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dc.contributor.authorGrimvall, Anders
dc.contributor.authorWackernagel, Hans
dc.contributor.authorLajaunie, Christian
dc.contributor.editorHilty, Lorenz M.
dc.contributor.editorGilgen, Paul W.
dc.date.accessioned2019-09-16T09:32:08Z
dc.date.available2019-09-16T09:32:08Z
dc.date.issued2001
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/26763
dc.description.abstractNormalisation of environmental data aims at clarifying the human impact on the environment by suppressing meteorologically driven fluctuations and other natural variation in the collected data. This paper shows that the procedures presently used to adjust ai r and water quality data have a common probabilistic framework. Furthermore, this framework can support a number of new techniques for the normalisation of both temporal and spatial patterns in environmental data. In particular, it is shown that deterministic, physics-based models can be incorporated into statistical normalisation procedures.de
dc.description.urihttp://enviroinfo.eu/sites/default/files/pdfs/vol104/0583.pdfde
dc.publisherMetropolis
dc.relation.ispartofSustainability in the Information Society
dc.relation.ispartofseriesEnviroInfo
dc.titleNormalisation of Environmental Quality Datade
dc.typeText/Conference Paper
dc.pubPlaceMarburg
mci.conference.sessiontitleEnvironmental Statistics
mci.conference.locationZürich
mci.conference.date2001


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