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Challenges in Water Stress Quantification Using Small Unmanned Aerial System (sUAS): Lessons from a Growing Season of Almond

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Abstract

We conducted a study in a large almond farm in Merced County, California, to monitor water status by using high-resolution multi-spectral imagery accquired by a Small Unmanned Aerial System (sUAS). More specifically, we would like to predict Stem Water Potential (SWP) via canopy Normalized Difference Vegetation Index (NDVI). During 2014, an aircraft equipped with multi-spectral cameras flew over the orchard weekly throughout the growing season. At the same time, SWP was measured for the sample trees under five different water treatment levels. Instead of averaging pixels in an orchard level, a block level or a canopy level, pixels were analyzed in the sub-canopy level to obtain canopy NDVI. An improved correlation between SWP and canopy NDVI was obtained by applying lower NDVI threshold. The relationship between SWP and canopy NDVI was also discussed at different growing stages–fruit development and post-harvest. However, tests of equality of distribution indicated that canopy NDVI distributions from different flights within a day were significantly different. Therefore, further calibration regarding the effects of solar motion on canopy NDVI is necessary.

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Acknowledgments

The authors would like to thank Larry Burrow for lending his expertise in almond orchard. Thanks go to the MESA Lab Scientific Data Drone crew members Ph.D. student Brendan Smith and Undergraduate Researchers Alejandro Sanchez, Yoni Shchemelinin and Andreas Anderson for contributions in conducting flight missions in the 2014 growing season.

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Authors and Affiliations

  1. Mechatronics, Embedded Systems and Automation Lab, University of California, Merced, CA, 95343, USA

    Tiebiao Zhao, Brandon Stark & YangQuan Chen

  2. University of California, Cooperative Extension (UCCE) Merced County, 2145 Wardrobe Avenue, Merced, CA, 95341-6445, USA

    Andrew L. Ray & David Doll

Authors
  1. Tiebiao Zhao
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  2. Brandon Stark
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  3. YangQuan Chen
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  4. Andrew L. Ray
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  5. David Doll
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Corresponding author

Correspondence to YangQuan Chen.

Additional information

This work is supported in part by UC ANR Competitive Grant Award No. 13-2628 (2014-2019) entitled “Evaluating and extending the use of small, multi-rotor unmanned aerial vehicles (UAV’s) as a crop monitoring tool.”

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Zhao, T., Stark, B., Chen, Y. et al. Challenges in Water Stress Quantification Using Small Unmanned Aerial System (sUAS): Lessons from a Growing Season of Almond. J Intell Robot Syst 88, 721–735 (2017). https://doi.org/10.1007/s10846-017-0513-x

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  • DOI: https://doi.org/10.1007/s10846-017-0513-x

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