@article {JRN55324,
	title = {Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems},
	journal = {Remote Sensing in Ecology and Conservation},
	year = {2021},
	month = {7/7/2021},
	abstract = {Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9\%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1{\textendash}10 ha-1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.},
	keywords = {Canopy height model, drone, fine spatial resolution remote sensing, plant height, structure-from-motion photogrammetry, UAV},
	doi = {10.1002/rse2.228},
	url = {files/bibliography/21-035.pdf},
	author = {Andrew M. Cunliffe and Karen Anderson and Fabio Boschetti and Richard E. Brazier and Hugh A. Graham and Isla H. Myers-Smith and Thomas Astor and Matthias M. Boer and Leonor G. Calvo and Patrick E. Clark and Michael D. Cramer and Miguel S. Encinas-Lara and Stephen M. Escarzaga and Maria Fern{\'a}ndez-Gim{\'e}nez and Adrian G. Fisher and Breahna M. Gillespie and Anne Griebel and Niall Hanan and Muhammad S. Hanggito and Stefan Haselberger and Caroline A. Havrilla and Phil Heilman and W Ji and Jason W. Karl and Mario Kirchhoff and Sabine Kraushaar and Mitchell B. Lyons and Irene Marzolff and Marguerite Mauritz and Cameron D. McIntire and Daniel Metzen and Luis A. M{\'e}ndez-Barroso and Simon C. Power and Ji{\v r}{\'\i} Pro{\v s}ek and Enoc Sanz-Ablanedo and Katherine J. Sauer and Damian Schulze-Br{\"u}ninghoff and Petra {\v S}{\'\i}mov{\'a} and Stephen Sitch and Julian L. Smit and Caitriana Steele and Susana Su{\'a}rez-Seoane and Sergio A. Vargas and Miguel L Villarreal and Fleur Visser and Michael Wachendorf and Hannes Wirnsberger and Robert Wojcikiewicz}
}
