High-resolution topography data sets have improved the spatial and temporal scales at which we are able to investi-gate the landscape through the analysis of landform attributes and the computation of topographic changes. Yet, to date, there havebeen only limited attempts to infer key geomorphic processes in terms of contributions to shaping the landscape. Highly erodiblelandscapes such as badlands provide an ideal demonstration of such an approach owing to the rapid changes observed over a rel-atively short time frame. In this technical note we present the Mapping Geomorphic Processes in the Environment (MaGPiE): a newalgorithm that allows mapping of geomorphic process signatures through analysis of repeat high-resolution topography data sets. Themethod is demonstrated in an experimental badland located in the southern central Pyrenees. MaGPiE is a geographic informationsystem (GIS)-based algorithm that uses as input: (a) terrain attributes (i.e. Slope, Roughness and Concentrated Runoff Index) extractedfrom digital elevation models (DEMs), and (b) a map of topographic changes (DEM of difference, DoD). Initial results demonstratethat MaGPiE allows the magnitude and the spatial distribution of the main geomorphic processes reshaping badlands to be inferredfor the first time.

Geomorphic process signatures reshaping sub‐humid Mediterranean badlands: 1. Methodological development based on high‐resolution topography

Llena, Manel
;
2020

Abstract

High-resolution topography data sets have improved the spatial and temporal scales at which we are able to investi-gate the landscape through the analysis of landform attributes and the computation of topographic changes. Yet, to date, there havebeen only limited attempts to infer key geomorphic processes in terms of contributions to shaping the landscape. Highly erodiblelandscapes such as badlands provide an ideal demonstration of such an approach owing to the rapid changes observed over a rel-atively short time frame. In this technical note we present the Mapping Geomorphic Processes in the Environment (MaGPiE): a newalgorithm that allows mapping of geomorphic process signatures through analysis of repeat high-resolution topography data sets. Themethod is demonstrated in an experimental badland located in the southern central Pyrenees. MaGPiE is a geographic informationsystem (GIS)-based algorithm that uses as input: (a) terrain attributes (i.e. Slope, Roughness and Concentrated Runoff Index) extractedfrom digital elevation models (DEMs), and (b) a map of topographic changes (DEM of difference, DoD). Initial results demonstratethat MaGPiE allows the magnitude and the spatial distribution of the main geomorphic processes reshaping badlands to be inferredfor the first time.
Llena, Manel; Vericat, Damià; Smith, Mark W.; Wheaton, Joseph M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/737686
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