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Monitoring irrigation volumes using high resolution NDVI image time series. Calibration and validation in the Kairouan plain

机译:使用高分辨率NDVI图像时间序列监控灌溉量。 Kairouan Plain中的校准和验证

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The increasing availability of high resolution high repetitively VIS-NIR remote sensing, like the forthcoming Sentinel-2 mission to be launched in 2015, offers unprecedented opportunity to improve agricultural monitoring. In this study, regional evapotranspiration and crop water consumption were estimated over an irrigated area located in the Kairouan plain (central Tunisia) using the FAO-56 dual crop coefficient water balance model combined with NDVI image time series providing estimates of the actual basal crop coefficient (Kcb) and vegetation fraction cover. Three time series of high-resolution SPOT5 images have been acquired for the 2008-2009, 2011-2012 and 2012-2013 hydrological years. We also benefited from a SPOT4 time series acquired in the frame of the SPOT4-Take5 experiment. The SPOT5 images were radiometrically corrected, first, using the SMAC6s Algorithm, and then improved using invariant objects located on the scene. The method was first calibrated using ground measurements of evapotranspiration achieved using eddy-correlation devices installed on irrigated wheat and barley plots. For other crops for which no calibration data was available, parameters were taken from bibliography. Then, the model was run to spatialize irrigation over the whole area and a validation was done using cumulated seasonal water volumes obtained from ground survey for three irrigated perimeters. In a subsequent step, evapotranspiration estimates were obtained using a large aperture scintillometer and were used for an additional validation of the model outputs.
机译:高分辨率高度重复的可获得的可获得高度重复的Vis-Nir遥感,如2015年即将推出的哨兵-2任务,为改善农业监测提供了前所未有的机会。在这项研究中,使用FAO-56双重作物系数水平衡模型与NDVI图像时间序列提供了实际基础作物系数的估算,估计区域蒸发和作物用水量估计在位于Kairouan Plane(中央突尼斯)的灌溉区域估计。 (KCB)和植被分数盖。 2008-2009,2011-2012和2012-2013水文年份已经获得了三次高分辨率Spot5图像的三次时间。我们还受益于在Spot4-Take5实验框架中获得的Spot4时间序列。首先使用SMAC6S算法,使用SMAC6S算法进行辐射校正,然后使用位于场景上的不变对象来改进。使用安装在灌溉小麦和大麦图上的涡流相关装置实现的蒸散进行地进行校准该方法。对于没有可用校准数据的其他作物,从参考书目中取出参数。然后,该模型运行到全部区域的空间化灌溉,并使用从地面调查获得的三个灌溉周长获得的累积季节性水量进行验证。在随后的步骤中,使用大孔径闪烁计获得蒸发估计,并用于额外验证模型输出。

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