Massive amount of vehicle trajectory data is an important data source and has been widely used in many research fields. However, due to the huge volume and variety of application scenarios, it is still not easy to achieve the application-oriented and efficient retrieval of vehicle trajectory. The paper proposes a multi-granularity vehicle trajectory index method based on the concept lattice model. The method identifies the multi-granularity feature regions for application requirements to segment vehicle trajectory and employs the concept lattice model to maintain the complex relationships between vehicle trip and the feature regions, to realize the vehicle travel trajectory data retrieval for the multi-granularity feature regions. In this experiment, shanghai city is divided into 21 feature regions according to the county-level area of Shanghai, and the concept lattice index structure of vehicle trips is constructed. The availability and efficiency of the proposed method are verified by the comparative experimental results.
Using GIS technology, this paper studied and evaluated the potential earthquake hazard existing in Memphis electric
substations. Two earthquake scenarios were selected in the potential earthquake hazard analysis at Memphis electric
substations. The moment magnitude of each scenario earthquake was set to 6.5, 7.0 and 7.5, all of which would put much
damage on the performance of the 44 electric substations in Memphis and Shelby County. The GIS map algebra
approach was applied to the analysis of the potential hazard that would result from each moment magnitude earthquake.
This included the reclassification and overlay of each spatial data layer. Four major kinds of data layers were included in
the study. Results about the relative potential hazard existing at each substation were illustrated in tables and analyzed.
The applicability of these results was also discussed.
KEYWORDS: Cameras, Data modeling, Geographic information systems, Information security, Video surveillance, Environmental monitoring, Network security, Computer security, Visual process modeling, Video
The paper presents a GIS-based approach to assisting video surveillance in micro-spatial environments, such as inside a
building. The approach consists of a node-arc network model representing the accessibility in a building and a
topological data structure maintaining the locational relationships among the accessibility network, accessible places,
and cameras' FOV (field of vision). Human walking behavior is considered in order to determine the spatial extent of
nodes and arcs in the accessibility network. Different measures are employed to deal with some special scenarios in a
building, such as spaces between two floors and large open spaces. Based on the network model and the data structure, a
number of applications can be realized. One of them elaborated in the paper is to quickly locate suspicious moving
objects. Besides the procedure, a detailed description is given to explain how to implement the procedure and how to link
the above research output to monitors and cameras.
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