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Christian Conoscenti

Researcher at University of Palermo

Publications -  71
Citations -  2870

Christian Conoscenti is an academic researcher from University of Palermo. The author has contributed to research in topics: Landslide & Topographic Wetness Index. The author has an hindex of 26, co-authored 66 publications receiving 2038 citations.

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Gully erosion susceptibility assessment by means of GIS-based logistic regression: a case of Sicily (Italy)

TL;DR: In this paper, the susceptibility conditions to gully erosion by means of GIS and multivariate statistical analysis was characterized by using field surveys and interpretation of aerial images of 260 gullies in a 9.5 km 2 river catchment in central-northern Sicily.
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A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran

TL;DR: Four methods were tested: evidential belief function (EBF), frequency ratio (FR), Technique for Order Preference by Similarity To ideal Solution (TOPSIS) and Vlse Kriterijumsk Optimizacija Kompromisno Resenje (VIKOR) for flood hazard susceptibility mapping (FHSM) in this area and all models except VIKOR showed acceptable accuracy of classification.
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Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy)

TL;DR: In this article, binary logistic regression (BLR) and stochastic gradient treeboost (SGT) methods were compared in assessing landslide susceptibility within the Mediterranean region for multiple-occurrence regional landslide events.
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Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice River basin (western Sicily, Italy)

TL;DR: In this paper, the effect of pre-failure topography on earth-flow spatial distribution was explored by reconstructing topography before the landslide occurrence using a topo-to-raster algorithm.
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Using topographical attributes to evaluate gully erosion proneness (susceptibility) in two mediterranean basins: advantages and limitations

TL;DR: In this article, two multivariate predictive models were generated for two gully erosion processes in San Giorgio basin (Italy) and Mula River basin (Spain) using only topographical attributes as independent variables.