An automatic method for clean glacier and nonseasonal snow area change estimation in High Mountain Asia from 1990 to 2018

Abstract

Large-scale glacier area expansion or shrinkage is among the most conspicuous indicators of regional and global climate change. Glacier extraction from satellite images is an essential step in large-scale area change monitoring. However, glacier extraction is usually influenced by cloud cover and seasonal snow, and thus far, there is no effective and automatic method to monitor glacier area change in large regions. In this study, a new method ‘multi-temporal minimum NDSI composite’ is proposed for clean glacier and nonseasonal snow extraction, and the results agree well with the glacier inventory (excluding the debris part), except in Himalayan regions where non-seasonal snow exists widely out of glaciers. This method is also used to estimate the glacier and nonseasonal snow area changes in High Mountain Asia (HMA) over the past 29 years. With this method, we can use abundant Landsat images of summer seasons from continuous years to composite a cloud-free and seasonal snow-free glacial image pixel by pixel. Glacial maps for the whole HMA are produced every 10 years beginning in 1990, so glacier changes are presented in different subregions and periods. The number of images which is used to composite a glacial map in each pixel is also given for uncertainty analysis. According to the results, the clean glacier and nonseasonal snow area in HMA decreased by −0.43 ± 0.19%/a during 1990–2018 but had high temporal and spatial heterogeneity. Clean glacier and nonseasonal snow area decreased rapidly during 1990–2000, slowed down during 2000–2010, and then sped up during 2010–2018. The fastest reductions were in Hengduan Shan at rates of approximately −1.05 ± 0.09%/a, and the only area with growth (at a rate of 0.50 ± 0.11%/a) was in West Kun Lun during 1990–2018.