FP7-SPA.2010.1.1-04. BIO_SOS: Biodiversity Multi-source Monitoring System: from Space to Species GA. 263435 (Progetti)

Type
Label
  • FP7-SPA.2010.1.1-04. BIO_SOS: Biodiversity Multi-source Monitoring System: from Space to Species GA. 263435 (Progetti) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Alternative label
  • Palma Blonda, Panyotis Dimopoulos, MAria Petrou, Rob Jongman, Harini Nagendra, Daniela Iasillo, Alain Arnaud, Paola Mairota, Joao Honrado, Emilio Padoa Schioppa, Richard Lucas, Laurent Durieux, Bollanos, LAura Candela, Andrea Baraldi, Jordi Inglada (2010)
    FP7-SPA.2010.1.1-04. BIO_SOS: Biodiversity Multi-source Monitoring System: from Space to Species GA. 263435
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Palma Blonda, Panyotis Dimopoulos, MAria Petrou, Rob Jongman, Harini Nagendra, Daniela Iasillo, Alain Arnaud, Paola Mairota, Joao Honrado, Emilio Padoa Schioppa, Richard Lucas, Laurent Durieux, Bollanos, LAura Candela, Andrea Baraldi, Jordi Inglada (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1. Consiglio Nazionale delle Ricerche (CNR), Italy (blonda@ba.issia.cnr.it , c.maragi@ba.iac.cnr.it) 2. Panepistimio Ioanninon (UOI), Greece (pdimopul@uwg.gr ) 3. Centre for Research and Technology Hellas (CE.R.T.H.) Greece ( { imanakos, kosmido }@iti.gr ) 4. Alterra, Wageningen UR, The Netherlands ({rob.jongman, sander.mucher}@wur.nl) 5. Ashoka trust for Research in Ecology and the Environment (ATREE), India (nagendra@atree.org ) 6. Planetek Italia SRL (PKI), Italy ({iasillo, stutte }@planetek.it ) 7. Altamira Information SL (ALTAMIRA), Spain (alain.arnaud@altamira-information.com ) 8. Universita degli Studi di Bari \"ALDO MORO\" (UNIBA), Italy (p.mairota@agr.uniba.it ) 9. ICETA - Instituto de Ciências e Tecnologias Agrárias e Agro-Alimentares (CIBIO), Portugal (jhonrado@fc.up.pt ) 10. Universita degli Studi de Milano-Bicocca (UNIMIB), Italy (emilio.padoaschioppa@unimib.it ) 11. Aberystwyth University (ABERY), United Kingdom (rml@aber.ac.uk ) 12. Institut de Recherche pour le Developpement (IRD), France (laurent.durieux@ird.fr ) 13. Planetek Hellas (PKH), Greece (bollanos@planetek.gr ) 14. Agenzia Spaziale Italiana (ASI), Italy (laura.candela@asi.it ) 15. Baraldi Consultancy in Remote Sensing (BACRES), Italy. The participation of Partner 15 has been terminated as per Amendment n. 1, taking effect on 15/09/2011. (andrea6311@gmail.com ) 16. Université Paul Sabatier (UPS), France. (jordi.inglada@cesbio.cnes.fr). The addition of the new Partner 16, starting on 15/12/2011, was approved in Amendment n. 1 dated 03/02/2012. (literal)
Titolo
  • FP7-SPA.2010.1.1-04. BIO_SOS: Biodiversity Multi-source Monitoring System: from Space to Species GA. 263435 (literal)
Descrizione sintetica
  • BIO_SOS (BIOdiversity Multi-Source MOnitoring System: From Space To Species; www.biosos.eu ) addresses topic SPACE.2010.1.1-04 \"Stimulating the development of GMES services in specific areas\" with application to (B) BIODIVERSITY. The main objective of BIO-SOS is the development of a knowledge-based pre-operational ecological modelling system suitable for effective and timely multi-annual monitoring of NATURA 2000 sites and their surrounding areas particularly exposed to different and combined type of pressures. Its input data sources are satellite-based measurements and on-site data. Ontologies and semantic network are used to formally represent the expert knowledge. The proposed system, named EO Data for Habitat Monitoring (EODHaM), is compliant with on-going GEOSS, GMES and INSPIRE initiatives. Study areas in three Mediterranean and two Western Europe Countries are under way. To extrapolate from European test cases such that the methods can be applied more generally, additional areas are being considered in two tropical countries (i.e., Brazil and India), where the Natura 2000 system does not exist, but the availability of advanced monitoring systems is particularly important for Biodiversity conservation. BIO_SOS has made progress steps towards developing: o Novel pre-operational automatic high spatial resolution (HR), very high spatial resolution (VHR) and hyper-spectral resolution EO data understanding techniques for land cover/use (LC/LU) map and LC/LU change map generation as an improvement of GMES core services; o New GMES down-stream services based on ecological modelling, at habitat and landscape level, to combine EO and in-situ data and provide HR and VHR General Habitat Categories (GHCs) (http://www.ebone.wur.nl) and Annex 1 Habitat maps, their changes and adequate indicators of biodiversity o Quantitative landscape pattern analysis (QLPA) framework to produce composite, site/scale specific indicator set for monitoring and Natura 2000 buffer area identification; o Ecological niche modelling (ENM) to evaluate the importance of GHCs as environmental variables to explain the distribution of the target species better than LC/LU. o Threat analysis framework to use EO data to extract pressure trends through direct detection or monitoring of impacts on landscapes, land cover/habitat types, communities and species. o BIO_SOS metadata geoportal. The EODHaM proposed system is a 3-stage processing system (Figure 1). It has adopted the Food and Agriculture (FAO) Land Cover Classification System (LCCS) scheme and taxonomy for LC/LU class identification because LCCS is more suitable than CORINE as the land cover/use categories can be more readily translated to habitat categories. EODHaM 1st- stage provides robust classification of bi-temporal radiometrically calibrated EO images into LCCS Levels 1 to 2, with this based primarily on spectral data, followed by a 2nd stage that additionally utilises contextual information to discriminate and map classes in LCCS level 3 and beyond. Based on expert knowledge of botanists, ecologists and local site managers, land cover/use and habitat classes are described by the experts in terms of their temporal characteristics and/or spatial relationships which are used in both 2nd and 3rd third EODHaM stages. The outputs of the 2nd stage are LC/LU maps. The outputs of the 3rd stage include General Habitat Categories (GHCs), Annex 1 habitats as well as biodiversity indices and their trends. Thematic change maps are also provided. Once LC/LU classes and habitats are described through a semantic language, any site can theoretically be mapped and subsequently monitored over time. (literal)
Abstract
  • BIO_SOS (BIOdiversity multi-SOurce monitoring System: from Space TO Species is a response to the Call for proposals FP7- SPACE-2010-1, addressing topic SPACE.2010.1.1-04 \"Stimulating the development of GMES services in specific areas\" with application to (B) BIODIVERSITY. BIO_SOS is a pilot project for effective and timely multi-annual monitoring of NATURA 2000 sites and their surrounding in support to management decisions in sample areas, mainly in Mediterranean regions and for the reporting on status and trends according to National and EU obligations. The aim of BIO_SOS is two-fold: 1) the development and validation of a prototype multi-modular system to provide a reliable long term biodiversity monitoring service at high to very high-spatial resolution; 2) to embed monitoring information (changes) in innovative ecological (environmental) modelling for Natura 2000 site management. The system will be developed and validated within ecologically sensitive 'sampling' sites and their borders exposed to combined human-induced pressures. Different environmental characteristics of the selected sites have been considered in order to ensure system robustness. Sites characteristics ranges from mountain rough to flat coastal morphologies, from rangeland to human dominated landscapes and land uses. BIO_SOS intends to deeply investigate issues related to very high spatial (VHR) (and spectral) resolution Earth Observation data (EO) image processing for automatic land cover maps updating and change detection. Such maps are at the base of biodiversity indicators provision. On the other hand, it intends to develop a modelling framework to combine multi-scale (high to very high resolution) EO data and in-situ/ancillary data to provide indicators and their trends. This means the development of more appropriate and accurate models in support to a deeper understanding, assessment and prediction of the impacts that human induced pressures may have on biodiversity loss. (literal)
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