Global clear sky near-surface imagery from multiple satellite daily imagery time series

被引:6
作者
Mikelsons, Karlis [1 ,2 ]
Wang, Menghua [1 ]
机构
[1] NOAA Natl Environm Satellite, Data & Informat Serv, Ctr Satellite Applicat & Res, E-RA3,5830 Univ Res Court, College Pk, MD 20740 USA
[2] Global Sci & Technol Inc, Greenbelt, MD 20770 USA
关键词
Remote sensing; Surface feature; True color; False color; VIIRS; Sentinel-3; OLCI; Landsat; CLOUD SHADOW; THICK CLOUD; COLOR; OCEAN; REMOVAL; RECONSTRUCTION; REGRESSION; ALGORITHM; MODIS;
D O I
10.1016/j.isprsjprs.2021.08.013
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
We develop a new statistically-robust adaptive regression method (SARM) to extract clear sky true color imagery, approximating the near-surface imagery, derived from multiple satellite daily imagery time series, while avoiding artifacts due to clouds and cloud shadows. We compare the SARM-derived near-surface imagery against simpler approaches for various surface types, and perform a quantitative evaluation. Existing mapped daily imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20, and the Ocean and Land Colour Instrument (OLCI) on the Sentinel-3A and Sentinel-3B satellites is used to produce global clear sky near-surface imagery over various time intervals. We provide several examples of satellite-derived clear sky near-surface imagery over various regions to show potential applications. In addition, we apply this new method to derive clear sky near-surface imagery using higher spatial resolution Landsat-8 data, and discuss characteristics and limitations of our approach. The clear sky near-surface imagery is a useful satellite-derived product, representing the human perception of Earth's near-surface features, which can be more directly interpreted and easily understood by the general public, and aids visualization and interpretation of various types of satellite derived data.
引用
收藏
页码:238 / 254
页数:17
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