Supplementary Data for Manuscript "Machine Learning Driven Glacier Thickness Estimation in Diverse Continental Glaciers Using Innovative Pixel Based Skeletonization Approach"

This dataset contains the trained XGBoost-based glacier thickness prediction Machine learning models and the associated GUI tool developed for the manuscript titled: Machine Learning Driven Glacier Thickness Estimation in Diverse Continental Glaciers Using Innovative Pixel Based Skeletonization Approach. The repository includes: Trained XGBoost models for six study glaciers (Bara Shigri, Gangotri, Zemu, Aletsch, Koxkar, and Saskatchewan) The developed GUI-based application for glacier thickness prediction Sample input datasets required to run the model Example output thickness maps