The 2023 Outstanding Student and PhD candidate Presentation (OSPP) Award is awarded to Marianne Böhm for the poster/PICO entitled:
Characterizing forest structure using LiDAR and multi-frequency SAR remote sensing (Böhm, M.; Zehner, M.; Schellenberg, K.; Bueso-Bello, J.-L.; Rizzoli, P.; Schmullius, C.; Dubois, C.)
Click here to download the poster/PICO file.
Marianne Böhm is a Master’s student of climate and environmental change at the Friedrich-Schiller-University Jena (Germany), where she works in a group that focuses on applications of remote sensing for describing properties of forests. Her main interests are climate change impacts on forests as well as high-latitude ecosystems and their carbon cycle.
Her poster presented the results of comparing observations from several satellite-borne sensors operating in the microwave spectrum on their capacities to characterize forest structure, using LiDAR-derived indices as reference. The results indicate that deriving forest structure from radar backscatter intensity alone, even in a multifrequency approach, will not be accurately possible. However, especially when L- and X-Band were used in synthesis, a certain proportion of backscatter variation appeared to be related to forest structure. This knowledge is relevant for further studies, either as a predictor, or confounding variable for other target information like biomass.