Filtering spatial error from DEMs: Implications for morphological change estimation
Scour and fill estimation from digital elevation model (DEM) subtraction or differencing is an increasingly common technique in morphological and sediment transport investigations. The technique is commonly used to estimate scour and fill volumes and to produce scour and fill maps that provide proce...
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Published in | Geomorphology (Amsterdam, Netherlands) Vol. 125; no. 1; pp. 160 - 171 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
2011
Elsevier |
Subjects | |
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Abstract | Scour and fill estimation from digital elevation model (DEM) subtraction or differencing is an increasingly common technique in morphological and sediment transport investigations. The technique is commonly used to estimate scour and fill volumes and to produce scour and fill maps that provide process-based information to geomorphologists. Accounting for sources of uncertainty within the DEM is of critical importance. DEM error is spatially variable and has a tendency to be greater at breaks of slope such as bar and bank edges. In the past however, this has been achieved using a uniform error metric across the DEM, resulting in over-conservative estimates of error. In turn this has led to over-conservative scour and fill volumes, and incorrect process interpretation. This paper applies a new approach that permits assessment of spatially distributed error across a DEM. The method is tested on a sequence of field surveys of the gravel-bed River Nent, Cumbria, UK. The results demonstrate some dramatic differences: application of conventional techniques that account for mean error across a DEM led to a 15 and 31% underestimation in scour and fill volumes, respectively, between July and October 1998, whilst for the October 1998–June 1999 subtraction 31 and 13% of scour and fill were underestimated respectively. Use of a uniform error across a surface captures less change in comparison to a spatially distributed approach. Furthermore, the changes captured using a uniform error are biased toward areas of the channel that have more local topographic variability such as bar and bank edges. In contrast the use of a spatially distributed approach provides information on change from flatter surfaces such as bar tops that would otherwise be missed. This study also demonstrates that estimates of morphological change can be misleading in the absence of an error filter. Where the raw survey data is available, it is recommended that sediment budgeting studies take account of the spatial variability of error in each DEM involved in the subtraction. |
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AbstractList | Scour and fill estimation from digital elevation model (DEM) subtraction or differencing is an increasingly common technique in morphological and sediment transport investigations. The technique is commonly used to estimate scour and fill volumes and to produce scour and fill maps that provide process-based information to geomorphologists. Accounting for sources of uncertainty within the DEM is of critical importance. DEM error is spatially variable and has a tendency to be greater at breaks of slope such as bar and bank edges. In the past however, this has been achieved using a uniform error metric across the DEM, resulting in over-conservative estimates of error. In turn this has led to over-conservative scour and fill volumes, and incorrect process interpretation. This paper applies a new approach that permits assessment of spatially distributed error across a DEM. The method is tested on a sequence of field surveys of the gravel-bed River Nent, Cumbria, UK. The results demonstrate some dramatic differences: application of conventional techniques that account for mean error across a DEM led to a 15 and 31% underestimation in scour and fill volumes, respectively, between July and October 1998, whilst for the October 1998-June 1999 subtraction 31 and 13% of scour and fill were underestimated respectively. Use of a uniform error across a surface captures less change in comparison to a spatially distributed approach. Furthermore, the changes captured using a uniform error are biased toward areas of the channel that have more local topographic variability such as bar and bank edges. In contrast the use of a spatially distributed approach provides information on change from flatter surfaces such as bar tops that would otherwise be missed. This study also demonstrates that estimates of morphological change can be misleading in the absence of an error filter. Where the raw survey data is available, it is recommended that sediment budgeting studies take account of the spatial variability of error in each DEM involved in the subtraction. |
Author | Fuller, Ian C. Heritage, George L. Large, Andrew R.G. Milan, David J. |
Author_xml | – sequence: 1 givenname: David J. surname: Milan fullname: Milan, David J. email: dmilan@glos.ac.uk organization: Department of Natural & Social Sciences, University of Gloucestershire, Cheltenham, GL50 4AZ, United Kingdom – sequence: 2 givenname: George L. surname: Heritage fullname: Heritage, George L. organization: JBA Consulting, The Brew House, Wilderspool Park, Greenhalls Avenue, Warrington, WA4 6HL, United Kingdom – sequence: 3 givenname: Andrew R.G. surname: Large fullname: Large, Andrew R.G. organization: Earth Surface Processes Research Group, School of Geography & Politics, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom – sequence: 4 givenname: Ian C. surname: Fuller fullname: Fuller, Ian C. organization: School of People, Environment & Planning Massey University, Private Bag 11 222, Palmerston North, 4442, New Zealand |
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SubjectTerms | Applied geophysics Banks DEM of difference (DoD) DEM subtraction digital elevation models Discrete element method Earth sciences Earth, ocean, space Error analysis Errors Estimates Exact sciences and technology Geomorphology Geomorphology, landform evolution Gravel-bed river Internal geophysics Marine and continental quaternary Permissible error rivers Sediment transport sediments Spatially distributed error Subtraction Surficial geology Surveys uncertainty |
Title | Filtering spatial error from DEMs: Implications for morphological change estimation |
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