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An Adaptive Terrain-Dependent Method for SRTM DEM Correction Over Mountainous Areas

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成果类型:
期刊论文
作者:
Zhou, Cui*;Zhang, Gui*;Yang, Zefa*;Ao, Minsi;Liu, Zhiwei;...
通讯作者:
Zhou, Cui;Zhang, Gui;Yang, Zefa
作者机构:
[Zhou, Cui; Zhang, Gui; Zhou, C] Cent South Univ Forestry & Technol, Coll Sci, Key Lab Digital Dongting Lake Basin Hunan Prov, Changsha 410001, Hunan, Peoples R China.
[Yang, Zefa] Cent South Univ, Sch Geosci & Infophys, Dept Surveying & Remote Sensing, Changsha 410083, Hunan, Peoples R China.
[Zhu, Jianjun; Liu, Zhiwei] Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Hunan, Peoples R China.
[Ao, Minsi] Hunan Engn & Res Ctr Nat Resource Invest & Monito, Changsha 410007, Hunan, Peoples R China.
通讯机构:
[Zhou, C; Zhang, G; Yang, Zefa] C
Cent South Univ Forestry & Technol, Coll Sci, Key Lab Digital Dongting Lake Basin Hunan Prov, Changsha 410001, Hunan, Peoples R China.
Cent South Univ, Sch Geosci & Infophys, Dept Surveying & Remote Sensing, Changsha 410083, Hunan, Peoples R China.
语种:
英文
关键词:
Mathematical model;Market research;Adaptation models;Vegetation mapping;Geology;Spaceborne radar;Estimation;SRTM DEM;global error trends;local nonlinear terrain-related errors;adaptive model;robust estimation
期刊:
IEEE ACCESS
ISSN:
2169-3536
年:
2020
卷:
8
页码:
130878-130887
基金类别:
This work was supported in part by the Young Elite Scientists Sponsorship Program by Hunan province of China under Grant 2018RS3093, in part by the National Natural Science Foundation of China under Grant 41604012, in part by the China Postdoctoral Science Foundation under Grant 2017M612604, in part by the Hunan Science and Technology Innovation Platform and Talent Plan Project under Grant 2017TP1022, and in part by the Opening Foundation of Hunan Engineering and Research Center of Natural Resource Investigation and Monitoring under Grant 2020-13.
机构署名:
本校为第一且通讯机构
院系归属:
理学院
摘要:
This paper presents a terrain-related method to simultaneously correct the global error trends and local linear/nonlinear terrain-related errors of the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), which have not been focused in most of the previous methods. To meet this goal, an adaptive strategy for modelling the SRTM DEM errors is first proposed, especially over mountainous areas, based on the Bayesian information criterion. Then, the M-estimator, instead of the ordinary least squares solver, is utilized to estimate ...

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