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Título

Remotely Sensed Agroclimatic Classification and Zoning in Water-Limited Mediterranean Areas towards Sustainable Agriculture

AutorFaraslis, Ioannis; Dalezios, Nicolas R.; Alpanakis, Nicolás; Tziatzios, Georgios A.; Spiliotopoulos, Marios; Sakellariou, Stavros; Sidiropoulos, Pantelis; Dercas, Nicholas; Domínguez, Alfonso; Martínez-López, José Antonio; López-Urrea, Ramón; Karam, Fadi; Amami, Hacib; Nciri, Radhouan
Palabras claveAgroclimatic zoning
Hydroclimatic zoning
Non-crop-specific zoning
Crop-specific zoning
Agricultural suitability zones
Mediterranean agroecosystems
Fecha de publicación13-dic-2023
EditorMultidisciplinary Digital Publishing Institute
CitaciónRemote Sensing 15(24): 5720 (2023)
ResumenAgroclimatic classification identifies zones for efficient use of natural resources leading to optimal and non-optimal crop production. The aim of this paper is the development of a methodology to determine sustainable agricultural zones in three Mediterranean study areas, namely, “La Mancha Oriental” in Spain, “Sidi Bouzid” in Tunisia, and “Bekaa” valley in Lebanon. To achieve this, time series analysis with advanced geoinformatic techniques is applied. The agroclimatic classification methodology is based on three-stages: first, the microclimate features of the region are considered using aridity and vegetation health indices leading to water-limited growth environment (WLGE) zones based on water availability; second, landform features and soil types are associated with WLGE zones to identify non-crop-specific agroclimatic zones (NCSAZ); finally, specific restricted crop parameters are combined with NCSAZ to create the suitability zones. The results are promising as compared with the current crop production systems of the three areas under investigation. Due to climate change, the results indicate that these arid or semi-arid regions are also faced with insufficient amounts of precipitation for supporting rainfed annual crops. Finally, the proposed methodology reveals that the employment and use of remote sensing data and methods could be a significant tool for quickly creating detailed, and up to date agroclimatic zones.
Versión del editorhttps://doi.org/10.3390/rs15245720
URIhttp://hdl.handle.net/10261/341583
DOI10.3390/rs15245720
E-ISSN2072-4292
Identificadoresdoi: 10.3390/rs15245720
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