Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS
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, Dataset
Dale, J; Bierlich, KC; Schick, RS; Johnston, DW; Goldbogen, JA; Friedlaender, AS; Hewitt, J
July 6, 2021
Duke Scholars
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Dale, J., Bierlich, K. C., Schick, R. S., Johnston, D. W., Goldbogen, J. A., Friedlaender, A. S., & Hewitt, J. (2021). Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. https://doi.org/10.7924/r4sj1jj6s
Dale, J., K. C. Bierlich, R. S. Schick, David W. Johnston, J. A. Goldbogen, A. S. Friedlaender, and J. Hewitt. “Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS,” July 6, 2021. https://doi.org/10.7924/r4sj1jj6s.
Dale J, Bierlich KC, Schick RS, Johnston DW, Goldbogen JA, Friedlaender AS, et al. Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. 2021.
Dale, J., et al. Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. 6 July 2021. Crossref, doi:10.7924/r4sj1jj6s.
Dale J, Bierlich KC, Schick RS, Johnston DW, Goldbogen JA, Friedlaender AS, Hewitt J. Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. 2021.