Rashid Irfan, Najar Nadeem Ahmad, Majeed Ulfat, Rasool Waseem
Department of Geoinformatics, University of Kashmir, Hazratbal Srinagar, Jammu and Kashmir 190006, India.
Data Brief. 2022 Apr 12;42:108176. doi: 10.1016/j.dib.2022.108176. eCollection 2022 Jun.
Glaciers in the Himalayan arc are receding rapidly in the eastern and western parts as compared to other regions. Contrararily, the glaciers in the Trans-Himalayan region of Ladakh are comparatively stable. The differential retreat could be due to various climatic, topographic, and geologic influences. The use of multi-source remotely sensed imagery from open-source platforms and the GlabTop model has been discussed in this paper. This paper draws insights from a recently published paper which details the recession of 87 glaciers in the Trans Himalayan region of Ladakh using remote sensing data [1]. The use of remote sensing data from USGS and Planet Labs for assessing glacier area changes, frontal retreat, debris cover, topographic characteristics, and comparison with existing inventories has been discussed in this study. The geodetic mass changes have been assessed using SRTM and TanDEM-X of 2000 and 2012 respectively. The use of remotely sensed data discussed in this article will help glaciologists to better characterize and understand the glacier recession in the region. The GlabTop model has been used to simulate proglacial lake expansion to understand glacier-bed overdeepenings of four glaciers in the region. The GlabTop simulations will help disaster managers to better quantify the vulnerability and risk of downstream population and infrastructure to Glacial Lake Outburst Floods (GLOFs).
与其他地区相比，喜马拉雅弧形地带的冰川在东部和西部正迅速消退。相反，拉达克跨喜马拉雅地区的冰川相对稳定。这种差异退缩可能是由于各种气候、地形和地质影响。本文讨论了使用来自开源平台的多源遥感影像和GlabTop模型。本文借鉴了最近发表的一篇论文的见解，该论文利用遥感数据详细阐述了拉达克跨喜马拉雅地区87条冰川的退缩情况[1]。本研究讨论了使用美国地质调查局（USGS）和行星实验室的遥感数据来评估冰川面积变化、前沿退缩、碎屑覆盖、地形特征以及与现有清单进行比较。分别使用2000年和2012年的航天飞机雷达地形测绘任务（SRTM）和TanDEM-X数据评估了大地测量质量变化。本文讨论的遥感数据的使用将有助于冰川学家更好地描述和理解该地区的冰川退缩情况。GlabTop模型已被用于模拟冰前湖扩张，以了解该地区四条冰川的冰床过度加深情况。GlabTop模拟将有助于灾害管理人员更好地量化下游人口和基础设施遭受冰川湖突发洪水（GLOF）的脆弱性和风险。
