RT info:eu-repo/semantics/article T1 Multiple Endmember Spectral Mixture Analysis (MESMA) Applied to the Study of Habitat Diversity in the Fine-Grained Landscapes of the Cantabrian Mountains A1 Fernández García, Víctor A1 Marcos Porras, Elena María A1 Fernández Guisuraga, José Manuel A1 Fernández Manso, Alfonso A1 Quintano Pastor, Carmen A1 Suárez-Seoane, Susana A1 Calvo Galván, María Leonor A2 Ecologia K1 Biología K1 Ecología. Medio ambiente K1 Ingeniería forestal K1 Multiple Endmember Spectral Mixture Analysis (MESMA) K1 Landsat K1 Iberian Peninsula K1 Spectral unmixing K1 Alpha diversity K1 Beta diversity K1 Gamma diversity K1 Delta diversity K1 Epsilon diversity K1 2417.13 Ecología Vegetal K1 2499 Otras Especialidades Biológicas K1 3199 Otras Especialidades Agrarias AB Heterogeneous 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 thespectral 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 0.025in 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 referencedata (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 ofecological diversity in complex landscapes, showing the potential of MESMA to quantify habitat diversity in a comprehensive way using Landsat imagery PB MDPI SN 2072-4292 LK http://hdl.handle.net/10612/13116 UL http://hdl.handle.net/10612/13116 NO P. 1-19 Artículo DS BULERIA. Repositorio Institucional de la Universidad de León RD 29-mar-2024