It’s been a long time since my previous post. Meanwhile I have been mostly working with non-canopy problems, especially lidar-based forest inventory. I’ve also had some teaching and supervision responsibilities, and a six-month visit to Norwegian University of Life Sciences, where I (for a change) had plenty of time for research. Thus I finally got out the first paper based on our 2011 field campaign: crown volume estimation using airborne lidar data.
The roots of this study go back to 2005 when I collected data for my master’s thesis at Metla’s Suonenjoki research station. Pola and Miina had employed three students to work there, and one of us, Sanna, made some curious measurements using an instrument called angle measurer (a.k.a. “miinaharava”). It is a T-shaped stick that can be used to measure crown widths at different heights, enabling estimation of vertical canopy profiles and crown volume. The data was needed for developing spectral reflectance models – some papers have been published in AFM and Silva Fennica.
The angle measurer
Example of a crown profile.
Sanna’s work came back to my mind later when I learned what a colleague of mine at the UEF, Jari Vauhkonen, was studying. Jari worked with detecting individual tree crowns from airborne lidar data, and was the first person to test the alpha shape method in the prediction of tree attributes. Alpha shapes are a method that can be used to combine a set of 3D points into one geometrical shape, which is defined by the alpha parameter. The volume of the shape can be calculated based on the triangulation of its individual points (=lidar echoes). Thus, when the echoes represent a tree crown, its volume can be estimated automatically. Our idea was to validate these estimates using the angle measurer.
Thus Juha and Laura measured the crown volumes of 89 trees during the 2011 field campaign. 77 of these trees were detected from the lidar data and used in the analysis. The echo segmentation phase was somewhat laborious, as my automated algorithm did not always delineate the tree perfectly and plenty of manual work was needed to remove this error source (and actually this had to be done several times because of some personal blunders and errors in the lidar data preprocessing). Based on the delineated echoes, Jari calculated the crown volumes and we simply plotted them against field-measured values. The results showed that the lidar-based volumes were clearly smaller than field values, mainly because there were not enough echoes from the lower part of the crown. Yet the results were better than those obtained using a general model for the crown dimensions and assuming an ellipsoidal crown shape. Full paper can be read here.
This simple experiment is anyway a step into a direction that is very interesting to me – using features derived directly from the lidar point cloud instead of predictions based on forestry databases. Most of the existing theoretical forest models use traditional forest attributes such as tree density, height, and basal area, which are increasingly estimated using lidar, so why not directly use lidar point cloud features instead? One problem is that the lidar features can be sensitive to scanner settings. Nevertheless, in my opinion more this kind of investigations should be made in the near future.