Abstract
Abstract. Oak trees are the primary component in Mediterranean agro-silvopastoral systems. Since the second half of the 20th century, however, a severe oak decline has been observed. Climate change reinforces this problem, which is consistent with worldwide observable tree dieback. As the trees have significant ecological and socio-economic functions, their observation and assessment of vitality are increasingly researched. Satellite remote sensing is very well suitable for large-scale surveys of the extensive and sometimes hardly accessible areas. This study investigates the usability of high-resolution WorldView-3 data for the classification of tree vitality. The ground truth was collected on an Andalusian dehesa at the end of September 2019, timely corresponding with the satellite data acquisition. After customary post-processing of the WorldView-3 data, 10 vegetation indices (ARVI, CIgreen, CSI, DPI, EVI, GNDVI, NDVI, PSRI, RENDVI, and RGI) were calculated from the multispectral image. Three machine learning classifiers (Maximum Likelihood, Random Forest, and Support Vector Machine) were then used for a supervised image classification with three vitality classes (healthy, sick, and dead). Independent ground truth data were used for the validation. The best results were achieved with the red edge normalized difference vegetation index (RENDVI) and the Support Vector Machine classifier (F1 scores between 0.27 and 0.72). A maximal overall accuracy of around 0.6 is, however, improvable. Further studies should focus on other classification methods, more reliable ground truth, and combined analyses of spectral and structural data.
Highlights
Agroforestry is regarded as a promising solution for sustainable land use and achieving the ambitious climate goals of the European Union (Eichhorn et al, 2006; Hernández-Morcillo et al, 2018; Tittensor et al, 2014)
The aim of this study is a first investigation of the usability of WV-3 data for mapping tree vitality in a dehesa ecosystem in a mountainous region
This study investigates tree vitality on a Spanish dehesa by calculating vegetation indices (VIs) from multispectral WV-3 data and classifying tree vitality using supervised image classification techniques
Summary
Agroforestry is regarded as a promising solution for sustainable land use and achieving the ambitious climate goals of the European Union (Eichhorn et al, 2006; Hernández-Morcillo et al, 2018; Tittensor et al, 2014). Mixing the cultivation of trees, pasture, and crops in agro-silvopastoral systems can help to reduce soil erosion and nitrogen leaching, fix CO2, and enhance biodiversity (den Herder et al, 2017; Kay et al, 2019; Palma et al, 2007). In the western Mediterranean, sparse holm oak (Quercus ilex) and cork oak (Quercus suber) coverage in a savannah-like landscape characterize the agro-silvopastoral systems of dehesas in Spain and montados in Portugal. Both terms are hereinafter summarized as dehesas. The socio-economic value bases on cork production, the famous Iberian ham (jamón ibérico), big game hunting, and tourism (Fagerholm et al, 2019; Moreno and Obrador, 2007; Moreno and Pulido, 2009)
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