Title
Linking movement and environmental data: The need for representation
Abstract
In several domains, there has been an increasing interest in analysing moving objects due to the recent ubiquity of location tracking devices. These locations are commonly abstracted and stored as trajectories: a finite set of ordered in time geometries. Tracked objects tend to move in a certain environment that influences their movement behaviour. Time dependent environmental data are commonly abstracted and stored in grid/array structures that have different granularities and characteristics compare to the trajectory datasets. Movement analysis requires linking these two data types. However, little consideration has been given to the issues of integration in the moving objects databases that is primarily dealing with trajectory storage and analysis as well as in array databases dealing mainly with the storage and retrieval of grid structures. In this paper, we propose a database model that utilizes abstract data types for combining trajectories and time dependent environmental data. We introduce a set of spatio-temporal operations for interacting with raster data and integrating them with the moving geometries. We demonstrate how the integration operations can be used for manipulation and analysis of moving objects, using trajectories of tropical cyclone and environmental data, using sea surface temperature (SST) for the period from 1980 to 2009 as a case study. Since tropical cyclones generally gain strength over the warmer seas, the proposed operations are used to answer questions about genesis and movement patterns of tropical cyclones, in relation to the changing patterns of the SST. (C) 2015 Elsevier B.V. All rights reserved.
Year
DOI
Venue
2016
10.1016/j.jag.2015.10.012
International Journal of Applied Earth Observation and Geoinformation
Keywords
Field
DocType
Movement data,Environmental data,Spatiotemporal representation,Spatiotemporal data integration,Movement behaviour
Abstract data type,Data mining,Raster data,Database model,Sea surface temperature,Remote sensing,Data type,Environmental data,Geography,Trajectory,Grid
Journal
Volume
ISSN
Citations 
45
0303-2434
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
Ahmed Ibrahim162.38
Ulanbek D. Turdukulov2213.13
Menno-Jan Kraak338633.93