Improving spatial consistency of grassland canopy traits derived from imaging spectroscopy data through reflectance anisotropy compensation

Imaging spectroscopy is a versatile technology for acquiring spectral information about the Earth’s surface across ecosystems, typically covering the wavelength range of the electromagnetic spectrum between 400 and 2500 nm. Imaging spectrometers can be installed on varying platforms (e.g., drones, aircrafts, satellites) and provide valuable downstream products for biodiversity monitoring and understanding across multiple spatial scales. Exemplary downstream products for grasslands include species composition, plant life-forms, plant traits, and indicator values.

Due to the reflectance anisotropy of natural surfaces, i.e., the non-uniform scattering of incident light from surfaces in different directions, the signal measured by a spectrometer may still exhibit surface type specific dependencies on the observation and illumination geometry that also vary across wavelengths. Without adequate compensation for these effects, downstream products can be impacted, with consequences for change detection, causal inference, and management strategies. Although several compensation methods have been developed, they are not yet incorporated into most data processing pipelines, and our understanding of their effectiveness on various downstream products across ecosystems remains limited.

Using an airborne imaging spectroscopy dataset acquired over the Swiss National Park, we aim to quantify and analyze the effect of applying a reflectance anisotropy compensation method when studying alpine grassland ecosystems. Our focus lies on grassland canopy trait information derived from acquired spectroscopy data using the PROSAIL radiative transfer model. We particularly focus on the canopy traits leaf area index, chlorophyll content, and leaf mass per area that are often used to quantify the diversity, functioning and resilience of vegetation ecosystems. We investigate the capacity of a reflectance anisotropy compensation method to reduce anisotropy effects in data covering the topographically challenging Swiss National Park, and to eventually improve the spatial consistency of derived grassland canopy traits.

Our results facilitate multi-temporal biodiversity assessments based on spatially consistent grassland canopy trait information derived from imaging spectroscopy data. Insights are also relevant for validation attempts of ongoing and future spaceborne imaging spectroscopy missions. Furthermore, we critically reflect on the current state and future needs of methods available to compensate for reflectance anisotropy.