蒸發散量(Evapotranspiration)在水文循環中扮演著一個非常重要的因素。估算蒸發散量的方法相當多，以往多半都是利用蒸發皿量測單點的蒸發散量，或是利用氣象資料經相關公式推估單點的潛勢蒸發散量，再把經驗公式應用到整個地面區域，並無法反應出區域性的實際狀況。近年來由於遙測技術的進步，因此利用遙測影像推估蒸發散量，可由傳統單點的估算轉而對整個區域面的估算。 本研究利用空載和衛載的遙測資料做為反演蒸發散量的依據：空載的遙測資料包括可見光、近紅外光與熱紅外光多波段資料，而衛載資料則是利用MODIS的影像資料，配合地面氣象站所量測得的氣象資料(風速、大氣溫度)，進行地表熱通量的估計，地表熱通量包括潛熱通量及可感熱通量。推估方法基於地表能量平衡演算法，依據大氣不穩定的修正模式初步推估潛熱通量和可感熱通量，再利用乾、濕控制曲線結合初步推估的蒸發散量和可感熱通量重新分配淨可用能量。在大氣不穩定修正方程式中則利用Paulson(1970)、Dyer(1974)和Brustaert(1992)三種不同的修正方程，求出最適合的反演方式。 研究結果顯示，利用本研究的反演模式，不管是應用於空載或MODIS的衛星影像，都可求出良好的乾、濕控制曲線。蒸發散量在MODIS影像部分與地面測站的相關係數可到0.66，均方根差為97.81(W/m2)﹔可感熱通量相關係數則到0.76，均方根差為124.33(W/m2)。新的反演模式配合MODIS影像，可得到不錯的結果，希望本研究可提供相關領域研究之參考。 Evaportranspiration is an important factor in hydrology cycle. There are many ways to estimate evapotransporation. In the past, we got the local evaportransporation by using basin, or formula with meteorology data. And apply the empirical formula in the regional area. But it couldn’t represent the regional evaportranspiration. Recently, because of the improved remote sensing technology, we estimate evaportranspiration from local to region. Airborne and satellite image were utilized in this study. The airborne image included visible, near infrared, and thermal infrared bands. MODIS data was used in satellite image. We estimate surface heat flux by airborne and satellite image with meteorology measurements. The surface heat flux includes latent heat flux and sensible heat flux. We set the initial latent heat flux and sensible heat flux by using surface energy budget and unstable atmosphere correct function. Finding the radiation and evaporation controlled lines by initial latent heat flux and sensible heat flux and redistributing the net radiation flux. We test three different unstable atmosphere correct function, Paulson (1970), Dyer (1974) and Brustaent (1992) in order to find the suitable method. The result reveals that we can find good radiation and evaporation controlled line with airborne and satellite image. The correlation coefficient of latent heat flux and sensible heat flux with actual observations are 0.66 and 0.76. The root mean squared error of latent heat flux and sensible heat flux with actual observations are 97.81(W/m2) and 124.33(W/m2). We get a good result by the new retrieval method with MODIS data in this study. Hope that this study can be referred in relevant field.
