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Erratum: Novelli, F., et al. Assimilation of Sentinel-2 Leaf Area Index Data into a Physically-Based Crop Growth Model for Yield Estimation. Agronomy 2019, 9, 255
Open AccessArticle

Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy

1
Department of Agriculture, Food, Environment and Forestry, University of Florence, Piazzale delle Cascine 18, 50144 Firenze, Italy
2
Department of Agricultural Sciences, University of Naples “Federico II”, Via Università 100, 80055 Portici (NA), Italy
3
Ariespace s.r.l., Spin off Company, University of Napoli “Federico II”, Centro Direzionale IS A3, 80143 Napoli, Italy
4
CREA Research Centre for Agricultural Policies and Bioeconomy, Via Po 14, 00198 Roma, Italy
*
Author to whom correspondence should be addressed.
Agronomy 2019, 9(7), 404; https://doi.org/10.3390/agronomy9070404
Received: 1 June 2019 / Revised: 17 July 2019 / Accepted: 18 July 2019 / Published: 21 July 2019
(This article belongs to the Special Issue Remote Sensing Applications for Agriculture and Crop Modelling)
A research study was conducted in an open field tomato crop in order to: (i) Evaluate the capability of Sentinel-2 imagery to assess tomato canopy growth and its crop water requirements; and (ii) explore the possibility to predict crop water requirements by assimilating the canopy cover estimated by Sentinel-2 imagery into AquaCrop model. The pilot area was in Campania, a region in the south west of Italy, characterized by a typical Mediterranean climate, where field campaigns were conducted in seasons 2017 and 2018 on processing tomato. Crop water use and irrigation requirement were estimated by means of three different methods: (i) The AquaCrop model; (ii) an irrigation advisory service based on Sentinel-2 imagery known as IRRISAT and (iii) assimilating the canopy cover estimated by Sentinel-2 imagery into AquaCrop model Sentinel-2 imagery proved to be effective for monitoring canopy growth and for predicting irrigation water requirements during mid-season stage of the crop, when the canopy is fully developed. Conversely, the integration of the Sentinel-2 imagery with a crop growth model can contribute to improve the irrigation water requirement predictions in the early and development stage of the crop, when the soil evaporation is not negligible with respect to the total evapotranspiration. View Full-Text
Keywords: fractional cover; irrigation; satellite; crop simulation model; AquaCrop fractional cover; irrigation; satellite; crop simulation model; AquaCrop
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MDPI and ACS Style

Dalla Marta, A.; Chirico, G.B.; Falanga Bolognesi, S.; Mancini, M.; D’Urso, G.; Orlandini, S.; De Michele, C.; Altobelli, F. Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy. Agronomy 2019, 9, 404. https://doi.org/10.3390/agronomy9070404

AMA Style

Dalla Marta A, Chirico GB, Falanga Bolognesi S, Mancini M, D’Urso G, Orlandini S, De Michele C, Altobelli F. Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy. Agronomy. 2019; 9(7):404. https://doi.org/10.3390/agronomy9070404

Chicago/Turabian Style

Dalla Marta, Anna; Chirico, Giovanni B.; Falanga Bolognesi, Salvatore; Mancini, Marco; D’Urso, Guido; Orlandini, Simone; De Michele, Carlo; Altobelli, Filiberto. 2019. "Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy" Agronomy 9, no. 7: 404. https://doi.org/10.3390/agronomy9070404

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