Analysis and Optimization of the MODIS Leaf Area Index Algorithm Retrievals Over Broadleaf Forests

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dc.contributor.author Shabanov, Nikolay en_US
dc.contributor.author Huang, Dong en_US
dc.contributor.author Yang, Wenze en_US
dc.contributor.author Tan, Bin en_US
dc.contributor.author Knyazikhin, Yuri en_US
dc.contributor.author Myneni, Ranga en_US
dc.contributor.author Ahl, Douglas en_US
dc.contributor.author Gower, Stith en_US
dc.contributor.author Huete, Alfredo en_US
dc.contributor.author Aragao, Luiz en_US
dc.contributor.author Shimabukuro, Yosio en_US
dc.contributor.editor en_US
dc.date.accessioned 2010-05-28T09:43:49Z
dc.date.available 2010-05-28T09:43:49Z
dc.date.issued 2005 en_US
dc.identifier 2009001369 en_US
dc.identifier.citation Shabanov Nikolay et al. 2005, 'Analysis and Optimization of the MODIS Leaf Area Index Algorithm Retrievals Over Broadleaf Forests', IEEE, vol. 43, no. 8, pp. 1855-1865. en_US
dc.identifier.issn 0196-2892 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/8533
dc.description.abstract Broadleaf forest is a major type of Earth's land cover with the highest observable vegetation density. Retrievals of biophysical parameters, such as leaf area index (LAI), of broadleaf forests at global scale constitute a major challenge to modern remote sensing techniques in view of low sensitivity (saturation) of surface reflectances to such parameters over dense vegetation. The goal of the performed research is to demonstrate physical principles of LAI retrievals over broadleaf forests with the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI algorithm and to establish a basis for algorithm refinement. To sample natural variability in biophysical parameters of broadleaf forests, we selected MODIS data subsets covering deciduous broadleaf forests of the eastern part of North America and evergreen broadleaf forests of Amazonia. The analysis of an annual course of the Terra MODIS Collection 4 LAI product over broadleaf forests indicated a low portion of best quality main radiative transfer-based algorithm retrievals and dominance of low-reliable backup algorithm retrievals during the growing season. en_US
dc.language en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/TGRS.2005.852477 en_US
dc.title Analysis and Optimization of the MODIS Leaf Area Index Algorithm Retrievals Over Broadleaf Forests en_US
dc.parent IEEE Transactions on Geoscience and Remote Sensing en_US
dc.journal.volume 43 en_US
dc.journal.number 8 en_US
dc.publocation United States en_US
dc.identifier.startpage 1855 en_US
dc.identifier.endpage 1865 en_US
dc.cauo.name SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 090900 en_US
dc.personcode 0000058710 en_US
dc.personcode 0000058711 en_US
dc.personcode 0000058712 en_US
dc.personcode 0000058713 en_US
dc.personcode 0000058714 en_US
dc.personcode 0000058715 en_US
dc.personcode 0000058716 en_US
dc.personcode 0000058717 en_US
dc.personcode 108636 en_US
dc.personcode 0000058718 en_US
dc.personcode 0000058719 en_US
dc.percentage 100 en_US
dc.classification.name Geomatic Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords South America ; North America ; Amazonia ; surface properties ; stochastic processes ; cycles ; seasonal variations ; accuracy ; simulation ; models ; anomalies ; quality ; wavelength ; refinement ; reflectance ; saturation ; Space remote sensing ; vegetation ; density ; land cover ; forests ; algorithms ; optimization ; en_US


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