The Impacts of Spatial Resolution, Viewing Angle, and Spectral Vegetation Indices on the Quantification of Woody Mediterranean Species Seasonality Using Remote Sensing

Discriminating between woody plant species using a single image is not straightforward due to similarity in their spectral signatures, and limitations the spatial resolution of many sensors. Seasonal changes vegetation indices can potentially improve mapping; however, for mapping at individual level, very high needed. In this study we examined ability Israel/French satellite VENμS other sensors with higher resolutions, identifying Mediterranean species, based on seasonal patterns (VIs). For area, chose site natural highly heterogeneous Judean Mountains (Israel), which well represents maquis region. We used three from were derived: consumer-grade ground-based camera (weekly images VIS-NIR; six VIs; 547 plants), UAV imagery (11 images, five bands, seven VIs) resampled 14, 30, 125, 500 cm simulate resolutions available some satellites, Level 1 product (with nominal 5.3 m nadir; 1551 plants). The various described species’ VIs different levels success. Strong correlations near-surface given VI mostly persisted all ≤125 cm. ExG index presented ground data most (pixel size cm; 9 12 R ≥ 0.85; p < 0.001), classification accuracies ≤30 8 >70%), demonstrating possibility detailed space. dynamics obtained demonstrated dominant role ephemeral herbaceous signal recorded by sensor. low variance as observed may be explained its coarse (effective 7.5) non-nadir viewing angle (29.7°) over area. However, considering challenging characteristics research site, it that type sensor ~1 m) nadir point view more homogeneous dense areas would allow seasonality.