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Article: The GLASS Land Surface Temperature Product

TitleThe GLASS Land Surface Temperature Product
Authors
KeywordsGlobal Land Surface Satellite (GLASS)
land surface temperature (LST)
National Oceanic and Atmospheric Administration (NOAA) AHVRR
split-window algorithm
Terra/Aqua MODIS
Issue Date2019
Citation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, v. 12, n. 2, p. 493-507 How to Cite?
AbstractLand surface temperature (LST) is one of the most important geophysical parameters at the earth's surface. Satellite LST products are beneficial for scientific communities with a variety of applications. The Global Land Surface Satellite (GLASS) LST product has been generated for 1983, 1993, 2003, and 2013 from historical NOAA-7 and NOAA-14 AVHRR data and recent Terra/Aqua MODIS data. The spatial resolution of the instantaneous GLASS LST product is 0.05° for 1983 and 1993 and is 1 km for 2003 and 2013. The algorithm for generating the GLASS LST product is based on a multialgorithm ensemble approach, which combines nine split-window algorithms with good performance in training, testing, and sensitivity analysis. The validation results based on in situ measurements demonstrate that the GLASS-AVHRR LST product has an accuracy of 2.89 K at Barrow site; the GLASS-MODIS LST product has an accuracy of 1.82-2.15 K at six grassland/cropland SURFRAD sites at nighttime, which is a similar accuracy to the official MODIS LST product. Systematic underestimation of LST at Desert Rock, NV (arid shrubland) has been found and has been attributed to uncertainties associated with land surface emissivities and other input datasets. Further intercomparison indicates that the GLASS-MODIS LST product agrees well with the official MODIS LST, with mean bias deviations/root mean square deviations of -1.19 K/1.87 K and 1.89 K/2.27 K for the two granules under examination. Nevertheless, the validation of the GLASS LST product is currently in a preliminary stage, and more in-depth examinations are still needed.
Persistent Identifierhttp://hdl.handle.net/10722/321807
ISSN
2023 Impact Factor: 4.7
2023 SCImago Journal Rankings: 1.434
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhou, Ji-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorCheng, Jie-
dc.contributor.authorWang, Yujia-
dc.contributor.authorMa, Jin-
dc.date.accessioned2022-11-03T02:21:34Z-
dc.date.available2022-11-03T02:21:34Z-
dc.date.issued2019-
dc.identifier.citationIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, v. 12, n. 2, p. 493-507-
dc.identifier.issn1939-1404-
dc.identifier.urihttp://hdl.handle.net/10722/321807-
dc.description.abstractLand surface temperature (LST) is one of the most important geophysical parameters at the earth's surface. Satellite LST products are beneficial for scientific communities with a variety of applications. The Global Land Surface Satellite (GLASS) LST product has been generated for 1983, 1993, 2003, and 2013 from historical NOAA-7 and NOAA-14 AVHRR data and recent Terra/Aqua MODIS data. The spatial resolution of the instantaneous GLASS LST product is 0.05° for 1983 and 1993 and is 1 km for 2003 and 2013. The algorithm for generating the GLASS LST product is based on a multialgorithm ensemble approach, which combines nine split-window algorithms with good performance in training, testing, and sensitivity analysis. The validation results based on in situ measurements demonstrate that the GLASS-AVHRR LST product has an accuracy of 2.89 K at Barrow site; the GLASS-MODIS LST product has an accuracy of 1.82-2.15 K at six grassland/cropland SURFRAD sites at nighttime, which is a similar accuracy to the official MODIS LST product. Systematic underestimation of LST at Desert Rock, NV (arid shrubland) has been found and has been attributed to uncertainties associated with land surface emissivities and other input datasets. Further intercomparison indicates that the GLASS-MODIS LST product agrees well with the official MODIS LST, with mean bias deviations/root mean square deviations of -1.19 K/1.87 K and 1.89 K/2.27 K for the two granules under examination. Nevertheless, the validation of the GLASS LST product is currently in a preliminary stage, and more in-depth examinations are still needed.-
dc.languageeng-
dc.relation.ispartofIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing-
dc.subjectGlobal Land Surface Satellite (GLASS)-
dc.subjectland surface temperature (LST)-
dc.subjectNational Oceanic and Atmospheric Administration (NOAA) AHVRR-
dc.subjectsplit-window algorithm-
dc.subjectTerra/Aqua MODIS-
dc.titleThe GLASS Land Surface Temperature Product-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/JSTARS.2018.2870130-
dc.identifier.scopuseid_2-s2.0-85054237530-
dc.identifier.volume12-
dc.identifier.issue2-
dc.identifier.spage493-
dc.identifier.epage507-
dc.identifier.eissn2151-1535-
dc.identifier.isiWOS:000460663600010-

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