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Forecasting of Cereal Yields in a Semi-arid Area Using the Simple Algorithm for Yield Estimation (SAFY) Agro-Meteorological Model Combined with Optical SPOT/HRV Images

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      Abstract

      In semi-arid areas characterized by frequent drought events, there is often a strong need for an operational grain yield forecasting system, to help decision-makers with the planning of annual imports. However, monitoring the crop canopy and production capacity of plants, especially for cereals, can be challenging. In this paper, a new approach to yield estimation by combining data from the Simple Algorithm for Yield estimation (SAFY) agro-meteorological model with optical SPOT/ High Visible Resolution (HRV) satellite data is proposed. Grain yields are then statistically estimated as a function of Leaf Area Index (LAI) during the maximum growth period between 25 March and 5 April. The LAI is retrieved from the SAFY model, and calibrated using SPOT/HRV data. This study is based on the analysis of a rich database, which was acquired over a period of two years (2010–2011, 2012–2013) at the Merguellil site in central Tunisia (North Africa) from more than 60 test fields and 20 optical satellite SPOT/HRV images. The validation and calibration of this methodology is presented, on the basis of two subsets of observations derived from the experimental database. Finally, an inversion technique is applied to estimate the overall yield of the entire studied site.

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            Author and article information

            Affiliations
            [1]LR17AGR01 (LR GREEN-TEAM)/INAT, University Carthage, Avenue de la République, P.O. Box 77, Carthage, Tunis 1054, Tunisia; chehbi.aicha@123456gmail.com (A.C.B.); zohra.lili.chabaane@123456gmail.com (Z.L.-C.)
            [2]ISET_Nabeul, Campus Universitaire Mrezgua, Nabeul 8000, Tunisie
            [3]CESBIO (CNRS/UPS/IRD/CNES), 18 Avenue Edouard Belin, 31401 Toulouse CEDEX 9, France; Bernard.mougenot@123456ird.fr
            Author notes
            [*]Correspondence: mehrez.zribi@123456ird.fr; Tel.: +33-561-558-525
            Journal
            Sensors (Basel)
            Sensors (Basel)
            sensors
            Sensors (Basel, Switzerland)
            MDPI
            1424-8220
            03 July 2018
            July 2018
            : 18
            : 7
            29970840
            6068716
            10.3390/s18072138
            sensors-18-02138
            © 2018 by the authors.

            Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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