An Efficient Approach for VIIRS RDR to SDR Data Processing

The Visible Infrared Imaging Radiometer Suite (VIIRS) Raw Data Records (or Level-0 data) are processed using the current standard Algorithm Development Library (ADL) to produce Sensor Data Records (SDR; or Level-1B data). The ocean color Environmental Data Records (EDR), one of the most important product sets derived from VIIRS, are processed from the SDR of the visible and near-infrared moderate resolution (M) bands. As the ocean color EDR are highly sensitive to the quality of the SDR, the bands from which the EDR data arise must be accurately calibrated. These bands are calibrated on-orbit using the onboard Solar Diffuser, and the derived calibration coefficients are called F-factors. The F-factors used in the forward operational process may have large uncertainty due to various reasons, and thus, to obtain high-quality ocean color EDR, the SDR needs to be regularly reprocessed with improved F-factors. The SDR reprocessing, however, requires tremendous computational power and storage space, which is about 27 TB for one year of ocean-color-related SDR data. In this letter, we present an efficient and robust method for reduction of the computational demand and storage requirement. The method is developed based on the linear relationship between the SDR radiance/reflectance and the F-factors. With this linear relationship, the new SDR radiance/reflectance can be calculated from the original SDR radiance/reflectance and the ratio of the updated and the original F-factors at approximately 100th or less of the original central processing unit requirement. The produced SDR with this new approach fully agrees with those generated using the ADL package. This new approach can also be implemented to directly update the SDR in the EDR data processing, which eliminates the hassle of a huge data storage requirement as well as that of intensive computational demand. This approach may also be applied to other remote sensors for data reprocessing from raw instrument data to science data.

[1]  C. McClain.  A decade of satellite ocean color observations. , 2009, Annual review of marine science.

[2]  Menghua Wang,et al.  The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing. , 2007, Optics express.

[3]  Xiaoxiong Xiong,et al.  Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[4]  K. Voss,et al.  Impacts of VIIRS SDR performance on ocean color products , 2013 .

[5]  Menghua Wang,et al.  Evaluation of the VIIRS Ocean Color Monitoring Performance in Coastal Regions , 2013 .

[6]  Menghua Wang,et al.  Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm. , 1994, Applied optics.

[7]  Atmospheric Correction for Remotely-Sensed Ocean-Colour Products , 2009 .

[8]  J. Butler,et al.  VIIRS on‐orbit calibration methodology and performance , 2014 .

[9]  Menghua Wang,et al.  Estimation of ocean contribution at the MODIS near‐infrared wavelengths along the east coast of the U.S.: Two case studies , 2005 .

[10]  Menghua Wang.  Remote sensing of the ocean contributions from ultraviolet to near-infrared using the shortwave infrared bands: simulations. , 2007, Applied optics.

[11]  Robert E. Wolfe,et al.  Suomi NPP VIIRS prelaunch and on‐orbit geometric calibration and characterization , 2013 .

[12]  M. Kahru,et al.  Ocean Color Chlorophyll Algorithms for SEAWIFS , 1998 .

[13]  H. Gordon,et al.  Normalized water-leaving radiance: revisiting the influence of surface roughness. , 2005, Applied optics.

[14]  Xi Shao,et al.  Suomi NPP VIIRS sensor data record verification, validation, and long‐term performance monitoring , 2013 .

[15]  Menghua Wang,et al.  Effects of ocean surface reflectance variation with solar elevation on normalized water-leaving radiance. , 2006, Applied optics.

[16]  K. Carder,et al.  Semianalytic Moderate‐Resolution Imaging Spectrometer algorithms for chlorophyll a and absorption with bio‐optical domains based on nitrate‐depletion temperatures , 1999 .

[17]  B Gentili,et al.  Diffuse reflectance of oceanic waters: its dependence on Sun angle as influenced by the molecular scattering contribution. , 1991, Applied optics.

[18]  Gabriel Moy,et al.  Automated calibration of the Suomi National Polar‐Orbiting Partnership (S‐NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) reflective solar bands , 2013 .

[19]  Curt H. Davis,et al.  Ocean Color products from Visible Infared Imager Radiometer Suite (VIIRS) , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.