A new approach to derive productivity of tropical forests using radar remote sensing measurements.

Deriving gross & net primary productivity (GPP & NPP) and carbon turnover time of forests from remote sensing remains challenging. This study presents a novel approach to estimate forest productivity by combining radar remote sensing measurements, machine learning and an individual-based forest model. In this study, we analyse the role of different spatial resolutions on predictions in the context of the Radar BIOMASS mission (by ESA).

A five-axis parallel kinematic mirror unit for soft X-ray beamlines at MAX IV.

With the introduction of the multi-bend achromats in the new fourth-generation storage rings the emittance has decreased by an order of magnitude resulting in increased brightness. However, the higher brightness comes with smaller beam sizes and narrower radiation cones. As a consequence, the requirements on mechanical stability regarding the beamline components increases.