Hyperspectral indicators of vegetation vitality across scales: From trees to forests

Remotely sensed vegetation indices (VIs) are used as indicators of vegetation vitality and warning signals that indicate stress responses at the leaf and canopy level. Novel hyperspectral sensors increase the number and sensitivity of VIs which can be acquired from space-borne observations with the potential to map the health of forests at large scales. Besides stress-induced impacts on foliage, these VIs are also sensitive to confounding structural effects, relating to canopy cover, crown architecture and shadow fraction variations. Here we use remote sensing data at three increasingly coarse spatial resolutions acquired by drone and aircraft from the peak of the growing season in 2023 and 2024 to assess how VIs resolve vitality-related differences between tree crowns of different species and functional types. We show that most VIs still clearly resolve variations between tree crowns when using high (1 m) resolution aircraft data compared to very high (0.1 m) resolution drone-based data, which better distinguishes sunlit leaves from shade and non-photosynthetic material (R 2 = 0.46 – 0.86). At landscape scale, we found that data resampled to moderate (30 m) spatial resolution to mimic satellite data appeared sensitive to spatial variations in available water capacity (AWC) for the photochemical reflectance indices (PRI), chlorophyll and water content VIs. These indices are also considerably influenced by vegetation structure and functional type variations, which must be taken into account for mixed forests when mapping vegetation health indicators and linking tree-level monitoring networks to remote sensing information. • Both 0.1 m and 1 m resolution data resolves VI differences between tree crowns • Functional type has a strong impact on VIs at 30 m spatial resolution • PRI and Chlorophyll index are sensitive to variations of available water capacity • Across broadleaf stands, water content indices appear most sensitive to AWC