衛星影像植被增顯方法

The Enhanced Method of Vegetation Satellite Image

10.30153/JCAGST.201003.0014

練智恒(Chih-Heng Lien)；蘇有(Yu Su)；李興緯(Hsing-Wei Lee)

中華印刷科技年報

2010（2010 / 03 / 01）

205 - 212

繁體中文

隨著商用衛星發展技術的提升，除了人眼所能觀測的可見光影像之外，進一步更能偵測如近紅外光等短波段輻射資訊，因此本研究將針對高解析衛星影像之多光譜(multispectral)影像特性，配合其全色態(panchromatic)影像進行地表植被特徵增顯作業。一般用於低解析度衛星影像植被增顯的方法為常態化差異植生指標(NDVI, Normalized Difference Vegetation Index)與纓帽轉換法(TCT, Tasseled-Cap Transformation)，而本研究擬開發基於上述兩種方法且適合高解析度衛星影像之植被增顯技術。經實驗成果顯示，本研究所提出之高解析度衛星影像植被增顯技術對於植被萃取的正確性及植被增顯後的清晰度均可大幅提升，可有效輔助後續判讀與製圖作業。

With the development of commercial satellite technology, in addition to the visible light image, further more, this technology can detect short wave radiation such as near-infrared light, so this study will address the high-resolution satellite images as much as multispectral images, coupled with panchromatic images of surface vegetation characteristics by significant operations. The Normalized Difference Vegetation Index (NDVI) and the Tasseled Cap transformation method (TCT) are generally used for low-resolution satellite images of vegetation explicit methods, and this study was to develop the suitable high-resolution satellite images of vegetation display technology based on the above-mentioned methods. The experimental results show this technology can significantly increased the accuracy and definition of extracted vegetation, which can effectively support the follow-up interpretation and mapping operations.

1. Digitalglobe, Quickbird Imagery Products Product Guide, pp.5, 2001..
2. Canada Centre for Remote Sensing, Natural Resources Canada(2008).Fundamentals of Remote Sensing.
3. Horne,J.(2003).A Tasseled Cap Transformation for Ikonos Images.ASPRS Annual Conference,Anchorage, Alaska:
4. 何炳賢(2009)。碩士論文(碩士論文)。桃園，國防大學理工學院環境資訊及工程學系。
5. 徐百輝(2007)。大地的辨識密碼高光譜影像。科學發展，416
6. 劉榮寬(2009)。高等遙感探測教材。國防大學理工學院。
7. 蘇有(2005)。博士論文(博士論文)。桃園，元智大學。