Abstract
Red-edge (RE) spectral vegetation indices (SVIs)—combining bands on the sharp change region between near infrared (NIR) and visible (VIS) bands—alongside with SVIs solely based on NIR-shoulder bands (wavelengths 750–900 nm) have been shown to perform well in estimating leaf area index (LAI) from proximal and remote sensors. In this work, we used RE and NIR-shoulder SVIs to assess the full potential of bands provided by Sentinel-2 (S-2) and Sentinel-3 (S-3) sensors at both temporal and spatial scales for grassland LAI estimations. Ground temporal and spatial observations of hyperspectral reflectance and LAI were carried out at two grassland sites (Monte Bondone, Italy, and Neustift, Austria). A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), we demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. The RENDVI783.740 SVI was the least affected by traits co-variation, and more studies are needed to confirm its potential for heterogeneous grasslands LAI monitoring using S-2, S-3, or Gaofen-5 (GF-5) and PRISMA bands.
Highlights
Canopy structural organization describes the three-dimensional geometric distribution of the aboveground photosynthetic and non-photosynthetic vegetation components [1]
While the visible (VIS) and shortwave infrared (SWIR, 1100–2500 nm) parts of the reflectance spectrum are mainly determined by pigments and water content absorption, respectively, in the near infrared (NIR, 750–1400), reflectance is high compared to the VIS domain because individual leaves and whole plant canopies strongly scatter NIR, and the degree of NIR scattering is driven by the internal leaf structure alongside with canopy structure and the ratio between green and non-photosynthetic components [5]
The hyperspectral analysis highlighted the suitability of the spectral regions related to water absorption features for leaf area index (LAI) estimations [10,65]
Summary
Canopy structural organization describes the three-dimensional geometric distribution of the aboveground photosynthetic and non-photosynthetic vegetation components [1]. Canopy structure is described by plant traits (PTs) such as leaf area index (LAI), aboveground biomass (AGB) and other canopy and leaf structural traits such as leaf angle distribution (LAD), gap fraction, leaf clumping, the proportion of photosynthetic and non-photosynthetic elements [2,3,4], specific leaf area (SLA) and leaf dry matter, which can influence absorption and scattering light dynamics [5,6]. When more structural traits co-vary, LAI estimation based on spectral data may be challenging [5], as reflectance is sensitive to multiple leaf and canopy traits and disentangling LAI from structural and biochemical drivers is difficult [12]. The impact of vegetation structural heterogeneity on the ability of different optical-based models to retrieve LAI has not been sufficiently described in the literature, and new knowledge is needed to quantify the uncertainties of such models and disentangle the impact of structural and biochemical heterogeneity on LAI estimations
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