ORBi: Alvera Azcarate Aïda - Outlier detection in satellite data using spatial coherence

Reference : Outlier detection in satellite data using spatial coherence


	Document type :	Scientific journals : Article
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
	To cite this reference:	http://hdl.handle.net/2268/112582

Title :	Outlier detection in satellite data using spatial coherence
Language :	English
Author, co-author :	Alvera Azcarate, Aïda [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
	Sirjacobs, Damien [Université de Liège - ULg > Département des sciences de la vie > Phylogénomique des eucaryotes >]
	Barth, Alexander [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
	Beckers, Jean-Marie [Université de Liège - ULg > Département d'astrophysique, géophysique et océanographie (AGO) > GHER > >]
Publication date :	2012
Journal title :	Remote Sensing of Environment
Publisher :	Elsevier Science
Volume :	119
Pages :	84-91
Audience :	International
ISSN :	0034-4257
Keywords :	[en] Outlier detection ; Satellite Data ; Empirical Orthogonal Functions ; Sea Surface Temperature ; Chlorophyll-a concentration
Abstract :	[en] Satellite data sets often contain outliers (i.e., anomalous values with respect to the surrounding pixels), mostly due to undetected clouds and rain or to atmospheric and land contamination. A methodology to detect outliers in satellite data sets is presented. The approach uses a truncated Empirical Orthogonal Function (EOF) basis. The information rejected by this EOF basis is used to identify suspect data. A proximity test and a local median test are also performed, and a weighted sum of these three tests is used to accurately detect outliers in a data set. Most satellite data undergo automated quality-check analyses. The approach presented exploits the spatial coherence of the geophysical fields, therefore detecting outliers that would otherwise pass such checks. The methodology is applied to infrared sea surface temperature (SST), microwave SST and chlorophyll-a concentration data over different domains, to show the applicability of the technique to a range of variables and temporal and spatial scales. A series of sensitivity tests and validation with independent data are also conducted.
Research units :	Centre Interfacultaire de Recherches en Océanologie - MARE
Funders :	Politique Scientifique Fédérale (Belgique) = Belgian Federal Science Policy ; Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
Name of the research project :	HiSea, Geocolour
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/2268/112582
DOI :	10.1016/j.rse.2011.12.009
Other URL :	http://www.sciencedirect.com/science/article/pii/S0034425711004469

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