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dc.contributorFacultad de Ciencias Biologicas y Ambientaleses_ES
dc.contributor.authorFernández García, Víctor 
dc.contributor.authorMarcos Porras, Elena María 
dc.contributor.authorFernández Guisuraga, José Manuel 
dc.contributor.authorFernández Manso, Alfonso 
dc.contributor.authorQuintano Pastor, Carmen
dc.contributor.authorSuárez-Seoane, Susana 
dc.contributor.authorCalvo Galván, María Leonor 
dc.contributor.otherEcologiaes_ES
dc.date2021-03-04
dc.date.accessioned2021-05-04T08:40:50Z
dc.date.available2021-05-04T08:40:50Z
dc.identifier.issn2072-4292
dc.identifier.otherhttps://www.mdpi.com/2072-4292/13/5/979es_ES
dc.identifier.urihttp://hdl.handle.net/10612/13116
dc.descriptionP. 1-19 Artículoes_ES
dc.description.abstractHeterogeneous and patchy landscapes where vegetation and abiotic factors vary at small spatial scale (fine-grained landscapes) represent a challenge for habitat diversity mapping using remote sensing imagery. In this context, techniques of spectral mixture analysis may have an advantage over traditional methods of land cover classification because they allow to decompose the spectral signature of a mixed pixel into several endmembers and their respective abundances. In this work, we present the application of Multiple Endmember Spectral Mixture Analysis (MESMA) to quantify habitat diversity and assess the compositional turnover at different spatial scales in the fine-grained landscapes of the Cantabrian Mountains (northwestern Iberian Peninsula). A Landsat-8 OLI scene and high-resolution orthophotographs (25 cm) were used to build a region-specific spectral library of the main types of habitats in this region (arboreal vegetation; shrubby vegetation; herbaceous vegetation; rocks–soil and water bodies). We optimized the spectral library with the Iterative Endmember Selection (IES) method and we applied MESMA to unmix the Landsat scene into five fraction images representing the five defined habitats (root mean square error, RMSE 0.025 in 99.45% of the pixels). The fraction images were validated by linear regressions using 250 reference plots from the orthophotographs and then used to calculate habitat diversity at the pixel ( -diversity: 30 30 m), landscape (-diversity: 1 1 km) and regional ("-diversity: 110 33 km) scales and thecompositional turnover ( - and -diversity) according to Simpson’s diversity index. Richness and evenness were also computed. Results showed that fraction images were highly related to reference data (R2 0.73 and RMSE 0.18). In general, our findings indicated that habitat diversity was highly dependent on the spatial scale, with values for the Simpson index ranging from 0.20 0.22 for -diversity to 0.60 0.09 for -diversity and 0.72 0.11 for "-diversity. Accordingly, we found -diversity to be higher than -diversity. This work contributes to advance in the estimation of ecological diversity in complex landscapes, showing the potential of MESMA to quantify habitat diversity in a comprehensive way using Landsat imageryes_ES
dc.languageenges_ES
dc.publisherMDPIes_ES
dc.subjectBiologíaes_ES
dc.subjectEcología. Medio ambientees_ES
dc.subjectIngeniería forestales_ES
dc.subject.otherMultiple Endmember Spectral Mixture Analysis (MESMA)es_ES
dc.subject.otherLandsates_ES
dc.subject.otherIberian Peninsulaes_ES
dc.subject.otherSpectral unmixinges_ES
dc.subject.otherAlpha diversityes_ES
dc.subject.otherBeta diversityes_ES
dc.subject.otherGamma diversityes_ES
dc.subject.otherDelta diversityes_ES
dc.subject.otherEpsilon diversityes_ES
dc.titleMultiple Endmember Spectral Mixture Analysis (MESMA) Applied to the Study of Habitat Diversity in the Fine-Grained Landscapes of the Cantabrian Mountainses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doihttps://doi.org/10.3390/rs13050979
dc.description.peerreviewedSIes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleRemote Sensinges_ES
dc.volume.number13 (5)es_ES
dc.issue.number979es_ES
dc.page.initial1es_ES
dc.page.final19es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES
dc.subject.unesco2417.13 Ecología Vegetales_ES
dc.subject.unesco2499 Otras Especialidades Biológicases_ES
dc.subject.unesco3199 Otras Especialidades Agrariases_ES
dc.rights.copyrightCC BYes_ES
dc.identifier.editorialMDPIes_ES


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