Estimation of crop water stress index and leaf area index based on remote sensing data
نویسندگان
چکیده
Abstract Estimation of crop water stress index (CWSI) and leaf area (LAI) over large-irrigation schemes requires the use cutting-edge technologies. Combinations remote sensing techniques with ground-truth data have become available for at catchment level. These approaches allow us to estimate actual evapotranspiration capability monitoring status saving irrigation in water-scarce regions. This study was conducted eastern Mediterranean Region Turkiye. Fully distributed CWSI maps were generated we assessed relationship between LAI some specific crops winter season 2021. Landsat 7 8 used meteorological acquired from two stations area. ‘Mapping Evapotranspiration high Resolution Internalized Calibration’ methodology applied energy balance components. displayed spatiotemporal changes tandem crop-type variations. Consequently, results presented a correlation (r = 0.95 r 0.99 wheat lettuce, respectively) LAI, moderate 0.44) potatoes season. Thus, by utilizing remotely sensed data, values would be directly estimated without requiring any situ measurements canopy air temperature over-irrigation scheme.
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ژورنال
عنوان ژورنال: Water Science & Technology: Water Supply
سال: 2023
ISSN: ['1606-9749', '1607-0798']
DOI: https://doi.org/10.2166/ws.2023.051