| 土地覆盖的图像融合动态监测 |
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| 引用本文： | 罗彩莲,徐涵秋.土地覆盖的图像融合动态监测[J].地球信息科学,2005,7(1):111-115. |
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| 作者姓名： | 罗彩莲 徐涵秋 |
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| 作者单位： | 福州大学环境与资源学院,福州,350002;福州大学环境与资源学院,福州,350002 |
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| 摘 要： | 近20年来,关于图像融合应用分析方法,如HIS,PCS,HPF,SFIM,SVR,Wavelet和Brovey等均有新的进展。本文主要是对不同时相的影像进行融合,如Brovey-融合法将不同时相的TM(1986年7月26日)和ETM+(2000年5月4日)的PAN波段影像进行融合,然后对其采用非监督分类和PCS分析,将两时相的土地覆盖变化区域提取出来。同时将两时相影像,用后分类法进行分类提取出变化区域。研究表明融合法具有快速、简便和准确的特点。
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| 关 键 词： | 影像融合 Brovey融合 主成分分析 非监督分类 动态监测 |
| 收稿时间： | 2004-03-26; |
| 修稿时间： | 2004年3月26日 |
Auto-Detection of Land Cover Changes Based on Satellite Image Fusion Technique |
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| LUO Cailian,XU Hanqiu.Auto-Detection of Land Cover Changes Based on Satellite Image Fusion Technique[J].Geo-information Science,2005,7(1):111-115. |
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| Authors: | LUO Cailian XU Hanqiu |
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| Institution: | College of Environmental and Resources, Fuzhou University, Fuzhou 350002, China |
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| Abstract: | There are many image fusion methods developed in recent years with the development of multi sensor, multi-temporal and multi -spectral remote sensing technologies. Of these, the HIS, PCS, HPF, SFIM, SVR, Wavelet and Brovey fusion methods are widely used. However, the traditional image fusion is a technology that usually merges the images with the same temporal or near temporal data to increase the image spatial resolution and multi -spectral resolution. The fusion image can largely improve the image visualization and increase the classification accuracy when using appropriate image merging technique. However, this paper proposes a merging method that uses different time serial TM/ETM+ images to do image fusion. After this process we can apply the unsupervised classification method and the second principal component method on the resultant fusion image to detect and extract land cover change areas. To evaluate accuracy of the methods, we use post-classification method to classify TM image of 1986 and ETM+ image of 2000, and then extract land cover change areas. After this, the detected results of unsupervised classification and the second component analysis were compared with that detected using the post-classification method. The comparison reveals that the two methods used in this study have much higher accuracy than the post-classification method. The study indicates that these two methods can quickly and efficiently detect land cover changes. |
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| Keywords: | image fusion Brovey fusion principal component analysis unsupervised classification change detection |
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