摘要 本文利用空載遙測資料：可見光、近紅外光與熱紅外光多波段資料，配合地面氣象站所量測得的氣象資料，進行地表通量的估計，地表通量包括蒸發散量及可感熱通量。推估方法基於地表能量平衡方程式，反演的地表參數包含反照率(albedo)、地表溫度及標準差植被指數(Normalized Difference Vegetation Index; NDVI )。其中，對於地表溫度的部分，係利用NDVI推求熱紅外光波段的放射率，再透過Lowtran7程式套校正大氣所造成的微小誤差；最終，將校正的輻射量值轉換為地表溫度。至於潛熱通量與可感熱的分配，則以地表氣象資訊與溫度-反照率空間散佈圖的乾、濕控制條件配合推求。本研究先依照遙測取像時的氣象條件，以數值迭代的方法推求各像元的潛勢蒸發散量；再以遙測多光譜的特性，重新分配潛熱與可感熱通量。將本反演結果與S-SEBI模式比較，顯示本研究所反演出的潛熱通量與可感熱通量，均較接近渦度儀(eddy correlation)測值。並以田間量測葉面蒸散量與遙測推估值做比對，兩者具有相同的空間變異趨勢。以上多點均說明了，透過多波段遙測資料推估潛熱通量與可感熱通量的合理性。 Abstract In order to retrieve the latent and sensible heat fluxes, high-resolution airborne imageries with visible, near infrared, and thermal infrared bands and ground-based meteorology measurements are utilized in this thesis. The retrieval scheme is based on construction of surface energy budget and momentum equations. There are three basic surface parameters including surface albedo(α), normalized difference vegetation index(NDVI) and surface kinetic temperature(T0). Lowtran 7 code is used to correct the atmosphere effect what the imageries were taken on 28 April and 5 May 2003. From the scattering plot of data set, we observed the critical dry and wet pixels which can use to drive for fitting the dry and wet controlled lines. We assumed all pixels in this scene being the wet condition, so that the numerical iteration method could solve whole imagery without correction. Then the sensible heat and latent heat fluxes are derived from previous procedure which mentions the partition factor Λ. The retrieved latent and sensible heat fluxes are compared with many in situ measurements, including eddy correlation and porometer measurements, and the consequence shows they and their spatial variation from our model are better agreement with experimental data than those from S-SEBI model.
