Extracting Leaf Area Index by Sunlit Foliage Component from Downward-Looking Digital Photography under Clear-Sky Conditions
文献类型：期刊论文
| 作者 | Zeng, Yelu1,2,3,4; Li, Jing1,2,3; Liu, Qinhuo1,2,3; Hu, Ronghai1,2; Mu, Xihan1,2; Fan, Weiliang1,2; Xu, Baodong1,2,4; Yin, Gaofei1,2,5 ; Wu, Shengbiao1,2,4
|
| 刊名 | Remote Sensing
 |
| 出版日期 | 2015-10-01 |
| 卷号 | 7期号:10页码:13410-13435 |
| 关键词 | leaf area index near-surface remote sensing digital photography gap fraction clumping index sunlit foliage component clear-sky conditions |
| ISSN号 | 2072-4292 |
| 通讯作者 | Li, Jing ; Liu, Qinhuo |
| 英文摘要 | The development of near-surface remote sensing requires the accurate extraction of leaf area index (LAI) from networked digital cameras under all illumination conditions. The widely used directional gap fraction model is more suitable for overcast conditions due to the difficulty to discriminate the shaded foliage from the shadowed parts of images acquired on sunny days. In this study, a new LAI extraction method by the sunlit foliage component from downward-looking digital photography under clear-sky conditions is proposed. In this method, the sunlit foliage component was extracted by an automated image classification algorithm named LAB2, the clumping index was estimated by a path length distribution-based method, the LAD and G function were quantified by leveled digital images and, eventually, the LAI was obtained by introducing a geometric-optical (GO) model which can quantify the sunlit foliage proportion. The proposed method was evaluated at the YJP site, Canada, by the 3D realistic structural scene constructed based on the field measurements. Results suggest that the LAB2 algorithm makes it possible for the automated image processing and the accurate sunlit foliage extraction with the minimum overall accuracy of 91.4%. The widely-used finite-length method tends to underestimate the clumping index, while the path length distribution-based method can reduce the relative error (RE) from 7.8% to 6.6%. Using the directional gap fraction model under sunny conditions can lead to an underestimation of LAI by (1.61; 55.9%), which was significantly outside the accuracy requirement (0.5; 20%) by the Global Climate Observation System (GCOS). The proposed LAI extraction method has an RMSE of 0.35 and an RE of 11.4% under sunny conditions, which can meet the accuracy requirement of the GCOS. This method relaxes the required diffuse illumination conditions for the digital photography, and can be applied to extract LAI from downward-looking webcam images, which is expected for the regional to continental scale monitoring of vegetation dynamics and validation of satellite remote sensing products. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Remote Sensing |
| 研究领域[WOS] | Remote Sensing |
| 关键词[WOS] | RADIATIVE-TRANSFER MODEL ; HEMISPHERICAL PHOTOGRAPHY ; BOREAL FORESTS ; CORRECT ESTIMATION ; ANGLE DISTRIBUTION ; CANOPY STRUCTURE ; GAP FRACTION ; NEAR-SURFACE ; REFLECTANCE ; CROPS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000364328600037 |
| 源URL | [http://ir.imde.ac.cn/handle/131551/13840]  |
| 专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
| 作者单位 | 1.Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China 2.Beijing Normal Univ, Beijing 100101, Peoples R China 3.Joint Ctr Global Change Studies, Beijing 100875, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zeng, Yelu,Li, Jing,Liu, Qinhuo,et al. Extracting Leaf Area Index by Sunlit Foliage Component from Downward-Looking Digital Photography under Clear-Sky Conditions[J]. Remote Sensing,2015,7(10):13410-13435. |
| APA | Zeng, Yelu.,Li, Jing.,Liu, Qinhuo.,Hu, Ronghai.,Mu, Xihan.,...&Wu, Shengbiao.(2015).Extracting Leaf Area Index by Sunlit Foliage Component from Downward-Looking Digital Photography under Clear-Sky Conditions.Remote Sensing,7(10),13410-13435. |
| MLA | Zeng, Yelu,et al."Extracting Leaf Area Index by Sunlit Foliage Component from Downward-Looking Digital Photography under Clear-Sky Conditions".Remote Sensing 7.10(2015):13410-13435. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。