Features detection in spatial point processes via multivariate techniques
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http://dx.doi.org/10.1002/env.1028 |
Metadatos
Título
Features detection in spatial point processes via multivariate techniquesFecha de publicación
2010Editor
John Wiley & Sons, Ltd.ISSN
1180-4009Cita bibliográfica
Environmetrics Special Issue: Spatio-Temporal Stochastic Modelling: Environmental and Health Processes (2010) 21, 3-4, p. 400-414Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://onlinelibrary.wiley.com/doi/10.1002/env.1028/abstractPalabras clave / Materias
Resumen
We consider the problem of detecting features of general shape in spatial point processes in the presence of substantial clutter. Our goal is to remove clutter from images where one or several features are present and ... [+]
We consider the problem of detecting features of general shape in spatial point processes in the presence of substantial clutter. Our goal is to remove clutter from images where one or several features are present and have to be detected. We use a method based on local indicators of spatial association (LISA) functions. Each LISA function is considered an observation in a multidimensional space. We thus perform cluster and multidimensional scaling to classify these observations, and in turn to discriminate between points belonging to the feature and clutter points. Two environmental problems based on forest fires and earthquakes are developed. [-]
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Copyright © 2009 John Wiley & Sons, Ltd.
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