Comparison of Three Different Satellite-Based Approaches for Aboveground Biomass Estimation

Abstract

Effective estimation of crop yield on a regional scale in a short time with low cost would only be possible utilizing remote sensing. Several approaches have been proposed based on remotely sensed data for estimating Aboveground Biomass (AGB). In this study, three satellite-based approaches, including Radiation Use Efficiency (RUE). The soil water atmosphere plant (SWAP) model, and FAO33, were evaluated in the irrigated wheat and barley fields in the Qazvin irrigation network, Iran. To this end, the leaf area index (LAI) and relative evapotranspiration (ETrel) were extracted from the Landsat data and incorporated into the methods. A comparative analysis was undertaken to evaluate the performance of the satellite-based approaches using percent absolute error (PAE). By updating SWAP with satellite-derived LAI and surface incoming solar radiation, the PAE decreased significantly. Results of different Spectral Indices (SIs) in the RUE method showed that NDVI performed best with PAE of 1.52 percent and RMSE of 664.6 kg ha−1. Also, the RUE method with RMSE of 664.6 kg ha−1 had 4.7 and 23.8 lower PAE compared to the SWAP (RMSE = 2221.4 kg ha−1) and FAO33 (RMSE = 4394.2 kg ha−1), respectively. However, this was not the only criteria for a well-performed method, because earlier AGB forecast was only feasible by making use of SWAP since the satellite-derived parameters were only incorporated into the model about one month before the harvest.