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Article

Multivariate Analysis of Geological Data for Regional Studies of Geodiversity

1
Norwegian Institute for Nature Research, NO-0855 Oslo, Norway
2
Geological Survey of Norway, NO-7491 Trondheim, Norway
3
Geological Survey of Sweden, SE-75128 Uppsala, Sweden
*
Author to whom correspondence should be addressed.
Academic Editor: Paulo Pereira
Resources 2022, 11(6), 51; https://doi.org/10.3390/resources11060051
Received: 12 April 2022 / Revised: 10 May 2022 / Accepted: 18 May 2022 / Published: 24 May 2022
(This article belongs to the Special Issue Geodiversity Assessment: What, Why and How?)
In Norway, a landscape map exists which gives the opportunity to collect data in landscape units for further analysis. This study covers parts of Norway and Sweden, so the landscape map was extended into Sweden to form a unified landscape structure. A collection of geological and terrain data within landscape units can serve as a tool to describe the geodiversity profile of the units, study their geographical distribution and analyse similarities and dissimilarities between them. We collected geological and terrain data for an area covering large parts of southern Norway and Sweden. The data were collected as attributes in landscape polygons. The data were then analysed using multivariate techniques (Principle component analyses) where the first four axes of variation were definable. The first axis is a terrain axis, the second a bedrock unit axis, the third a bedrock diversity axis and the fourth a soil/sediment axis. In total, the four gradients answer for 54.9% of the total variation in the material. Links are found between the terrain data and geological units, but these links are relatively weak. The four gradients represent a step-less model of the geodiversity profile of the landscape areas but are dependent on the quality and scale of the input data. Norwegian and Swedish data had to be harmonised in order to be analysed together; however, because of this they ended up having a coarser resolution than desired, both spatially and scientifically. The stepless model was clustered to form 16 geodiversity profile groups for easy comparison and regional overview. The procedure can serve as a baseline for more detailed and field-based studies of geodiversity profiles, and give the opportunity to make analytical maps through simple overlay techniques and to compare areas with each other with respect to their geodiversity profile. This can be carried out both alone and in a wider landscape setting. View Full-Text
Keywords: geodiversity profile; geodiversity clustering; landscape; multivariate analysis geodiversity profile; geodiversity clustering; landscape; multivariate analysis
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MDPI and ACS Style

Erikstad, L.; Bakkestuen, V.; Dahl, R.; Arntsen, M.L.; Margreth, A.; Angvik, T.L.; Wickström, L. Multivariate Analysis of Geological Data for Regional Studies of Geodiversity. Resources 2022, 11, 51. https://doi.org/10.3390/resources11060051

AMA Style

Erikstad L, Bakkestuen V, Dahl R, Arntsen ML, Margreth A, Angvik TL, Wickström L. Multivariate Analysis of Geological Data for Regional Studies of Geodiversity. Resources. 2022; 11(6):51. https://doi.org/10.3390/resources11060051

Chicago/Turabian Style

Erikstad, Lars, Vegar Bakkestuen, Rolv Dahl, Mari Lie Arntsen, Annina Margreth, Tine Larsen Angvik, and Linda Wickström. 2022. "Multivariate Analysis of Geological Data for Regional Studies of Geodiversity" Resources 11, no. 6: 51. https://doi.org/10.3390/resources11060051

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