Forest Diversity Assessment through the Integration of PRISMA Spectral Metrics and BIOMASS P-band SAR Structural Information

This study explores the potential of integrating structural information from the European Space Agency (ESA) BIOMASS P-band Synthetic Aperture Radar (SAR) mission with spectral information from PRISMA hyperspectral imagery to assess forest diversity in the Amazon. The study area was defined based on the spatial and temporal overlap of available PRISMA and BIOMASS acquisitions.

Forest structural diversity was derived from BIOMASS data acquired on 6 June 2025 using polarisation variability, polarimetric SAR (PolSAR) metrics, polarimetric interferometric SAR (PolInSAR), and texture measures of above-ground biomass to characterise variations in vertical structure and stand complexity. In particular, the cross-polarised backscattering coefficient (HV/VH), which is sensitive to volume scattering, was used to capture differences in forest height and canopy structure.

Spectral diversity was estimated from PRISMA Level-2D surface reflectance data acquired on 29 July 2025 (234 bands spanning 406–2497 nm). Principal Component Analysis (PCA) was applied, and several vegetation indices were derived. In addition, spectral diversity indicators—including Rao’s Q, spectral variance, and clustering-based “spectral species”—were computed to describe variability in canopy composition and biochemical properties associated with species and functional diversity.

The analysis examines relationships between radar-derived structural diversity and hyperspectral spectral diversity to evaluate how forest structural heterogeneity corresponds to compositional variability across different forest environments. Available LiDAR canopy height data and, where feasible, field-based observations of species composition and functional traits are used as supporting reference information. Correlation and multivariate analyses are applied to assess the consistency, complementarity, and added value of the combined indicators.

This multi-sensor Earth observation approach contributes to advancing satellite-based monitoring of forest biodiversity in tropical ecosystems and demonstrates the potential of the ESA BIOMASS mission for biodiversity-oriented forest applications.