The Earth Observation Data for Habitat Monitoring (EODHaM) system

Authors Organisations
  • Richard Lucas(Author)
    University of New South Wales
  • Palma Blonda(Author)
    National Research Council – Institute of Intelligent Systems for Automation (CNR-ISSIA)
  • Pete Bunting(Author)
  • Gwawr Jones(Author)
  • Jordi Inglada(Author)
    CESBIO (CNES/CNRS/UPS/IRD)
  • Marcela Arias(Author)
    CESBIO (CNES/CNRS/UPS/IRD)
  • Vasiliki Kosmidou(Author)
    Information Technologies Institute (ITI),
  • Zisis I Petrou(Author)
    Information Technologies Institute (ITI),
  • Ioannis Manakos(Author)
    Information Technologies Institute (ITI),
  • Maria Adamo(Author)
    National Research Council – Institute of Intelligent Systems for Automation (CNR-ISSIA)
  • Rebecca Charnock(Author)
  • Cristina Tarantino(Author)
    National Research Council – Institute of Intelligent Systems for Automation (CNR-ISSIA)
  • Caspar A Mücher(Author)
    Wageningen University and Research Centre
  • Rob H. G. Jongman(Author)
    Wageningen University and Research Centre
  • Henk Kramer(Author)
    Wageningen University and Research Centre
  • Damien Arvor(Author)
    UMR ESPACE-DEV
  • João Pradinho Honrado(Author)
    Universidade do Porto
  • Paola Mairota(Author)
    University of Bari
Type Article
Original languageEnglish
Pages (from-to)17-28
Number of pages12
JournalInternational Journal of Applied Earth Observation and Geoinformation
Volume37
Early online date18 Nov 2014
DOI
Publication statusPublished - May 2015
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Abstract

To support decisions relating to the use and conservation of protected areas and surrounds, the EU-funded BIOdiversity multi-SOurce monitoring System: from Space TO Species (BIO_SOS) project has developed the Earth Observation Data for HAbitat Monitoring (EODHaM) system for consistent mapping and monitoring of biodiversity. The EODHaM approach has adopted the Food and Agriculture Organization Land Cover Classification System (LCCS) taxonomy and translates mapped classes to General Habitat Categories (GHCs) from which Annex I habitats (EU Habitats Directive) can be defined. The EODHaM system uses a combination of pixel and object-based procedures. The 1st and 2nd stages use earth observation (EO) data alone with expert knowledge to generate classes according to the LCCS taxonomy (Levels 1 to 3 and beyond). The 3rd stage translates the final LCCS classes into GHCs from which Annex I habitat type maps are derived. An additional module quantifies changes in the LCCS classes and their components, indices derived from earth observation, object sizes and dimensions and the translated habitat maps (i.e., GHCs or Annex I). Examples are provided of the application of EODHaM system elements to protected sites and their surrounds in Italy, Wales (UK), the Netherlands, Greece, Portugal and India.

Keywords

  • habitat, land cover, classification, monitoring, remote sensing