Segmentation-based and rule-based spectral mixture analysis for estimating urban imperviousness
文献类型：期刊论文
| 作者 | Li, Miao1; Zang, Shuying1; Wu, Changshan1; Deng, Yingbin1 |
| 刊名 | ADVANCES IN SPACE RESEARCH
 |
| 出版日期 | 2015 |
| 卷号 | 55期号:5页码:834-846 |
| 关键词 | Linear spectral mixture analysis Segmentation-based analysis Rule-based analysis Urban imperviousness |
| 通讯作者 | Li, M (reprint author), Harbin Normal Univ, Key Lab Remote Sensing Monitoring Geog Environm, Coll Heilongjiang Prov, Harbin 150025, Peoples R China. |
| 英文摘要 | For detailed estimation of urban imperviousness, numerous image processing methods have been developed, and applied to different urban areas with some success. Most of these methods, however, are global techniques. That is, they have been applied to the entire study area without considering spatial and contextual variations. To address this problem, this paper explores whether two spatio-contextual analysis techniques, namely segmentation-based and rule-based analysis, can improve urban imperviousness estimation. These two spatio-contextual techniques were incorporated to a classic urban imperviousness estimation technique, fully-constrained linear spectral mixture analysis (FCLSMA) method. In particular, image segmentation was applied to divide the image to homogenous segments, and spatially varying endmembers were chosen for each segment. Then an FCLSMA was applied for each segment to estimate the pixel-wise fractional coverage of high-albedo material, low-albedo material, vegetation, and soil. Finally, a rule-based analysis was carried out to estimate the percent impervious surface area (%ISA). The developed technique was applied to a Landsat TM image acquired in Milwaukee River Watershed, an urbanized watershed in Wisconsin, United States. Results indicate that the performance of the developed segmentation-based and rule-based LSMA (S-R-LSMA) outperforms traditional SMA techniques, with a mean average error (MAE) of 5.44% and R-2 of 0.88. Further, a comparative analysis shows that, when compared to segmentation, rule-based analysis plays a more essential role in improving the estimation accuracy. (C) 2014 COSPAR. Published by Elsevier Ltd. All rights reserved. |
| 研究领域[WOS] | Astronomy & Astrophysics ; Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000349727800004 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38472]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Li, Miao 2.Zang, Shuying] Harbin Normal Univ, Key Lab Remote Sensing Monitoring Geog Environm, Coll Heilongjiang Prov, Harbin 150025, Peoples R China 3.[Wu, Changshan] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China 4.[Wu, Changshan 5.Deng, Yingbin] Univ Wisconsin, Dept Geog, Milwaukee, WI 53201 USA |
| 推荐引用方式 GB/T 7714 | Li, Miao,Zang, Shuying,Wu, Changshan,et al. Segmentation-based and rule-based spectral mixture analysis for estimating urban imperviousness[J]. ADVANCES IN SPACE RESEARCH,2015,55(5):834-846. |
| APA | Li, Miao,Zang, Shuying,Wu, Changshan,&Deng, Yingbin.(2015).Segmentation-based and rule-based spectral mixture analysis for estimating urban imperviousness.ADVANCES IN SPACE RESEARCH,55(5),834-846. |
| MLA | Li, Miao,et al."Segmentation-based and rule-based spectral mixture analysis for estimating urban imperviousness".ADVANCES IN SPACE RESEARCH 55.5(2015):834-846. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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