Skip to main content
padlock icon - secure page this page is secure

The continuous spatio-temporal model (CSTM) as an exhaustive framework for multi-scale spatio-temporal analysis

Buy Article:

$60.00 + tax (Refund Policy)

When studying geographical phenomena, different levels of spatial and temporal granularity often have to be considered. While various approaches have been proposed to analyse geographical data in a multi-scale perspective, they have all focused on either spatial or temporal attributes rather than on the integration of space and time over multiple scales. This study introduces the continuous spatio-temporal model (CSTM), a conceptual model that seeks to address this shortcoming. The presented model is based on (1) the continuous temporal model (CTM), a multi-scale model for temporal information, and (2) the continuous spatial model (CSM), an extension of CTM for multi-scale spatial raster data. At the core of the presented conceptual model is a spatio-temporal evolution element or, in short, stevel, which is described by four variables: (1) pixel location, (2) spatial resolution, (3) temporal interval, and (4) temporal resolution. By varying one or more of these variables, a CSTM-tree consisting of (sets of) stevel arrays is created, forming the basis of an exhaustive CSTM-typology. These arrays can then be used to systematically cluster spatio-temporal information. The value of our approach is illustrated by means of a simplified example of mean temperature evolution. Various suggestions are made for modifications to be developed in future research.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: conceptual model; continuous spatio-temporal model (CSTM); multi-resolution analysis; multi-scale raster data; spatio-temporal evolution element (stevel)

Document Type: Research Article

Affiliations: 1: Department of Geography, Ghent University, Ghent, Belgium 2: Department of Environmental Sciences, Louisiana State University, Baton Rouge, LA, USA

Publication date: May 4, 2014

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more