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A stand-alone remote sensing approach based on the use of the optical trapezoid model for detecting the irrigated areas

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  • Longo-Minnolo, Giuseppe
  • Consoli, Simona
  • Vanella, Daniela
  • Ramírez-Cuesta, Juan Miguel
  • Greimeister-Pfeil, Isabella
  • Neuwirth, Martin
  • Vuolo, Francesco

Abstract

Under the current water scarcity scenario, the promotion of water saving strategies is essential for improving the sustainability of the irrigated agriculture. In particular, high resolution irrigated area maps are required for better understanding water uses and supporting water management authorities. The main purpose of this study was to provide a stand-alone remote sensing (RS) methodology for mapping irrigated areas. Specifically, an unsupervised classification approach on Normalized Difference Vegetation Index (NDVI) data was coupled with the OPtical TRApezoid Model (OPTRAM) for detecting actual irrigated areas without the use of any reference data. The proposed methodology was firstly applied and validated at the Marchfeld Cropland region (Austria) during the irrigation season 2021, showing a good agreement with an overall accuracy of 70%. Secondly, it was applied at the irrigation district Quota 102,50 (Italy) for the irrigation seasons 2019–2020. The results of the latter were instead compared with the data declared by the Reclamation Consortium, finding an overestimation of irrigated areas of 21%. In conclusion, this study suggests an easy-to-use approach, eventually independent of reference data such as agricultural statistical surveys or records and replicable under different agricultural settings in continental or Mediterranean climates to support stakeholders for regular estimation of irrigated areas in different growing years or detecting eventual unauthorized water uses. However, some uncertainties should be considered, needing further analyses for improving the accuracy of the proposed approach.

Suggested Citation

  • Longo-Minnolo, Giuseppe & Consoli, Simona & Vanella, Daniela & Ramírez-Cuesta, Juan Miguel & Greimeister-Pfeil, Isabella & Neuwirth, Martin & Vuolo, Francesco, 2022. "A stand-alone remote sensing approach based on the use of the optical trapezoid model for detecting the irrigated areas," Agricultural Water Management, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:agiwat:v:274:y:2022:i:c:s0378377422005224
    DOI: 10.1016/j.agwat.2022.107975
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    References listed on IDEAS

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    1. Babak Ghassemi & Markus Immitzer & Clement Atzberger & Francesco Vuolo, 2022. "Evaluation of Accuracy Enhancement in European-Wide Crop Type Mapping by Combining Optical and Microwave Time Series," Land, MDPI, vol. 11(9), pages 1-15, August.
    2. Mutlu Ozdogan & Curtis Woodcock & Guido Salvucci & Hüseyin Demir, 2006. "Changes in Summer Irrigated Crop Area and Water Use in Southeastern Turkey from 1993 to 2002: Implications for Current and Future Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(3), pages 467-488, June.
    3. Thompson, R.B. & Gallardo, M. & Valdez, L.C. & Fernandez, M.D., 2007. "Using plant water status to define threshold values for irrigation management of vegetable crops using soil moisture sensors," Agricultural Water Management, Elsevier, vol. 88(1-3), pages 147-158, March.
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    1. Longo-Minnolo, Giuseppe & D’Emilio, Alessandro & Vanella, Daniela & Consoli, Simona, 2024. "Advancing in satellite-based models coupled with reanalysis agrometeorological data for improving the irrigation management under the European Water Framework Directive," Agricultural Water Management, Elsevier, vol. 301(C).

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