Article Version 1 Preserved in Portico This version is not peer-reviewed
Greenness Indices from a Low-Cost UAV Imagery as Tools for Monitoring after-Fire Forest Recovery
Version 1 : Received: 1 November 2018 / Approved: 2 November 2018 / Online: 2 November 2018 (05:17:07 CET)
A peer-reviewed article of this Preprint also exists.
Larrinaga, A.R.; Brotons, L. Greenness Indices from a Low-Cost UAV Imagery as Tools for Monitoring Post-Fire Forest Recovery. Drones 2019, 3, 6. Larrinaga, A.R.; Brotons, L. Greenness Indices from a Low-Cost UAV Imagery as Tools for Monitoring Post-Fire Forest Recovery. Drones 2019, 3, 6.
During recent years UAVs have been increasingly used in agriculture and forestry research and application. Nevertheless, most of this work has been devoted to improving accuracy and explanatory power, often at the cost of usability and affordability. We tested a low-cost UAV and a simple workflow to apply four different greenness indices to the monitoring of pine (Pinus sylvestris and P. nigra) after-fire regeneration in a Mediterranean forest. We selected two sites and masured all pines within a pre-selected plot. Winter flights were carried out at each of the sites, at two flight altitudes (50 and 100 m). Automatically normalizing images entered an SfM based photogrammetric software for restitution and the obtained point cloud and orthomosaic processed to get a canopy height model and four different greenness indices. Sum of pine DBH was regressed on summary statistics of greenness indices and canopy height model. ExGI and GCC indices outperformed VARI and GRVI in estimating pine DBH, while canopy height model slightly improved the models. Flight altitude did not severely affect model performance. Our results show that low cost UAVs may improve forest monitoring after disturbance, even in those habitats and situations were resource limitation is an issue.
low-cost UAV; greenness index; Pinus nigra; Pinus sylvestris; forest regeneration; flight altitude; small UAV
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