Estimating Winter Wheat Leaf Area Index from Ground and Hyperspectral Observations Using Vegetation Indices
文献类型：期刊论文
| 作者 | Xie, Qiaoyun1; Huang, Wenjiang1; Zhang, Bing1; Chen, Pengfei1; Song, Xiaoyu1; Pascucci, Simone1; Pignatti, Stefano1; Laneve, Giovanni1; Dong, Yingying1 |
| 刊名 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
 |
| 出版日期 | 2016 |
| 卷号 | 9期号:2页码:771-780 |
| 关键词 | REMOTE-SENSING DATA VEGETATION INDEXES SPATIAL ASSOCIATION SPECTRAL INDEXES PLANT-LEAVES REFLECTANCE CHLOROPHYLL CANOPY FOREST LEAF |
| 英文摘要 | Growing numbers of studies have focused on evaluating the ability of vegetation indices (VIs) to predict biophysical parameters such as leaf area index (LAI) and chlorophyll. In this study, empirical models were used to estimate winter wheat LAI based on three spectral indices [the normalized difference vegetation index (NDVI), the modified simple ratio index (MSR), and the modified soil-Adjusted vegetation index (MSAVI)], and three band-selection approaches (the conventional approach, the red edge approach, and the best correlated approach), which were used to calculate VIs. The aim was to enhance the relationships between the indices and LAI values by improving the band-selection approaches so as to produce a suitable VI for winter wheat LAI estimation. Using hyperspectral airborne data and ground-measured spectra as well as ground LAI measurements collected during two field campaigns, winter wheat LAIs were estimated and validated using different VIs calculated by different band combinations. Our results showed that the MSAVI provided the best LAI estimations when using ground measured spectra with \textR2over 0.74 and RMSE less than 0.98. The NDVI provided the most robust estimation results across different sites, years, and sensors, although it was not adequate for LAI estimation of moderately dense canopies due to the saturation that occurred when \textLAI> 3. The MSR demonstrated more severe scattering and lower predictive accuracy than the NDVI and, therefore, was not a perfect solution to the saturation issue. In addition, it was also shown that the best correlated approach improved the predictive power of the indices and revealed the importance of red edge bands for LAI estimation; meanwhile, the red edge approach (based on the reflectance at 705 and 750 nm) was not always superior to the conventional approach (based on the reflectance at 670 and 800 nm). The results were promising and should facilitate the use of VIs in crop LAI measurements. © 2008-2012 IEEE. |
| 学科主题 | Engineering; Physical Geography; Remote Sensing; Imaging Science & Photographic Technology |
| 类目[WOS] | Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20154401478946 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39282]  |
| 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 Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China 2. University of Chinese Academy of Sciences, Beijing, China 3. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Science and Natural Resources, Research of Chinese Academy of Sciences, Beijing, China 4. Beijing Research Center for Information Technology in Agriculture, Beijing, China 5. Institute of Methodologies for Environmental Analysis, National Research Council of Italy, Rome, Italy 6. Department of Astronautics, Electrics and Energetic, Sapienza University of Rome, Rome, Italy |
| 推荐引用方式 GB/T 7714 | Xie, Qiaoyun,Huang, Wenjiang,Zhang, Bing,et al. Estimating Winter Wheat Leaf Area Index from Ground and Hyperspectral Observations Using Vegetation Indices[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2016,9(2):771-780. |
| APA | Xie, Qiaoyun.,Huang, Wenjiang.,Zhang, Bing.,Chen, Pengfei.,Song, Xiaoyu.,...&Dong, Yingying.(2016).Estimating Winter Wheat Leaf Area Index from Ground and Hyperspectral Observations Using Vegetation Indices.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,9(2),771-780. |
| MLA | Xie, Qiaoyun,et al."Estimating Winter Wheat Leaf Area Index from Ground and Hyperspectral Observations Using Vegetation Indices".IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9.2(2016):771-780. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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