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Sentinel-2 Imagery Monitoring Vine Growth Related to Topography in a Protected Designation of Origin Region

Author

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  • Dimitrios Tassopoulos

    (GIS Research Unit, Laboratory of Soils and Agricultural Chemistry, Department of Natural Resources and Agricultural Engineering, Agricultural University of Athens, 118 55 Athina, Greece)

  • Dionissios Kalivas

    (GIS Research Unit, Laboratory of Soils and Agricultural Chemistry, Department of Natural Resources and Agricultural Engineering, Agricultural University of Athens, 118 55 Athina, Greece)

  • Rigas Giovos

    (GIS Research Unit, Laboratory of Soils and Agricultural Chemistry, Department of Natural Resources and Agricultural Engineering, Agricultural University of Athens, 118 55 Athina, Greece)

  • Nestor Lougkos

    (GIS Research Unit, Laboratory of Soils and Agricultural Chemistry, Department of Natural Resources and Agricultural Engineering, Agricultural University of Athens, 118 55 Athina, Greece)

  • Anastasia Priovolou

    (GIS Research Unit, Laboratory of Soils and Agricultural Chemistry, Department of Natural Resources and Agricultural Engineering, Agricultural University of Athens, 118 55 Athina, Greece)

Abstract

Remote sensing satellite platforms provide accurate temporal and spatial information useful in viticulture with an increasing interest in their use. This study aims to identify the possibilities of freely available and with frequent revisit time Sentinel-2 satellites, to monitor vine growth at regional scale on a vine-growing Protected Designation of Origin (PDO) zone during the growing season of the year 2019. This study aims to: (i) investigate through several Vegetation Indices (VIs) the vine growth differences across the zone and relations with topographic parameters; (ii) identify VIs that best recognize differences on subzones of different climatic conditions; (iii) explore the effectiveness of the Sentinel-2 data monitoring management applications. A total of 27 vineyards were selected for field and satellite data collection. Several VIs have been calculated per vineyard from a 20-date time series dataset. VIs showed high negative correlation with topographic parameter of elevation on the flowering stage. The analysis of variance between the VIs of the subzones showed that these regions have statistically significant differences, that most VIs can expose on the flowering and harvest stage, and only Normalized Difference Vegetation Index (NDVI) and VIs using Red-Edge bands during the veraison period. Sentinel-2 data show great effectiveness on monitoring management applications (tillage and trimming).

Suggested Citation

  • Dimitrios Tassopoulos & Dionissios Kalivas & Rigas Giovos & Nestor Lougkos & Anastasia Priovolou, 2021. "Sentinel-2 Imagery Monitoring Vine Growth Related to Topography in a Protected Designation of Origin Region," Agriculture, MDPI, vol. 11(8), pages 1-20, August.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:8:p:785-:d:615996
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    References listed on IDEAS

    as
    1. Bretreger, David & Yeo, In-Young & Quijano, Juan & Awad, John & Hancock, Greg & Willgoose, Garry, 2019. "Monitoring irrigation water use over paddock scales using climate data and landsat observations," Agricultural Water Management, Elsevier, vol. 221(C), pages 175-191.
    2. Rigas Giovos & Dimitrios Tassopoulos & Dionissios Kalivas & Nestor Lougkos & Anastasia Priovolou, 2021. "Remote Sensing Vegetation Indices in Viticulture: A Critical Review," Agriculture, MDPI, vol. 11(5), pages 1-20, May.
    3. Evangelos Anastasiou & Athanasios Balafoutis & Nikoleta Darra & Vasileios Psiroukis & Aikaterini Biniari & George Xanthopoulos & Spyros Fountas, 2018. "Satellite and Proximal Sensing to Estimate the Yield and Quality of Table Grapes," Agriculture, MDPI, vol. 8(7), pages 1-17, June.
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    Cited by:

    1. Christos Kyriakos & Manolis Vavalis, 2023. "Business Intelligence through Machine Learning from Satellite Remote Sensing Data," Future Internet, MDPI, vol. 15(11), pages 1-29, October.

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