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Estimation of Crop Coefficients by Remote Sensing based Vegetation Index

机译:基于遥感的植被指数估算作物系数

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Crop coefficient plays a vital role in estimation of crop evapotranspiration for irrigation scheduling in a canal command. Remote sensing-based vegetation indices can help in efficient irrigation water management, as the irrigation systems need near real-time spatial information on types of crop, area under irrigation, crop water requirement, etc.The Surface Energy Balance Algorithm for Land (SEBAL) was used for estimating actual evapotranspiration (AET) based on remotely sensed data. The summer groundnut crop coefficients were estimated using AET and ET0. The FAO-56 method helped to estimate reference evapotranspiration (ET0) and crop evapotranspiration using crop coefficient. The remote sensing based Normalized Difference Vegetation Index (NDVI) for different days of year (DOY) were derived using Landsat imageries for summer crop season in 2014. The relationship between the NDVI and K. for different DOY was established to estimate the crop coefficients of summer groundnut at field and regional scales for different growth stages for the Ozat-II canal command of Junagadh district of Gujarat State, India. The developed equation might be useful for estimation of crop water requirement and irrigation scheduling of canal command using remote sensing data.
机译:作物系数在估算渠系灌溉计划的作物蒸散量中起着至关重要的作用。基于遥感的植被指数可以帮助有效地管理灌溉水,因为灌溉系统需要有关作物类型,灌溉面积,作物需水量等的近乎实时的空间信息。土地表面能量平衡算法(SEBAL)用于基于遥感数据估算实际蒸散量(AET)。使用AET和ET0估算夏季花生的作物系数。 FAO-56方法有助于利用作物系数估算参考蒸散量(ET0)和作物蒸散量。使用2014年夏季作物季节的Landsat影像,得出了基于遥感的一年中不同日期的植被指数(NDVI)。建立了不同DOY的NDVI和K.之间的关系,以估算作物的系数印度古吉拉特邦贾纳格德区的Ozat-II运河指挥部在不同生长阶段的田间和区域规模的夏季花生。所开发的等式对于利用遥感数据估算作物需水量和渠系灌溉计划可能有用。

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