A radiative transfer model-based method for the estimation of grassland aboveground biomass

摘要: Abstract This paper presents a novel method to derive grassland aboveground biomass (AGB) based on the PROSAILH (PROSPECT + SAILH) radiative transfer model (RTM). Two variables, leaf area index (LAI, m2m−2, defined as one-side per unit of horizontal ground area) and dry matter content (DMC, gcm−2, area), were retrieved using reflectance data from Landsat 8 OLI product. The result LAI × DMC was regarded estimated AGB according their definitions. well-known ill-posed inversion problem when inverting alleviated ecological criteria constrain simulation scenario therefore number simulated spectra. A case study presented applied plateau in China estimate its AGB. results compared those obtained an exponential regression, partial least squares regression (PLSR) artificial neural networks (ANN). RTM-based offered higher accuracy (R2 = 0.64 RMSE = 42.67 gm−2) than (R2 = 0.48 RMSE = 41.65 gm−2) ANN (R2 = 0.43 RMSE = 46.26 gm−2). However, proposed similar performance PLSR better determination coefficient (R2 = 0.55) but RMSE (RMSE = 37.79 gm−2). Although it is still necessary test these methodologies other areas, offers greater robustness reproducibility at large scale without need collect field measurements considered most promising methodology.