| Summary: | 碩士 === 國立屏東科技大學 === 土木工程系碩士班 === 92 === Recently, as the widespread applications of remote sensing technique, the imagery of the satellite has the advantages of short revisiting cycle, comprehending the rapid change of land surface in large area, and the ability of observing by multi-spectral bands. Contrast to traditional ground survey methods which are difficult and time consuming; it is more efficient to acquire land use information precisely by using remote sensing technology.
The study area is located in Zhangtan workstation of Meinung area in this research. Utilizing the characteristics of different vegetation reflective spectrum, the Normalized Difference Vegetation Index (NDVI) was used to improve the classification accuracy. According to the standard spectrum of the vegetation, there are two peak values located in the near infrared and the short-wave infrared bands of SPOT 4 satellite. Those two bands were applied to the NDVI and compared their contribution in the classification accuracy in two rice growing periods. Results indicated that the classification accuracy of the short-wave infrared NDVI is better than that of near infrared. The User’s Accuracy of the paddy classification is 85.71 % using the short-wave NDVI in the image of Feb. 27, 2003. The Overall Classification Accuracy is 82.49%, and the Kappa Statistics is 0.7836. The User’s Accuracy of the paddy is 87.10 % using the short-wave NDVI in the image of Jul. 19, 2003. The Overall Classification Accuracy is 77.54%, and the Kappa Statistics is 0.7216. The spectrum values in the training area were exported to investigate the relation of each band in the classification. The result shows that short-wave NDVI is less dependent than other bands in the classification. In other words, the short-wave NDVI is a better band to be used in classification.
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