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Detecting Alluvial Fans Using Quantitative Roughness Characterization and Fuzzy Logic Analysis
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Detecting Alluvial Fans Using Quantitative Roughness Characterization and Fuzzy Logic Analysis
Andrea Taramelli1, 2 and Laura Melelli2
| (1) |
Lamont Doherty Earth Observatory of Columbia University, New York, Route 9W, Palisades, NY 10964, USA |
| (2) |
Dipartimento di Scienze della Terra, Università degli Studi di Perugia, via Faina, 4, 06123 Perugia, Italy |
Abstract
This research, based on a similarity geometric model, uses quantitative roughness characterization and fuzzy logic analysis
to map alluvial fans. We choose to work in the Italian central Apennine intermountain basins because much human activities
could mask this kind of landforms and because the timing of alluvial deposition is tied to land surface instabilities caused
by regional climate changes. The main aim of the research is to understand where they form and where they extent in an effort
to develop a new approach using the backscatter roughness parameters and primary attributes (elevation and curvature) derived
from the SRTM DEM. Moreover, this study helps to provide a benchmark against which future alluvial fans detection using roughness
and fuzzy logic analysis can be evaluated, meaning that sophisticated coupling of geomorphic and remote sensing processes
can be attempted, in order to test for feedbacks between geomorphic processes and topography.
Keywords Alluvial Fan - DEM - Roughness - Fuzzy Logic - Curvature - Elevation
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