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Surveillance Camera-Based Monitoring of Plant Flowering Phenology

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Geo-Spatial Knowledge and Intelligence (GRMSE 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 698))

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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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Authors and Affiliations

  1. School of Earth Sciences and Resources, China University of Geosciences, Beijing, 100083, China

    Lijun Deng & Wei Shen

  2. School of Earth and Space Sciences, Institute of Remote Sensing and GIS, Peking University, Beijing, 100871, China

    Yi Lin

  3. School of Geology and Geomatics, Tianjin Chengjian University, Tianjin, 300384, China

    Wei Gao

  4. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China

    Jiayuan Lin

Authors
  1. Lijun Deng
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  2. Wei Shen
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  3. Yi Lin
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  4. Wei Gao
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  5. Jiayuan Lin
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Corresponding author

Correspondence to Yi Lin .

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Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Hanning Yuan

  2. Beijing Institute of Technology, Beijing, China

    Jing Geng

  3. Wuhan University, Wuhan, China

    Fuling Bian

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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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  • DOI: https://doi.org/10.1007/978-981-10-3966-9_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3965-2

  • Online ISBN: 978-981-10-3966-9

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