Abstract
Landslide susceptibility mapping is a crucial initial step in risk mitigation strategies. Landslide hazards are widely spread all over the world and, as such, mapping the relevant susceptibility levels is in constant research and development. As a result, numerous modelling techniques and approaches have been adopted by scholars, implementing these models at different scales and with different terrains, in search of the best-performing strategy. Nevertheless, a direct comparison is not possible unless the strategies are implemented under the same environmental conditions and scenarios. The aim of this work is to implement three statistical-based models (Statistical Index, Logistic Regression, and Random Forest) at the basin scale, using various scenarios for the input datasets (terrain variables), training samples and ratios, and validation metrics. A reassessment of the original input data was carried out to improve the model performance. In total, 79 maps were obtained using different combinations with some highly satisfactory outcomes and others that are barely acceptable. Random Forest achieved the highest scores in most of the cases, proving to be a reliable modelling approach. While Statistical Index passes the evaluation tests, most of the resulting maps were considered unreliable. This research highlighted the importance of a complete and up-to-date landslide inventory, the knowledge of local conditions, as well as the pre- and post-analysis evaluation of the input and output combinations.
Highlights
Landslides are considered to be one of the most diffused and devastating geohazards in the world (Guzzetti et al 1999; Iadanza et al 2009; Van Den Eeckhaut and Hervás 2012; Trigila et al 2015; Reichenbach et al 2018), as they are movements of rock mass, debris, or earth material (Varnes 1984) rushing downslope causing enormous damage
Since the model relies on the class weights computed according to the landslide density, the resulting maps do not exhibit a probability value ranging from 0 to 1 rather it can be a range of values from different sizes, even starting from the negative domain
No further processing and analyses were applied to these results, rather the focus was on the maps obtained with natural and quantile breaks
Summary
Landslides are considered to be one of the most diffused and devastating geohazards in the world (Guzzetti et al 1999; Iadanza et al 2009; Van Den Eeckhaut and Hervás 2012; Trigila et al 2015; Reichenbach et al 2018), as they are movements of rock mass, debris, or earth material (Varnes 1984) rushing downslope causing enormous damage (physical and economical).
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call