IUFRO Division 4 meeting: Extending Forest Inventory and Monitoring over Space and Time, May 19-22, 2009, Quebec City, Canada Remote Sensing Based Inversion of Gap Fraction for Determination of Leaf Area Index

The major physiological processes of vegetation including photosynthesis and evapotranspiration are determined by the vegetation biophysical parameters that describe the canopy structure. Leaf area index (LAI) is one of the principal biophysical parameters in climate, weather, and ecological studies, and has been routinely estimated from remote sensing measurements. LAI is defined as one half the total radiation intercepting leaf area per unit ground horizontal surface area (Gonsamo and Pellikka 2008). Several numerical models require a continuous field of high spatial and temporal resolution LAI measurements due to heterogeneity and size of vegetation or natural agricultural patches, and the large seasonal dynamics of vegetation. To fulfill these needs, the LAI retrieval methods including the processing of the remotely sensed data expected to be efficient and convenient for the end users. Generally speaking, the success of LAI estimation from remotely sensed data remains cumbersome and there is always a need to calibrate remotely retrieved parameters with ground based observation. This study is aimed at demonstrating the feasibility of the large scale LAI inversion algorithms using red and near-infrared reflectance obtained from high resolution satellite imagery. The algorithms are developed based on the principle commonly used for ground-based optical determination of LAI by applying Beer-Lambert’s law and by assuming extinction coefficient for the gap fraction retrieved from spectral vegetation indices (SVIs).