The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1753–1757, 2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1753–1757, 2019

  05 Jun 2019

05 Jun 2019


S. D. Jawak1, M. Joshi2,3, A. J. Luis4, P. H. Pandit5, S. Kumar6, S. F. Wankhede4, and Anirudh T. Somadas7 S. D. Jawak et al.
  • 1Svalbard Integrated Arctic Earth Observing System (SIOS), SIOS Knowledge Centre, University Centre in Svalbard (UNIS), P.O. Box 156, N-9171, Longyearbyen, Svalbard, Norway
  • 2Department of Geoinformatics, Mangalore University, Mangalore, Karnataka─574199, India
  • 3Divecha Centre for Climate Change, Indian Institute of Science, Bangalore, Karnataka – 560012, India
  • 4Earth System Science Organization - National Centre for Polar and Ocean Research, Ministry of Earth Sciences, Government of India, Headland Sada, Vasco-da-Gama, Goa 403804, India
  • 5National Bureau of Soil Survey and Land Use planning (NBSS & LUP) - Indian Agriculture Research Institute (IARI), New Delhi, India
  • 6Centre for Land Resource Management, Central University of Jharkhand, Ranchi – 835205, India
  • 7University of Twente, Faculty ITC, P. O. Box 217, 7500 AE Enschede, The Netherlands

Keywords: glacier velocity, image matching, pixel tracking, Landsat-8 OLI, Antarctic glacier

Abstract. Most of the glaciers have been retreating and thinning globally due to climate change. Glacier velocity is one such important parameter of glacier dynamics, which helps to understand the mass balance. The variations in velocity at different areas of the glacier can be used to identify the zones of ablation and accumulation. Zones of accumulation are identified as areas with higher velocity. This data is useful to incorporate in the glacier mass balance analysis. This study aims to derive the glacier velocity, using feature tracking technique for Potsdam glacier, east Antarctica. Feature tracking is an efficient way to derive glacier velocity, which is based on a cross-correlation algorithm that seeks offsets of the maximal correlation window on repeated satellite images. In this technique, two temporally different images are acquired for the same area and a distinct feature on both images is identified and the velocity is calculated with respect to the movement of that particular feature from one image to the other. Landsat-8 data for the year 2016 was used to derive velocity. Finer resolution promotes better feature tracking so the panchromatic band (band 8) of Landsat-8 OLI with a resolution of 15 m was utilized for deriving velocity. This technique was performed using COSI-Corr module in ENVI. This tool calculates displacement between the east-west and north-south directions, and the resultant velocity is calculated using the displacement in both directions and the temporal difference of two images. The velocity map generated at a resolution of 240 m showed that the resultant velocity ranged between 18.60 and 285.28 ma−1. Bias and root mean square error (RMSE) have been calculated with respect to the point-by-point MEaSUREs data provided by National Snow and Ice Data Centre at 1000 m resolution. The RMSE was found to be 78.06 ma−1 for 2016. The velocity for Potsdam glacier was also pictorially validated with the DGPS measurements from literature.