Focusing on the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) and the recently proposed General Habitat Categories (GHCs) classifycation system, this paper illustrates how expert knowledge concerning class spatial arrangement in the scene at hand class, class phenology and class spectral signature in multitemporal EO images can fill the gaps between the two classification systems and provide LC/LU to habitat translation. An application to a Natura 2000 site in Southern Italy which includes a wetland costal area is discussed.

Exploitation of Remote Sensing data for Land Cover to Habitat map translation: a case study

Adamo M;Tarantino C;Tomaselli V;Blonda P
2013

Abstract

Focusing on the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) and the recently proposed General Habitat Categories (GHCs) classifycation system, this paper illustrates how expert knowledge concerning class spatial arrangement in the scene at hand class, class phenology and class spectral signature in multitemporal EO images can fill the gaps between the two classification systems and provide LC/LU to habitat translation. An application to a Natura 2000 site in Southern Italy which includes a wetland costal area is discussed.
2013
Istituto di Bioscienze e Biorisorse
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
978-3-87907-532-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/201092
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