TY - JOUR
T1 - Applicability of Landsat 8 data for characterizing glacier facies and supraglacial debris
AU - Bhardwaj, Anshuman
AU - Joshi, P. K.
AU - Snehmani, null
AU - Sam, Lydia
AU - Singh, Mritunjay Kumar
AU - Singh, Shaktiman
AU - Kumar, Rajesh
N1 - Acknowledgements
The authors would like to thank Editor-in-Chief Prof. F.D. van der Meer, Associate editor Prof. A. Stein and anonymous reviewers for insightful comments and suggestions which improved a previous version of this manuscript. The authors express their gratitude to Ms Anusheema Chakraborty for editing English language.
PY - 2015/6
Y1 - 2015/6
N2 - The present work evaluates the applicability of operational land imager (OLI) and thermal infrared sensor (TIRS) on-board Landsat 8 satellite. We demonstrate an algorithm for automated mapping of glacier facies and supraglacial debris using data collected in blue, near infrared (NIR), short wave infrared (SWIR) and thermal infrared (TIR) bands. The reflectance properties in visible and NIR regions of OLI for various glacier facies are in contrast with those in SWIR region. Based on the premise that different surface types (snow, ice and debris) of a glacier should show distinct thermal regimes, the ‘at-satellite brightness temperature’ obtained using TIRS was used as a base layer for developing the algorithm. This base layer was enhanced and modified using contrasting reflectance properties of OLI bands. In addition to facies and debris cover characterization, another interesting outcome of this algorithm was extraction of crevasses on the glacier surface which were distinctly visible in output and classified images. The validity of this algorithm was checked using field data along a transect of the glacier acquired during the satellite pass over the study area. With slight scene-dependent threshold adjustments, this work can be replicated for mapping glacier facies and supraglacial debris in any alpine valley glacier.
AB - The present work evaluates the applicability of operational land imager (OLI) and thermal infrared sensor (TIRS) on-board Landsat 8 satellite. We demonstrate an algorithm for automated mapping of glacier facies and supraglacial debris using data collected in blue, near infrared (NIR), short wave infrared (SWIR) and thermal infrared (TIR) bands. The reflectance properties in visible and NIR regions of OLI for various glacier facies are in contrast with those in SWIR region. Based on the premise that different surface types (snow, ice and debris) of a glacier should show distinct thermal regimes, the ‘at-satellite brightness temperature’ obtained using TIRS was used as a base layer for developing the algorithm. This base layer was enhanced and modified using contrasting reflectance properties of OLI bands. In addition to facies and debris cover characterization, another interesting outcome of this algorithm was extraction of crevasses on the glacier surface which were distinctly visible in output and classified images. The validity of this algorithm was checked using field data along a transect of the glacier acquired during the satellite pass over the study area. With slight scene-dependent threshold adjustments, this work can be replicated for mapping glacier facies and supraglacial debris in any alpine valley glacier.
KW - Glacier facies
KW - Landsat 8
KW - Remote sensing
KW - Supraglacial debris
UR - http://www.scopus.com/inward/record.url?scp=84941649630&partnerID=8YFLogxK
U2 - 10.1016/j.jag.2014.12.011
DO - 10.1016/j.jag.2014.12.011
M3 - Article
AN - SCOPUS:84941649630
VL - 38
SP - 51
EP - 64
JO - International Journal of Applied Earth Observation and Geoinformation
JF - International Journal of Applied Earth Observation and Geoinformation
SN - 0303-2434
ER -