Because it has similar spectral characteristics as glaciers, snow around glaciers is a complicating factor in glacier inventory from satellite images. It is rare to acquire snowless and cloud-free satellite images in perennial snow mountain regions, and, moreover, glaciers are also usually shaded by mountain shadows. Therefore, a monotemporal satellite image can hardly map an intact glacier boundary. An object-oriented image segmentation method is proposed to map glaciers and their changes with multitemporal Landsat imagery. First, a “global-local” iteration segmentation method was used to delineate the snow and ice boundaries with each single phase image. Second, the mountain shadows of multitemporal Landsat images with different sun angles were mapped by methods of terrain analyses, and some parts of the glaciers inside these shadow regions can be identified. Finally, the complete glacier boundaries were restored with multitemporal images, and then these boundaries were intersected to get the minimum glacier extents. The method was tested with multitemporal Landsat images during 1977–2013 in the eastern Tienshan Mountains of Central Asia, and the spatial patterns and temporal process of these glacier changes in the last years were also analyzed. The results showed that the proposed method performs well in mapping glaciers in rugged alpine regions. Combining multiple images in different seasons provides a more effective way of removing disturbing factors during the process of glacier extraction. The total glacier area in the eastern Tienshan Mountains has decreased to 106.83 km2 in 2013, with a loss of 21.5% since 1977, and the rate of glacier shrinkage accelerates in recent decades. The relationship between glacier recession and river runoffs was also analyzed, and the results showed that small glaciers whose areas are about 1.1 km2 provide less runoff than those larger glaciers with about 2.5 km2.
Automatic remotely sensed glacier mapping in high mountainous areas is restricted due to confusion of glacier and snow. Most of current methods map glacier boundaries with a single remote sensing image, but it is hard to find one snow-free one cloud-free image. The paper presents an object-oriented image segmentation to delineate the full glacier extents with multi-temporal Landsat images and digital elevation models (DEM). Landsat images with different acquisition dates are limited within one or two year, so as to map the glacier extents with minimum snow coverage. Topographic features derived from DEMs and different solar angles are also used to separate mountain shadows from glaciers, so the glaciers shaded by mountain shadows can also be identified. The method is tested with 6 Landsat images (2009-2010) and SRTM DEM data in Bogeda Mountain of Tienshan Mountain, Xinjiang ,China. It showed that the minimum glacier extents derived with the proposed method can accurately match the SPOT-5 glacier map, and the geometric accuracy is less than 30 meters. Results are satisfying for annual glacier mapping for glacier change detection studies.
Lakes in arid regions of Central Asia act as essential components of regional water cycles, providing sparse but valuable
water resource for the fragile ecological environments and human lives. Lakes in Central Asia are sensitive to climate
change and human activities, and great changes have been found since 1960s. Mapping and monitoring these inland
lakes would improve our understanding of mechanism of lake dynamics and climatic impacts. ICESat/GLAS satellite
laser altimetry provides an efficient tool of continuously measuring lake levels in these poorly surveyed remote areas. An
automated mapping scheme of lake level changes is developed based on GLAS altimetry products, and the spatial and
temporal characteristics of 9 typical lakes in Central Asia are analyzed to validate the level accuracies. The results show
that ICESat/GLAS has a good performance of lake level monitoring, whose patterns of level changes are the same as
those of field observation, and the max differences between GLAS and field data is 3cm. Based on the results, it is
obvious that alpine lakes are increasing greatly in lake levels during 2003-2009 due to climate change, while open lakes
with dams and plain endorheic lakes decrease dramatically in water levels due to human activities, which reveals the
overexploitation of water resource in Central Asia.
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