Kartläggning av till­stånd och föränd­ringar med tidsserier av satellit­radardata för framtidens skogsbruks­planering

I projektet undersöks hur tidsserier av satellitradardata kan användas för att få fram trädhöjd, diameter, basarea, stamvolym och biomassa ovanför marken. Syftet är att se hur tidsserierna kan utgöra underlag för olika skogsskötselåtgärder.

The research project aims to investigate time series of X-, C- and L-band synthetic aperture radar (SAR) data, separately and in combination, from the satellites TanDEM-X, Sentinel-1 and ALOS/-2, respectively, for tree height, diameter, basal area, stem volume and above-ground biomass (AGB) estimation and their change over time with special focus on diameter distribution. The time series will be used to map forest changes and be the base for proposing appropriate silviculture treatments. The change studies will also include detection and mapping of clear-cuts, thinnings and growth. The study will be carried out at two super test sites covering both hemi-boreal (Remningstorp, Västra Götaland) and boreal (Krycklan, Västerbotten) forests. The research will focus on using advanced SAR techniques including polarimetry and interferometry. Firstly, methods and algorithms will be developed and evaluated at plot level (radius 10 m) relating the forest variables estimated from field data to SAR data (state and change). In a second step, error assessment will be performed at stand level (≥ 0.5 ha), where the estimates also will be compared to estimates from airborne laser scanning data. Finally, an up-scaling will be performed to cover the two counties mentioned above. Time series of data from nearby weather stations will be collected to understand, model and mitigate the effect of environmental conditions (precipitation, temperature, wind etc.) on SAR data. Using multi-frequency time series of SAR data, the estimates of forest state and change as well as detection and mapping of clear-cuts, thinnings and growth are expected to be improved compared to using single-frequency data. Funding of this project will secure one Ph.D. student to finish the studies in the fall of 2022. SLU and Chalmers have a unique competence based on almost 30 years of research in the area, which will be used in the project to demonstrate the operational use of SAR data for forestry applications.