Synoptic Maps Forecast Using Spatio-temporal Models

  • J. L. Crespo
  • P. Bernardos
  • M. E. Zorrilla
  • E. Mora
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4739)


The objective of this paper is to study several approaches to forecasting the temporal evolution of meteorological synoptic maps that carry information in visual form but without objects. Window-based descriptors are used in order to accomplish continuity so the prediction task is possible. Linear and non-linear models are applied for the prediction task, the first one being based on a spatio-temporal autoregressive (STAR) model whereas the second one is based on artificial neural networks. The method and obtained results are discussed.


Hide Layer Previous Time Step Prediction Task Numerical Descriptor Multiple Object Tracking 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • J. L. Crespo
    • 1
  • P. Bernardos
    • 1
  • M. E. Zorrilla
    • 2
  • E. Mora
    • 1
  1. 1.Department of Applied Mathematics and Computer Sciences, University of Cantabria. Avda. de los Castros s/n 39005 SantanderSpain
  2. 2.Department of Mathematics, Statistics and Computation, University of Cantabria. Avda. de los Castros s/n 39005 SantanderSpain

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