Terra衛星所酬載的ASTER感測器涵蓋廣泛的光譜範圍，從可見光到熱紅外線共有14個波段。藉由分析不同波段的影像，可以辨別和繪製地表的岩石種類和預測礦物的風化程度與組合。本研究利用ASTER影像對南蒙古戈壁南蒙古沙漠進行多光譜分析。該地區極度乾旱、幾乎無植被的地表，十分有利應用遙測技術於地表岩性判釋。將衛星影像進行幾合與輻射修正，以及光譜分析後，本研究提出該地區地表風化礦物的分類。光譜分類根據下列步驟進行：
a）以最小噪音分離轉換（MNF）降低光譜雜訊
b）以像素純度指數（PPI）分析降低像素數目
c）使用N維視覺化工具(N-dimentional visualizer)進行端元判定
此外，本研究亦結合遙測影像和地形圖，應用地理資訊系統技術，配合地質資料來檢測所繪製的風化礦物分佈圖。結果顯示在本研究區域中，應用MNF、PPI、n-D visualizer等分析方法於風化礦物的判釋確實可行。

The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) cover a wide spectral region with 14 bands from visible to the thermal infrared. The different band ranges can be capable discriminating and mapping surface rocks and predict minerals on alteration assemblages of potential targets. The aim of this work is a multispectral analysis of the area of interest using ASTER sensor image on board the satellite Terra. This research work presents classification of different minerals in Gobi (Southern Mongolia) desert and almost non-vegetated arid area. The Satellite imagery has been corrected geometrically and radiometrically. The spectral classification was done according to the following steps:
a) Spectral reduction by the Minimum Noise Fraction (MNF) transformation,
b) Spatial reduction by the Pixel Purity Index (PPI) and
c) Manual identification of the endmembers using the N-dimensional visualizer.
This research work was used remotely sensed imagery and topographical map, and Remote Sensing and GIS techniques to detect mineral alteration mapping. Ground truth data have been used for validation as a reference. The application of the sequence MNF, PPI and n-D visualizer in the study area showed possibility of the identification of different mineral and different rock types.

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