Abstract
Phenology plays an important role in understanding the feedbacks of plants to climate change. However, phenology observation is not a trivial task, particularly for large covers with huge diversities of plants. To handle this issue, this study attempted to apply wide-spread surveillance cameras (SCs) for plant phenology monitoring. In the case of flowering phenology, multiple phenological indices were proposed and derived from SC image series to identify the starting and ending dates. Test showed that the derived flowering phases for Robinia pseudoacacia (Fabaceae), Prunus cerasifera (Prunus) and Malus micromalus (Malus) agreed well with the ground-truth data. The feasibility of assuming SCs for plant flowering phenology monitoring was validated. Furthermore, this study alludes to a potential way of using SCs to compose regional- to continental-scale networks for phenology monitoring.
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Acknowledgment
This work was supported in part by the National Natural Science Foundation of China (Grant No. 41471281), in part by the Research Fund for Doctoral Program of Higher Education of China (Grant No. 20130001120016), and in part by the SRF for ROCS, SEM, China.
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Deng, L., Shen, W., Lin, Y., Gao, W., Lin, J. (2017). Surveillance Camera-Based Monitoring of Plant Flowering Phenology. In: Yuan, H., Geng, J., Bian, F. (eds) Geo-Spatial Knowledge and Intelligence. GRMSE 2016. Communications in Computer and Information Science, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-10-3966-9_31
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