IGSNRR OpenIR
Using MLR to model the vertical error distribution of ASTER GDEM V2 data based on ICESat/GLA14 data in the Loess Plateau of China
Zhao, Shangmin1; Cheng, Weiming2; Zhou, Chenghu2; Liu, Haijiang3; Su, Qiaomei1; Zhang, Shifang4; He, Weican1; Wang, Li1; Wu, Wenjiao1
2017
Source PublicationZEITSCHRIFT FUR GEOMORPHOLOGIE
ISSN0372-8854
Volume61Pages:9-26
Corresponding AuthorZhao, Shangmin(zhaoshangmin@tyut.edu.cn)
AbstractUsing the multinomial logistic regression (MLR) model, this study quantitatively simulate the vertical error distribution of ASTER GDEM V2 data based on the ICESat/GLA14 data and land surface factors (including topographic, NDVI and land use factors) in the Loess Plateau of China. Research results show: (1) there is a positive correlation between the vertical error and the topographic factors including elevation, relief and slope factors. With regard to the aspect factor, a symmetrical aspect direction for the distribution of the negative and positive error values is found. In general, the vertical error decreases with increasing NDVI values. With regard to land use factor, the highest vertical error distributes in forestland and grassland. (2) The vertical error distribution probability shows a near normal distribution with marginal negative skewness. (3)The accuracy of the model results is estimated to be higher than 70 % based on the different checked datasets including the simulated and checked ICESat/GLA14 data and ground control points in topographic maps.
Keywordvertical error distribution MLR model ASTER GDEM V2 ICESat/GLA14 land surface factors
DOI10.1127/zfg_suppl/2016/0325
WOS KeywordBAND SRTM DEM ; LOGISTIC-REGRESSION ; ACCURACY ASSESSMENT ; FEATURE-SELECTION ; ELEVATION DATA ; VALIDATION ; CLASSIFICATION ; ALTIMETRY
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41301469] ; National Natural Science Foundation of China[41171332] ; Open Foundation of the LREIS ; National Science Technology Basic Work Special Project[2011FY110400-2] ; Qualified Personnel Foundation of Taiyuan University of Technology (QPFT)[tyut-rc201221a]
Funding OrganizationNational Natural Science Foundation of China ; Open Foundation of the LREIS ; National Science Technology Basic Work Special Project ; Qualified Personnel Foundation of Taiyuan University of Technology (QPFT)
WOS Research AreaPhysical Geography ; Geology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary
WOS IDWOS:000417964400002
PublisherGEBRUDER BORNTRAEGER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/56775
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhao, Shangmin
Affiliation1.Taiyuan Univ Technol, Coll Min Engn, Dept Surveying & Mapping, Taiyuan 030024, Shanxi, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.China Natl Environm Monitoring Ctr, Beijing 100012, Peoples R China
4.Taiyuan Univ Technol, Dept Earth Sci & Engn, Coll Min Engn, Taiyuan 030024, Shanxi, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Shangmin,Cheng, Weiming,Zhou, Chenghu,et al. Using MLR to model the vertical error distribution of ASTER GDEM V2 data based on ICESat/GLA14 data in the Loess Plateau of China[J]. ZEITSCHRIFT FUR GEOMORPHOLOGIE,2017,61:9-26.
APA Zhao, Shangmin.,Cheng, Weiming.,Zhou, Chenghu.,Liu, Haijiang.,Su, Qiaomei.,...&Wu, Wenjiao.(2017).Using MLR to model the vertical error distribution of ASTER GDEM V2 data based on ICESat/GLA14 data in the Loess Plateau of China.ZEITSCHRIFT FUR GEOMORPHOLOGIE,61,9-26.
MLA Zhao, Shangmin,et al."Using MLR to model the vertical error distribution of ASTER GDEM V2 data based on ICESat/GLA14 data in the Loess Plateau of China".ZEITSCHRIFT FUR GEOMORPHOLOGIE 61(2017):9-26.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhao, Shangmin]'s Articles
[Cheng, Weiming]'s Articles
[Zhou, Chenghu]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhao, Shangmin]'s Articles
[Cheng, Weiming]'s Articles
[Zhou, Chenghu]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhao, Shangmin]'s Articles
[Cheng, Weiming]'s Articles
[Zhou, Chenghu]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.