摘要
Obtaining multi-source satellite geodesy and ocean observation data to map the high-resolution global digital elevation models(DEMs)is a formidable task at present.The key theoretical and technological obstacles to fine modeling must be overcome before the geographical ditribution of ocean topography and plate move-ment patterns can be explored.Geodesy.
目前,通过多源卫星大地测量和海洋观测数据来绘制高分辨率全球数字高程模型(DEM)及其变化是一项巨大的挑战.为了探索海洋地形的空间分布和板块运动规律,需要突破精细建模的关键理论和技术难题.由于技术限制和设备测量成本等原因,美国和世界许多地区还无法获得高分辨率全球DEM.作为一种替代方法,增强现有数据集的分辨率——超分辨率(Super-Resolution,SR)可以看作是填补空白的极佳方法.本研究基于30 m分辨率的NASADEM卫星影像、联合国政府间海洋学委员会公开450 m分辨率GEBCO_(2)021数据和部分区域高分辨率海洋地形数据,采用深度残差预训练神经网络和迁移学习相结合技术,构建了适用于全球区域DEM-SRNet模型,制作了首个3弧秒(90 m)分辨率的全球DEM产品GDEM2022.该数据为研究不同地形复杂度下的全球海陆重力场与地形的理论关系,探索不同海陆构造单元的均衡机制、以及海陆地形对海洋潮流运动,全球气候变化、地球圈层物质交换、海底板块构造等方面起到重要的作用与影响.
作者
Bo Zhang
Wei Xiong
Muyuan Ma
Mingqing Wang
Dong Wang
Xing Huang
Le Yu
Qiang Zhang
Hui Lu
Danfeng Hong
Fan Yu
Zidong Wang
Jie Wang
Xuelong Li
Peng Gong
Xiaomeng Huang
张博;熊巍;马牧原;王明清;王冬;黄兴;俞乐;张强;卢麾;洪丹枫;于璠;王紫东;王杰;李学龙;宫鹏;黄小猛(Ministry of Education Key Laboratory for Earth System Modeling,Institute for Global Change Studies,Department of Earth System Science,Tsinghua University,Beijing 100084,China;Key Laboratory of Computational Optical Imaging Technology,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;Huawei Technologies Co.Ltd,Hangzhou 310007,China;Peng Cheng Laboratory,Shenzhen 518000,China;School of Artificial Intelligence,OPtics and ElectroNics(iOPEN),Northwestern Polytechnical University,Xi’an 710072,China;Department of Geography and Department of Earth Sciences,University of Hong Kong,Hong Kong,China)
基金
supported by the National Key Research and Development Program of China(2020YFA0607900,2020YFA0608003,and 2021YFC3101601)
the National Natural Science Foundation of China(42125503 and 42075137)
the National Key Scientific and Technological Infrastructure Project‘‘Earth System Science Numerical Simulator Facility”(Earth Lab)。
