期刊
PERMAFROST AND PERIGLACIAL PROCESSES
卷 18, 期 2, 页码 115-127出版社
WILEY
DOI: 10.1002/ppp.584
关键词
periglacial features; distribution modelling; logistic regression; hierarchical partitioning; subarctic; Finland
Identification of the environmental drivers of geomorphological processes in cold regions is a central topic in periglacial research. The objective of this study was to develop and test a methodology to: (1) predict the occurrence of palsas, earth hummocks, sorted solifluction sheets and periglacial deflation sites in a subarctic landscape and (2) determine the most important environmental factors affecting the distribution of these features at the landscape scale. The study was performed using an empirical ly-derived data-set of landforms from an area of 600 km(2) in northern Finland at a 25 ha resolution (n = 2272). Logistic regression and hierarchical partitioning were used to analyse the data and the predictive performance of the models was evaluated using area under the curve (AUC) measures. The explanatory variables highlighted as important predictors of the occurrence of periglacial features coincided well with the hypothesised determinants. Predictions for palsa, earth hummock and sorted solifluction sheet models were excellent (AUC = 0.92-0.95) and the deflation site model was good (AUC = 0. 8 1). The results encourage further application of the grid-based modelling approach, for example in predicting feature occurrences in other periglacial regions, studying scale dependency of proces s- environment interactions and determining the effect of climate change on the distribution of frost-related processes. Copyright (C) 2007 John Wiley & Sons, Ltd.
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