Comparison of In Situ and Remotely Sensed Leaf Area Index of Northeastern American Deciduous, Mixed, and Coniferous Forests for SMAPVEX19-22

Leaf Area Index (LAI) is a critical ecological parameter for quantifying the foliage density in forest ecosystems. As such it may also be effective for estimating the amount of leafy vegetation blocking sensor signals, like the radiometer on board NASA’s Soil Moisture Active Passive (SMAP) satellite, from reaching the ground surface. This study presents a comprehensive comparative analysis of LAI measurements acquired through in situ and remotely sensed (RS) methods in diverse forest ecosystems of northeastern America, including deciduous, mixed, and coniferous forests. We compare RS and ground-truth LAI data to understand the variation between the RS LAI products, the impacts of RS spatial resolution on analysis, and the effect of seasonality on both the RS and in situ data. We find strong (R2 > 0.83) positive relationships between in situ LAI and the tested RS products, with improved positive relationships (R2 > 0.92) for higher spatial resolution (<30m) RS LAI products. We also discuss considerations for the LAI algorithms. Smaller slopes for the higher resolution RS products (slope < 0.96) relative to the lower resolution products (slope > 1.16) could potentially indicate limitations of the RS LAI algorithms for dense forests. Smaller y-intercept values (< -0.56) associated with the high resolution products relative to the lower resolution products (> -0.29) could indicate greater influence of woody biomass on high resolution RS LAI algorithms relative to low resolution RS LAI algorithms.