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http://dx.doi.org/10.7780/kjrs.2015.31.2.9

A comparative study for reconstructing a high-quality NDVI time series data derived from MODIS surface reflectance  

Lee, Jihye (Department of Environmental Science, Kangwon National University)
Kang, Sinkyu (Department of Environmental Science, Kangwon National University)
Jang, Keunchang (Department of Agriculture Environment, National Academy of Agricultural Science)
Hong, Suk Young (Department of Agriculture Environment, National Academy of Agricultural Science)
Publication Information
Korean Journal of Remote Sensing / v.31, no.2, 2015 , pp. 149-160 More about this Journal
Abstract
A comparative study was conducted for alternative consecutive procedures of detection of cloud-contaminated pixels and gap-filling and smoothing of time-series data to produce high-quality gapless satellite vegetation index (i.e. Normalized Difference Vegetation Index, NDVI). Performances of five alternative methods for detecting cloud contaminations were tested with ground-observed cloudiness data. The data gap was filled with a simple linear interpolation and then, it was applied two alternative smoothing methods (i.e. Savitzky-Golay and Wavelet transform). Moderate resolution imaging spectroradiometer (MODIS) data were used in this study. Among the alternative cloud detection methods, a criterion of MODIS Band 3 reflectance over 10% showed best accuracy with an agreement rate of 85%, which was followed by criteria of MODIS Quality assessment (82%) and Band 3 reflectance over 20% (81%), respectively. In smoothing process, the Savitzky-Golay filter was better performed to retain original NDVI patterns than the wavelet transform. This study demonstrated an operational framework of gapdetection, filling, and smoothing to produce high-quality satellite vegetation index.
Keywords
MODIS; Cloud; NDVI time series; Savitzky-Golay filter; Wavelet transform;
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Times Cited By KSCI : 3  (Citation Analysis)
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