TY  - JOUR
A1  - Ullmann, Tobias
A1  - Schmitt, Andreas
A1  - Roth, Achim
A1  - Duffe, Jason
A1  - Dech, Stefan
A1  - Hubberten, Hans-Wolfgang
A1  - Baumhauer, Roland
T1  - Land Cover  Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada
N2  - In this work the potential of polarimetric Synthetic Aperture Radar (PolSAR) data of dual-polarized TerraSAR-X (HH/VV) and quad-polarized Radarsat-2 was examined in combination with multispectral Landsat 8 data for unsupervised and supervised classification of tundra land cover types of Richards Island, Canada. The classification accuracies as well as the backscatter and reflectance characteristics were analyzed using reference data collected during three field work campaigns and include in situ data and high resolution airborne photography. The optical data offered an acceptable initial accuracy for the land cover classification. The overall accuracy was increased by the combination of PolSAR and optical data and was up to 71% for unsupervised (Landsat 8 and TerraSAR-X) and up to 87% for supervised classification (Landsat 8 and Radarsat-2) for five tundra land cover types. The decomposition features of the dual and quad-polarized data showed a high sensitivity for the non-vegetated substrate (dominant surface scattering) and wetland vegetation (dominant double bounce and volume scattering). These classes had high potential to be automatically detected with unsupervised classification techniques.
KW  - radar
KW  - arctic
KW  - tundra
KW  - land cover
KW  - classification
KW  - polarimetry
KW  - PolSAR
KW  - SAR
KW  - TerraSAR-X
KW  - Radarsat-2
Y1  - 2014
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-113303
ER  - 
TY  - JOUR
A1  - Dietz, Andreas J.
A1  - Conrad, Christopher
A1  - Kuenzer, Claudia
A1  - Gesell, Gerhard
A1  - Dech, Stefan
T1  - Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data
JF  - Remote Sensing
N2  - Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of similar to 4 Mio km(2). The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation.
KW  - AVHRR data
KW  - satellite
KW  - Northern Xinjiang
KW  - cloud
KW  - products
KW  - Central Asia
KW  - climate change
KW  - Amu Darya
KW  - Syr Darya
KW  - Tian Shan
KW  - snow
KW  - snow cover
KW  - snow cover duration
KW  - Pamir
KW  - AVHRR
KW  - MODIS
KW  - algorithm
KW  - validation
Y1  - 2014
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-114470
SN  - 2072-4292
VL  - 6
IS  - 12
ER  -