Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images
文献类型：期刊论文
| 作者 | Yang, Zhi1; Li, Kun1; Shao, Yun1; Brisco, Brian1; Liu, Long1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2016 |
| 卷号 | 8期号:10 |
| 关键词 | REMOTE-SENSING IMAGES IMPERVIOUS SURFACE ESTIMATION SAR IMAGES LAND-COVER LACUNARITY FUSION |
| 通讯作者 | Li, K (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth RADI, Datun Rd, Beijing 100094, Peoples R China. |
| 英文摘要 | Rice growth monitoring is very important as rice is one of the staple crops of the world. Rice variables as quantitative indicators of rice growth are critical for farming management and yield estimation, and synthetic aperture radar ( SAR) has great advantages for monitoring rice variables due to its all-weather observation capability. In this study, eight temporal RADARSAT-2 full-polarimetric SAR images were acquired during rice growth cycle and a modified water cloud model ( MWCM) was proposed, in which the heterogeneity of the rice canopy in the horizontal direction and its phenological changes were considered when the double-bounce scattering between the rice canopy and the underlying surface was firstly considered as well. Then, three scattering components from an improved polarimetric decomposition were coupled with the MWCM, instead of the backscattering coefficients. Using a genetic algorithm, eight rice variables were estimated, such as the leaf area index ( LAI), rice height ( h), and the fresh and dry biomass of ears ( F-e and D-e). The accuracy validation showed the MWCM was suitable for the estimation of rice variables during the whole growth season. The validation results showed that the MWCM could predict the temporal behaviors of the rice variables well during the growth cycle ( R-2 > 0.8). Compared with the original water cloud model ( WCM), the relative errors of rice variables with the MWCM were much smaller, especially in the vegetation phase ( approximately 15% smaller). Finally, it was discussed that the MWCM could be used, theoretically, for extensive applications since the empirical coefficients in the MWCM were determined in general cases, but more applications of the MWCM are necessary in future work. |
| 学科主题 | Remote Sensing |
| 类目[WOS] | Remote Sensing |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000387357300092 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39223]  |
| 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.Chinese Acad Sci, Inst Remote Sensing & Digital Earth RADI, Datun Rd, Beijing 100094, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Yuquan Rd, Beijing 100049, Peoples R China 3.Nat Resources Canada, Earth Sci Sect, Earth Observat & Geosolut Div EOGD, Canada Ctr Remote Sensing, Ottawa, ON K1S 4M2, Canada |
| 推荐引用方式 GB/T 7714 | Yang, Zhi,Li, Kun,Shao, Yun,et al. Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images[J]. REMOTE SENSING,2016,8(10). |
| APA | Yang, Zhi,Li, Kun,Shao, Yun,Brisco, Brian,&Liu, Long.(2016).Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images.REMOTE SENSING,8(10). |
| MLA | Yang, Zhi,et al."Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images".REMOTE SENSING 8.10(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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