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Visualising and analysing time series data in GIS

Yi Qiang UGent, Katrin Asmussen UGent, Matthias Delafontaine UGent, Steven Logghe, Philippe De Maeyer UGent and Nico Van de Weghe UGent (2010) 13th AGILE conference on geographical information science : geospatial thinking, Abstracts.
abstract
This paper introduces an innovative representation of time series data, namely, the Continuous Triangular Model (CTM). In CTM, time series data of different intervals are displayed by a continuous field. Every position in the field represents a specific time interval. From the bottom to the top, the length of intervals increases. The value at each position represents a certain kind of information during the interval. In this paper, we show that CTM provides a direct overview of time series data at multiple scales. On the other hand, sets of intervals that are decided by values in the third dimension can be represented by areas in the CTM field, forming a basis for answering queries with non-temporal constraints. Besides time series data, CTM can also be applied to other types of sequential data. Since CTM represents data in a two-dimensional space, a lot of techniques in geographical information science are available to manipulate and analyse CTM.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
Geographical Information Science, Time Series Analysis, Triangular Model, Continuous Triangular Model, Time Interval
in
13th AGILE conference on geographical information science : geospatial thinking, Abstracts
conference name
13th AGILE conference on Geographical Information Science : Geospatial Thinking
conference location
Guimarães, Portugal
conference start
2010-05-11
conference end
2010-05-14
language
English
UGent publication?
yes
classification
C3
id
1233072
handle
http://hdl.handle.net/1854/LU-1233072
date created
2011-05-24 12:12:25
date last changed
2016-12-19 15:36:26
@inproceedings{1233072,
  abstract     = {This paper introduces an innovative representation of time series data, namely, the Continuous Triangular Model (CTM). In CTM, time series data of different intervals are displayed by a continuous field. Every position in the field represents a specific time interval. From the bottom to the top, the length of intervals increases. The value at each position represents a certain kind of information during the interval. In this paper, we show that CTM provides a direct overview of time series data at multiple scales. On the other hand, sets of intervals that are decided by values in the third dimension can be represented by areas in the CTM field, forming a basis for answering queries with non-temporal constraints. Besides time series data, CTM can also be applied to other types of sequential data. Since CTM represents data in a two-dimensional space, a lot of techniques in geographical information science are available to manipulate and analyse CTM.},
  author       = {Qiang, Yi and Asmussen, Katrin and Delafontaine, Matthias and Logghe, Steven and De Maeyer, Philippe and Van de Weghe, Nico},
  booktitle    = {13th AGILE conference on geographical information science : geospatial thinking, Abstracts},
  keyword      = {Geographical Information Science,Time Series Analysis,Triangular Model,Continuous Triangular Model,Time Interval},
  language     = {eng},
  location     = {Guimar{\~a}es, Portugal},
  title        = {Visualising and analysing time series data in GIS},
  year         = {2010},
}

Chicago
Qiang, Yi, Katrin Asmussen, Matthias Delafontaine, Steven Logghe, Philippe De Maeyer, and Nico Van de Weghe. 2010. “Visualising and Analysing Time Series Data in GIS.” In 13th AGILE Conference on Geographical Information Science : Geospatial Thinking, Abstracts.
APA
Qiang, Yi, Asmussen, K., Delafontaine, M., Logghe, S., De Maeyer, P., & Van de Weghe, N. (2010). Visualising and analysing time series data in GIS. 13th AGILE conference on geographical information science : geospatial thinking, Abstracts. Presented at the 13th AGILE conference on Geographical Information Science : Geospatial Thinking.
Vancouver
1.
Qiang Y, Asmussen K, Delafontaine M, Logghe S, De Maeyer P, Van de Weghe N. Visualising and analysing time series data in GIS. 13th AGILE conference on geographical information science : geospatial thinking, Abstracts. 2010.
MLA
Qiang, Yi, Katrin Asmussen, Matthias Delafontaine, et al. “Visualising and Analysing Time Series Data in GIS.” 13th AGILE Conference on Geographical Information Science : Geospatial Thinking, Abstracts. 2010. Print.