On-orbit noise characterization of MODIS reflective solar bands

Amit Angal; Xiaoxiong J. Xiong; Junqiang Sun; Xu Geng

doi:10.1117/1.JRS.9.094092

6 October 2015 On-orbit noise characterization of MODIS reflective solar bands

Amit Angal, Xiaoxiong J. Xiong, Junqiang Sun, Xu Geng

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 094092 (October 2015). https://doi.org/10.1117/1.JRS.9.094092

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS), launched on the Terra and Aqua spacecrafts, was designed to collect complementary and comprehensive measurements of the Earth’s properties on a global scale. The 20 reflective solar bands (RSBs), covering a wavelength range from 0.41 to 2.1 μm, are calibrated on-orbit using regularly scheduled solar diffuser (SD) observations. Although primarily used for on-orbit gain derivation, the SD observations also facilitate the characterization of the detector signal-to-noise ratio (SNR). In addition to the calibration requirement of 2% for the reflectance factors and 5% for the radiances, the required SNRs are also specified for all RSB at their typical scene radiances. A methodology to characterize the on-orbit SNR for the MODIS RSB is presented. Overall performance shows that a majority of the RSB continue to meet the specification, therefore performing well. A temporal decrease in the SNR, observed in the short-wavelength bands, is attributed primarily to the decrease in their detector responses. With the exception of the inoperable and noisy detectors in band 6 identified prelaunch, the detectors of Aqua MODIS RSB perform better than Terra MODIS. The approach formulated for on-orbit SNR characterization can also be used by other sensors that use on-board SDs for their on-orbit calibration (e.g., Suomi National Polar-Orbiting Partnership [SNPP]-Visible Infrared Imaging Radiometer Suite).

Citation Download Citation

Amit Angal, Xiaoxiong J. Xiong, Junqiang Sun, and Xu Geng "On-orbit noise characterization of MODIS reflective solar bands," Journal of Applied Remote Sensing 9(1), 094092 (6 October 2015). https://doi.org/10.1117/1.JRS.9.094092

Published: 6 October 2015

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