Landscapes and thermokarst lake area changes in Yedoma regions under modern climate conditions, Kolyma lowland tundra

• Main Authors: Veremeeva, Alexandra, Glushkova, Nadezhda, Günther, Frank, Nitze, Ingmar, Grosse, Guido
• Format: Conference Object
• Language: unknown
• Published: 2016
• Subjects: Ice; permafrost; Thermokarst; Tundra; wedge*; Yakutia
• Online Access: https://epic.awi.de/id/eprint/42540/; https://epic.awi.de/id/eprint/42540/1/ICOP_2016_Book-of-Abstracts_605.pdf; https://hdl.handle.net/10013/epic.49198; https://hdl.handle.net/10013/epic.49198.d001

Recent landscape changes in the Yedoma region are particularly pronounced in varying thermokarst lake areas reflecting the reaction of the land surface on modern climate changes. However, although thermokarst lake change detection is essential for the quantification of water body expansion and drainage within a region, remote sensing-derived surface reflection trends additionally provide valuable information about the general landscape development. The aim of this research is to reveal the regularities of landscape and thermokarst lakes area changes in the Kolyma lowland tundra in comparison with meteorological data and geological and geomorphological features. The Kolyma lowland tundra occupies about 44500 km2 and is located in Northeast Yakutia within the continuous permafrost zone. Mapping of Quaternary deposits using Landsat images shows that Yedoma (Last Pleistocene remnants formed by ice-rich silty to sandy syngenetic deposits with large polygonal ice wedges) occupies only 16 % of the entire region, while the largest part of it is occupied by alas complex (72 %), formed as a result of Yedoma thaw during the Holocene (Veremeeva and Glushkova, 2016). For the analysis of the landscape and thermokarst lakes area changes of the last 15 years, the entire available Landsat archive from 1999 until 2015 was used for time-series analysis. For this purpose around 800 scenes were processed with an automated workflow, undergoing several necessary processing steps, such as masking, data distribution and calculation of multi-spectral indices. Multi-spectral indices (Landsat Tasseled Cap, NDVI, NDWI, NDMI) were calculated for each unobstructed (cloud-, shadow- and snow-free) observation within the summer months (June to September) between 1999 and 2015. A robust linear trend analysis has been applied to each pixel for the spatial representation of changes of different land surface properties over the observation period. This map shows the magnitude and direction of changes for each multi-spectral index, which are used as ...