本研究旨在探討應用衛星遙測資料估測六龜台灣杉人工林葉面積指數之可行性。採用樹冠透光法,於地面估算其葉面積指數。衛星遙測資料方面,採用二期SPOT衛星影像資料依去除外在效應之有無與超圓方向餘弦轉換等共分七種處理組合,探討NDVI與NIR/R值與葉面積指數之關係。結果顯示SPOT衛星影像資料若僅使用原始輻射值仍嫌不足,有必要去除外在效應,方可得到與LAI較佳之相關關係。而夏天影像受路徑輻射影響較大,於去除路徑輻射後,其NDVI推估LAI之迴歸式為:LAI=-4.17+33.81 NDVI (R^2=0.71)。冬天影像則以地形漫射效應影響較大,經HSDC轉換去除該效應後,其NDVI推估LAI之迥歸式為:LAI=-11.48+28.07 NDVI (R^2=0.44)。上式中,NDVI推估冬天LAI值效果有限,若欲應用冬天影像估測冬天LAI,其影響之真正機制仍待進一步研究。
The purpose of this study is to apply a remote sensing method for estimating the Leaf Area Index, LAI, of Taiwania plantations in the Lukuei area. Based on the canopy transmittance method, LAI was derived from the Beer-Lambert Law with an assumed light extinction coefficient of 0.52. Two SPOT images were used to estimate LAI of Taiwania plantations with the remote sensing method. Based on the consideration of path radiation, sky light, and topographic effects, 7 treatments were compared in this study. Both normalized difference vegetation index (NDVI) and near infrared/red (NIR/R) were utilized to estimate LAI. The rsu1ts indicate that the removal of the external effects was necessary for estimating LAI. There was a high correlation between NDVI and LAI when the path radiation was removed from the original radiation in the summer image. The regression for using NDVI to estimate LAI is as follows: LAI=-24.17+33.81 NDVI (R^2=0.71). The topographic effect is the main factor in the winter image. Therefore, the NDVI calculated by hyperspherical direction cosine transformation (HSDC) had the highest correlation with LAI. The regression equation is: LAI=-11.48+28.07 NDVI (R^2=0.44). Because the correlation between NDVI and LAI was low, further studies need to be done in the future in order to understand the main effect of estimating LAI in the winter image.
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