Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents
文献类型：期刊论文
| 作者 | Li, Wang; Niu, Zheng; Sun, Gang; Gao, Shuai; Wu, Mingquan |
| 刊名 | Optics Express
 |
| 出版日期 | 2016 |
| 卷号 | 24期号:5页码:4771-4785 |
| 关键词 | LEAF-AREA INDEX CROP SURFACE MODELS FORM LIDAR DATA VEGETATION INDEXES POINT CLOUDS FOREST INVENTORY AIRBORNE LIDAR USE EFFICIENCY UAV CORN |
| 英文摘要 | Hyperspectral light detection and ranging (HSL) is a newly developed active remote sensing technique. In this study, we firstly presented an improved hyperspectral full-waveform LiDAR system with 32 detection channels. Then, the quality of the data collected from two types of leaves by this system was evaluated using signal to noise ratio. Two different reflective factors that can describe the backscatter capability of detected targets were developed based on the HSL data. Hundreds of vegetation indices (VIs) were calculated through a full search for the possible combination of the reflective factors at near-infrared and visible wavelengths. Finally, the high-dimensional VIs (n = 998) were used to estimate three leaf biochemical contents using principle component regression (PCR) models with cross validation. Results showed that high correlations were found between leaf biochemical contents and the HSLderived VIs at shorter visible wavelengths. The prediction of biochemical contents obtained satisfactory results with a root mean squared error of 0.45% for nitrogen content (R2= 0.71), 1.41 mgg-1for chlorophylla/b content (R2= 0.83), and 0.38 mgg-1for carotenoid content (R2= 0.77), respectively. To conclude, the improved HSL system showed great potential for the remote estimation of vegetation biochemical contents, which will significantly extend the scope of quantitative remote sensing with vegetation. © 2016 Optical Society of America. |
| 学科主题 | Optics |
| 类目[WOS] | Optics |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20161502208204 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39199]  |
| 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 | State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Li, Wang,Niu, Zheng,Sun, Gang,et al. Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents[J]. Optics Express,2016,24(5):4771-4785. |
| APA | Li, Wang,Niu, Zheng,Sun, Gang,Gao, Shuai,&Wu, Mingquan.(2016).Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents.Optics Express,24(5),4771-4785. |
| MLA | Li, Wang,et al."Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents".Optics Express 24.5(2016):4771-4785. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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