Effects of scale and data source in periglacial distribution modelling in a high arctic environment, western Svalbard

The effects of scale (modelling resolution) and sources of data were explored in relation to periglacial distribution modelling for an area on western Svalbard in the High Arctic. To assess the effects of scale on predictive performance, the distributions of sorted circles and solifluction lobes were modelled at two resolutions (20 × 20 m and 200 × 200 m) using a boosted regression tree, a novel statistical ensemble method. To analyse the effects of sources of data on periglacial distribution modelling, a generalised linear model and a variation partitioning method were used. The explanatory variables were topographic parameters computed from a digital elevation model, vegetation and soil moisture indices derived from a Landsat TM 5 scene, and field survey‐based information on surficial materials. Firstly, similar levels of success were achieved in predicting the periglacial feature distributions at the local (20 m) and landscape (200 m) scales. Secondly, results indicated the potential for modelling to replace labour‐intensive field observations. The importance of topographic parameters for predicting the distribution of periglacial features in the sparsely vegetated High Arctic environment was also evident. Methodologically, novel statistical techniques and earth observation data provided an efficient combination for analysing periglacial landforms and processes in this remote region. Copyright © 2010 John Wiley & Sons, Ltd.