Synergistic retrievals of leaf area index and leaf chlorophyll content in deciduous broadleaf forests from Sentinel-2 and Landsat

Leaf area index (LAI) and leaf chlorophyll content (LCC) are essential for ecological applications. Physically based algorithms enable the synergistic retrieval of LAI and LCC, but their performance is often limited by simplifications in radiative transfer (RT) models, which can induce mutual error compensation between these two parameters. In this study, we systematically evaluate synergistic LAI and LCC retrievals for deciduous broadleaf forests from Sentinel-2 and Landsat-7/8 data by examinin