This chapter provides a workflow taking advantage of imaging spectroscopy and physical modeling to assess a set of vegetation traits then used to feed remotely sensed (RS) diversity mapping techniques in the context of forest ecosystems. This approach intends to explicitly account for vegetation traits related to structural, compositional, and functional properties when computing diversity metrics. This study is based on three main R packages. The packages prospect and prosail are used to assess vegetation biophysical properties from imaging spectroscopy data: Leaf Area Index, leaf chlorophyll content, equivalent water thickness, and leaf mass per area. Prosail includes functions to run the radiative transfer model PROSAIL in both forward mode (simulation of canopy reflectance) and inverse mode (assessment of vegetation biophysical properties from canopy reflectance). The package biodivMapR is then used to compute various diversity metrics from these vegetation biophysical properties, including α- and β-diversity metrics usually obtained from species inventories in ecological applications, and a set of functional metrics. This workflow is illustrated with an application on imaging spectroscopy data acquired from a temperate forest site. Validation is based on inventories collected on a plot network. Results show consistent estimation of α-diversity, moderate agreement between observed, and RS β-diversity metrics. Further investigations are required for the validation of functional diversity metrics.