Evaluation of SNPP and NOAA-20 VIIRS Datasets Using RadCalNet and Landsat 8/OLI Data

dc.contributor.authorJing, Xin
dc.contributor.authorUprety, Sirish
dc.contributor.authorLiu, Tung-Chang
dc.contributor.authorZhang, Bin
dc.contributor.authorShao, Xi
dc.date.accessioned2023-10-19T19:46:26Z
dc.date.available2023-10-19T19:46:26Z
dc.date.issued2022-08-12
dc.description.abstractIn this study, we used RVUS data from RadCalNet as a benchmark to verify the radiometric accuracy and stability of operational and reprocessed SNPP/VIIRS data and the accuracy of NOAA-20/VIIRS data, as well as to assess the efficiency of the SNPP/VIIRS reprocessing algorithm. In addition, to remove the uncertainty of the RVUS site itself, we used Landsat 8/OLI as another benchmark with which to validate the accuracy and stability of VIIRS data through the RUVS site. The radiometric biases of the operational and reprocessed SNPP VIIRS bands were within ±4% and ±2%, respectively, as compared with the RUVS site and OLI, except for the M10 and M11 bands. In particular, the biases of the M5 and M7 bands were reduced by ~2% in this study. NOAA-20 VIIRS, on the other hand, was consistently lower than SNPP by ~2 to ~4% for all the bands. For the equivalent bands, the drift differences between operational and reprocessed SNPP/VIIRS and OLI were no larger than 0.24%/year and 0.1%/year, respectively. The reprocessing algorithm of SNPP VIIRS efficiently improved the radiometric accuracy and stability of the SNPP/VIIRS dataset to meet its specifications.
dc.description.urihttps://doi.org/10.3390/rs14163913
dc.identifierhttps://doi.org/10.13016/dspace/mmno-syix
dc.identifier.citationJing, X.; Uprety, S.; Liu, T.-C.; Zhang, B.; Shao, X. Evaluation of SNPP and NOAA-20 VIIRS Datasets Using RadCalNet and Landsat 8/OLI Data. Remote Sens. 2022, 14, 3913.
dc.identifier.urihttp://hdl.handle.net/1903/31084
dc.language.isoen_US
dc.publisherMDPI
dc.relation.isAvailableAtDigital Repository at the University of Maryland
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md)
dc.subjectRadCalNet
dc.subjectevaluation
dc.subjectSNPP
dc.subjectNOAA-20
dc.subjectVIIRS
dc.subjectLandsat 8
dc.titleEvaluation of SNPP and NOAA-20 VIIRS Datasets Using RadCalNet and Landsat 8/OLI Data
dc.typeArticle
local.equitableAccessSubmissionNo

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
remotesensing-14-03913.pdf
Size:
1.95 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.55 KB
Format:
Item-specific license agreed upon to submission
Description: