Unsupervised detection of InSAR time series patterns based on PCA and K-means clustering

Unsupervised detection of InSAR time series patterns based on PCA and K-means clustering

The need for implementing efficient value-adding tools able to optimise Earth Observation data usage, compels the scientific community to find innovative solutions for the downstream of Earth Observation information. In this paper we present an unsupervised and automated approach based on Principal...

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Bibliographic Details
Main Authors:	Davide Festa, Alessandro Novellino, Ekbal Hussain, Luke Bateson, Nicola Casagli, Pierluigi Confuorto, Matteo Del Soldato, Federico Raspini
Format:	Article
Language:	English
Published:	Elsevier 2023-04-01
Series:	International Journal of Applied Earth Observations and Geoinformation
Subjects:	InSAR time series PCA Unsupervised learning Data mining Automated approach EO data downstream
Online Access:	http://www.sciencedirect.com/science/article/pii/S1569843223000985

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