Remote Sensing | |
Extracting Leaf Area Index by Sunlit Foliage Component from Downward-Looking Digital Photography under Clear-Sky Conditions | |
Yelu Zeng1  Jing Li1  Qinhuo Liu1  Ronghai Hu1  Xihan Mu1  Weiliang Fan1  Baodong Xu1  Gaofei Yin1  Shengbiao Wu1  Alfredo R. Huete2  | |
[1] State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20A, Datun Road, Beijing 100101, China; E-Mails:State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20A, Datun Road, Beijing 100101, China; | |
关键词: leaf area index; near-surface remote sensing; digital photography; gap fraction; clumping index; sunlit foliage component; clear-sky conditions; | |
DOI : 10.3390/rs71013410 | |
来源: mdpi | |
【 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
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190005006ZK.pdf | 1994KB | download |