Geography Research Works

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

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Author: search.filters.author.Chen, MingzhenEnd date: 2009

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    Atmospheric Correction of Landsat ETM+ Land Surface Imagery—Part I: Methods
    (Institute of Electrical and Electronics Engineers, 2001-11) Liang, Shunlin; Fang, Hongliang; Chen, Mingzhen
    To extract quantitative information from the Enhanced Thematic Mapper-Plus (ETM+) imagery accurately, atmospheric correction is a necessary step. After reviewing historical development of atmospheric correction of Landsat thematic mapper (TM) imagery, we present a new algorithm that can effectively estimate the spatial distribution of atmospheric aerosols and retrieve surface reflectance from ETM+ imagery under general atmospheric and surface conditions. This algorithm is therefore suitable for operational applications. A new formula that accounts for adjacency effects is also presented. Several examples are given to demonstrate that this new algorithm works very well under a variety of atmospheric and surface conditions. The companion paper will validate this method using ground measurements, and illustrate the improvements of several applications due to atmospheric correction.
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    Atmospheric Correction of Landsat ETM+ Land Surface Imagery: II. Validation and Applications
    (Institute of Electrical and Electronics Engineers, 2002) Liang, Shunlin; Morisette, Jeffrey T.; Fang, Hongliang; Chen, Mingzhen; Shuey, Chad J.; Daughtry, Craig S. T.; Walthall, Charles L.
    This is the second paper of the series on atmospheric correction of ETM+ land surface imagery. In the first paper, a new algorithm that corrects heterogeneous aerosol scattering and surface adjacency effects was presented. In this study, our objectives are to 1) evaluate the accuracy of this new atmospheric correction algorithm using ground radiometric measurements; 2) apply this algorithm to correct MODIS and SeaWiFS imagery; and 3) demonstrate how much atmospheric correction of ETM+ imagery can improve land cover classification, change detection, and broadband albedo calculations. Validation results indicate that this new algorithm can retrieve surface reflectance from ETM+ imagery accurately. All experimental cases demonstrate that this algorithm can be used for correcting both MODIS and SeaWiFS imagery. Although more tests and validation exercises are needed, it has been proven promising to correct different multispectral imagery operationally. We have also demonstrated that atmospheric correction does matter.