Geography Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1641

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Author: search.filters.author.Fang, HongliangSubject: search.filters.subject.LAI

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    Retrieving Leaf Area Index With a Neural Network Method: Simulation and Validation
    (Institute of Electrical and Electronics Engineers, 2003-09) Liang, Shunlin; Fang, Hongliang
    Leaf area index () is a crucial biophysical parameter that is indispensable for many biophysical and climatic models. A neural network algorithm in conjunction with extensive canopy and atmospheric radiative transfer simulations is presented in this paper to estimateLAIfromLandsat-7 Enhanced ThematicMapper Plus data. Two schemes were explored; the first was based on surface reflectance, and the second on top-of-atmosphere (TOA) radiance. The implication of the second scheme is that atmospheric corrections are not needed for estimating the surface LAI. A soil reflectance index (SRI) was proposed to account for variable soil background reflectances. Ground-measured LAI data acquired at Beltsville, MD were used to validate both schemes. The results indicate that both methods can be used to estimate LAI accurately. The experiments also showed that the use of SRI is very critical.
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    Estimation and Validation of Land Surface Broadband Albedos and Leaf Area Index From EO-1 ALI Data
    (Institute of Electrical and Electronics Engineers, 2003-06) Liang, Shunlin; Fang, Hongliang; Kaul, Monisha; Van Niel, Tom G.; McVicar, Tim R.; Pearlman, Jay S.; Huemmrich, Karl Fred; Walthall, Charles L.; Daughtry, Craig S. T.
    The Advanced Land Imager (ALI) is a multispectral sensor onboard the National Aeronautics and Space Administration Earth Observing 1 (EO-1) satellite. It has similar spatial resolution to Landsat-7 Enhanced Thematic Mapper Plus (ETM+), with three additional spectral bands. We developed new algorithms for estimating both land surface broadband albedo and leaf area index (LAI) from ALI data. A recently developed atmospheric correction algorithm for ETM+ imagery was extended to retrieve surface spectral reflectance from ALI top-of-atmosphere observations. A feature common to these algorithms is the use of new multispectral information from ALI. The additional blue band of ALI is very useful in our atmospheric correction algorithm, and two additional ALI near-infrared bands are valuable for estimating both broadband albedo and LAI. Ground measurements at Beltsville, MD, and Coleambally, Australia, were used to validate the products generated by these algorithms.