The Earth Observation Data for Habitat Monitoring (EODHaM) system

ribution was double-blind reviewed as extended abstract. As part of the Biodiversity Multi-Source Monitoring System (BIO_SOS), a new approach to the classification of Food and Agricultural Organisation (FAO) Land Cover Classification System (LCCS) classes from very high resolution (VHR) remote sensing data has been developed. These classes are also translated to General Habitat Categories (GHCs). Examples of the classification are presented for Cors Fochno in Wales but can be generated for any site where appropriate remote sensing data have been acquired. The system has been developed for operational monitoring of protected areas and their surrounds.

• Type: Journal
• Year: 2015
• Where: AEOG
• Authors: Richard M. Lucas, Palma Blonda, Peter Bunting, Gwawr Jones, Jordi Inglada, Marcela Arias, Vasiliki Kosmidou, Zisis I. Petrou, Ioannis Manakos, Maria Adamo, Rebecca Charnock, Cristina Tarantino, Caspar A. Mücher, Rob H. G. Jongman, Henk Kramer, Damien Arvor, João Pradinho Honrado, Paola Mairota
• Keywords: AEOG 2015, Artificial Intelligence