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Estimation of forest canopy leaf area index using MODIS, MISR, and LiDAR observations

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Fu Z, Wang JD, Song JL, Zhou HM, Pang Y, Chen BS. Estimation of forest canopy leaf area index using MODIS, MISR, and LiDAR observations.Journal of Applied Remote Sensing, 2011, 5(053530), 10.1117/1.3594171.

文献信息
Type Of Reference JOUR
Title Estimation of forest canopy leaf area index using MODIS, MISR, and LiDAR observations
Authors Fu, Zhuo| Wang, Jindi| Song, Jinling| Zhou, Hongmin| Pang, Yong| Chen, Baisong|
Secondary Title Journal of Applied Remote Sensing
Abstract A new approach for determining the forest leaf area index (LAI) from a geometric-optical model inversion using multisensor observations is developed. For improving the LAI estimate for the forested area on rugged terrain, a priori information on tree height and the spectra of four scene components of a geometric-optical mutual shadowing (GOMS) model are extracted from airborne light-detection and ranging (LiDAR) data and optical remote sensing data with high spatial resolution, respectively. The slope and aspect of the study area are derived from digital elevation model data. These extracted parameters are applied in an inversion to improve the estimates of forest canopy structural parameters in a GOMS model. For the field investigation, a bidirectional reflectance factor data set of needle forest pixels is collected by combining moderate-resolution-imaging–spectroradiometer (MODIS) and multiangle-imaging–spectroradiometer (MISR) multiangular remote sensing observations. Then, forest canopy parameters are inverted based on the GOMS model. Finally, the LAI of the forest canopy of each pixel is estimated from the retrieved structural parameters and validated by field measurements. The results indicate that the accuracy of forest canopy LAI estimates can be improved by combining observations of passive multiangle and active remote sensors.
Date 2011///
Year 2011
DOI 10.1117/1.3594171
Database Provider Silverchair
volume 5
Issue Number 1
Start Page 053530
Alternate Title1 J. Appl. Remote Sens
Issn 1931-3195
Url http://dx.doi.org/10.1117/1.3594171
Access Date 2013/10/04/06:06:14
Keywords LiDAR| MODIS| Reflectivity| remote sensing|
file_attachments2 http://remotesensing.spiedigitallibrary.org/article.aspx?articleid=1182394%20
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