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dc.contributor.authorValle, Mireia-
dc.contributor.authorPala, Vicenc-
dc.contributor.authorLafon, Virgine-
dc.contributor.authorDehouck, Aurelie-
dc.contributor.authorBorja, Angel-
dc.contributor.authorChust, Guillem-
dc.contributor.authorGarmendia, Joxe Mikel-
dc.date.accessioned2017-08-23T08:52:07Z-
dc.date.available2017-08-23T08:52:07Z-
dc.date.issued2015-
dc.identifierISI:000367862400043-
dc.identifier.citationESTUARINE COASTAL AND SHELF SCIENCE, 2015, 164, 433-442-
dc.identifier.issn0272-7714-
dc.identifier.urihttp://dspace.azti.es/handle/24689/210-
dc.description.abstractEstuaries and coasts are among the most productive ecosystems and constitute valuable habitats for biodiversity and ecosystem services. Amongst nearshore ecosystems, seagrass beds play a major role enhancing biodiversity and water quality. Consequently, the development of new approaches to create extensive and high-resolution habitat maps is required not only to implement conservation, restoration and management plans, but also to establish adaptation plans to face climate change impacts. This study particularly assesses the capability of hyperspectral airborne imagery acquired with Compact Airborne Spectrographic Imager (CASI) to discriminate and map estuarine habitats, with special focus on Zostera noltii seagrass meadows. To this end, 13 habitats were defined along the supralittoral, intertidal and subtidal zones of an estuary, including Z noltii seagrass meadows. The CASI sensor was configured to acquire 25 bands in the visible and near infrared wavelengths with a ground sampling distance of 2 m. Spectral bands were selected for species discrimination based on the spectral signature of the different habitat classes. Six different band combinations were tested applying maximum likelihood classification algorithm. The most accurate classification was obtained with 10 band combination (a mean producer accuracy 92\% and a mean user accuracy 94\%). The classification of Z noltii beds has been found to be restricted to moderate and high dense meadows, however a vegetation index has been defined which could be applied for mapping Z noltii meadow cover. These results highlight the value of CASI data to discriminate and map estuarine habitats, providing key information to be used in supporting the implementation of environmental legislation, protection and conservation of coastal habitats. (C) 2015 Elsevier Ltd. All rights reserved.-
dc.description.sponsorshipThis investigation was funded by the Basque Water Agency (URA) under an agreement with AZTI; likewise by the Ministry of Economy and Competitiveness of the Spanish Government (Project Ref.: CTM2011-29473). M. Valle has benefited from a PhD Scholarship granted by the Inaki Goenaga - Technology Centres Foundation. We wish to thank the botanist Amador Prieto for his support in plant species identification which was essential for a correct classification of the different habitats analysed, Mercedes Herrera from the Flora and Vegetation Research Group of the University of the Basque Country (UPV/EHU) for her valuable comments on (Table 2) and Inigo Onandia from AZTI for the photographs taken during the field sampling carried out. Finally, the authors greatly acknowledge the CNES for funding the SYNIHAL project. The comments from the editor and three anonymous reviewers have improved considerably the first manuscript draft. This paper is contribution number 728 from AZTI (Marine Research Division).-
dc.language.isoeng-
dc.publisherACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD-
dc.subjectHabitat classification-
dc.subjectEstuaries-
dc.subjectRemote sensing-
dc.subjectZostera noltii-
dc.subjectCompact airborne spectrographic imager-
dc.subjectZOSTERA-NOLTII-
dc.subjectECOSYSTEM SERVICES-
dc.subjectCLASSIFICATION ACCURACY-
dc.subjectSPECTRAL REFLECTANCE-
dc.subjectCOASTAL-
dc.subjectVEGETATION-
dc.subjectLIDAR-
dc.subjectIDENTIFICATION-
dc.subjectBIODIVERSITY-
dc.subjectSATELLITE-
dc.titleMapping estuarine habitats using airborne hyperspectral imagery, with special focus on seagrass meadows-
dc.typeArticle-
dc.identifier.journalESTUARINE COASTAL AND SHELF SCIENCE-
dc.format.page433-442-
dc.format.volume164-
dc.contributor.funderBasque Water Agency (URA)-
dc.contributor.funderMinistry of Economy and Competitiveness of the Spanish Government \[CTM2011-29473]-
dc.contributor.funderInaki Goenaga - Technology Centres Foundation-
dc.contributor.funderCNES-
dc.identifier.e-issn1096-0015-
dc.identifier.doi10.1016/j.ecss.2015.07.034-
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