Multiangular and Hyperspectral Forest Reflectance Modeling in the Hemiboreal Zone: A Case Study With CHRIS PROBA Data

The hemiboreal and boreal forests of the northern hemisphere form the largest unbroken forest zone in the world and play a key role in global climate studies. Obtaining information on the state of forests over large regions at a weekly or monthly schedule is possible only by remote sensing. A prerequisite for the development of image interpretation methods for such large scale remote sensing applications is an understanding of the physical principles behind the spectral signal measured by satellite or airborne instruments. Efficient use of forest canopy reflectance models which adopt the physical principles of remote sensing of forests has been hindered by the lack of hyperspectral and multiangular data. Recently, several missions, e.g. CHRIS PROBA, providing such imagery have been launched. In this study, we examine and identify links between canopy structure and multiangular, hyperspectral reflectance properties of typical deciduous and coniferous hemiboreal forests using CHRIS PROBA data and a recently improved forest reflectance model PARAS. The PARAS model is based on the concept of photon recollision probability, and thus provides a powerful, yet simple, method for modeling the spectral behavior of forest canopy scattering. Empirical ground reference data for the study were collected from the Jarvselja Training and Experimental Forestry District in southeastern Estonia, and model simulation results were validated using three simultaneous CHRIS PROBA mode 3 scenes over the study site.