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Evaluation of Soil Data Interpolation Methods

dc.contributor.authorMattei, Mirjam
dc.contributor.authorArgento, Francesco
dc.contributor.authorCockburn, Marianne
dc.contributor.editorGandorfer, Markus
dc.contributor.editorMeyer-Aurich, Andreas
dc.contributor.editorBernhardt, Heinz
dc.contributor.editorMaidl, Franz Xaver
dc.contributor.editorFröhlich, Georg
dc.contributor.editorFloto, Helga
dc.date.accessioned2020-03-04T13:06:28Z
dc.date.available2020-03-04T13:06:28Z
dc.date.issued2020
dc.description.abstractApplying geostatistical interpolation methods that predict soil properties of the surrounding area may present an efficient solution to create interpolation maps for site-specific field management. These statistical methods produce different distributions of interpolated data. According to the data type, different methods are appropriate. In this study, we compared Kriging and Inverse Distance Weighting to determine the potential application within management zones. Therefore, we interpolated soil mineral nitrogen content (Nmin) data. We evaluated the accuracy of real vs. predicted data by bootstrapping and considering the standard error. Both interpolation methods were able to predict the Nmin content with a root mean square error of below 0.025.en
dc.identifier.isbn978-3-88579-693-0
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/31889
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof40. GIL-Jahrestagung, Digitalisierung für Mensch, Umwelt und Tier
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-299
dc.subjectInterpolation
dc.subjectsite-specific fertilisation
dc.subjectmanagement zones
dc.subjectNmin
dc.titleEvaluation of Soil Data Interpolation Methodsen
dc.typeText/Conference Paper
gi.citation.endPage174
gi.citation.publisherPlaceBonn
gi.citation.startPage169
gi.conference.date17.-18. Februar 2020
gi.conference.locationWeihenstephan, Freising

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