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Application of Deep Learning in Remote Sensing Monitoring of Large Herbivores- A Case Study in Qinghai Tibet Plateau

Application of Deep Learning in Remote Sensing Monitoring of Large Herbivores- A Case Study in Qinghai Tibet Plateau

Wei Luo 1,2,3, Yongtao Jin 1,2,3, Xuqing Li 1,2,3 and Ke Liu 1,2,3*

1School of Remote Sensing Information, North China Institute of Aerospace Eingering, Langfang 065000, Hebei Province, China
2Collaborative Innovation Center of Aerospace Remote Sensing Information Processing and Application of Hebei Province, Langfang 065000, Hebei Province, China
3National Joint Engineering Research Center of Space Remote Sensing Information Application Technology, Langfang 065000, Hebei Province, China

*      Corresponding author: liuke1176@163.com

Fig. 1.

Track and identifier of the UAV investigation of large herbivorous in Maduo County.

Fig. 2.

UAVs used for this aerial photography: electric fixed wing UAV (a) and oil powered fixed wing UAV (b).

Fig. 3.

Mask R-CNN structure.

Fig. 4.

Loss curves generated during the detection process.

Fig. 5.

Results of the detection and location of herbivores: Domestic Yak (a), Tibetan sheep (b), horse (c), Tibetan wild ass (d), Tibetan gazelle (e), and Blue sheep (f).

Fig. 6.

Density distribution of domestic herbivores investigation belt in various zones.

Fig. 7.

Density distribution of wild herbivores investigation belt in various zones.

Fig. 8.

Density distribution of large herbivores investigation belt in various zones.

Fig. 9.

Comparison of the number of domestic herbivores on hand between UAV investigation and official provide.

Pakistan Journal of Zoology

February

Vol. 54, Iss. 1, Pages 1-501

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