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Data from: Drones and deep learning produce accurate and efficient monitoring of large-scale seabird colonies

Publication ,  Dataset
Hayes, M; Johnston, DW; Gray, PC; Sedgwick, W; Crawford, V; Chazal, N; Harris, G
September 17, 2020

Population monitoring in some colonial seabirds is often complicated by the large size of colonies, remote locations, and by close inter- and intra-species aggregation. While drones have been successfully used to monitor large inaccessible colonies, the vast amount of imagery collected introduces a data analysis bottleneck. Convolutional neural networks are evolving as a prominent means for object detection and can be applied to drone imagery for population monitoring. In this study, we explore the use of these technologies to increase capabilities for seabird monitoring by using convolutional neural networks to detect and enumerate Black-browed Albatross (Thalassarche melanophris) and Southern Rockhopper Penguins (Eudyptes c.chrysocome) at one of their largest breeding colonies, the Falkland (Malvinas) Islands. Our results show these techniques have great potential for seabird monitoring at significant and spatially complex colonies, producing accuracies of 97.66% and 87.16% with ninety percent of automated counts being within 5% of manual counts. The results of this study imply our methods are a viable population assessment tool, presenting many opportunities to reduce manual labor, cost, and human error. This dataset contains all relevant drone imagery and associated training, testing, and validation labels for the creation of a convolutional neural network to detect seabirds.

Duke Scholars

DOI

Publication Date

September 17, 2020
 

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Hayes, M., Johnston, D. W., Gray, P. C., Sedgwick, W., Crawford, V., Chazal, N., & Harris, G. (2020). Data from: Drones and deep learning produce accurate and efficient monitoring of large-scale seabird colonies. https://doi.org/10.7924/r4dn45v9g
Hayes, Madeline, David W. Johnston, Patrick C. Gray, Wade Sedgwick, Vivon Crawford, Natalie Chazal, and Guillermo Harris. “Data from: Drones and deep learning produce accurate and efficient monitoring of large-scale seabird colonies,” September 17, 2020. https://doi.org/10.7924/r4dn45v9g.
Hayes M, Johnston DW, Gray PC, Sedgwick W, Crawford V, Chazal N, et al. Data from: Drones and deep learning produce accurate and efficient monitoring of large-scale seabird colonies. 2020.
Hayes M, Johnston DW, Gray PC, Sedgwick W, Crawford V, Chazal N, Harris G. Data from: Drones and deep learning produce accurate and efficient monitoring of large-scale seabird colonies. 2020.

DOI

Publication Date

September 17, 2020