43016
2019
2019
eng
475
489
15
725
postprint
1
2019-06-14
2019-06-14
--
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
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.
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.
Using lidar data with point density of ∼10 pts m−2 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∘ (0.9∘) from TE and 5.5∘ (14.5∘) 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∘ (0.75∘) from TE and 5∘ (12.5∘) 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.
Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
10.25932/publishup-43016
urn:nbn:de:kobv:517-opus4-430165
1866-8372
Earth Surface Dynamics 7 (2019) S. 475–489 DOI: 10.5194/esurf-7-475-2019
<a href="http://publishup.uni-potsdam.de/opus4-ubp/frontdoor/index/index/docId/43017">Bibliographieeintrag der Originalveröffentlichung/Quelle</a>
false
true
CC-BY - Namensnennung 4.0 International
Taylor Smith
Aljoscha Rheinwalt
Bodo Bookhagen
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
725
eng
uncontrolled
Digital Elevation Model
eng
uncontrolled
River Incision Model
eng
uncontrolled
Accuracy Asseessment
eng
uncontrolled
Landscape Response
eng
uncontrolled
Error
eng
uncontrolled
Slope
eng
uncontrolled
Uncertainties
eng
uncontrolled
Extraction
eng
uncontrolled
Expression
eng
uncontrolled
Patterns
open_access
Institut für Geowissenschaften
Referiert
Open Access
Universität Potsdam
https://publishup.uni-potsdam.de/files/43016/pmnr725.pdf
43017
2019
2019
eng
475
489
15
7
article
Copernicus Publ.
Göttingen
1
2019-05-29
2019-05-29
--
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
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.
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.
Using lidar data with point density of ∼10 pts m−2 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∘ (0.9∘) from TE and 5.5∘ (14.5∘) 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∘ (0.75∘) from TE and 5∘ (12.5∘) 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.
Earth Surface Dynamics
10.5194/esurf-7-475-2019
2196-6311
2196-632X
Universität Potsdam
PA 2019_48
1374.45
<a href="http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-430165">Zweitveröffentlichung in der Schriftenreihe Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 725</a>
false
false
CC-BY - Namensnennung 4.0 International
Taylor Smith
Aljoscha Rheinwalt
Bodo Bookhagen
eng
uncontrolled
Digital Elevation Model
eng
uncontrolled
River Incision Model
eng
uncontrolled
Accuracy Asseessment
eng
uncontrolled
Landscape Response
eng
uncontrolled
Error
eng
uncontrolled
Slope
eng
uncontrolled
Uncertainties
eng
uncontrolled
Extraction
eng
uncontrolled
Expression
eng
uncontrolled
Patterns
Geowissenschaften
open_access
Institut für Geowissenschaften
Referiert
Publikationsfonds der Universität Potsdam
Open Access