The accurate and rapid extraction of glacier boundaries plays an important role in the study of glacier inventory, glacier change and glacier movement. With the successive launches of high-resolution remote-sensing satellites and the increasing abundance of available remote-sensing data, great opportunities and challenges now exist. In this study, we improved the DeepLab V3+ as Attention DeepLab V3+ and designed a complete solution based on the improved network to automatically extract glacier outlines from Gaofen-6 panchromatic and multispectral (PMS) images with a spatial resolution of 2 m. In the solution, test-time augmentation (TTA) was adopted to increase model robustness, and the convolutional block attention module (CBAM) was added into the atrous spatial pyramid pooling (ASPP) structure in DeepLab V3+ to enhance the weight of the target pixels and reduce the impact of superfluous features. The results show that the improved model effectively increases the robustness of the model, enhances the weight of target image elements and reduces the influence of non-target elements. Compared with deep-learning models, such as full convolutional network (FCN), U-Net and DeepLab V3+, the improved model performs better in the test dataset. Moreover, our method achieves superior performance for glacier boundary extraction in parts of the Tanggula Mountains, the Kunlun Mountains and the Qilian Mountains based on Gaofen-6 PMS images. It could distinguish glaciers from terminal moraine lakes, thin snow and clouds, thus demonstrating excellent performance and great potential for rapid and precise extraction of glacier boundaries.

The southeastern Tibetan Plateau, where monsoonal temperate glaciers are most developed, has a huge number of glacial lakes. Based on Landsat Operational Land Imager (OLI) images, 192 glacial lakes with a total area of 45.73 ± 6.18 km² in 2016 were delineated in the Yi’ong Zangbo River Basin. Glacial lakes with areas of less than 0.1 km² accounted for 81.77% of the total number, and glacial lakes located above 4500 m elevation comprised 83.33%. Dramatic glacier melting caused by climate warming has occurred, resulting in the formation and expansion of glacial lakes and the increase of potential glacial lake outburst floods (GLOFs) risk. From 1970 to 2016, the total area of glaciers in the basin has decreased by 35.39%, whereas the number and total area of glacial lakes have, respectively, increased by 86 and 1.59 km². In that time, 110 new glacial lakes emerged, whereas 24 of the original lakes disappeared. The newly formed lakes have a smaller mean area but higher mean elevation than the lakes that disappeared. Based on five indicators, a first-order method was used to identify glacial lakes that pose potential threats. We identified 10 lakes with very high, 7 with high, 31 with medium, and 19 with low GLOF susceptibility, out of 67 moraine-dammed glacial lakes with areas larger than 0.02 km². Understanding the behavior of glaciers and glacial lakes is a vital aspect of GLOFs disaster management, and the monitoring of glacial lakes should be strengthened.

Since the 1980s, with rapid economic development and increased attention given to ecological protection, China has launched a series of ecological-restoration programs to restore the local environment through afforestation and natural forest protection. The evaluation of vegetation restoration is an important part of evaluating the effectiveness of ecological restoration. The Loess Plateau is an area where ecological problems are concentrated, and it is a key area of ecological construction in China. This paper takes the Loess Plateau as the research area, using remote sensing and geographic information technology combined with ecosystem structural changes and an improved residual model to study vegetation restoration. The following main conclusions were drawn: (1) From 1990 to 2000, the farmland area increased by 3084.81 km², resulting in the encroachment of a large area of grassland and shrubland. (2) With the implementation of ecological engineering, the area of returning farmland to forest and grassland reached 18,001.88 km²; in this period, the NDVI of vegetation increased rapidly, and the area that increased comprised 91.90% of the total area, of which the area of significant increase reached 65.78%. The quality of vegetation was restored to a great extent, and ecological engineering played a major role in this stage. (3) Under the background of large-scale implementation of ecological restoration, the urban area of the Loess Plateau continues to expand.