以多时期与PCANDVI法改善地物分类之正确性与完整性.PDF

49 地理研究 第57期 民國 101年 11月 Journal of Geographical Research No.57, November 2012 以多時期與PCA+NDVI法改善地物分類之正確性與完整性 Using Multi-temporal and PCA ＋NDVI to Improve the Accuracy and Integrity of Land Cover Classification a b c 張國楨 田應平 施孝謙 Kuo-chen Chang Ying-Ping Tian Hsiao-Chien Shih Abstract Satellite image analysis is one of the main methods of monitoring of environmental changes. The accuracy and credibility of the results depend on the spectral resolution of the imagery used and the spectral separability between features being monitored. If original imagery from single period is used to perform classification, the results are often affected by the noise of imagery itself and spectral similarity between different features. In this research, we proposed an improved solution for change detection that combines a Principle Component Analysis (PCA) process to remove noise and a multi-temporal process to increase spectral resolution. The study area is located on Shezi Island with imageries from 2005, 2006, 2007. The original imageries were processed with PCA to retain the first two major components which account for over 95% of total explanation. The resulting imageries were inversed by IPCA process back to 4 bands imageries. NDVI was calculated for each time period and stacked with IPCA imageries to create a new multi-temporal imagery for further unsupervised classification. The experimental results showed that the PCA process does enhance the spectral characteristic of features being monitored. An unsup