Estimation of Glacier Retreat from Landsat Images

• Activity Number: 619
• Type: Contributed
• Date/Time: Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Armin Schwartzman*+ and Joseph Usset and Arnab Maity and Ana-Maria Staicu
• Companies: North Carolina State University and North Carolina State University and North Carolina State University and North Carolina State University
• Keywords: Non-parametric Regression ; Change-Point Estimation ; Image analysis ; Climate change ; Remote sensing

Abstract

Mountain glacier retreat is an important problem related to temperature increase caused by global climate change. The retreat of mountain glaciers has been studied from the ground, but there exists a need for automated methods to catalog glacial change where ground measurements are not available. We propose a new statistical algorithm to track glacial termini over time from Landsat images. First, intensity profiles are obtained from the Landsat images along the glacier flow line and are smoothed using regression splines. Based on the assumption that the glacial terminus location lies near a point of high negative change in each smoothed profile, an algorithm is proposed that seeks a minimum of aggregated first derivative values across the profiles, to obtain a approximate path of termini locations over time. Then spline smoothing is applied to this approximate path for estimation of long-term terminus movement. The predictions from the method are evaluated on simulated data and compared to ground measurements obtained for the Franz Josef, Gorner, Rhone, and Nigardsbreen glaciers.