Abstract
Modern satellite radiometers have many detectors with different relative spectral response (RSR). Effect of RSR differences on striping and the root cause of striping in sensor data record (SDR) radiance and brightness temperature products have not been well studied. A previous study used MODTRAN radiative transfer model (RTM) to analyze striping. In this study, we make efforts to find the possible root causes of striping. Line-by-Line RTM (LBLRTM) is used to evaluate the effect of RSR difference on striping and the atmospheric dependency for VIIRS bands M15 and M16. The results show that previous study using MODTRAN is repeatable: the striping is related to the difference between band-averaged and detector-level RSR, and the BT difference has some atmospheric dependency. We also analyzed VIIRS earth view (EV) data with several striping index methods. Since the EV data is complex, we further analyze the onboard calibration data. Analysis of Variance (ANOVA) test shows that the noise along track direction is the major reason for striping. We also found evidence of correlation between solar diffuser (SD) and blackbody (BB) for detector 1 in M15. Digital Count Restoration (DCR) and detector instability are possibly related to the striping in SD and EV data, but further analysis is needed. These findings can potentially lead to further SDR processing improvements.
Highlights
Suomi National Polar Orbiting Partnership (S-NPP) spacecraft was successfully launched on 28 October 2011 with the Visible Infrared Imaging Radiometer Suite (VIIRS), which provides capacities for operational environmental remote sensing for weather, climate and other environmental applications
It is noted that the results from Line-by-Line RTM (LBLRTM) is similar to those in a previous study with MODTRAN [4]
We found that V ratio between scans is much larger than that between samples for both of M15 and M16, which means that the variation between scans is one of the major reasons for the striping observed in VIIRS imagery
Summary
Suomi National Polar Orbiting Partnership (S-NPP) spacecraft was successfully launched on 28 October 2011 with the Visible Infrared Imaging Radiometer Suite (VIIRS), which provides capacities for operational environmental remote sensing for weather, climate and other environmental applications. In contrast to conventional imaging radiometers [1], a single scan for VIIRS M bands (16 detectors aligned in the along-track direction) has a slower scan rate than that of the traditional single detector, the spatial resolution is enhanced without losing the signal-to-noise (SNR). An anomalous striping pattern has been observed in SNPP VIIRS sea surface temperature products [2,3,4]. These striping are assumed to be caused by differences in the detector-level RSR. SST EDR team developed an adaptive destriping algorithm to improve the operational SST imagery, but this destriping algorithm does not solve the Remote Sens. 2016, 8, 145; doi:10.3390/rs8020145 www.mdpi.com/journal/remotesensing
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