New publication: Estimating over- and understorey canopy density by LiDAR data

New publication: Estimating over- and understorey canopy density by LiDAR data

August 27, 2015

A new publication recently appeared by Forestry opens some new outlook in leveraging airborne LiDAR derivatives for monitoring the vertical structure of temperate mixed forest stands. Led by Dr. Hooman Latifi from University of Würzburg, the study focuses on associating aerially-mapped habitat characteristics with 3D metrics extracted from fullwave LiDAR data to model canopy density across multiple stand stories.Whereas the
majority of methods applied so far typically concentrate on the structure of the overstorey, the main focus here is on the understorey layers of stands, which are of particular importance for wildlife and forest management applications, especially in protected areas.

LiDAR metrics and information on forest habitat types were combined via regression models to investigate LiDAR metrics that are significantly correlated with vegetation density. The top canopy and the herbal layer showed strong correlations with the applied LiDAR metrics. Moreover, the results suggest that the relationship between LiDAR predictors and vegetation density depends on the forest type. In conclusion, this study highlights the value of the LiDAR metrics for characterizing the structural properties of lower forest layers, with direct and indorect implications for wildlife and forest management.

The published version of this article can be retrieved through the following link.

Latifi, H., Heurich, M., Hartig, F., Müller, J., Krzystek, P., Jehl, H., Dech, S. 2015. Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data. Forestry, DOI.10.1093/forestry/cpv032

you may also like:

New Team Member: Sofia Haag

New Team Member: Sofia Haag

Sofia Haag joined the EORC in February 2025 as a research assistant for the EO4CAM project. After completing her Bachelor's degree in Geography at the University of Heidelberg, she pursued her Master's in Applied Physical Geography at the University of Würzburg. Sofia...

New publication on time-series web application

New publication on time-series web application

Our PhD student Luisa Pflumm published an article on "GEE-PICX: generating cloud-free Sentinel-2 and Landsat image composites and spectral indices for custom areas and time frames – a Google Earth Engine web application." in Ecography. Check out the contente here from...