Application of Landsat-7 satellite data and a DEM for the quantification of thermokarst-affected terrain types in the periglacial Lena–Anabar coastal lowland
Version of Record online: 8 JAN 2007
Volume 25, Issue 1, pages 51–67, January 2006
How to Cite
Grosse, G., Schirrmeister, L. and Malthus, T. J. (2006), Application of Landsat-7 satellite data and a DEM for the quantification of thermokarst-affected terrain types in the periglacial Lena–Anabar coastal lowland. Polar Research, 25: 51–67. doi: 10.1111/j.1751-8369.2006.tb00150.x
- Issue online: 8 JAN 2007
- Version of Record online: 8 JAN 2007
Extensive parts of Arctic permafrost-dominated lowlands were affected by large-scale permafrost degradation, mainly through Holocene thermokarst activity. The effect of thermokarst is nowadays observed in most periglacial lowlands of the Arctic. Since permafrost degradation is a consequence as well as a significant factor of global climate change, it is necessary to develop efficient methods for the quantification of its past and current magnitude. We developed a procedure for the quantification of periglacial lowland terrain types with a focus on degradation features and applied it to the Cape Mamontov Klyk area in the western Laptev Sea region. Our terrain classification approach was based on a combination of geospatial datasets, including a supervised maximum likelihood classification applied to Landsat-7 ETM+ data and digital elevation data. Thirteen final terrain surface classes were extracted and subsequently characterized in terms of relevance to thermokarst and degradation of ice-rich deposits. 78% of the investigated area was estimated to be affected by permafrost degradation. The overall classification accuracy was 79%. Thermokarst did not develop evenly on the coastal plain, as indicated by the increasingly dense coverage of thermokarst-related areas from south to north. This regionally focused procedure can be extended to other areas to provide the highly detailed periglacial terrain mapping capabilities currently lacking in global-scale permafrost datasets.