Hot dark spot index method based on multi-angular remote sensing for leaf area index retrieval
文献类型：期刊论文
| 作者 | Meng, Qingyan1; Wang, Chunmei1; Gu, Xingfa1; Sun, Yunxiao1; Zhang, Ying1; Vatseva, Rumiana1; Jancso, Tamas1 |
| 刊名 | Environmental Earth Sciences
 |
| 出版日期 | 2016 |
| 卷号 | 75期号:9 |
| 关键词 | SOCIAL FORCE MODEL CROWD DYNAMICS ESCAPE |
| 通讯作者 | Meng, Qingyan (mengqy@radi.ac.cn) |
| 英文摘要 | Leaf area index (LAI) is an important parameter of vegetation ecosystems for crop monitoring and yield estimations. To resolve the ‘saturation phenomenon’ and develop an ideal LAI retrieval model for Chinese satellite HJ-1 CCD data, a hot dark spot (HDS) index method based on multi-angular remote sensing was investigated in this study. Experiments were conducted to obtain in situ measured spectral reflectance and LAI data. An effective vegetation index, HJVI, was put forward according to the unique characteristics of HJ-1 CCD bands. This index alleviated the vegetation index saturation phenomenon based on the ratio of the red bands to near-infrared bands. The canopy HDSs of winter wheat were simulated for different growth stages using the PROSAIL model and the HDS indices were calculated for different bands. The HDS_HJVI was then developed using an HDS of 865 nm, which was the most sensitive to LAI retrieval (R2 = 0.9953). HDS_HJVI was shown to be more sensitive to LAI than NDVI, HDS_NDVI, and HJVI. Thus, the LAI was retrieved using the HDS_HJVI index model and validated with the measured data (R2 = 0.8622 and 0.8512, respectively). Overall, these results indicate that the HDS index method based on multi-angular remote sensing is effective and can serve as a reference for other relative quantitative retrieval research. © 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:20161802326266 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39305]  |
| 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. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China 2. National Institute of Geophysics, Geodesy and Geography, Bulgarian Academy of Sciences, Sofia, Bulgaria 3. Alba Regia Technical Faculty, Obuda University, Budai ut 45, Szekesfehervar, Hungary |
| 推荐引用方式 GB/T 7714 | Meng, Qingyan,Wang, Chunmei,Gu, Xingfa,et al. Hot dark spot index method based on multi-angular remote sensing for leaf area index retrieval[J]. Environmental Earth Sciences,2016,75(9). |
| APA | Meng, Qingyan.,Wang, Chunmei.,Gu, Xingfa.,Sun, Yunxiao.,Zhang, Ying.,...&Jancso, Tamas.(2016).Hot dark spot index method based on multi-angular remote sensing for leaf area index retrieval.Environmental Earth Sciences,75(9). |
| MLA | Meng, Qingyan,et al."Hot dark spot index method based on multi-angular remote sensing for leaf area index retrieval".Environmental Earth Sciences 75.9(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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