Measuring glacier changes in the Tianshan Mountains over the past 20 years using Google Earth Engine and machine learning

Abstract

Glaciers in the Tianshan Mountains are an essential water resource in Central Asia, and it is necessary to identify their variations at large spatial scales with high resolution. We combined optical and SAR images, based on several machine learning algorithms and ERA-5 land data provided by Google Earth Engine, to map and explore the glacier distribution and changes in the Tianshan in 2001, 2011, and 2021. Random forest was the best performing classifier, and the overall glacier area retreat rate showed acceleration from 0.87%/a to 1.49%/a, while among the sub-regions, Dzhungarsky Alatau, Central and Northern/Western Tianshan, and Eastern Tianshan showed a slower, stable, and sharp increase rates after 2011, respectively. Glacier retreat was more severe in the mountain periphery, low plains and valleys, with more area lost near the glacier equilibrium line. The sustained increase in summer temperatures was the primary driver of accelerated glacier retreat. Our work demonstrates the advantage and reliability of fusing multisource images to map glacier distributions with high spatial and temporal resolutions using Google Earth Engine. Its high recognition accuracy helped to conduct more accurate and time-continuous glacier change studies for the study area.