Multiple Endmember Spectral Mixture Analysis (MESMA) Applied to the Study of Habitat Diversity in the Fine-Grained Landscapes of the Cantabrian Mountains
| Autor: | Susana Suárez-Seoane, Víctor Fernández-García, Carmen Quintano, Leonor Calvo, José Manuel Fernández-Guisuraga, Elena Marcos, Alfonso Fernández-Manso |
|---|---|
| Přispěvatelé: | Ecologia, Facultad de Ciencias Biologicas y Ambientales |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Beta diversity
Endmember Spectroscopic imaging 010504 meteorology & atmospheric sciences Gamma diversity Biología 0211 other engineering and technologies Epsilon diversity Delta diversity 02 engineering and technology Ingeniería forestal 01 natural sciences Diversity index Landsat-8 OLI spectral unmixing Paisaje - España - Cordillera Cantábrica Alpha diversity Ecosystem diversity lcsh:Science 021101 geological & geomatics engineering 0105 earth and related environmental sciences Landsat Iberian Peninsula alpha diversity beta diversity gamma diversity delta diversity epsilon diversity Spectral signature 2417.13 Ecología Vegetal Vegetation 3307 Tecnología Electrónica Spectrum analysis Ecología. Medio ambiente Image processing - Digital techniques Spectral imaging 2499 Otras Especialidades Biológicas General Earth and Planetary Sciences Environmental science lcsh:Q Physical geography Multiple Endmember Spectral Mixture Analysis (MESMA) Spectral unmixing 3199 Otras Especialidades Agrarias |
| Zdroj: | Remote Sensing, Vol 13, Iss 979, p 979 (2021) Scopus RUO. Repositorio Institucional de la Universidad de Oviedo instname Remote Sensing; Volume 13; Issue 5; Pages: 979 BULERIA: Repositorio Institucional de la Universidad de León Universidad de León BULERIA. Repositorio Institucional de la Universidad de León Instituto de Salud Carlos III (ISCIII) |
| ISSN: | 2072-4292 |
| Popis: | Producción Científica 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 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 (α-diversity: 30 × 30 m), landscape (γ-diversity: 1 × 1 km) and regional (ε-diversity: 110 × 33 km) scales and the compositional turnover (β- and δ-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 α-diversity to 0.60 ± 0.09 for γ-diversity and 0.72 ± 0.11 for ε-diversity. Accordingly, we found β-diversity to be higher than δ-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 imagery. Ministerio de Agricultura, Pesca y Alimentación - (Project 0190020007497) Ministerio de Educación, Cultura y Deporte - (Project FPU16/03070) |
| Databáze: | OpenAIRE |
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