Searching for the optimal sampling design for measuring LAI in an upland rainforest

Leaf Area Index (LAI) and vegetation cover are important metrics for deriving structural information of forest ecosystems across multiple scales. Ground-based measurements of LAI are necessary for up-scaling to coarse resolution satellite products as well as for calibrating and validating such products derived from airborne and satellite remote sensing datasets, which are increasingly being used for forestry and ecosystem health applications across the globe. A crucial consideration when gathering field measurements is determining a suitable sampling design, which ensures the collection of representative measurements. In this study, we address this question by obtaining LAI measurements across the Terrestrial Ecosystem Research Network (TERN) 25ha Robson Creek Supersite, which is representative of upland rainforests in Far North Queensland. The Robson Creek supersite contains over 200 species of woody vegetation and has one of the highest levels of biomass found in forest ecosystems globally. A variety of ad hoc and established sampling designs such as the State wide Land cover and Trees Survey (SLATS) and the Validation of Land European Remote Sensing Instruments (VALERI) cross elementary sampling unit protocol were applied across the site. Measurements obtained from the ground-based sampling designs were then compared to measurements derived from satellite imagery (i.e., Landsat). Preliminary results indicate the measurements obtained from between-plot sampling designs were highly correlated and comparable. On the other hand, there was disagreement between the ground-based measurements and values estimated from the Foliage Projective Cover (FPC) satellite product. The study suggests that at least in dense canopy forests, different sampling designs will yield similar results. Consequently, the sampling strategy should ultimately be driven according to the desired spatial resolution of the final product.