Automated classification of A-DInSAR-based ground deformation by using random forest

Automated classification of A-DInSAR-based ground deformation by using random forest

Wide-area ground motion monitoring is nowadays achievable via advanced Differential Interferometry SAR (A-DInSAR) techniques which benefit from the availability of large sets of Copernicus Sentinel-1 images. However, it is of primary importance to implement automated solutions aimed at performing in...

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Bibliographic Details
Main Authors: Davide Festa, Nicola Casagli, Francesco Casu, Pierluigi Confuorto, Claudio De Luca, Matteo Del Soldato, Riccardo Lanari, Michele Manunta, Mariarosaria Manzo, Federico Raspini
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:GIScience & Remote Sensing
Subjects:
ground deformation
a-dinsar
machine learning
random forest
automated classification
Online Access:http://dx.doi.org/10.1080/15481603.2022.2134561

Internet

http://dx.doi.org/10.1080/15481603.2022.2134561

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