Spatial modeling of periglacial processes

Research themes

Determination of the environmental factors controlling earth surface processes and landform patterns in cold regions is one of the central themes in periglacial geomorphology. New statistical techniques and modelling methods have gained more attention in the field of periglacial geomorphology during the last decade. To deepen geomorphic understanding, it is crucial to examine robust methods to study the connection between geomorphic theory and field observations and, more importantly, to test these links. Here we focus on the different spatial modelling approaches that integrate topographical, ground and remote sensing information in predictive geomorphological mapping. Especially in the context of global change, spatial models are essential tools for assessing the impacts of changing environmental conditions on geomorphological processes.
The main objectives:

• Relative importance of different environmental drivers in periglacial processes
• Integration of climate, topography, ground and remote sensing information in spatial modelling of geomorphological processes
• Evaluation of statistical approaches for predictive geomorphological mapping

Staff

Professor PhD Jan Hjort (University of Oulu, Department of geography)
Professor PhD Miska Luoto (University of Helsinki, Department of Geography)

Research projects

Project: Global change impacts on sub-arctic palsa mires and greenhouse gas feedbacks to the climate system PALSALARM, Funded by Nordic Council of Ministers' Cooperation Programme for the Arctic (2006-2008)

Main publications

• Hjort, J. & M. Luoto. (In press). Statistical methods for geomorphic distribution modeling. In: Shroder, J., Jr., Baas, A.C.W. (Eds.). Treatise on Geomorphology: Quantitative Modeling in Geomorphology. Academic Press, San Diego.
• Hjort, J. & M. Luoto (2011). Novel theoretical insights into geomorphic process-environmen–relationships using simulated response curves. Earth Surface Processes and Landforms 36, 363–371.

• Hjort, J., Etzelmüller, B. & J. Tolgensbakk (2010). Effects of scale and data source in periglacial distribution modelling in a High Arctic environment, western Svalbard. Permafrost and Periglacial Processes 21, 345–354.
• Luoto, M., Marmion, M. & J. Hjort (2010). Assessing the spatial uncertainty in predictive geomorphological mapping: a multi-modelling approach. Computers and Geosciences 36, 355-361.
• Hjort, J. & M. Marmion (2009). Periglacial distribution modelling with a boosting method. Permafrost and Periglacial Processes 20, 15–25.
• Marmion, M., Hjort, J., Thuiller, W. & M. Luoto (2009). Statistical consensus methods for improving predictive geomorphology maps. Computers and Geosciences 35, 615–625.
• Hjort, J. & M. Marmion (2008). Effects of sample size on the accuracy of geomorphological models. Geomorphology 102, 341–350.
• Marmion, M., Hjort, J., Thuiller, W. & M. Luoto (2008). A comparison of predictive methods in modelling the distribution of periglacial landforms in Finnish Lapland. Earth Surface Processes and Landforms 33, 2241–2254.
• Luoto, M. & Hjort, J. (2008). Downscaling of coarse-grained geomorphological data. Earth Surface Processes and Landforms 33, 75-89.
• Hjort, J. & Luoto, M. (2008). Can abundance of geomorphological features be predicted using presence-absence data? Earth Surface Processes and Landforms 33, 741-75