Data–driven classification of landslide types at a national scale by using Artificial Neural Networks

Data–driven classification of landslide types at a national scale by using Artificial Neural Networks

Classification of landslide type is an essential step in risk management, although is often missing in large inventories. Here we propose a novel data-driven method that uses easily accessible morphometric and geospatial input parameters to classify landslides type at a national scale in Italy by me...

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Bibliographic Details
Main Authors: Gabriele Amato, Lorenzo Palombi, Valentina Raimondi
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Data-driven classification
Artificial Neural Network
Machine Learning
Landslide inventory
Landslide type
Geospatial modelling
Online Access:http://www.sciencedirect.com/science/article/pii/S0303243421002567

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http://www.sciencedirect.com/science/article/pii/S0303243421002567

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