Determining Glacier Drift Ages Using Multispectral Remote Sensing Data

• Main Author: Crock, Paula
• Format: Text
• Language: unknown
• Published: UND Scholarly Commons 2017
• Subjects: Ong Valley; Transantarctic Mountains; Antarc*; Antarctica
• Online Access: https://commons.und.edu/theses/2106; https://commons.und.edu/cgi/viewcontent.cgi?article=3107&context=theses

Determining the ages of glacier drifts in Antarctica can help paleoclimatologists determine the changes Earth’s climate has gone through and thereby inform models for future climate change prediction. However, many of these drifts are difficult to reach for sample collection necessary to determine their ages. This research attempts to use multispectral remote sensing data to expand the mapping of drift ages from known point measurements regionally. This research is based on existing drift ages from Ong Valley, Transantarctic Mountains. Two methods were used to determine a combination of the image band data that would sufficiently distinguish the three age-distinct drift regions: Principal Component Analysis (PCA) and an empirical analysis based on observed trends in the data. The PCA results showed that virtually all bands contribute equally to the differences in the image data from the three drift regions, precluding the use of a small number of bands in an index to classify the regions. An index was developed from the empirical analysis but this index was unable to sufficiently overcome the count variations in the data sets to successfully classify the regions. Although neither method provided a conclusive means to distinguish the drift regions from the remote sensing data used in this analysis other remote sensing data, e.g. – data at different or more extensive bands ranges, or other analysis techniques, e.g. – more preprocessing of the data or machine learning algorithms applied to the image data, may yet yield successful results.