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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Format: | Article |
Language: | English |
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Copernicus Publications
2019-05-01
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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> pts 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 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 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 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> |
first_indexed | 2024-12-13T05:26:12Z |
format | Article |
id | doaj.art-759701f41bff4dbbbe049f2a1eb11ea5 |
institution | Directory Open Access Journal |
issn | 2196-6311 2196-632X |
language | English |
last_indexed | 2024-12-13T05:26:12Z |
publishDate | 2019-05-01 |
publisher | Copernicus Publications |
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series | Earth Surface Dynamics |
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> pts 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 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 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 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 |