Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Remote Sensing Technology and Application》 2017-01
Add to Favorite Get Latest Update

The Retrieval of Leaf Area Index based on Remote Sensing by Unmanned Aerial Vehicle

Chu Hongliang;Xiao Qing;Bai Junhua;Cheng Juan;State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences;University of Chinese Academy of Sciences;  
Remote sensed leaf area index(LAI)products need the ground measurements for the validation of the product accuracy.The widely used LAI measurement instruments,such as LAI2200,AccuPAR,Sunscan,Demon,TRAC and so on,need manual operations at each sample,which is labor-intensive and timeconsuming.The increasingly widely used automatic wireless sensor networks made significant progress in recent years,while the high technology costs,inconvenience for moving and other factors restrict its further applications.With the rapid development of unmanned aerial vehicles(UAVs),the use of UAVs to collect data is very convenient.Firstly,optical images in the field of corn at high spatial resolution can be obtained by lightweight UAV.Then image processing algorithms are developed to distinguish vegetation and nonvegetation components.Finally,the LAI can be retrieved through the radiative transfer models and aggregation index theory.By the comparison with the data collected by LAI2200 and the true LAI measured by LI-3000 c,the LAI extracted by UAV has a good correlation with them in the pre-mature cornfield.Results suggest that UAV can be used as a fast and accurate means to extract LAI at the regional scale,which is promising to be widely used in the future.
【Fund】: 国家973计划项目“复杂地表遥感辐散射机理及动态建模(2013CB733401)”
【CateGory Index】: S127
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved