High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations

作者:Yue, LW (Yue, Linwei)^{[ 1 ]} ; Shen, HF (Shen, Huanfeng)^{[ 2,3 ]} ; Zhang, LP (Zhang, Liangpei)^{[ 1,3 ]} ; Zheng, XW (Zheng, Xianwei)^{[ 1 ]} ; Zhang, F(Zhang, Fan)^{[ 1 ]} ; Yuan, QQ (Yuan, Qiangqiang)^{[ 3,4 ]}

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

卷: 123

页: 20-34

DOI: 10.1016/j.isprsjprs.2016.11.002

出版年: JAN 2017

摘要

The absence of a high-quality seamless global digital elevation model (DEM) dataset has been a challenge for the Earth-related research fields. Recently, the 1-arc-second Shuttle Radar Topography Mission (SRTM-1) data have been released globally, covering over 80% of the Earth's land surface (60 degrees N-56 degrees S). However, voids and anomalies still exist in some tiles, which has prevented the SRTM-1 dataset from being directly used without further processing. In this paper, we propose a method to generate a seamless DEM dataset blending SRTM-1, ASTER GDEM v2, and ICESat laser altimetry data. The ASTER GDEM v2 data are used as the elevation source for the SRTM void filling. To get a reliable filling source, ICESat GLAS points are incorporated to enhance the accuracy of the ASTER data within the void regions, using an artificial neural network (ANN) model. After correction, the voids in the SRTM-1 data are filled with the corrected ASTER GDEM values. The triangular irregular network based delta surface fill (DSF) method is then employed to eliminate the vertical bias between them. Finally, an adaptive outlier filter is applied to all the data tiles. The final result is a seamless global DEM dataset. ICESat points collected from 2003 to 2009 were used to validate the effectiveness of the proposed method, and to assess the vertical accuracy of the global DEM products in China. Furthermore, channel networks in the Yangtze River Basin were also extracted for the data assessment. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

作者关键词:Digital elevation model (DEM); Multi-source data fusion; SRTM-1; ASTER GDEM; ICESat/GLAS

KeyWords Plus:DIGITAL ELEVATION MODELS; ARTIFICIAL NEURAL-NETWORK; SHUTTLE RADAR TOPOGRAPHY; TANDEM-X; ACCURACY ASSESSMENT; FILLING VOIDS; CHINA; VALIDATION; MISSION; VERIFICATION

通讯作者地址: Zhang, LP (通讯作者)

通讯作者地址: Shen, HF (通讯作者)

地址:

电子邮件地址:shenhf@whu.edu.cn; zlp62@whu.edu.cn

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ELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS

研究方向:Physical Geography; Geology; Remote Sensing; Imaging Science & Photographic Technology

Web of Science 类别:Geography, Physical; Geosciences, Multidisciplinary; Remote Sensing; Imaging Science & Photographic Technology

文献类型:Article

语种:English

入藏号: WOS:000392780200002

ISSN: 0924-2716

eISSN: 1872-8235

Impact Factor (影响因子): 4.188