Multi-angular assessment of early-season defoliation: Evaluating the sensitivity of vegetation indices to NPV visibility in temperate broadleaved forests

Early-season forest decline in temperate broadleaved stands often lacks detectable biochemical stress signals, manifesting primarily through reduced foliage density and increased visibility of non-photosynthetic vegetation (NPV). This study investigated the spectral separability of green leaves and NPV components under varying levels of canopy defoliation. Using a crane platform, we collected in situ leaf- and canopy-level spectrometer measurements alongside co-aligned photography to quantify the visible fraction of NPV. We analyzed the multi-angular reflectance characteristics and evaluated 35 vegetation indices (VIs) —including green biomass metrics and specialized NPV indices —using Random Forest to identify optimal spectral and geometric configurations. Sunlit young foliage exhibited high forward scatter, creating a nadir reflectance minimum. At canopy level, a nadir minimum was driven by the gap distribution resulting from sustainable forest management practices. Consequently, the optimal viewing angle for top-ranking VIs (e.g., SNC BAO , Ctr 2 , mNDVI 705 ) was near the hotspot geometry, minimizing shadowing and forest floor interference. While the total visible fraction of NPV remained mostly insensitive to viewing angles, its shaded proportion varied. VIs targeting green vegetation via red-edge and NIR domains consistently outperformed dedicated NPV indices based on SWIR cellulose and lignin absorption. This is attributed to low upper-canopy SWIR transmittance, which obscured the signals of the largely shaded NPV fraction. Top-performing VIs achieved R 2 = 0.92 for NPV visibility prediction, improving by 21 % over the best SWIR indices and 11 % over the nadir view. To accurately detect initial defoliation and overcome forest floor interference, adopting off-nadir viewing geometries is advantageous for capturing the optimal signal.