Modelling patterned ground distribution in Finnish Lapland: An integration of topographical, ground and remote sensing information

摘要

New data technologies and modelling methods have gained more attention in the field of periglacial geomorphology during the last decade. In this paper we present a new modelling approach that integrates topographical, ground and remote sensing information in predictive geomorphological mapping using generalized additive modelling (GAM). First, we explored the roles of different environmental variable groups in determining the occurrence of non-sorted and sorted patterned ground in a fell region of 100 km(2) at the resolution of 1 ha in northern Finland. Second, we compared the predictive accuracy of ground-topography- and remote-sensing-based models.