Abstract
We contribute to a better understanding of different remote sensing techniques for tree height estimation by comparing several techniques to both direct and indirect field measurements. From these comparisons, factors influencing the accuracy of reliable tree height measurements were identified. Different remote sensing methods were applied on the same test site, varying the factors sensor type, platform, and flight parameters. We implemented light detection and ranging (LiDAR) and photogrammetric aerial images received from unmanned aerial vehicles (UAV), gyrocopter, and aircraft. Field measurements were carried out indirectly using a Vertex clinometer and directly after felling using a tape measure on tree trunks. Indirect measurements resulted in an RMSE of 1.02 m and tend to underestimate tree height with a systematic error of −0.66 m. For the derivation of tree height, the results varied from an RMSE of 0.36 m for UAV-LiDAR data to 2.89 m for photogrammetric data acquired by an aircraft. Measurements derived from LiDAR data resulted in higher tree heights, while measurements from photogrammetric data tended to be lower than field measurements. When absolute orientation was appropriate, measurements from UAV-Camera were as reliable as those from UAV-LiDAR. With low flight altitudes, small camera lens angles, and an accurate orientation, higher accuracies for the estimation of individual tree heights could be achieved. The study showed that remote sensing measurements of tree height can be more accurate than traditional triangulation techniques if the aforementioned conditions are fulfilled.
Highlights
Individual tree height is a fundamental forest inventory parameter [1] and is often used for the estimation of forest growth, biomass, carbon stock and site productivity [2]
For the derivation of tree height, the results varied from an root mean squared error (RMSE) of 0.36 m for unmanned aerial vehicles (UAV)-light detection and ranging (LiDAR) data to 2.89 m for photogrammetric data acquired by an aircraft
The study showed that remote sensing measurements of tree height can be more accurate than traditional triangulation techniques if the aforementioned conditions are fulfilled
Summary
Individual tree height is a fundamental forest inventory parameter [1] and is often used for the estimation of forest growth, biomass, carbon stock and site productivity [2]. Indirect field-based measurements at the single tree level are expensive, time-consuming and often not feasible for large areas or for high temporal resolutions [4,5]. Various remote-sensing-based methods have been developed and studied. Remote sensing has the potential to provide consistent, reproducible and up-to-date information on various forest parameters in order to make inventories more efficient [6]. Previous studies mostly applied a specific remote sensing system to a single area and demonstrated how remote sensing can be used for quick assessment of forests at large spatial scales (see, e.g., [7,8,9,10,11,12,13,14,15,16]).
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