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T Kumpula: Remote sensing of cryogenic landslide activity in Central Yamal, Russia

Description

This presentation was held at the DUE Permafrost 2014 workshop, 12th of Febuary 2014, Frascati, Italy
Workshop: climate-cryosphere.org/meetings/due-permafrost-2014

 

T. Kumpula[1] T. Mikhaylova[2], M. Verdonen[1] & B.C. Forbes[3] 
[1] Department of Geographical and historical studies, University of Eastern Finland, Yliopistonkatu 7, 80101 Joensuu, Finland;
[2] Earth Cryosphere Institute Siberian Branch of Russian Academy of Science (ECISBRAS),
[3] Arctic Centre, University of Lapland, Box 122, 90601 Rovaniemi,

Finland In the late 1980’s there was high cryogenic landslide activity in Central Yamal peninsula, Arctic Russia. Database of satellite images was collected to follow landslide activity 1969-2013. Optical remote sensing imagery used were CORONA, Landsat MSS/TM/ETM7, SPOT, Terra ASTER VNIR, Quickbird-2 and Worldview-2 images from years 1969, 1988, 1993, 1998, 2001, 2004, 2011 & 2013. These image analysis will be combined to TerraSAR-X data and landslide dynamics can be followed accurately over 25 years. Field data was collected during several years and sites. Earliest data was collected in 1993. More recent data was collected in 2004, 2005, 2011 & 2013. From field for example vegetation, landslide spectral characteristics with ASD spectrometer, Leaf Area Index (LAI2200) were measured. CORONA image from 1969 is used as a starting date of analysis. Landsat TM image is dated from 1988 just before the major landslide event in 1989. This image was compared to SPOT (1993,1998), Landsat ETM+ (1999, 2001, 2011), Landsat TM (2011) and Terra ASTER VNIR (2001) images to detect occurred landslides. Quickbird-2 (2004) and Worldview-2 (2013) very high resolution images were used to interpretation and to detect small scale landslides (< 1 ha). TerraSAR-X data provides detailed terrain characteristics of landslide slopes. In data analysis we used ERDAS Imagine 2011 and ArcGIS 10. Final estimation of landslide occurrence was made with combined visual interpretations, change detection (NDVI), image classifications. Totally in the study area there were about 650 landslides.

Keywords: Remote sensing, Yamal, cryogenic landslides

 

 

 

 

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