Supplementary Data for Manuscript "Machine Learning Driven Glacier Thickness Estimation in Diverse Continental Glaciers Using Innovative Pixel Based Skeletonization Approach"
收藏Zenodo2026-04-07 更新2026-05-26 收录
下载链接：
https://zenodo.org/doi/10.5281/zenodo.18640484
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资源简介：
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
提供机构：
Zenodo
创建时间：
2026-04-07
