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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Taramelli, A., Melelli, L. (2009). Detecting Alluvial Fans Using Quantitative Roughness Characterization and Fuzzy Logic Analysis. In: Gavrilova, M.L., Tan, C.J.K. (eds) Transactions on Computational Science VI. Lecture Notes in Computer Science, vol 5730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10649-1_15
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DOI: https://doi.org/10.1007/978-3-642-10649-1_15
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