Become a member
Membership of IUFRO is open to any institution concerned with the promotion, support or conduct of research related to forests, trees and forest products.
Climate change is predicted to affect both tree growth and mortality, the latter directly through drought or indirectly through disturbances. Yet, there is still a lot of uncertainty on how trees will respond to climatic warming and an increased frequency in extreme events. A combination of ground-based tree growth measurements and remotely sensed vegetation indices can be used to scale up measurements for tree growth and develop early warning systems. However, scaling up-tree growth with remote sensing data is not straightforward, since remote sensing data reflects signals from leaves, while ground based measurements are more tightly linked to the stem xylogenesis. To date, few studies that link both, have been published. It is the scope of this interdisciplinary unit to foster and advance research on this emerging, cutting edge-topic, by connecting scientists from both fields around the globe, organizing conferences and events, special issues, publishing common papers and possibly by applying for research funds.
STATE OF KNOWLEDGE
Forests bind approximately 25 % of the yearly carbon emission and an increase in forest area and forest growth contributes to climate change mitigation. In turn increasing warming and a prolongation of drought periods alters growth and species distribution patterns and increases mortality directly or indirectly via an increase in biotic (insects, pests) and abiotic (wildfire, wind, floods, snow…) disturbances. There are rising concerns that forestry may become increasingly vulnerable. Tree growth reactions and mortality with climate change are still only partly understood, because the underlying physiological processes and stress response are very complex. Detailed high resolution monitoring of tree growth and mortality with dendrometers, micro-cores, tree rings, isotope analysis or sap-flow measurements provide excellent tools to advance research, but are available only for few sites and lack spatial coverage.
For earth observation, there is a plethora of passive and active sensors. Both passive multispectral and hyperspectral images within and beyond the human vision (visible, IR, NIR, TIR, microwave) and active sensors (LiDAR, InSAR) have been used in forestry to predict stand-level (land-use classification, stand volume, stand height, leaf area index, gross primary production) and tree level attributes (tree heights, crown diameters, tree species, tree mortality, crown defoliation and phenology) attributes. Studies mostly relate vegetation indices (Normalized difference vegetation index, enhanced vegetation index) and water indices (normalized difference infrared index, canopy water content, relative water content, normalized difference moisture index…) to the variable of interest. The vast majority of these studies focus, however, on the stand level and optical sensors, while studies at the plot and individual tree level, which are known to be more accurate and new sensor technologies provide new opportunities.
Remote sensing data is available in unprecedented detail, through the launch of new satellites with higher temporal and spatial resolution, the advancement of sensor technology and the availability of cloud storage and computation facilities (e.g. google earth engine) that make the processing of vast data sets possible and dedicated software packages (R-packages) that facilitate computation for scientists - a potential that is however largely underutilized. Studies linking tree growth with remote sensing data are still rare, but pioneer studies in this field linking tree growth and remote sensing at the tree and stand level demonstrate possibilities of fusion and advancement of research.