DOI: 10.1016/j.jag.2014.08.012
Scopus记录号: 2-s2.0-84920691202
论文题名: Robust methods for assessing the accuracy of linear interpolated DEM
作者: Wang B ; , Shi W ; , Liu E
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 34, 期: 1 起始页码: 198
结束页码: 206
语种: 英语
英文关键词: Confidence interval
; DEM accuracy
; Interpolation residuals
; Monte carlo simulation
; Robust estimation
Scopus关键词: accuracy assessment
; confidence interval
; digital elevation model
; interpolation
; Monte Carlo analysis
英文摘要: Methods for assessing the accuracy of a digital elevation model (DEM) with emphasis on robust methods have been studied in this paper.Based on the squared DEM residual population generated by the bi-linear interpolation method, three average-error statistics including (a) mean, (b) median, and (c) M-estimator are thoroughly investigated for measuring the interpolated DEM accuracy. Correspondingly, their confidence intervals are also constructed for each average error statistic to further evaluate the DEM quality. The first method mainly utilizes the student distribution while the second and third are derived from the robust theories. These innovative robust methods possess the capability of counteracting the outlier effects or even the skew distributed residuals in DEM accuracy assessment. Experimental studies using Monte Carlo simulation have commendably investigated the asymptotic convergence behavior of confidence intervals constructed by these three methods with the increase of sample size. It is demonstrated that the robust methods can produce more reliable DEM accuracy assessment results compared with those by the classical t-distribution-based method. Consequently, these proposed robust methods are strongly recommended for assessing DEM accuracy, particularly for those cases where the DEM residual population is evidently non-normal or heavily contaminated with outliers. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79500
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong; School of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
Recommended Citation:
Wang B,, Shi W,, Liu E. Robust methods for assessing the accuracy of linear interpolated DEM[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,34(1)