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Pegler, K.H. (1999) An Examination of Alternative Compensation Methods for the Removal of the Ridging Effect from Digital Terrain Model Data Files. Thesis Dissertation, University of New Brunswick.

has been cited by the following article:

  • TITLE: Fusing Digital Elevation Models to Improve Hydrological Interpretations

    AUTHORS: Shane Furze, Jae Ogilvie, Paul A. Arp

    KEYWORDS: DEM Fusion, LiDAR-Based Calibration, Hydrographic Interpretations, Stream Network, Wet-Areas Mapping

    JOURNAL NAME: Journal of Geographic Information System, Vol.9 No.5, September 18, 2017

    ABSTRACT: Improving the accuracy of digital elevation is essential for reducing hydro-topographic derivation errors pertaining to, e.g., flow direction, basin borders, channel networks, depressions, flood forecasting, and soil drainage. This article demonstrates how a gain in this accuracy is improved through digital elevation model (DEM) fusion, and using LiDAR-derived elevation layers for conformance testing and validation. This demonstration is done for the Province of New Brunswick (NB, Canada), using five province-wide DEM sources (SRTM 90 m; SRTM 30 m; ASTER 30 m; CDED 22 m; NB-DEM 10 m) and a five-stage process that guides the re-projection of these DEMs while minimizing their elevational differences relative to LiDAR-captured bare-earth DEMs, through calibration and validation. This effort decreased the resulting non-LiDAR to LiDAR elevation differences by a factor of two, reduced the minimum distance conformance between the non-LiDAR and LiDAR-derived flow channels to ± 10 m at 8.5 times out of 10, and dropped the non-LiDAR wet-area percentages of false positives from 59% to 49%, and of false negatives from 14% to 7%. While these reductions are modest, they are nevertheless not only consistent with already existing hydrographic data layers informing about stream and wet-area locations, they also extend these data layers across the province by comprehensively locating previously unmapped flow channels and wet areas.