Extending a canopy reflectance model for mangroves: A case study in south east queensland, Australia

Abstract

Mangroves are essential coastal wetland vegetation and their extent and leaf area index (LAI) have been mapped using remotely sensed Earth Observation images. However, the physics-based relationship between biophysical properties of mangroves, tidal height, and their spectral values remains underexplored. In order to quantitatively evaluate the impact of woody material on mangrove spectra from optical imagery, a canopy reflectance model (CRM) was extended to simulate and analyse the reflectance of mangroves. The fractional cover, leaf-to-total area ratio and water depth were included as model parameters, increasing the fidelity of the canopy architecture in the CRM. A mangrove study area in South East Queensland, Australia, was chosen for model parameterisation and verification using field and satellite data. Simulated Sentinel-2 reflectance spectra of the mangrove plots closely matched the observed pixel reflectance spectra, with their coefficient of determination (R2) values higher than 0.98 and root mean square error values lower than 0.01, which was better than the performance of the original CRM omitting the fractional cover and woody material. The inverted plant area index and fractional cover values from the satellite imagery closely matched the field-derived reference values (R2 = 0.78 and 0.97, respectively). Simulation results revealed that a higher proportion of woody material in crowns reduced the canopy reflectance of mangroves in the near infrared region and increased the reflectance in the shortwave infrared region. Moreover, the simulated reflectance of the Sentinel-2 red edge 1 (695–714 nm) was not sensitive to the wood proportion for the examined cases. The modelling framework may be used to evaluate the impact of woody material for estimating mangrove LAI from optical imagery. The model may also be used to quantitatively analyse the mangrove reflectance spectra when including other important factors such as tidal height.