![Masters Theses](../../assets/md5images/ebc0648ded2cd429f55e0a2fe4407546.gif)
Masters Theses
Date of Award
8-2000
Degree Type
Thesis
Degree Name
Master of Science
Major
Geography
Major Professor
Bruce Ralston
Committee Members
Cheng Liu, Shih-Lung Shaw
Abstract
Time, location, and attributes are three elements of a GIS, but all commercial GIS packages can only handle location and attributes; they are in fact a static GIS. Spatiotemporal GIS has been a hot research topic recentlySpatiotemporal GIS and its application in transportation research are still prematureThis thesis focuses on spatiotemporal query problems on travel data Specifically, It attempts to answer this question during a time period which trips pass through one or more specific streets? To speed up this spatiotemporal query for large data sets, a spatiotemporal index on the trip data is built by combining Avenue, AML, and C+. All the trip origin ends and those last destination ends for each individual on each day are geocoded using Avenue scripts The trip shortest path route system is created based on ArcInfo dynamic segmentation and network analysis functionsAn array of 2-D tree structures based on each trip's beginning time and ending time and each street traversed are then created in C++ and AvenueThis array of 2-D tree structures is stored in memory. Finally, the spatiotemporal query function is performed by examining the array of 2-D tree structures for a given time window using Avenue and C++. A sample trip log data file in the Knoxville Metropolitan Area and Knox county street shape file are used to implement the spatiotemporal query. This thesis is concluded that efficient indexing methods must be developed to handle complicated spatiotemporal queries for large travel data sets
Recommended Citation
Lü, Feng, "A spatiotemporal indexing method for disaggregate transportation data. " Master's Thesis, University of Tennessee, 2000.
https://trace.tennessee.edu/utk_gradthes/9418