Automatic detection of alien plant species in action camera images using the chopped picture method and the potential of citizen science

• Published in: Breeding Science Vol. 72; no. 1; pp. 96 - 106
• Main Authors: Takaya, Kosuke, Sasaki, Yu, Ise, Takeshi
• Format: Journal Article
• Language: English
• Published: Tokyo Japanese Society of Breeding 01.01.2022; Japan Science and Technology Agency
• Subjects: action camera; alien plant; Cameras; chopped picture method; citizen science; computer vision; Deep learning; Flowers & plants; Indigenous plants; Introduced plants; Invasive plants; Invasive species; Plant species; Research Paper; Satellite imagery; Solidago altissima
• ISSN: 1344-7610; 1347-3735
• DOI: 10.1270/jsbbs.21062

Monitoring and detection of invasive alien plant species are necessary for effective management and control measures. Although efforts have been made to detect alien trees using satellite images, the detection of alien herbaceous species has been difficult. In this study, we examined the possibility of detecting non-native plants using deep learning on images captured by two action cameras. We created a model for each camera using the chopped picture method. The models were able to detect the alien plant Solidago altissima (tall goldenrod) and obtained an average accuracy of 89%. This study proved that it is possible to automatically detect exotic plants using inexpensive action cameras through deep learning. This advancement suggests that, in the future, citizen science may be useful for conducting distribution surveys of alien plants in a wide area at a low cost.