Investigating different versions of PROSPECT and PROSAIL for estimating spectral and biophysical properties of photosynthetic and non-photosynthetic vegetation in mixed grasslands

摘要

The PROSPECT and PROSAIL family of radiative transfer models (RTMs) are among the most popular for simulating vegetation spectra and estimating vegetation properties at the leaf and canopy levels. However, the main limitation of the radiative transfer model approach is that model performance depends on the exhaustiveness of the calibration database(s). The PROSPECT model was calibrated mainly with photosynthetic leaves, and thus does not contain specific absorption coefficients of decay pigments responsible for the spectral behavior of non-photosynthetic vegetation. Hence, PROSPECT and PROSAIL may be ill-suited to mixed ecosystems (e.g., grasslands and wetlands), especially in the late growing season when the non-photosynthetic vegetation is likely to obfuscate the quantification of green vegetation. This study investigates the performance of different versions of PROSPECT/PROSAIL models for simulating spectra and estimating biophysical properties of photosynthetic and non-photosynthetic vegetation, and aims to better understand the limitations of these RTMs and identify possible ways to improve their performance. Results show that the PROSPECT-5 and PROSPECT-D had challenges in simulating spectra of non-photosynthetic leaves in a mixed grassland area, while a modified version (PROSPECT-5M) that considered the absorption effects of decay pigments achieved higher accuracy (e.g., mean Root Mean Square Error (RMSE) of 0.014 compared to 0.026 for the PROSPECT-5). In comparison, there is minimal difference in RMSE between models for simulating green photosynthetic leaves. At the canopy level, the original PROSAIL model simulated the spectra well for homogeneous green canopies (with mean RMSE around 0.012), while a modified PROSAIL model simulated the spectra more accurately for mixed canopies that have photosynthetic and non-photosynthetic leaves (e.g., with a mean RMSE of 0.010 compared to 0.020 of original PROSAIL). The original and modified PROSAIL were then inverted using helicopter-based high-spatial resolution hyperspectral imagery to estimate vegetation properties, and achieved higher accuracies for green and mixed canopies, respectively (e.g., estimating canopy chlorophyll with R-2 values over 0.75). Overall, different versions of PROSPECT/PROSAIL models have a varied performance for photosynthetic and non-photosynthetic vegetation. Understanding the limitations of the models and adopting corresponding measures to improve their performance is critical for successful applications of RTMs in the estimation of vegetation spectral and biophysical properties.