Spectral-Based Monitoring of Climate Effects on the Inter-Annual Variability of Different Plant Functional Types in Mediterranean Cork Oak Woodlands

Using remotely sensed data to estimate the biophysical properties of vegetation in woodlands is a challenging task due to their heterogeneous nature. The objective of this study was to assess the biophysical parameters of different vegetation types (cork oak trees, shrubs and herbaceous vegetation) in cork oak woodland through the analysis of temporal trends in spectral vegetation indices (VIs). A seven-year database (from 2011 until 2017) of in situ observations collected with a field spectroradiometer with a monthly basis was used and four VIs were derived, considered as proxies for several biophysical properties of vegetation such as biomass (Normalized Difference Vegetation Index—NDVI); chlorophyll content (MERIS Terrestrial Chlorophyll Index-MTCI), tissue water content (Normalized Difference Water Index—NDWI) and the carotenoid/chlorophyll ratio (Photochemical Reflectance Index—PRI). During the analyzed period, some key meteorological data (precipitation, temperature, relative air humidity and global radiation) were collected for the study site, aggregated at three different time-lags (short period (30 d), medium period (90 d) and hydrological period (HIDR)), and their relationship with VIs was analyzed. The results showed different trends for each vegetation index and vegetation type. In NDVI and NDWI, herbaceous vegetation showed a highly marked seasonal trend, whereas for MTCI, it was the cork oak and Cistus salvifolius, and for PRI, it was Ulex airensis that showed the marked seasonal trend. Shrubs have large differences depending on the species: the shallow-rooted Cistus salvifolius showed a higher seasonal variability than the deep-rooted Ulex airensis. Our results revealed the importance of temperature and precipitation as the main climatic variables influencing VI variability in the four studied vegetation types. This study sets up the relationships between climate and vegetation indices for each vegetation type. Spectral vegetation indices are useful tools for assessing the impact of climate on vegetation, because using these makes it easier to monitor the amount of “greenness”, biomass and water stress of vegetation than assessing the photosynthetic efficiency. Proximal remote sensing measurements are fundamental for the correct use of remote sensing in monitoring complex agroforest ecosystems, largely used to inform policies to improve resilience to drought, particularly in the Mediterranean region.