Species dominance and above ground biomass in the Białowieża Forest, Poland, described by airborne hyperspectral and lidar data

A study on the Białowieża Forest, Poland, demonstrates that airborne hyperspectral and lidar data can effectively monitor tree species dominance and above-ground biomass with high accuracy. Using a Classification and Regression Trees algorithm, researchers achieved over 90% accuracy in classifying plots dominated by deciduous, spruce, and pine trees. Hyperspectral vegetation indices, combined with a Multivariate Multiple Linear Regression model, provided the highest accuracy for deciduous-dominated plots (R² = 0.87), while lidar data, using an exponential regression model, estimated biomass with an overall R² of 0.66, improving slightly when hyperspectral data were added for pine-dominated plots. These methods offer a reliable tool for resource monitoring in this conservation-critical area, aiding local authorities in addressing threats from climate change and logging.

Vaglio Laurin, G., Puletti, N., Grotti, M., Stereńczak, K., Modzelewska, A., Lisiewicz, M., Sadkowski, R., Kuberski, Ł., Chirici, G., & Papale, D. (2020). Species dominance and above ground biomass in the Białowieża Forest, Poland, described by airborne hyperspectral and lidar data. International Journal of Applied Earth Observation and Geoinformation, 92, 102178. https://doi.org/10.1016/j.jag.2020.102178