Simultaneous retrieval of leaf area index and fractional canopy cover using SAIL model and PSO algorithm

Leaf area index inversion using remote sensing is crucial for obtain vegetation information and monitoring global climate change. For the invalid uniform continuous canopy hypothesis of SAIL model, fractional canopy cover (FCC) is introduced and a simultaneous retrieval method of LAI and FCC is developed. SAIL model, PSO algorithm, and linear spectral mixture theory are combined in the novel method. Different fitness functions are designed and tested with field measurement data and Landsat-8 OLI data. Results show that the underestimation of LAI of canopy caused by the invalid hypothesis of SAIL model is well restrained when appropriate fitness function is adopted. The RMSE of the new method is only 0.489, which indicates the satisfactory retrieval performance. Therefore, the novel method is suggested as an effective LAI inversion technique.