BIO_SOS: Biodiversity Multi-Source MOnitoring System: From Space To Species”
Project Description
The input data sources are multi-seasonal EO measurements and on-site data, including ancillary information and in-field measurements. The project is based on prior generation of land cover/use (LCLU) and change maps and their subsequent translation to categories of habitat appropriate to support conservation agencies and land managers in decisions relating to protection of NATURA 2000 sites. The system adopts deductive learning schemes: it is based on expert knowledge elicitation from botanist, ecologists, remote sensing experts and management authorities to fill the gap between LCLU and habitat domains. Ontologies are used to formally represent the expert knowledge: a) for LCLU and habitat classes description [prior knowledge of class spectral signatures, class phenology (i.e. temporal relations), spatial relations (e.g. adjacency, distance) as well as class attributes (e.g. shape)]; b) to translate LCLU into habitat classes as both GHC and Annex I maps; c) to evaluate the impacts that anthropic pressure may have on biodiversity. The Food and Agricultural Organization (FAO) Land Cover Classification Scheme (LCCS) and the General Habitat Categories (GHCs), from which Annex I Habitats can be defined, have been proposed for describing LCLU and habitat categories. EODHaM has been implemented in python (open source software).
