Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset

<p>Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface...

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Main Authors: T. Smith, A. Rheinwalt, B. Bookhagen
Format: Article
Language:English
Published: Copernicus Publications 2019-05-01
Series:Earth Surface Dynamics
Online Access:https://www.earth-surf-dynam.net/7/475/2019/esurf-7-475-2019.pdf
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author T. Smith
A. Rheinwalt
B. Bookhagen
author_facet T. Smith
A. Rheinwalt
B. Bookhagen
author_sort T. Smith
collection DOAJ
description <p>Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface as a grid (referred to as truncation error; TE) and from any DEM uncertainty. We analyze in detail the impacts of TE and propagated elevation uncertainty (PEU) on slope and aspect.</p> <p>Using synthetic data as a control, we define functions to quantify both TE and PEU for arbitrary grids. We then develop a quality metric which captures the combined impact of both TE and PEU on the calculation of topographic metrics. Our quality metric allows us to examine the spatial patterns of error and uncertainty in topographic metrics and to compare calculations on DEMs of different sizes and accuracies.</p> <p>Using lidar data with point density of <span class="inline-formula">∼10</span>&thinsp;pts&thinsp;m<span class="inline-formula"><sup>−2</sup></span> covering Santa Cruz Island in southern California, we are able to generate DEMs and uncertainty estimates at several grid resolutions. Slope (aspect) errors on the 1&thinsp;m dataset are on average 0.3<span class="inline-formula"><sup>∘</sup></span> (0.9<span class="inline-formula"><sup>∘</sup></span>) from TE and 5.5<span class="inline-formula"><sup>∘</sup></span> (14.5<span class="inline-formula"><sup>∘</sup></span>) from PEU. We calculate an optimal DEM resolution for our SCI lidar dataset of 4&thinsp;m that minimizes the error bounds on topographic metric calculations due to the combined influence of TE and PEU for both slope and aspect calculations over the entire SCI. Average slope (aspect) errors from the 4&thinsp;m DEM are 0.25<span class="inline-formula"><sup>∘</sup></span> (0.75<span class="inline-formula"><sup>∘</sup></span>) from TE and 5<span class="inline-formula"><sup>∘</sup></span> (12.5<span class="inline-formula"><sup>∘</sup></span>) from PEU. While the smallest grid resolution possible from the high-density SCI lidar is not necessarily optimal for calculating topographic metrics, high point-density data are essential for measuring DEM uncertainty across a range of resolutions.</p>
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spelling doaj.art-759701f41bff4dbbbe049f2a1eb11ea52022-12-21T23:58:12ZengCopernicus PublicationsEarth Surface Dynamics2196-63112196-632X2019-05-01747548910.5194/esurf-7-475-2019Determining the optimal grid resolution for topographic analysis on an airborne lidar datasetT. SmithA. RheinwaltB. Bookhagen<p>Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface as a grid (referred to as truncation error; TE) and from any DEM uncertainty. We analyze in detail the impacts of TE and propagated elevation uncertainty (PEU) on slope and aspect.</p> <p>Using synthetic data as a control, we define functions to quantify both TE and PEU for arbitrary grids. We then develop a quality metric which captures the combined impact of both TE and PEU on the calculation of topographic metrics. Our quality metric allows us to examine the spatial patterns of error and uncertainty in topographic metrics and to compare calculations on DEMs of different sizes and accuracies.</p> <p>Using lidar data with point density of <span class="inline-formula">∼10</span>&thinsp;pts&thinsp;m<span class="inline-formula"><sup>−2</sup></span> covering Santa Cruz Island in southern California, we are able to generate DEMs and uncertainty estimates at several grid resolutions. Slope (aspect) errors on the 1&thinsp;m dataset are on average 0.3<span class="inline-formula"><sup>∘</sup></span> (0.9<span class="inline-formula"><sup>∘</sup></span>) from TE and 5.5<span class="inline-formula"><sup>∘</sup></span> (14.5<span class="inline-formula"><sup>∘</sup></span>) from PEU. We calculate an optimal DEM resolution for our SCI lidar dataset of 4&thinsp;m that minimizes the error bounds on topographic metric calculations due to the combined influence of TE and PEU for both slope and aspect calculations over the entire SCI. Average slope (aspect) errors from the 4&thinsp;m DEM are 0.25<span class="inline-formula"><sup>∘</sup></span> (0.75<span class="inline-formula"><sup>∘</sup></span>) from TE and 5<span class="inline-formula"><sup>∘</sup></span> (12.5<span class="inline-formula"><sup>∘</sup></span>) from PEU. While the smallest grid resolution possible from the high-density SCI lidar is not necessarily optimal for calculating topographic metrics, high point-density data are essential for measuring DEM uncertainty across a range of resolutions.</p>https://www.earth-surf-dynam.net/7/475/2019/esurf-7-475-2019.pdf
spellingShingle T. Smith
A. Rheinwalt
B. Bookhagen
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
Earth Surface Dynamics
title Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
title_full Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
title_fullStr Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
title_full_unstemmed Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
title_short Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
title_sort determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
url https://www.earth-surf-dynam.net/7/475/2019/esurf-7-475-2019.pdf
work_keys_str_mv AT tsmith determiningtheoptimalgridresolutionfortopographicanalysisonanairbornelidardataset
AT arheinwalt determiningtheoptimalgridresolutionfortopographicanalysisonanairbornelidardataset
AT bbookhagen determiningtheoptimalgridresolutionfortopographicanalysisonanairbornelidardataset