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| 以不同分类法探讨SPOT与IKONOS两种卫星影像之分类准确度 | |
| 引用本文： | 吴守从,陈建璋,陈朝圳.以不同分类法探讨SPOT与IKONOS两种卫星影像之分类准确度[J].遥感学报,2006,10(4):573-577. |
| 作者姓名： | 吴守从 陈建璋 陈朝圳 |
| 作者单位： | 1. 实践大学,观光管理学系,中国台湾 2. 屏东科技大学,热带农业暨国际合作研究所,中国台湾 3. 屏东科技大学,森林系,中国台湾 |
| 摘 要： | 遥感探测可应用于大尺度环境之研究、规划及经营管理，故为探讨自然资源动态变迁之良好工具，惟现行影像来源与分类方法众多，研究者如何视其需要选择最佳组合，实有探讨之必要。本研究以SPOT及IKONOS两种不同空间解析力之卫星影像为材料，配合不同分类方法探讨台湾地区垦丁公园不同植群社会之空间分布信息，其结果均证实可行。而由研究过程发现，不同影像使用不同分类方法，其分类准确度有所差异，其中IKONOS影像因具有较高之空间解析力，有时反而容易造成影像分类的误授、漏授；而绿色植生部分尚无法由卫星影像之波谱值完全区隔，因此分类之精度仍有待精进。就影像分类而言，良好的训练样区配合正确的分类方法，可迅速获得一定准确度以上之分类结果，惟有时限于分类别的影像波谱值过于接近及各种地形效应、辐射效应之影响，会造成影像分类结果有误授、漏授及破碎化之情形产生，若能有效克服此一问题，则影像分类之成果将可提高其实用性。 |
| 关 键 词： | 遥感探测 分类准确度 波谱信息 |
| 文章编号： | 1007-4619(2006)04-0573-05 |
| 收稿时间： | 2005-08-15 |
| 修稿时间： | 2005-10-25 |
Using Different Classified Methods to Discuss the Classified Accuracy of SPOT and IKONOS Satellite Images |
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| WU Shou-tsung,CHEN Jan-chang and CHEN Chaur-tzuhn.Using Different Classified Methods to Discuss the Classified Accuracy of SPOT and IKONOS Satellite Images[J].Journal of Remote Sensing,2006,10(4):573-577. | |
| Authors: | WU Shou-tsung CHEN Jan-chang and CHEN Chaur-tzuhn |
| Institution: | 1. Department of Tourism Management, Shih Chien University, Taiwan, China ; 2. Institute of Tropical Agriculture and International Cooperation, Pingtung University of Science and Technology, Taiwan , China; 3. Department of Forest, Pingtung University of Science and Technology, Taiwan, China |
| Abstract: | Remote sensing technology can be applied in research, planning, and management on a large-scale environment. It is a powerful tool for natural resource investigation. However there are various sources of satellite images and classified methods, so the researchers have to find the best combination to meet their requirements. In this study, the SPOT and IKONOS satellite images were used as material, and collocated with different classified methods to examine the spatial distribution of vegetation types in Kenting National Park. It is feasible for discussing the above issue by using satellite images, and different classified methods to get different classified accuracy. Although the spatial resolution of IKONOS is higher than SPOT, it is contrary to get lower classified accuracy by omission and commission. Moreover, there are discrepancies between different vegetation types in spectrum characterlstics, so it needs to improve the accuracy of classification further. Good training area and proper methods can improve the accuracy of classification. But owing to the atmospheric effects, the topographic effects, and the overlap of spectrum characteristics in different categories, the classified accuracy of satellite images were always to be influenced. Therefore, if this problem can be solved effectively, the results of images classification will be usefulness. |
| Keywords: | remote sensing classified accuracy spectrum characteristics |
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