Journal
REMOTE SENSING OF ENVIRONMENT
Volume 113, Issue 6, Pages 1220-1235Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2009.02.009
Keywords
Field spectrometry; Spectral properties; Land-cover classification; Periglacial surface features; Lena Delta; North Siberia
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Important environmental parameters in arctic periglacial landscapes (i.e. permafrost temperature, active-layer depth, soil moisture, precipitation. vegetation cover) will very likely change in a warming climate. The thawing of permafrost, especially. might cause massive landscape changes due to thermokarst and an enhanced release of greenhouse gasses from the large amounts of carbon stored in frozen deposits, resulting in positive climate-warming feedback. For the identification, mapping, and quantification of such changes on various scales up to the entire circum-Arctic, remote sensing and spatial data analysis are essential tools. In this study an extensive field-work dataset including spectral surface properties, vegetation, soils, and geomorphology was acquired in the largest Arctic delta formed by a single river, the Siberian Lena River Delta. A portable field spectrometer (ASD FieldSpec Pro FR (R)) was used for spectral surveys of terrain surfaces, and optical satellite data (Landsat Enhanced Thematic Mapper (ETM+), CHRIS-Proba) were used for the characterization, manual mapping, and automatic classification of typical periglacial land-cover units in the Lena Delta. Qualitative data from soils, vegetation, soil moisture. and relief units were correlated with the field-spectral data and catalogued for a wide variety of surface types. The wide range of micro- and mesoscale variations of periglacial surface features in the delta results in distinctive spectral characteristics for different land-cover units. The three main delta terraces could also be spectrally separated and characterized. The present dataset provides a basis for further spectral data acquisitions in the Lena Delta and for comparisons with periglacial surfaces from other regions. (C) 2009 Elsevier Inc. All rights reserved.
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