Harmonizing the Land Cover Classification System (LCCS) and the General Habitat Categories (GHC) taxonomies
Strategic environmental conservation plans demand regular monitoring of the changes in land cover and habitats at various scales and standardized procedures are necessary to ensure consistency and compatibility between sites. Land cover mapping and its associated classification systems are driven by the remote sensing community, while habitat mapping and its associated classification systems are driven by the ecological research community. To improve biodiversity monitoring at local to global scales, the perceptions of both communities need to be integrated. There is also an emerging need to harmonize land cover and habitat classification systems and establish a class translation framework that allows existing land cover and habitat information to be utilised to more explicitly describe and quantify ecological functions and dynamics.
BIO_SOS adopted the Food and Agriculture Organization of the United Nations Land Cover Classification System (FAO-LCCS) and the General Habitat Categories (GHCs) due to their ability to facilitate consistent and reliable mapping of land cover and habitats respectively. In this research, the relations between the two taxonomies have been thoroughly investigated on the basis of their intrinsic characteristics in order to identify expert rules to map LCCS to the respective GHC classes. Ambiguity in the mapping rules was observed, mainly due to discrepancies in the terminology of height and the scale of observation that the two taxonomies adopt. In particular, the one-to-many relationships linking the LCCS and GHC taxonomies at a theoretical level highlighted the need for the inclusion of additional data including extensive height information, spatial features and topological rules to resolve mapping ambiguities.
The proposed framework was applied to an LCCS land cover map of two Natura 2000 study areas, in Italy (the Le Cesine site) and Wales (the Cors Fochno site). The results proved that the approach developed within the BIOSOS project can be used to derive habitat maps from land cover maps at a national, regional and global level, recognizing the potential of remote sensing to biodiversity monitoring.