Greetings MARMAM,

On behalf of my co-authors, I am pleased to announce our recent publication in 
Marine Mammal Science titled "Automated body length and body condition 
measurements of whales from drone videos for rapid assessment of population 
health".

The article is open-access and available at https://doi.org/10.1111/mms.13137

Bierlich, K.C., Karki, S., Bird, C. N., Fern, A., & Torres, L. G. (2024). 
Automated body length and body condition measurements of whales from drone 
videos for rapid assessment of population health. Marine Mammal Science, 
e13137. https://doi.org/10.1111/mms.13137

      Abstract: Monitoring body length and body condition of individuals helps 
determine overall population health and assess adaptation to environmental 
changes. Aerial photogrammetry from drone-based videos is a valuable method for 
obtaining body length and body condition measurements of cetaceans. However, 
the laborious manual processing of drone-based videos to select frames to 
measure animals ultimately delays assessment of population health and hinders 
conservation actions. Here, we apply deep learning methods to expedite the 
processing of drone-based videos to improve efficiency of obtaining important 
morphological measurements of whales. We develop two user-friendly models to 
automatically (1) detect and output frames containing whales from drone-based 
videos (“DeteX”) and (2) extract body length and body condition measurements 
from input frames (“XtraX”). We use drone-based videos of gray whales to 
compare manual versus automated measurements (n = 86). Our results show 
automated methods reduced processing times by one-ninth, while achieving 
similar accuracy as manual measurements (mean coefficient of variation <5%). We 
also demonstrate how these methods are adaptable to other species and identify 
remaining challenges to help further improve automated measurements in the 
future. Importantly, these tools greatly speed up obtaining key morphological 
data while maintaining accuracy, which is critical for effectively monitoring 
population health.

DeteX and XtraX can be viewed and accessed here:
https://mmi.oregonstate.edu/centers-excellence/codex/software-hardware/detex-xtrax

To receive updates on other hardware and software tools related to drone-based 
photogrammetry, you can join the Marine Mammal Institute's Center of Drone 
Excellence (CODEX) (https://mmi.oregonstate.edu/centers-excellence/codex) 
listserv here: https://lists.oregonstate.edu/mailman/listinfo/codex

Cheers,
KC



KC (Kevin) Bierlich, PhD, MEM

Postdoctoral Scholar

Geospatial Ecology of Marine Megafauna 
(GEMM<https://mmi.oregonstate.edu/gemm-lab>) Lab

Center of Drone Excellence 
(CODEX<https://mmi.oregonstate.edu/centers-excellence/codex>)

Marine Mammal Institute,

Dept. of Fisheries, Wildlife, & Conservation Sciences,

Oregon State University

Pronouns: he, him, his

kevin.bierl...@oregonstate.edu<mailto:kevin.bierl...@oregonstate.edu>

_______________________________________________
MARMAM mailing list
MARMAM@lists.uvic.ca
https://lists.uvic.ca/mailman/listinfo/marmam

Reply via email to