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A Low-Cost System to Estimate Leaf Area Index Combining Stereo Images and Normalized Difference Vegetation Index

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Progress in Artificial Intelligence (EPIA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11804))

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Abstract

In order to determine the physiological state of a plant it is necessary to monitor it throughout the developmental period. One of the main parameters to monitor is the Leaf Area Index (LAI). The objective of this work was the development of a non-destructive methodology for the LAI estimation in wine growing. This method is based on stereo images that allow to obtain a bard 3D representation, in order to facilitate the segmentation process, since to perform this process only based on color component becomes practically impossible due to the high complexity of the application environment. In addition, the Normalized Difference Vegetation Index will be used to distinguish the regions of the trunks and leaves. As an low-cost and non-evasive method, it becomes a promising solution for LAI estimation in order to monitor the productivity changes and the impacts of climatic conditions in the vines growth.

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Acknowledgements

This work was funded by FCT (Portuguese Foundation for Science and Technology), within the framework of the project “WaterJPI/0012/2016”. The authors would like to thank the EU and FCT for funding in the frame of the collaborative international consortium Water4Ever financed under the ERA-NET Water Works 2015 cofounded call. This ERA-NET is an integral part of the 2016 Joint Activities developed by the Water Challenge for a changing world joint programme initiation (Water JPI). This work was developed under the Doctoral fellowship with the reference “SFRH/BD/129813/2017”, from FCT.

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Authors and Affiliations

  1. INESC TEC – Institute for Systems and Computer Engineering, Technology and Science, Pólo da UTAD, Vila Real, Portugal

    Jorge Miguel Mendes, Vítor Manuel Filipe, Filipe Neves dos Santos & Raul Morais dos Santos

  2. Engineering Department, Quinta de Prados, UTAD – University of Trás-os-Montes e Alto Douro, Vila Real, Portugal

    Jorge Miguel Mendes, Vítor Manuel Filipe & Raul Morais dos Santos

Authors
  1. Jorge Miguel Mendes
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  2. Vítor Manuel Filipe
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  3. Filipe Neves dos Santos
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  4. Raul Morais dos Santos
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Corresponding author

Correspondence to Jorge Miguel Mendes .

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Editors and Affiliations

  1. INESC-TEC, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal

    Paulo Moura Oliveira

  2. University of Minho, Braga, Portugal

    Paulo Novais

  3. LIACC/UP, University of Porto, Porto, Portugal

    Luís Paulo Reis

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Mendes, J.M., Filipe, V.M., dos Santos, F.N., Morais dos Santos, R. (2019). A Low-Cost System to Estimate Leaf Area Index Combining Stereo Images and Normalized Difference Vegetation Index. In: Moura Oliveira, P., Novais, P., Reis, L. (eds) Progress in Artificial Intelligence. EPIA 2019. Lecture Notes in Computer Science(), vol 11804. Springer, Cham. https://doi.org/10.1007/978-3-030-30241-2_21

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  • DOI: https://doi.org/10.1007/978-3-030-30241-2_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30240-5

  • Online ISBN: 978-3-030-30241-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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