本文為一項為期三年試驗之研究成果報告，目的旨在探討利用地面遙測之植被覆蓋反射比光譜於估測水稻生長之可行性，並試予模式化兩者關係。田間試驗係在座落於臺中縣霧峰鄉（北緯24 02'，東經120 40'，海拔高度85m）之行政院農業委員會農業試驗所農場進行，栽培季節涵蓋1996年至1998年之一、二期稻作，參試品種為臺農67號（Oryza staiva L.cv. Tainung 67）。根據試驗結果，由典型的水稻植被反射比（或稱反射強度）光（波）譜發現不同波長（段）具有不等反射比，且不同生育階段之表現亦不相同。綜合水稻六期作全生育期植被反射比光譜曲線，經一次微分及光譜波峰與波谷轉折點比對，選取波長554、674（RED）及754nm（NIR）為三特徵波長。此三潻長在生育期間呈二次曲線趨勢，其中554及674 nm汳長反射比由生育初期高比值下降至近抽穗期達低點，再隨稻株成熟面上升；754 nm波長反射比變化則反之。標準差植被指數（或稱規整差植生指數，normalized difference vegetation index，NDVE）乃藉由674及754 nm波長計算，全生育期之變化亦呈二次曲線趨勢，其中一、二期作決定係數（R）分別為0.919及0.931。試驗又發現，水稻植被外觀物理徵狀與NDVI呈現指數關係，依決定係數高低分別為葉面積指數（LAI）0.811、葉片數（LN）0.809及葉片乾重（LDW）0.669。由此一高決定係數之指數相關結果顯示，吾人可利用植被覆蓋之反射比光譜於水稻生長之估測，尤其是LAI與NDVI之相關。

　　　　　A three-year study was carried out to develop a model for estimation of rice growth from reflectance spectra of ground vegetative cover. Field meadurements were conucted at the experimental farm of Taiwan Agricultural Research Institute, Council of Agriculture at Wufeng, Taiwan (24 02'N, 120 40'E, elevation of 85m) during the first and the second cropping seasons in 1996, 1997,and 1998. It showed that the typical curve of reflectance spectrum of rice vegetative cover (canopy) had a differential reflectance pattern in the varied wavebands as well as in different growth stages. By using the first order differentiation in cope with peaks and valleys observations from spectral waves, three characteristics wavelengths of 554,674 (RED), and 754nm (NIR) were selected from turning points of reflectance spectra. Their seasonal changes were curvilinear, reflectances of 554 and 674nm fell off to the lowest near heading and then climbed up as plants reached maturity; the trend was reversed for the near-infrared reflectance. Seasonal changes of normalized difference vegetation index (NDVE) show a similar curvilinear shape in both First (R = 0.919) and Second (R = 0.931) crops from 1996 to 1998. Relations of the measured physical growth characters and NDVI were exponential, the determining factors (R) were 0.811,0.809,and 0.669 for leaf area index (LAI), leaf number (LN), and leaf dry weight (LDW), respectively. The exponential curves estimate fairly accurately the advancement of growth characters from spectral transformation (NDVI), especially LAI.