Open AccessComparison of the Resampling Methods for Gridded DEM Downscaling
Author(s) -
Quang Minh Nguyen,
Thi Thu Huong Nguyen,
Phu Hien La,
Thi Tuyet Nhung Duong,
Van Anh Vu
Publication year - 2022
Publication title -
inżynieria mineralna
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.215
H-Index - 9
ISSN - 1640-4920
DOI - 10.29227/im-2019-02-78
Subject(s) - resampling , kriging , bilinear interpolation , downscaling , computer science , quantitative assessment , artificial intelligence , pattern recognition (psychology) , mathematics , statistics , machine learning , computer vision , precipitation , meteorology , geography
In this paper, a comparison and evaluation of three resamplingmethods for gridded DEM is implemented. The evaluation was based onthe results of bilinear resampling, bi-cubic and Kriging resamplingmethods for an experiment using both degraded and sampled datasets at 20m and 60 m spatial resolutions. The evaluation of the algorithms wasaccomplished comprehensively with visual and quantitative assessments.The visual assessment process was based on direct comparison of the sametopographic features in different downscaled images, scatterplots andprofiles. The quantitative assessment was based on the most commonlyused parameters for DEM accuracy assessment such as root mean squareerrors (RMSEs), linear regression parameters m and b, and correlationcoefficient R. Both visual and quantitative assessment revealed greateraccuracy of the Kriging over the other two conventional methods.