A spatio-temporal normalization method for geophysical data

The objective of the study was to introduce a normalization algorithm which highlights short-term, localized, non-periodic fluctuations in hyper-temporal satellite data by dividing each pixel by the mean value of its spatial neighbourhood set. The algorithm was designed to suppress signal patterns that are common in the central and surrounding pixels, utilizing spatial and temporal information at different scales.

Identifier
DOI https://doi.org/10.17026/dans-x7r-kgnr
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-kc-clcq
Related Identifier https://doi.org/10.1016/j.cageo.2016.02.016
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:112683
Provenance
Creator Pavlidou, E.
Publisher Data Archiving and Networked Services (DANS)
Contributor Meijde, M. van der; Hecker, C.A.; Werff, H.M.A. van der
Publication Year 2018
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/publicdomain/zero/1.0; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Representation
Language English
Resource Type Dataset
Discipline Other