multiple MultiPolygon layers for the RouteNet object to store multiple space-time path layers and multiple space-time prism layers on the path network, and build a separate index for each layer in the same way.

[0132] For details, please see Figure 8 , which is a conceptual diagram of the spatiotemporal index structure based on hierarchical compressed linear referencing technology.

[0133] By assigning the RouteNet attribute linkInRoute, which uses a hash table data structure to store the corresponding path and the position of the road segment in the path, efficient retrieval of the corresponding relationship between the road segment and the path can be achieved.

[0134] Only a single TopoNet object instance is constructed to express a unique road segment network; in the specific implementation process, multiple RouteNet object instances can be constructed to express multiple path networks based on different path semantics.

[0135] The space-time path layer includes the space-time baseline, and the space-time prism layer includes the space-time lifeline.

[0136] Example 4

[0137] Based on the same inventive concept, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed, the method described in the first embodiment is implemented.

[0138] Since the computer-readable storage medium described in the fourth embodiment of the present invention is used in the method for constructing a temporal geographic data model using hierarchical compressed linear referencing technology in the first embodiment of the present invention, those skilled in the art will be able to understand the specific structure and variations of the computer-readable storage medium based on the method described in the first embodiment of the present invention, and therefore will not be described in detail here. All computer-readable storage media used in the method of the first embodiment of the present invention fall within the scope of protection of the present invention.

[0139] Example 5

[0140] Based on the same inventive concept, the present application also provides a computer device, including storage, a processor, and a computer program stored in the storage and executable on the processor. When the processor executes the program, the method in the first embodiment is implemented.

[0141] Since the computer device described in Example 5 of the present invention is used to implement the method for constructing a temporal geographic data model using hierarchical compressed linear referencing technology in Example 1 of the present invention, those skilled in the art will be able to understand the specific structure and variations of the computer device based on the method described in Example 1 of the present invention, and therefore will not be described in detail here. All computer devices used in the method of Example 1 of the present invention fall within the scope of protection of the present invention.

[0142] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0143] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0144] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0145] Obviously, those skilled in the art may make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Thus, if such changes and modifications of the embodiments of the present invention fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, characterized in that: include: S1: Load the bottom-level segment-based road network and the upper-level path-based road network, build the subordinate relationship between segments and paths, establish a hierarchical road network structure, and establish a hierarchical linear reference system based on the hierarchical road network structure. The hierarchical linear reference system consists of the bottom-level segment-based reference system and the upper-level path-based reference system. S2: Using the hierarchical linear reference system as the positioning benchmark, the compressed linear reference technology is used to reduce the spatial and temporal dimensions of temporal geographic objects and their temporal and spatial relationships. Specifically, the compressed linear reference technology is used to convert 3D network space-time points, 3D network space-time paths, and 3D network space-time prisms into road segment-based space-time prisms. In time and space, temporal geographic objects include 3D network space-time points, 3D network space-time paths, and 3D network space-time prisms; S3: Uses a hierarchical linear referencing system based on the OpenGIS specification to store temporal geographic objects in a relational database; S4: Based on the hierarchical linear referencing system, hierarchical compressed linear referencing technology is used to establish a temporal geographic data model for the management of all-time geographic objects on the hierarchical road network. Specifically, a collection of temporal geographic entities of the same type that use the same linear referencing system as the positioning benchmark is organized into a layer to establish a temporal geographic data model; the semantic information of the temporal geographic entity elements is uniformly managed within the layer.

2. The method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology according to claim 1, wherein: S2 include: Using compressed linear referencing technology, network location points Unique identifier of the path and path-based linear referencing values Compress the integration into a single real number : Using compressed linear referencing technology, 3D network space-time points in space-time , equivalent to path-based 2D spacetime point in spacetime ; Will 3D network space-time paths in space-time , equivalent to path-based In space-time, it is expressed as: in, for 2D polyline segments in time and space, representing individuals along the path The motion of a spacetime segment along a path Composition, each space-time segment Represents two points in space and time and Uniform motion between space-time segments Speed The calculation method is: in, For path The length of the trajectory segment At any time The space-time position of , whose network location is calculated as: Will 3D network space-time prism in space-time , equivalent to path-based In space-time, it is expressed as: in, for 2D polygons in spacetime, representing paths All the spatiotemporal locations on the network where flexible activities can be arranged, for any network location , its height in the time dimension represents the maximum duration of the activity that can be participated in at this location, and is represented by the corresponding space-time point and Decision, among which and They represent the latest departure time and earliest arrival time of the network location, respectively. exist The projection on the dimension is a potential network region consisting of a set of disjoint linear regions; Using compressed linear referencing technology, 3D network space-time points, 3D network space-time paths and 3D network space-time prisms are converted to segment-based equivalents at the same time. In time and space.

3. The method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology according to claim 1, wherein: Step S3 includes: definition ClrSpaceTimePoint 、 ClrSpaceTimeStation 、 ClrSpaceTimePath 、 ClrSpaceTimePrism and ClrSpaceTimeLifeLine The objects represent or Spacetime points, spacetime baselines, spacetime paths, spacetime prisms, and spacetime lifelines in spacetime; Based on OpenGIS specifications, all or The temporal geographic entity classes in the time space are inherited from Geometry Class, where spacetime point ClrSpaceTimePoint Class inherits from SpacePoint Point Class, spatiotemporal baseline ClrSpaceTimeStation Classes and Space-Time Paths ClrSpaceTimePath Class inherits from Polyline MultiLineString Class, Spacetime Prism ClrSpaceTimePrism Classes and Spacetime Lifelines ClrSpaceTimeLifeLine Class inherits from multiple MultiPolygon kind; Based on the above data model design, the equivalent converted temporal geographic entities are stored in the spatial database.

4. A device for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology, characterized in that: The device is used to implement the method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology as claimed in claim 1, comprising: The hierarchical linear reference system construction module is used to load the bottom-level segment-based road network and the upper-level path-based road network, build the subordinate relationship between segments and paths, establish the current hierarchical road network structure, and establish a hierarchical linear reference system based on the hierarchical road network structure. The hierarchical linear reference system is composed of the bottom-level segment-based reference system and the upper-level path-based reference system. The spatiotemporal dimensionality reduction module is used to reduce the spatiotemporal dimensionality of temporal geographic objects and their spatiotemporal relationships using a hierarchical linear reference system as a positioning benchmark and compressed linear reference technology; Storage module, used to store temporal geographic objects in a relational database using a hierarchical linear referencing system based on the OpenGIS specification; The temporal geographic data model construction module is used to establish a temporal geographic data model based on a hierarchical linear reference system and adopt hierarchical compressed linear reference technology to manage all-time geographic objects on a hierarchical road network.

5. A method for constructing an index structure based on hierarchical compressed linear referencing technology, characterized in that: include: Based on the temporal geographic data model constructed by the method described in any one of claims 1 to 3, a spatiotemporal index structure based on a linear reference system is established to support queries on temporal geographic entities.

6. The method for constructing an index structure based on hierarchical compressed linear referencing technology according to claim 5, wherein: Based on the temporal geographic data model, a spatiotemporal index structure based on the linear reference system is established, including: definition TopoNet Object representation of a segment-based road network , using the adjacency table data structure to store the topological relationship between the road network nodes and the road edge; defining Node Objects and Link The objects represent the road network nodes and road network edges respectively, and the network nodes are stored in the hash table data structure. TopoNet Object; Use the linked list structure to store the road segment edges associated with each node in each network node object, and assign Link Object LineString Class shape properties shape Stores the geometry of road segments, which is used to implement temporal geographic entities on the edges of road segments. Space-time and segment-based Equivalent conversion between time and space; giving TopoNet Object indexing mechanism linkIndex , taking the minimum bounding box of the road segment as the road network All road segment edges construct an R-tree index, where the leaf nodes of the road segment edge R-tree point to the corresponding road segment network edge Link object; definition RouteNet Object representation of path-based road networks , to store the path collection; define Route The object expression path is stored in a linked list structure. Route The road network covered by the object Continuous road segments in Route Object LineString Class shape properties shape Stores the path geometry for implementing temporal geographic entities on the path Space-time and path-based Equivalent conversion between time and space; giving RouteNet Object indexing mechanism routeIndex , based on the minimum bounding box of the path edge space as the path network All paths build R-tree indexes, where the leaf nodes of the path R-tree point to the corresponding paths Route object; give Route Object path semantic attributes to support path-based semantic queries; RouteNet property linkInRoute ,property linkInRoute A hash table data structure is used to store the corresponding path and position of the road segment in the path, so as to retrieve the corresponding relationship between the road segment and the path; Based on the above TopoNet and RouteNet The object design stores the hierarchical road network in memory to support the index construction of temporal geographic entities on the hierarchical road network and the fast conversion of temporal geographic entities between different road networks; for TopoNet Object definition multiple MultiLineString Layers and multiple MultiPolygon Layers are used to store multiple spatiotemporal path layers and multiple spatiotemporal prism layers on the road network, and a separate index is built for each layer. TopoNet Object properties pathLayerSet This property uses a dynamic array data structure to store the independent index structure of each spatiotemporal path layer; TopoNet Object properties prismLayerSet This property uses a dynamic array data structure to store the independent index structure of each spatiotemporal prism layer; Link Object properties pathIndexSet , this property is stored in a dynamic array data structure Link All on the object MultiLineString R-tree index of the layer; given Link Object properties prismIndexSet , this property is stored in a dynamic array data structure Link All on the object MultiPolygon The R-tree index of the layer; TopoNet A single spatiotemporal path layer on the object builds a set of 2-dimensional R-trees as an independent index structure for the layer, and each R-tree corresponds to Link The R-tree index structure constructed by all spatiotemporal subpaths in the layer on the object instance, the leaf nodes of the R-tree point to the corresponding spatiotemporal subpath and the order within the spatiotemporal path; TopoNet Each spatiotemporal prism layer on an object builds a set of 2D R-trees as an independent index structure for the layer, with each R-tree corresponding to each Link An R-tree index structure constructed by all spatiotemporal sub-prisms in the layer on the object instance, where the leaf nodes of the R-tree point to the corresponding spatiotemporal sub-prisms and their order within the spatiotemporal prism; for RouteNet Object definition multiple MultiLineString Layers and multiple MultiPolygon Layers to store multiple space-time path layers and multiple space-time prism layers on the path network, and build a separate index for each layer in the same way.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed, the method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology as described in any one of claims 1 to 3 is implemented.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for constructing a temporal geographic data model based on hierarchical compressed linear referencing technology according to any one of claims 1 to 3 is implemented.

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