Larsen, G. D. , Falvo, C., Tuohy, C., Goerke, M., Friedlaender, A. S., Nichols, R. C., Pallin, L., Simms, A., Groff, D., Ciminio, M., Johnston, D. W. (2022). Aerial data from drone surveys of coastal habitats on the West Antarctic Peninsula during austral summer (January–March 2020 and February–March 2019). Duke Research Data Repository. https://doi.org/10.7924/r4sf2xs2w
Ridge, J. T., DiGiacomo, A. E., Rodriguez, A. B., Himmelstein, J. D., Johnston, D. W. (2022). Data from: Comparison of 3D structural metrics on oyster reefs using unoccupied aircraft photogrammetry and terrestrial LiDAR across a tidal elevation gradient. Duke Research Data Repository. https://doi.org/10.7924/r41j9jn7t
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Bierlich, K. C., Schick, R. S., Hewitt, J., Dale, J., Goldbogen, J. A., Friedlaender, A. S., & Johnston, D. W. (2020). Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from drones. Duke Research Data Repository. V2 https://doi.org/10.7924/r4sj1jj6s
Bierlich, K. C., Schick, R. S., Hewitt, J., Dale, J., Goldbogen, J. A., Friedlaender, A. S., Johnston, D. W. (2020). Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. Duke Research Data Repository. https://doi.org/10.7924/r4wd3x28b
Hayes, M. C., Gray, P. C., Harris, G., Sedgwick, W. C., Crawford, V. D., Chazal, N., Crofts, S., & Johnston, D. W. (2020). Data from: Drones and deep learning produce accurate and efficient monitoring of large-scale seabird colonies. Duke Research Data Repository. https://doi.org/10.7924/r4dn45v9g
