摘要
青海省(31°39′-39°19′N,89°35′-103°04′E)地处青藏高原东北部,其境内的昆仑山、唐古拉山、祁连山、阿尔金山和阿尼玛卿山等高海拔山地现代冰川普遍发育。在全球气候变暖背景下,青海省境内冰川呈现退缩态势,及时准确了解冰川规模现状是科学评价冰川变化对气候变化响应规律及合理制订水资源利用政策的基础。本数据集基于2018-2021年GF-1/2/6高分辨率遥感影像和SRTM DEM数字高程模型数据,利用深度学习和冰川中流线自动提取方法制作青海省冰川边界和长度矢量数据,精度分别为99.01%和98.89%,可反映青海省2020年冰川现状,为该地区冰川变化和气候变化等研究提供数据支持。
Located on the northeastern Qinghai-Tibet Plateau,Qinghai Province(31°39′-39°19′N,89°35′-103°04′E)is known for numerous modern glaciers,which is widely developed in high altitude mountains such as Kunlun Mountains,Tanggula Mountains,Qilian Mountains,Altun Mountains and A'Nyêmaqên Mountains.As a result of global warming,the glaciers in Qinghai Province are retreating in recent years.A good understanding of the contemporary glacier conditions is the basis for scientific evaluation of the response pattern of glacier changes on climate change and the formulation of policies for rational use of water resources.Based on the GF-1/2/6 high resolution remote sensing images from 2018 to 2021 and SRTM DEM data,we obtained a vector dataset of boundary and length of glaciers in Qinghai Province by using the deep learning method and automatic extraction method of glacier centerlines.And the accuracies of glacial boundary and length are 99.01%and 98.89%,respectively.The dataset can reflect the status of glaciers in Qinghai Province in 2020 and support the research on glacier and climate change.
作者
薛娇
姚晓军
褚馨德
庞文龙
张聪
周苏刚
XUE Jiao;YAO Xiaojun;CHU Xinde;PANG Wenlong;ZHANG Cong;ZHOU Sugang(College of Geography and Environmental Science,Northwest Normal University,Lanzhou 730070,P.R.China;Xining Center of Natural Resources Comprehensive Survey,China Geological Survey,Xining,810000,P.R.China)
基金
国家自然科学基金项目(41861013,42071089,42161027)
2020年山洪地质灾害防治气象保障工程项目(2020KYSJZTP-011)
国家冰川冻土沙漠科学数据中心开放基金项目(20D02)
中国地质调查项目(DD20211570)
关键词
冰川
高分
深度学习
青海省
glacier
GF image
deep learning
Qinghai Province
