Name
Title | ||
|---|---|---|
Data–driven classification of landslide types at a national scale by using Artificial Neural Networks |
Abstract | ||
|---|---|---|
•Artificial intelligence methods can classify landslide type for national scale inventories.•The classification relies on Digital Elevation Models and shape related parameters.•The spatial distribution of the landslides is considered as an important feature.•The classification is data-driven and does not require any rule setting by the user. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jag.2021.102549 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | DocType | Volume |
Data-driven classification,Artificial Neural Network,Machine Learning,Landslide inventory,Landslide type,Geospatial modelling | Journal | 104 |
ISSN | Citations | PageRank |
0303-2434 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabriele Amato | 1 | 0 | 0.34 |
| Lorenzo Palombi | 2 | 2 | 1.11 |
| valentina raimondi | 3 | 2 | 1.78 |