This is a review of forestry related multi-angular remote sensing which is a recent technology making use of optical remote sensing datasets collected from differing viewing-angles during a short period of time. A particular advantage of these datasets lies in their capability to capture structural information. Since forests can be considered to be one of the most complex natural surfaces of the Earth in terms of horizontal and vertical structure, multi-angular remote sensing is a promising tool which can be used to enhance existing remote-sensing applications in order to extract forest information products.
The general concept of multi-angular remote sensing and its relation to radiative transfer models is briefly presented. In the main section the paper gives an overview of multi-angular remote sensing applications in forestry by highlighting relevant publications of the latest years focusing on parameters such as LAI, canopy clumping, biomass, plant-chemical attributes, forest types and species (classification).