Applying spectral mixture analysis for large-scale sub-pixel impervious cover estimation based on neighbourhood-specific endmember signature generation
文献类型：期刊论文
| 作者 | Zhang, Zhang1; Liu, Chong1; Luo, Jiancheng1; Shen, Zhanfeng1; Shao, Zhenfeng1 |
| 刊名 | REMOTE SENSING LETTERS
 |
| 出版日期 | 2015 |
| 卷号 | 6期号:1页码:354-370 |
| 通讯作者 | Liu, C (reprint author), Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China. |
| 英文摘要 | Spectral mixture analysis (SMA) has been extensively adopted in estimating sub-pixel impervious surface fractions. As a key step of SMA, endmember extraction has a big impact on the reliability of unmixing result. Due to the difficulty in extracting spectrally pure pixels using traditional methods, SMA is seldom applied to coarse-resolution imagery. A promising strategy to overcome this challenge is to synthesize endmember signatures via generalized least squares solution (LSS) technique with known fractions of samples. However, this method yields constant endmember spectra across the entire image extent, indicating a potential over simplification of spatial heterogeneity. As such, in this study we developed a neighbourhood-specific endmember signature generation method to derive spatially variable endmember signatures using geographically weighted regression technique. According to our investigation results, the developed method performed well in mapping fractional imperviousness with a single date Moderate Resolution Imaging Spectroradiometer imagery and exhibited relatively high estimation accuracy (root mean square error of 10.98%, mean absolute error of 8.45% and bias of 0.25%) compared with the generalized LSS method. |
| 研究领域[WOS] | Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000356223300001 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38316]  |
| 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.[Zhang, Zhang 2.Luo, Jiancheng 3.Shen, Zhanfeng] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China 4.[Zhang, Zhang] Univ Chinese Acad Sci, Beijing, Peoples R China 5.[Liu, Chong] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China 6.[Liu, Chong 7.Shao, Zhenfeng] Collaborat Innovat Ctr Geospatial Technol, Wuhan, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Zhang,Liu, Chong,Luo, Jiancheng,et al. Applying spectral mixture analysis for large-scale sub-pixel impervious cover estimation based on neighbourhood-specific endmember signature generation[J]. REMOTE SENSING LETTERS,2015,6(1):354-370. |
| APA | Zhang, Zhang,Liu, Chong,Luo, Jiancheng,Shen, Zhanfeng,&Shao, Zhenfeng.(2015).Applying spectral mixture analysis for large-scale sub-pixel impervious cover estimation based on neighbourhood-specific endmember signature generation.REMOTE SENSING LETTERS,6(1),354-370. |
| MLA | Zhang, Zhang,et al."Applying spectral mixture analysis for large-scale sub-pixel impervious cover estimation based on neighbourhood-specific endmember signature generation".REMOTE SENSING LETTERS 6.1(2015):354-370. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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