| 光谱学与光谱分析 |
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| New Vegetation Index Fusing Visible-Infrared and Shortwave Infrared Spectral Feature for Winter Wheat LAI Retrieval |
| LI Xin-chuan1,2,3, BAO Yan-song3, XU Xin-gang1,2*, JIN Xiu-liang1,2, ZHANG Jing-cheng1,2, SONG Xiao-yu1,2 |
1. Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Science, Beijing 100097, China
2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
3. School of Atmosphere Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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Abstract Considering the great relationships between shortwave infrared (SWIR) and leaf area index (LAI), innovative indices based on water vegetation indices and visible-infrared vegetation indices were presented. In the present work, PROSAIL model was used to study the saturation sensitivity of new vegetation indices to LAI. The estimate models about LAI of winter wheat were built on the basis of the experiment data in 2009 acting as train sample and their precisions were evaluated and tested on the basis of the experiment data in 2008. Ten visible-infrared vegetation indices and five water vegetation indices were used to construct new indices. The result showed that newly developed indices have significant relationships with LAI by numerical simulations and in-situ measurements. In particular, by implementing modified standardized LAI Determining Index(sLAIDI*), all new indices were neither sensitive to water variations nor affected by saturation at high LAI levels. The evaluation models could improve prediction accuracy and have well reliability for LAI retrieval. The result indicated that visible-infrared vegetation indices combined with water index have greater advantage for LAI estimation.
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Received: 2013-01-07
Accepted: 2013-02-20
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Corresponding Authors:
XU Xin-gang
E-mail: xxgpaper@126.com
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