基于卫星的自动冰川湖库存和亚洲高山地区的变化检测
Ravindra Kumar1, Saurabh Vijay2
1Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.
Scientific reports
|January 19, 2026
概括
一种新的自动化方法使用遥感数据绘制了高山亚洲 (HMA) 超过31,000个冰川湖泊的地图. 这种方法提高了关键的冰川湖监测和该地区灾害风险评估的准确性和完整性.
科学领域:
- 冰川学和遥感技术的发展
- 地质形态学和自然危害
背景情况:
- 高山亚洲 (HMA) 有许多高海拔的冰川湖,增加了冰川湖爆发洪水 (GLOF) 的风险.
- 对这些动态冰川湖的准确和最新的绘制对于灾害管理和了解区域环境变化至关重要.
研究的目的:
- 开发和验证一种全自动化的方法,用于绘制HMA地区冰川湖泊的地图.
- 使用集成遥感数据集,为HMA创建一个全面的冰川湖库存.
- 分析冰川湖面积和不同时间段之间的分布的变化.
主要方法:
- 开源遥感数据的整合:Landsat-8,Sentinel-1,Sentinel-2和哥白尼的数字高度模型 (DEM).
- 开发一个全自动化处理链,用于冰川湖的检测和绘制地图.
- 应用该方法来生成2016-17年和2022-24年观察期的库存.
主要成果:
- 2022年的一份清单确定了31,698个冰川湖,覆盖HMA的约2,240平方公里,主要位于海拔4000-5400米之间.
- 该自动化方法在20,000-100,000平方米之间的湖泊中实现了超过96%的准确性,有效地绘制了小型和大型冰川湖泊.
- 分析显示,在2016-17年至2022-24年期间,HMA的冰川湖面积净增加了5.5%,山地区显示出最高的扩张率 (22.5%).
结论:
- 开发的自动化方法在冰川湖地图的数据集成,准确性和完整性方面提供了显著的改进.
- 综合的HMA冰川湖库存和变化分析为GLOF风险评估和环境监测提供了有价值的数据.
- 这种方法适用于像HMA这样的动态地区和全球冰川湖数据库的常规更新.
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