基于NOAA PAL数据集的地表蒸散遥感估算方法

An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset

基于NOAA AVHRR气象卫星长时间序列10d合成的PAL数据集(分辨率8km×8km)以及地表能量平衡原理和"VI-Ts"方法,建立了地表蒸散的遥感估算方法,该方法不需要地面气象观测数据的支持,所需参数可直接从遥感数据反演或推算,并选择国际上著名的遥感蒸散模型——SEBS模型对新建模型进行了验证比较.结果表明:新建模型和SEBS模型模拟的地表蒸散值及其季节性变化趋势非常一致,说明新构建模型的模拟结果比较可靠,能够反映地表蒸散的实际情况.新建地表蒸散遥感估算模型可操作性强,为利用长时间序列的卫星遥感数据研究我国乃至全球地表蒸散的时空变化规律提供了一个新的途径.

Based on the time series 10-day composite NOAA Pathfinder AVHRR Land （PAL） dataset （8 km × 8 kin） , and by using land surface energy balance equation and ＂ VI-Ts＂ （vegetation index-land surface temperature） method, a new algorithm of land surface evapotranspiration （ET） was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e. , SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.