Data · dataset · 2015
An alternative approach to transverse and profile terrain curvature
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Terrain curvature is one of the most important parameters of land surface topography.
Description
Well-established methods used in its measurement compute an index of plan or profile curvature for every single cell of a digital elevation model (DEM). The interpretation of these outputs may be delicate, especially when selected locations have to be analyzed.
Furthermore, they involve a high level of simplification, contrasting with the complex and multiscalar nature of the surface curvature itself. In this paper, we present a new method to assess vertical transverse and profile curvature combining real-scale visualization and the possibility to measure these two terrain derivatives over a large range of scales. To this purpose, we implemented a GIS tool that extracts longitudinal and transverse elevation profiles from a high-resolution DEM.
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The performance of our approach was compared with some of the most commonly used methods (ArcMap, Redlands, CA, USA; ArcSIE, Landserf) by analyzing the terrain curvature around charcoal production sites in southern Switzerland. The different methods produced comparable results. While conventional methods quickly summarize terrain curvature in the form of a matrix of values, they involve a loss of information.
The advantage of the new method lies in the possibility to measure and visualize the shape and size of the curvature, and to obtain a realistic representation of the average curvature for different subsets of spatial points. Moreover, the new method makes it possible to control the conditions in which the index of curvature is calculated.
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Where it is published
- Repository landing page tandf.figshare.com/articles/dataset/An_alternative_approach_to_transverse_and_pro… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.1339938 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1080/13658816.2014.995102 doi.org/10.1080/13658816.2014.995102 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.1339938 ↗
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- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.1339938 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Biological sciences · Chemical sciences · Mathematics
- From keywords
- Inorganic chemistry · Life Sciences · Mathematics & Statistics · Medicine & Health · Microbiology
- Inferred from text
- Longitudinal study 65%
Provenance · 1 source records, 15 field assertions
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|---|---|---|---|
| DataCite | 10.6084/m9.figshare.1339938 | 14 d ago | JSON v1 |
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| concepts[field].local:field:medicine-health | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Medicine'] |
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