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The development of statistical methods for retrieving MODIS missing data: Mean bias, regressions analysis and local variation method  

Kim, Min Wook ((주)에스이랩 부설연구소)
Yi, Jonghyuk ((주)에스이랩)
Park, Yeon Gu ((주)에스이랩)
Song, Junghyun ((주)에스이랩)
Publication Information
Journal of Satellite, Information and Communications / v.11, no.4, 2016 , pp. 94-101 More about this Journal
Abstract
Satellite data for remote sensing technology has limitations, especially with visible range sensor, cloud and/or other environmental factors cause missing data. In this study, using land surface temperature data from the MODerate resolution Imaging Spectro-radiometer(MODIS), we developed retrieving methods for satellite missing data and developed three methods; mean bias, regression analysis and local variation method. These methods used the previous day data as reference data. In order to validate these methods, we selected a specific measurement ratio using artificial missing data from 2014 to 2015. The local variation method showed low accuracy with root mean square error(RMSE) more than 2 K in some cases, and the regression analysis method showed reliable results in most cases with small RMSE values, 1.13 K, approximately. RMSE with the mean bias method was similar to RMSE with the regression analysis method, 1.32 K, approximately.
Keywords
Satellite missing data; MODIS data; Reconstruction method;
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