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Remote sensing of crop water requirements in orange orchards using high spatial resolution sensors

机译:使用高空间分辨率传感器遥感橙色果园作物需求

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With the aim to derive crop water requirements (ET_p) for an irrigated area covered by orange orchard in Sicily, Quick Bird and ASTER TERRA high resolution satellites data were used and compared with reference to their different spatial and spectral resolution. Satellites data allowed to improve the monitoring of canopy development in the irrigated area by identifying biophysical vegetation variable (LAI, albedo, vegetation indicators, etc...); this information was successively used for the evaluation of maximum crop water needs by means of the well known Penman-Monteith equation. The paper results evidence the importance of very-high resolution sensors such as QuickBird in areas characterised by strong spatial heterogeneity. The algorithms applied to estimate the canopy parameters and the crop water requirements were applied by considering different levels of radiometric calibration of the satellite data, which produced marked differences in the final results.
机译:旨在导出种植水需求(ET_P)在西西里岛覆盖的橙色果园覆盖的灌溉区域,使用快速鸟和艾斯特地区高分辨率卫星数据,并参考其不同的空间和光谱分辨率进行比较。卫星数据通过鉴定生物物理植被变量(Lai,Albedo,植被指标等)来改善灌溉区域中的树冠开发的监测;通过众所周知的Penman-Monteith方程,该信息连续地用于评估最大作物水需求。纸质结果证明了非常高分辨率传感器(如Quickbird)在特征在于强的空间异质性的区域的重要性。应用于估计顶篷参数和作物水要求的算法通过考虑卫星数据的辐射校准来应用,这在最终结果中产生了显着的差异。

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