Boundary Detection of Debris-Covered Glaciers Using Fractal Analysis and Normalized Differencing of Thermal and Infrared Bands in Remote-Sensed Landsat Datasets

Overview

The importance of studying glacial melting to understand the impact of climate change is amplified by number of glaciers in the world and complicated by the feasibility of monitoring them individually. Remote sensing techniques such as multiyear satellite imaging provide a valuable dataset for such comprehensive surveillance. Prior work by the author demonstrates the utility of fractal analysis of glacier Landsat images to serve as a predictive indicator of glacial melt. Critical to such analysis is a clear delineation of glacial extent and boundaries. The complexities of determining glacial extent of debris-covered glaciers are considered in this study to explore methods of delineating the boundaries of such glaciers. Debris-covered glaciers present unique challenges to identifying glacier presence and glacier edges as the underlying glacier is not readily evident. Understanding and characterizing these features are important for several reasons, including preparedness in regions prone to glacial lake outburst floods. This study combined normalized differences of moisture and thermal band data with fractal analysis of the resulting datasets to impute boundaries of debris-covered glaciers. It further attempted to delineate these boundaries for the world’s youngest glacier – the Crater Glacier in Mt. St. Helens in Washington, USA. The results also show promise in determining glacier boundaries of debris-covered glaciers and demonstrate that the fractal dimensions of such boundaries may be indicative of sub-surface water (p < 0.001). Confirmatory analysis was performed by comparing the imputed boundaries with those gleaned by surface LiDAR surveys, and these reveal adequately close approximation of the imputed boundary.

Competition history

JSHS 2022 Category not listed

Resources

National JSHS abstract book

Related projects

ISEF · 2022