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The influence of elevation uncertainty on derivation of topographic indices


Hebeler, Felix; Purves, Ross S (2009). The influence of elevation uncertainty on derivation of topographic indices. Geomorphology, 111(1-2):4-16.

Abstract

Digital elevation models at a variety of resolutions are increasingly being used in geomorphology, for example in comparing the hypsometric properties of multiple catchments. A considerable bodyof research has investigated the sensitivity of topographic indices to resolution and algorithms, but little work has been done to address the impact of DEM uncertainty and elevation value error on derived products. By using higher resolution data from the Shuttle Radar Topography Mission - of supposed higher accuracy - for comparison with the widely used GLOBE 1km data set, error surfaces for three mountainous regions were calculated. Correlation analysis showed that error surfaces related to a range of topographic variables for all three regions, namely roughness, minimum and mean extremity and aspect. This correlation of error with local topography was
used to develop a model of uncertainty including a stochastic component, permitting Monte Carlo Simulations. These suggest that global statistics for a range of topographic indices are robust to the introduction of uncertainty. However, the derivation of watersheds and related statistics per watershed (e.g. hypsometry) is shown to vary significantly as a result of the introduced uncertainty.

Abstract

Digital elevation models at a variety of resolutions are increasingly being used in geomorphology, for example in comparing the hypsometric properties of multiple catchments. A considerable bodyof research has investigated the sensitivity of topographic indices to resolution and algorithms, but little work has been done to address the impact of DEM uncertainty and elevation value error on derived products. By using higher resolution data from the Shuttle Radar Topography Mission - of supposed higher accuracy - for comparison with the widely used GLOBE 1km data set, error surfaces for three mountainous regions were calculated. Correlation analysis showed that error surfaces related to a range of topographic variables for all three regions, namely roughness, minimum and mean extremity and aspect. This correlation of error with local topography was
used to develop a model of uncertainty including a stochastic component, permitting Monte Carlo Simulations. These suggest that global statistics for a range of topographic indices are robust to the introduction of uncertainty. However, the derivation of watersheds and related statistics per watershed (e.g. hypsometry) is shown to vary significantly as a result of the introduced uncertainty.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2009
Deposited On:22 Jan 2010 13:32
Last Modified:26 Jan 2017 08:45
Publisher:Elsevier
ISSN:0169-555X
Publisher DOI:https://doi.org/10.1016/j.geomorph.2007.06.026

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