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Activity Number: 431 - Contributed Poster Presentations: Section on Statistics and the Environment
Type: Contributed
Date/Time: Wednesday, August 10, 2022 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #323223
Title: Statistical Modeling for Estimating Mountain Glacier Variations Through Landsat Satellite Imagery
Author(s): Jonathan Webb* and Thu Thu Hlaing and Nezamoddin N. Kachouie
Companies: University of Idaho and Ithaca College and Florida Institute of Technology
Keywords: Climate Change; Glacier Variation; Landsat ; Terminus; Multiple Regression; Generalized Additive Models
Abstract:

Glaciers are important indictors of climate change as changes in glaciers physical features such as their area is in response to measurable evidence of fluctuating climate factors such as temperature, precipitation, and CO2. The remote nature of glaciers renders direct measurement impractical on anything other than a local scale. This project uses satellite imagery, taken by Landsat at regular intervals. The goal of this project is to quantify changes in the terminal point and area of Franz Josef and Gorner glaciers in response to climate factors. Multiple Regression and generalized additive models (GAM) are employed to identify significant climate factors that can explain and predict variations in the terminal point and area of the glaciers. Local temperature, CO2, and precipitation are identified as significant factors for predicting changes in the area of the Franz Josef glacier and movements in the terminal point of both, Franz Josef and Gorner glaciers. Area fluctuations in the Gorner glacier were best predicted by a generalized additive model including local and global temperature, CO2, and precipitation.


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