Mapping Mangrove Extent and Change: A Globally Applicable Approach

This study demonstrates a globally applicable method for monitoring mangrove forest extent at high spatial resolution. A 2010 mangrove baseline was classified for 16 study areas using a combination of ALOS PALSAR and Landsat composite imagery within a random forests classifier. A novel map-to-image...

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Autors principals:	Nathan Thomas, Peter Bunting, Richard Lucas, Andy Hardy, Ake Rosenqvist, Temilola Fatoyinbo
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2018-09-01
Col·lecció:	Remote Sensing
Matèries:	mangrove machine learning global change change detection ALOS PALSAR
Accés en línia:	http://www.mdpi.com/2072-4292/10/9/1466
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