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International Conference on Computational Science and Its Applications

ICCSA 2008: Computational Science and Its Applications – ICCSA 2008 pp 1–15Cite as

Detecting Alluvial Fans Using Quantitative Roughness Characterization and Fuzzy Logic Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5072))

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.

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Authors and Affiliations

  1. Lamont Doherty Earth Observatory of Columbia University, New York, Route 9W, Palisades, NY 10964, USA

    Andrea Taramelli

  2. Dipartimento di Scienze della Terra, Università degli Studi di Perugia, via Faina, 4, 06123, Perugia, Italy

    Andrea Taramelli & Laura Melelli

Authors
  1. Andrea Taramelli
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  2. Laura Melelli
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Osvaldo Gervasi Beniamino Murgante Antonio Laganà David Taniar Youngsong Mun Marina L. Gavrilova

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Taramelli, A., Melelli, L. (2008). Detecting Alluvial Fans Using Quantitative Roughness Characterization and Fuzzy Logic Analysis. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69839-5_1

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  • DOI: https://doi.org/10.1007/978-3-540-69839-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69838-8

  • Online ISBN: 978-3-540-69839-5

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