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Quantifying DEM Uncertainty and its Effect on Topographic Parameters
Abstract
Digital elevation models (DEMs) are representations of topography with inherent errors that constitute uncertainty. DEM data are often used in analyses without quantifying the effects of these errors. This paper describes a Monte Carlo methodology for evaluation of the effects of uncertainty on elevation and derived topographic parameters. Four methods for representing DEM uncertainty that utilize metadata and spatial characteristics of a DEM are presented. Seven statistics derived from simulation results were used to quantify the effect of DEM error. When uncertainty was quantified by the average relative absolute difference, elevation did not deviate. The range of deviation across the four methods for slope was 5 to 8 percent, 460 to 950 percent for derived catchment areas and 4 to 9 percent for the topographic index. This research demonstrates how application of this methodology can address DEM uncertainty, contributing to more responsible use of elevation and derived topographic parameters, and ultimately results obtained from their use.
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Autocorrelation in random error was not accounted for, with completely random unfiltered error fields used instead.
“In contrast to Lewis (2021), autocorrelation in random error was not accounted for, with completely random unfiltered error fields used instead (Wechsler & Kroll, 2006).”
From Explaining known past routes, underdetermination, and the use of multiple cost functions (2024) · cites this paper as Wechsler & Kroll, 2006
The effect of the random error fields can be deemed as the worst-case scenario.
“As a result of the second advantage, the effect of the random error fields can be deemed as the worst-case scenario (Wechsler & Kroll, 2006).”
From Explaining known past routes, underdetermination, and the use of multiple cost functions (2024) · cites this paper as Wechsler & Kroll, 2006
A mean 77×77 filter was applied to ensure that the random error fields were spatially autocorrelated.
“To ensure that the random error fields were spatially autocorrelated with themselves, a mean 77×77 filter was applied (Wechsler & Kroll, 2006).”
From Probabilistic modelling for incorporating uncertainty in least cost path results: a postdictive roman road case study (2021) · cites this paper as Wechsler & Kroll, 2006
The error fields representing vertical error within the DEM were generated from random values drawn from a normal distribution with mean 0 and standard deviation 4, the RMSE of the DEM.
“The error fields representing vertical error within the DEM were generated from random values drawn from a normal distribution of mean = 0 and standard deviation = 4 (i.e. the RMSE of the DEM) (Fisher, 1998;Fisher & Tate, 2006;Wechsler & Kroll, 2006).”
From Probabilistic modelling for incorporating uncertainty in least cost path results: a postdictive roman road case study (2021) · cites this paper as Wechsler & Kroll, 2006
The DEM is often used as an error-free model of the topography in archaeological LCP studies.
“In particular, the digital elevation model (DEM), which forms the basis of the majority of archaeological LCP studies (Herzog, 2010;Verhagen, 2018), is often used as an error-free model of the topography (Wechsler & Kroll, 2006).”
From Probabilistic modelling for incorporating uncertainty in least cost path results: a postdictive roman road case study (2021) · cites this paper as Wechsler & Kroll, 2006
The 77×77 window size was derived through a semivariogram based on the DEM.
“The window size of 77×77 was derived through the use of a semivariogram based on the DEM (Wechsler & Kroll, 2006).”
From Probabilistic modelling for incorporating uncertainty in least cost path results: a postdictive roman road case study (2021) · cites this paper as Wechsler & Kroll, 2006
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Cited by
Sorted by citations
Lewis, J. (2021) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-021-09522-w · Cited by 53
Explaining known past routes, underdetermination, and the use of multiple cost functions
Lewis, J. (2024) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-023-09621-w · Cited by 15
Metadata
- Authors
- Wechsler, S. P., & Kroll, C. N.
- Venue
- Photogrammetric Engineering & Remote Sensing
- Published
- 2006-09-01
- Volume
- 72
- Issue
- 9
- Pages
- 1081-1090
- ISSN
- 0099-1112
- Cited by
- 148
- References
- 1
- Language
- en
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