Spatial information trajectory visualization method supporting expression of uncertainty level

Abstract

A spatial information trajectory visualization method supporting expression of uncertainty level, belonging to the field of visualization. The method comprises: on the basis of actual spatial information, extracting a spatial uncertainty level from spatial data to be expressed; according to the extracted spatial uncertainty level, performing abstract map node layout, organizing locations in the trajectory into a nested circular structure according to a spatial uncertainty level organization, placing locations having determined positions inside a circle, placing locations having uncertain positions on a circle boundary, and drawing a trajectory path using a quadratic Bézier curve. The present method targets spatial information trajectory data having an uncertainty level, and, by means of constraint conditions such as geographic space and linking relationships, obtains an optimized layout for abstract map nodes, thereby avoiding misunderstandings caused by uncertain places drawn on a geographic map, and retaining, as much as possible, known information and association relationships; trajectory characteristics can be objectively and effectively shown, and a reliable foundation is laid for the development of spatial information visualization.

Description

A trajectory visualization method that supports expressing uncertain hierarchical spatial information Technical Field

[0001] The present invention belongs to the field of visualization, and in particular relates to a trajectory visualization method that supports expressing uncertain hierarchical spatial information. Background Art

[0002] Visualization is an important means of data expression in the data age. Trajectory visualization can help understand and analyze the movement characteristics in trajectory data and is a classic research direction in the field of visualization.

[0003] Most existing trajectory visualization methods are based on geographic maps, either directly plotting trajectory paths or clustering trajectory data. For uncertain location information within a trajectory, encoding methods such as fuzziness, color, and size are used to indicate uncertainty. However, when spatial uncertainty in the data is significant, clustering a large number of ambiguous locations on a geographic map can easily lead to misinterpretation and make it difficult to reveal trajectory characteristics.

[0004] Summary of the Invention

[0005] To address the shortcomings of the existing technology, the present invention aims to provide a trajectory visualization method that supports the expression of spatial information with a hierarchy of uncertainty. For trajectory data with this hierarchy of uncertainty, locations in the trajectory are organized into a nested circular structure based on the extracted spatial uncertainty hierarchy. Locations with known positions are placed within the circles, while uncertain locations are placed at the circle boundaries. Directed edges represent movement between these locations. By applying constraints such as geographic space and link relationships, an optimized layout of abstract map nodes is achieved, thus avoiding the misunderstandings caused by plotting uncertain locations on a geographic map. While preserving known information and related relationships to the greatest extent possible, the method objectively and effectively reveals trajectory characteristics, laying a solid foundation for the development of spatial information visualization.

[0006] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0007] A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information, the method comprising the following steps:

[0008] S1. Extract spatial uncertainty levels from the spatial data to be expressed based on actual spatial information;

[0009] S2, performing abstract map node layout based on the spatial uncertainty hierarchy extracted in step S1;

[0010] S3. Based on the abstract map node layout, the trajectory path is drawn using quadratic Bezier curves.

[0011] Furthermore, the tree nodes in the spatial uncertainty hierarchy extracted in step S1 are divided into non-leaf nodes, certain leaf nodes and uncertain leaf nodes. Certain leaf nodes refer to leaf nodes without non-leaf sibling nodes, and uncertain leaf nodes refer to leaf nodes with non-leaf sibling nodes.

[0012] Furthermore, in step S2, the locations in the trajectory are organized into a nested circular structure according to the extracted spatial uncertainty hierarchy, with the locations with determined positions placed inside the circle and the uncertain locations placed at the circle boundary.

[0013] Furthermore, the abstract map node layout process in step S2 considers the spatial uncertainty level, link relationship and geographical location of the nodes.

[0014] Furthermore, step S2 includes the following sub-steps:

[0015] S21. Applying a circular treemap layout algorithm to perform internal node layout, wherein the internal nodes include non-leaf nodes and determined leaf nodes;

[0016] S22. Layout the uncertain leaf nodes at the parent node boundary of the uncertain leaf nodes.

[0017] Furthermore, in step S21, the internal nodes with the same parent node are represented as a group of circles, and the circular tree graph layout algorithm is applied. Starting from the leaf nodes, the circles are compactly arranged from the inside to the outside from the bottom up. During the internal node layout process, the edge chain is maintained, and the edge chain is initialized to three tangent circles. After that, two adjacent circles on the edge chain are selected each time, and the new circle is placed at the tangent point with them.

[0018] Furthermore, in step S22, for each uncertain leaf node, the center of gravity position of its neighboring nodes is first calculated, and the center of gravity of the parent node of the uncertain leaf node is connected with the center of gravity of the neighboring nodes to obtain a ray. The intersection of the ray and the boundary of the parent node is the center of the uncertain leaf node. If the newly placed uncertain leaf node coincides with the position of the existing uncertain leaf node, a small offset is added until there is no overlap between the uncertain leaf nodes.

[0019] Furthermore, the trajectory path in step S3 is represented by directed edges between abstract map nodes.

[0020] Furthermore, the width of the edge between two nodes in the trajectory path in step S3 encodes the number of trajectories from the starting point to the end point.

[0021] The beneficial technical effect of the present invention is that the trajectory visualization method disclosed in the present invention, which supports the expression of uncertain hierarchical spatial information, can effectively display trajectory data with hierarchical spatial uncertainty, avoid misunderstandings caused by uncertain locations, and objectively and effectively reveal trajectory characteristics, such as aggregation and dispersion, laying a solid foundation for the development of spatial information visualization. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] FIG1 is a schematic diagram of a process for constructing an abstract map using a trajectory visualization method supporting the expression of uncertain hierarchical spatial information according to a first embodiment of the present invention;

[0023] Among them, (a) is the actual spatial level, (b) is the uncertainty spatial information, such as the city or province to which the institution belongs is unknown, (c) is the uncertainty spatial level, and (d) is the abstract map structure;

[0024] FIG2 is a schematic diagram of a process of performing abstract map node layout using a trajectory visualization method supporting the expression of uncertain hierarchical spatial information according to the first embodiment of the present invention;

[0025] FIG3 is an abstract map constructed using the trajectory visualization method supporting the expression of uncertain hierarchical spatial information described in Example 1. DETAILED DESCRIPTION

[0026] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0027] Example 1

[0028] As shown in FIG1 , an embodiment of the present invention provides a trajectory visualization method that supports expressing uncertain hierarchical spatial information. The method includes the following steps:

[0029] S1. Based on the actual spatial information, the spatial uncertainty level is extracted from the spatial data to be expressed.

[0030] As shown in FIG1 , in this embodiment, taking the “country-province-city-institution” hierarchical spatial information as an example, as shown in FIG1( a ), the actual spatial information includes the complete hierarchical information from “country” to “institution” as shown in the figure.

[0031] As shown in Figure 1(b), in some cases, such as historical data, we may only know that an institution exists, but not its affiliated city or province. Based on different levels of spatial uncertainty, spatial data can be expressed as an uncertainty hierarchy, as shown in Figure (c), where lower-depth institution nodes have higher uncertainty. In subsequent steps, we can construct an abstract map, as shown in (d), based on the uncertainty hierarchy extracted in (c).

[0032] The nodes in the uncertainty hierarchy tree in Figure 1(c) can be divided into three categories: non-leaf nodes, deterministic leaf nodes, and uncertain leaf nodes. Non-leaf nodes, such as "country," "province," and "city," represent upper-level regions and have a certain geographic location. Deterministic leaf nodes are leaf nodes that have no non-leaf sibling nodes, such as organization nodes with known locations. Uncertain leaf nodes are leaf nodes that have non-leaf sibling nodes, such as organization nodes with unknown locations.

[0033] S2. Perform abstract map node layout based on the spatial uncertainty hierarchy extracted in step S1.

[0034] As shown in Figure 1(d), non-leaf nodes and definite leaf nodes are laid out in a circular tree graph, and uncertain leaf nodes are placed at the boundary of their parent nodes.

[0035] Abstract map node layout is divided into two sub-steps, taking into account node hierarchy constraints, link relationships (i.e., nodes connected by trajectory paths should be relatively close), and geographic location (i.e., the node layout should approximate real-world geographic locations). To facilitate the description of the layout algorithm, non-leaf nodes and certain leaf nodes are collectively referred to as internal nodes, and uncertain leaf nodes are referred to as boundary nodes.

[0036] As shown in Figure 2, the internal node positions are first determined with the goal of preserving the relative geospatial position relationship; then the boundary node positions are determined with the goal of minimizing the trajectory path length.

[0037] That is, step S2 includes the following steps:

[0038] S21. Apply the circular tree graph layout algorithm to perform internal node layout.

[0039] Internal nodes sharing the same parent node are represented as a set of circles. A circular treemap layout algorithm is applied to compactly arrange the circles from the inside out. During the layout process, the edge chain is maintained. The edge chain is initialized with three tangent circles. Each time, two adjacent circles on the edge chain are selected and placed at their tangent points. This ensures that after the new circle is added, the angular relationships between all circles minimize their differences from the real-world angular relationships. Starting from the leaf nodes, the circles are nested hierarchically from bottom to top. The area of ​​a leaf node maps to the number of trajectories passing through it.

[0040] As shown in Figure 2(a), C m Indicates the center of the mth circle, and the hollow circles are the three tangent circles C with a determined layout. m-1 、C m and C m+1 , place circles one by one, the solid circle C is the newly inserted circle, and the newly inserted circle C is placed between the two adjacent circles C on the edge chain m and C m+1Pm represents the geographical location coordinates corresponding to the mth circle, and the new circle C is set on the boundary so that the two adjacent circles are tangent with the minimum loss of geographical angle.

[0041] S22. Layout the boundary nodes at the boundaries of their parent nodes.

[0042] For each boundary node, first calculate the center of gravity of its neighboring nodes. Then connect the center of the circle of its parent node with the center of gravity of the neighboring nodes. The intersection of this ray with the parent node's boundary is the center of the boundary node circle. If the newly placed boundary node overlaps with the position of an existing boundary node, a small offset is added until there is no overlap.

[0043] As shown in Figure 2(b), the neighboring nodes of the boundary node center C have centers C1, C2, C3, and C4, respectively, and the center of gravity of the neighboring nodes is G. The parent node is a dotted circle with center Cp. The boundary node center C is located at the intersection of the ray from the parent node center Cp to the neighboring node center G and the parent node's circumference. For example, in Figure 2(b), the position of C can be calculated from the angle α of the ray CpG and the radius of the circle Cp.

[0044] S3. Based on the abstract map node layout, the trajectory path is drawn using quadratic Bezier curves.

[0045] As shown in Figure 3, trajectories are represented by directed edges between nodes, drawn using quadratic Bezier curves, and the width of the edge between two nodes encodes the number of trajectories from the starting point to the end point.

[0046] The above embodiments show that the present invention discloses a trajectory visualization method that supports the expression of uncertain hierarchical spatial information. For trajectory data with uncertain hierarchical spatial information, the method obtains an optimized layout of abstract map nodes through constraints such as geographic space and link relationships, thereby avoiding misunderstandings caused by drawing uncertain locations on geographic maps. At the same time, the method retains known information and related relationships to the greatest extent, objectively and effectively reveals trajectory characteristics, and lays a solid foundation for the development of spatial information visualization.

[0047] The method described in the present invention is not limited to the embodiments described in the specific implementation manner. Those skilled in the art may derive other implementation manners based on the technical solution of the present invention, which also fall within the scope of the technical innovation of the present invention.

Claims

1. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information, the method comprising the following steps: S1. Extract spatial uncertainty levels from the spatial data to be expressed based on actual spatial information; S2, performing abstract map node layout according to the spatial uncertainty level extracted in step S1; S3. Based on the abstract map node layout, the trajectory path is drawn using quadratic Bezier curves.

2. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information according to claim 1, characterized in that: The tree nodes in the spatial uncertainty hierarchy extracted in step S1 are divided into non-leaf nodes, determined leaf nodes and uncertain leaf nodes. Determined leaf nodes refer to leaf nodes without non-leaf sibling nodes, and uncertain leaf nodes refer to leaf nodes with non-leaf sibling nodes.

3. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information according to claim 1, characterized in that: In step S2, the locations in the trajectory are organized into a nested circular structure according to the extracted spatial uncertainty hierarchy, and the locations with determined positions are placed inside the circle, and the uncertain locations are placed at the circle boundary.

4. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information according to claim 1, characterized in that: The abstract map node layout process in step S2 takes into account the spatial uncertainty level, link relationship and geographical location of the nodes.

5. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information as claimed in claim 2, characterized in that: Step S2 includes the following sub-steps: S21, applying a circular tree graph layout algorithm to perform internal node layout, wherein the internal nodes include non-leaf nodes and determined leaf nodes; S22. Layout the uncertain leaf nodes at the parent node boundary of the uncertain leaf nodes.

6. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information according to claim 5, characterized in that: In step S21, the internal nodes with the same parent node are represented as a group of circles, and the circular tree graph layout algorithm is applied. Starting from the leaf nodes, the circles are compactly arranged from the inside to the outside from the bottom up. During the internal node layout process, the edge chain is maintained. The edge chain is initialized to three tangent circles. After that, two adjacent circles on the edge chain are selected each time, and the new circle is placed at the tangent point.

7. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information according to claim 5, characterized in that: In step S22, for each uncertain leaf node, the center of gravity of its neighboring nodes is first calculated, and the center of gravity of the parent node of the uncertain leaf node is connected with the center of gravity of the neighboring nodes to obtain a ray. The intersection of the ray and the parent node boundary is the center of gravity of the uncertain leaf node. If the newly placed uncertain leaf node overlaps with the position of an existing uncertain leaf node, a small offset is added until there is no overlap between the uncertain leaf nodes.

8. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information according to claim 1, characterized in that: The trajectory path in step S3 is represented by directed edges between abstract map nodes.

9. A trajectory visualization method supporting the expression of uncertainty hierarchical spatial information according to claim 8, characterized in that: The width of the edge between two nodes in the trajectory path in step S3 encodes the number of trajectories from the starting point to the end point.

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