Integrated use of Sentinel-1 and Sentinel-2 data and open-source machine learning algorithms for land cover mapping in a Mediterranean region

Integrated use of Sentinel-1 and Sentinel-2 data and open-source machine learning algorithms for land cover mapping in a Mediterranean region

This paper aims to develop a supervised classification integrating synthetic aperture radar (SAR) Sentinel-1 (S1) and optical Sentinel-2 (S2) data for land use/land cover (LULC) mapping in a heterogeneous Mediterranean forest area. The time-series of each SAR and optical bands, three optical indices...

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Bibliographic Details
Main Authors: Giandomenico De Luca, João M. N. Silva, Salvatore Di Fazio, Giuseppe Modica
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:European Journal of Remote Sensing
Subjects:
synthetic aperture radar (sar)
sar interferometry (insar)
interferometric coherence
google earth engine (gee)
sar and multispectral time-series analysis
biophysical indicators
Online Access:http://dx.doi.org/10.1080/22797254.2021.2018667

Internet

http://dx.doi.org/10.1080/22797254.2021.2018667

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