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Phenological analysis of unmanned aerial vehicle based time series of barley imagery with high temporal resolution

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Abstract

Emerging strategies and technologies in agriculture, such as precision farming and phenotyping depend on detailed data on all stages of crop development. Unmanned aerial vehicles promise to deliver such time series as they allow very frequent measurements. In this study, we analyse a field trial with two barley cultivars and two contrasting sowing densities in a random plot design over 2 consecutive years using the aerial images of 28 flight campaigns, providing a very high temporal resolution. From empirically corrected RGB images, we calculated the green-red-vegetation-index (GRVI) and evaluated the time-series for its potential to track the seasonal development of the crop. The time series shows a distinct pattern during crop development that reflected the different developmental stages from germination to harvest. The simultaneous comparison to ground based assessment of phenological stages, allowed us to relate features of the airborne time series to actual events in plant growth and development. The measured GRVI values range from −0.10 (bare soil) to 0.20 (fully developed crop) and show a clear drop at time of ear pushing and ripening. Lower sowing densities were identified by smaller GRVI values during the vegetative growth phase. Additionally, we could show that the time of corn filling was strongly fixed and happened around 62 days after seeding in both years and under both density treatments. This case study provides a proof-of-concept evaluation how RGB data can be utilized to provide quantitative data in crop management and precision agriculture.

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Acknowledgements

The authors acknowledge the diligent farming work at the barley experiment done by the team of the field lab Campus Klein-Altendorf, namely Mr. Winfried Bungert as the responsible technician. Huge thanks go to Domenik Radke for preparing parts of the image rectification. The authors acknowledge the funding of the CROP.SENSe.net project and PhenoCrops in the context of Ziel 2-Programmes NRW 2007–2013 “Regionale Wettbewerbsfähigkeit und Beschäftigung (EFRE)” by the Ministry for Innovation, Science and Research (MIWF) of the state of North Rhine–Westphalia (NRW) and European Union Funds for regional development (EFRE) (FKZ 005-1012-0001).

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  1. Forschungszentrum Jülich, Institute of Bio- and Geosciences, IBG-2: Plant Sciences, 52428, Jülich, Germany

    A. Burkart, V. L. Hecht & U. Rascher

  2. Field Lab Campus Klein-Altendorf, Agricultural Faculty, University of Bonn, Klein-Altendorf 2, 53359, Rheinbach, Germany

    T. Kraska

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  1. A. Burkart
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Burkart, A., Hecht, V.L., Kraska, T. et al. Phenological analysis of unmanned aerial vehicle based time series of barley imagery with high temporal resolution. Precision Agric 19, 134–146 (2018). https://doi.org/10.1007/s11119-017-9504-y

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