Comparing terrestrial laser scanning and unmanned aerial vehicle structure from motion to assess top of canopy structure in tropical forests

Comparing terrestrial laser scanning and unmanned aerial vehicle structure from motion to assess top of canopy structure in tropical forests

Terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) equipped with digital cameras have attracted much attention from the forestry community as potential tools for forest inventories and forest monitoring. This research fills a knowledge gap about the viability and dissimilarities of using these technologies for measuring the top of canopy structure in tropical forests. In an empirical study with data acquired in a Guyanese tropical forest, we assessed the differences between top of canopy models (TCMs) derived from TLS measurements and from UAV imagery, processed using structure from motion. Firstly, canopy gaps lead to differences in TCMs derived from TLS and UAVs. UAV TCMs overestimate canopy height in gap areas and often fail to represent smaller gaps altogether. Secondly, it was demonstrated that forest change caused by logging can be detected by both TLS and UAV TCMs, although it is better depicted by the TLS. Thirdly, this research shows that both TLS and UAV TCMs are sensitive to the small variations in sensor positions during data collection. TCMs rendered from UAV data acquired over the same area at different moments are more similar (RMSE 0.11-0.63 m for tree height, and 0.14-3.05 m for gap areas) than those rendered from TLS data (RMSE 0.21-1.21 m for trees, and 1.02-2.48 m for gaps). This study provides support for a more informed decision for choosing between TLS and UAV TCMs to assess top of canopy in a tropical forest by advancing our understanding on: (i) how these technologies capture the top of the canopy, (ii) why their ability to reproduce the same model varies over repeated surveying sessions and (iii) general considerations such as the area coverage, costs, fieldwork time and processing requirements needed.

Authors: Rosca, S.; Suomalainen, J.; Bartholomeus, H.; Herold, M.

Topic: remote sensing, tropical forests, climate change, mitigation

Publication Year: 2018

ISSN: 2042-8901

Source: Interface Focus 8: 20170038

DOI: 10.1098/rsfs.2017.0038


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