Comparison of Machine Learning Methods Applied to SAR Images for Forest Classification in Mediterranean Areas

Comparison of Machine Learning Methods Applied to SAR Images for Forest Classification in Mediterranean Areas

In this paper, multifrequency synthetic aperture radar (SAR) images from ALOS/PALSAR, ENVISAT/ASAR and Cosmo-SkyMed sensors were studied for forest classification in a test area in Central Italy (San Rossore), where detailed in-situ measurements were available. A preliminary discrimination of the ma...

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Bibliographic Details
Main Authors: Alessandro Lapini, Simone Pettinato, Emanuele Santi, Simonetta Paloscia, Giacomo Fontanelli, Andrea Garzelli
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Remote Sensing
Subjects:
sar
mediterranean forests
forest features
forest/non-forest areas
land classification
machine learning
Online Access:https://www.mdpi.com/2072-4292/12/3/369

Internet

https://www.mdpi.com/2072-4292/12/3/369

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