Daniel Kükenbrink

Thanks a lot Mike!

12.03.2025 21:02 — 👍 1    🔁 0    💬 0    📌 0

Overall, handheld MLS showed great potential to support the Swiss NFI in the near future, giving us ways to analyse the diversity and dynamics of forests in new ways that are currently not possible with conventional methods.

06.03.2025 08:48 — 👍 1    🔁 0    💬 1    📌 0

Tree detection rate of NFI measured trees was at 82.6% on average with an RMSE of 2.8 cm for the DBH estimation. Especially steeper terrain challenged accurate DBH estimation and should be investigated more.

06.03.2025 08:48 — 👍 2    🔁 0    💬 1    📌 0

Example of a vertical transect through the point cloud and occlusion grid. Yellow to violet colours denote the percentage of occluded voxels relative to the total number of voxels in the transect depth. Therefore, occlusion of 100% means that all voxels were occluded. Green shades denote the logarithm of the sum of laser returns of all voxels within the voxel stack. The black dashed line represents the canopy height model (CHM) estimated from MLS data, and the solid blue line represents the CHM estimated from the reference ALS data

e 2D occlusion map for the same plot and the acquisition pattern. The two dashed circles denote two concentric plots for tree evaluations in the NFI. Highlighted rectangular area denotes the transect area shown in the vertical transect shown on the left.

Occlusion over all evaluated plots was minimal with 9% of the entire canopy volume in average. This ensures that handheld MLS with employed measurement strategy delivers a high coverage of the entire 3D canopy.

06.03.2025 08:48 — 👍 0    🔁 0    💬 1    📌 0

MLS showed high reliability to produce analysis ready point clouds for forest structural assessment also under challenging conditions with very dense understorey vegetation or very steep terrain gradients

06.03.2025 08:48 — 👍 0    🔁 0    💬 1    📌 0

Redirecting

🚀New paper alert!🚀 Interested in hearing about our experience with handheld mobile laser scanning (MLS) to support the Swiss National Forest Inventory (NFI) in the near future? Read about it here: doi.org/10.1016/j.rs... @wslresearch.bsky.social

06.03.2025 08:31 — 👍 12    🔁 4    💬 1    📌 0