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TitleReprojection of VIIRS SDR imagery using concurrent gradient search
AuthorTrishchenko, A P
SourceIEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers) vol. 56, no. 7, 2018 p. 4016-4024, https://doi.org/10.1109/TGRS.2018.2819825
Year2018
Alt SeriesNatural Resources Canada, Contribution Series 20170381
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; Nature and Environment; remote sensing; satellite imagery; methodology; gradient methods; Visible Infrared Imaging Radiometer Suite (VIIRS); satellite data record (SDR) imagery; Moderate Resolution Imaging Spectroradiometer (MODIS); image processing; image registration; image sampling; geolocation
Illustrationssatellite images; schematic diagrams; histograms; tables; sketch maps; plots; photographs
ProgramLand Surface Characterization, Remote Sensing Science
Released2018 04 18
AbstractThe application of the gradient search method for reprojection of Visible Infrared Imaging Radiometer Suite (VIIRS) satellite data record (SDR) imagery is described. The method is an extension of the scheme developed earlier for reprojection of Moderate Resolution Imaging Spectroradiometer (MODIS) L1B imagery. The new scheme has three important improvements: 1) the interscan and intrascan search steps are combined into a single step to save computational time; 2) one-sided (left-right, up-down) gradients are utilized to improve convergence; and 3) the use of the map projection instead of the latitude-longitude coordinate system to improve performance and robustness. The scheme is computationally very fast, employing only basic arithmetic operations and precalculated matrices of spatial gradients. An average number of iteration steps for the reprojection of mid-latitude quadruple VIIRS SDR granule is less than 1.5, i.e., the scheme usually converges in less than 2 iterations. The ambiguity in the overlapping areas due to the bow-tie effect is resolved by forcing a solution located closer to the scan line center. In addition, the accuracy of VIIRS imagery geo-location was evaluated by comparison against MODIS 250 m images. Absolute geolocation biases of the VIIRS imagery over the 1-year period from June 01, 2016 to May 01, 2017 were found on average to be within 0.004 and -0.003 of the sample size (delta line) in the along-track direction and 0.055 and 0.035 of the sample size (delta pixel) in the along-scan direction for bands I2 and M7, respectively. These results demonstrate the excellent geometric performance of the VIIRS Suomi National Polar-orbiting Partnership sensor and are consistent with those reported by the VIIRS geolocation teams.
Summary(Plain Language Summary, not published)
The application of gradient search method for re-projection of VIIRS Satellite Data Record (SDR) imagery is described. The method is an extension of the scheme developed earlier for re-projection of MODIS L1B imagery. The scheme is computationally very fast. An average number of iteration steps is less than 1.5, i. e. the scheme usually converges in less than 2 iterations. The accuracy of VIIRS imagery geo-location was evaluated by comparison against MODIS 250m images. Absolute geolocation biases were found on average to be within 0.004 and -0.003 of the sample size (Dline) in the along-track direction and 0.055 and 0.035 of the sample size (Dpixel) in the along-scan direction. These results demonstrate the excellent geometric performance of the VIIRS S-NPP sensor and are consistent with those reported by the VIIRS geolocation team. The IIRS data are used for generation of Long-Term Satellite Data Records over Canada landmass.
GEOSCAN ID308070