A fusion approach of the improved Dubois model and best canopy water retrieval models to retrieve soil moisture through all maize growth stages from Radarsat-2 and Landsat-8 data
文献类型：期刊论文
| 作者 | Meng, Qingyan1; Xie, Qiuxia1; Wang, Chunmei1; Ma, Jianxin1; Sun, Yunxiao1; Zhang, Linlin1 |
| 刊名 | Environmental Earth Sciences
 |
| 出版日期 | 2016 |
| 卷号 | 75期号:20 |
| 关键词 | HEMISPHERICAL PHOTOGRAPHY DIGITAL PHOTOGRAPHY ANGLE DISTRIBUTION INCLINATION RETRIEVAL STANDS CROPS LAI |
| 通讯作者 | Wang, Chunmei (wangcm@radi.ac.cn) |
| 英文摘要 | Soil moisture (SM) retrieval from synthetic aperture radar data in maize fields is a challenging process, as the proportion of surface scattering from underlying soil declines with maize growth. The goal of this study was to develop an SM retrieval algorithm from multi-source fusion data, through the sowing (bare soil), jointing, heading and flowering stages. At the sowing stage, the relationship between backscattering simulations based on an integration equation model and impact factors showed that the influence of surface roughness could be reduced by using the co-polarized difference (CPD). Furthermore, the Dubois model was improved by developing a new CPD model. Comparison of measured and estimated SM contents showed that the improved Dubois model (IDubois) was better than the Dubois model, based on root mean square errors (RMSEIDubois = 0.0371, RMSEDubois = 0.0654). At other growth stages, a variety of vegetation indices were simulated by the PROSAIL model for correlation analysis with the equivalent water thickness of maize leaves. The normalized difference water index was found to be the best vegetation index, and the ideal canopy water (CW) retrieval model could be obtained. The best CW retrieval and IDubois models were subsequently used in the water cloud model (WCM) to retrieve SM content in the maize field. The retrieved SM content agreed well with the measured data (RMSEHH = 0.0278, 0.1226, 0.0719, RMSEVV = 0.0346, 0.1809, 0.0723). Overall, these results indicated that the WCM was effective for SM retrieval at some maize growth stages. It was most suitable for estimating SM content at the maize jointing stage. © 2016, Springer-Verlag Berlin Heidelberg. |
| 学科主题 | Environmental Sciences & Ecology; Geology; Water Resources |
| 类目[WOS] | Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20164302943970 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39459]  |
| 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. Key Laboratory of Agri-Informatics, Ministry of Agriculture, Beijing 2.100081, China 3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 4.100101, China 5. Shan Dong University of Science and Technology, Qing Dao 6.266590, China 7. Key Laboratory of Mine Spatial Information and Technology of NAS G, Jiaozuo 8.454003, China |
| 推荐引用方式 GB/T 7714 | Meng, Qingyan,Xie, Qiuxia,Wang, Chunmei,et al. A fusion approach of the improved Dubois model and best canopy water retrieval models to retrieve soil moisture through all maize growth stages from Radarsat-2 and Landsat-8 data[J]. Environmental Earth Sciences,2016,75(20). |
| APA | Meng, Qingyan,Xie, Qiuxia,Wang, Chunmei,Ma, Jianxin,Sun, Yunxiao,&Zhang, Linlin.(2016).A fusion approach of the improved Dubois model and best canopy water retrieval models to retrieve soil moisture through all maize growth stages from Radarsat-2 and Landsat-8 data.Environmental Earth Sciences,75(20). |
| MLA | Meng, Qingyan,et al."A fusion approach of the improved Dubois model and best canopy water retrieval models to retrieve soil moisture through all maize growth stages from Radarsat-2 and Landsat-8 data".Environmental Earth Sciences 75.20(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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