A Statistical Exploratory Analysis of Inventoried Slide-Type Movements for South Tyrol (Italy)

Steger, Stefan, Mair, Volkmar, Kofler, Christian, Pittore, Massimiliano, Zebisch, Marc and Schneiderbauer, Stefan, "A Statistical Exploratory Analysis of Inventoried Slide-Type Movements for South Tyrol (Italy)" in Understanding and Reducing Landslide Disaster Risk ed. Guzzetti, Fausto, Snježana, Arbanas Mihalić, Reichenbach, Paola, Sassa, Kyoji, Bobrowsky, Peter T. and Takara, Kaoru (Cham: Springer Nature Switzerland AG, 2020), 305-311.

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  • Author Steger, Stefan
    Mair, Volkmar
    Kofler, Christian
    Pittore, Massimiliano
    Zebisch, Marc
    Schneiderbauer, Stefan
    Book Editor Guzzetti, Fausto
    Snježana, Arbanas Mihalić
    Reichenbach, Paola
    Sassa, Kyoji
    Bobrowsky, Peter T.
    Takara, Kaoru
    Chapter Title A Statistical Exploratory Analysis of Inventoried Slide-Type Movements for South Tyrol (Italy)
    Book Title Understanding and Reducing Landslide Disaster Risk
    Publication Date 2020-12-23
    Place of Publication Cham
    Publisher Springer Nature Switzerland AG
    Start page 305
    End page 311
    Language eng
    Abstract Landslides of the slide-type movement represent common damaging phenomena in the Italian province of South Tyrol. Up to January 2019, the landslide inventory of the province lists 1928 accurately mapped landslides that required intervention by e.g. the local road service or the provincial geological survey. Thus, this landslide data set mainly includes events that caused damage. The aim of this contribution was to investigate and critically interpret statistical associations between the inventoried slide-type movements and a variety of spatial environmental variables. The assessment of conditional frequencies and the discriminatory power of single variables revealed conditions that are typically present at landslide mapping locations, e.g. topography, land cover, rock types, and proximity to infrastructure. A critical interpretation of thestatistical results highlighted the need to consider the landslide data origin (i.e. background information) in order to avoid misleading statements and wrong inferences. The findings of the here presented work show that the availability of detailed landslide information does not always ensure that valid process-related conclusions can be drawn from subsequent statistical analyses (e.g. identification of important landslide controls). Despite considerable methodical advancements in the field of statistical data analysis and machine learning, we conclude that the principle ‘correlation does not necessarily imply (geomorphic) causation’ remains of particular relevance.
    Keyword Landslide inventory
    South Tyrol
    Exploratory data analysis
    IFFI sampling bias
    Copyright Holder Springer Nature Switzerland AG
    Copyright Year 2021
    Copyright type All rights reserved
    ISBN 9783030602260
    DOI 10.1007/978-3-030-60227-7_34
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    Created: Thu, 25 Feb 2021, 21:43:45 JST by Austin Gonzales on behalf of UNU EHS