Glacier boundary extraction and spatiotemporal variation analysis in Geladandong region
Haotian Liu, Dongchuan Wang, Tingrong Li, Ang Yue, Shuang Zhao, Lihui Zhang, Kai Ye, Haotian Zhang, Shuaizheng Ji
TL;DR
This study uses a new remote sensing method to track glacier changes in the Geladandong region and finds that glaciers have been shrinking, especially in certain terrain conditions.
Contribution
The study introduces the NDI-RF method, which improves glacier boundary extraction accuracy compared to existing methods.
Findings
The NDI-RF method outperformed NDSI and Random Forest in glacier boundary extraction with higher Kappa, OA, F1-score, recall, and precision values.
Glaciers in the Geladandong region decreased by 110.29 km² from 2000 to 2024, with the most significant retreat occurring from 2010 to 2015.
Glacier retreat was most pronounced at lower altitudes, steeper slopes, and north-west facing slopes, and showed a negative correlation with rising temperatures.
Abstract
Glaciers, as sensitive indicators of global climate change, play a crucial role in influencing the global water cycle, sea level rise, and ecosystem dynamics. Understanding the interactive mechanisms between glacier boundary changes and multidimensional factors such as climate and topography is essential for revealing the complex relationships underlying the ecological functions supported by glacier systems. This study proposes a Remote Sensing Index–Random Forest fusion method (NDI-RF) to map glacial extent. The NDI-RF approach combines remote sensing index techniques with Random Forest modelling, ensuring the extraction accuracy of the Random Forest model while effectively enhancing boundary extraction precision in mosaic pixel scenarios. Then, the spatiotemporal changes in glacier extent and their response to climate change were analyzed. The experimental results indicate that the…
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Taxonomy
TopicsCryospheric studies and observations · Arctic and Antarctic ice dynamics · Climate change and permafrost