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Wilson, J.P. (2012) Digital Terrain Modeling. Geomorphology, 137, 107-121.
https://doi.org/10.1016/j.geomorph.2011.03.012

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.