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- Publisher Website: 10.1109/JSTARS.2018.2870130
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Article: The GLASS Land Surface Temperature Product
Title | The GLASS Land Surface Temperature Product |
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Authors | |
Keywords | Global Land Surface Satellite (GLASS) land surface temperature (LST) National Oceanic and Atmospheric Administration (NOAA) AHVRR split-window algorithm Terra/Aqua MODIS |
Issue Date | 2019 |
Citation | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, v. 12, n. 2, p. 493-507 How to Cite? |
Abstract | Land 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 Identifier | http://hdl.handle.net/10722/321807 |
ISSN | 2023 Impact Factor: 4.7 2023 SCImago Journal Rankings: 1.434 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhou, Ji | - |
dc.contributor.author | Liang, Shunlin | - |
dc.contributor.author | Cheng, Jie | - |
dc.contributor.author | Wang, Yujia | - |
dc.contributor.author | Ma, Jin | - |
dc.date.accessioned | 2022-11-03T02:21:34Z | - |
dc.date.available | 2022-11-03T02:21:34Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, v. 12, n. 2, p. 493-507 | - |
dc.identifier.issn | 1939-1404 | - |
dc.identifier.uri | http://hdl.handle.net/10722/321807 | - |
dc.description.abstract | Land 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.language | eng | - |
dc.relation.ispartof | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | - |
dc.subject | Global Land Surface Satellite (GLASS) | - |
dc.subject | land surface temperature (LST) | - |
dc.subject | National Oceanic and Atmospheric Administration (NOAA) AHVRR | - |
dc.subject | split-window algorithm | - |
dc.subject | Terra/Aqua MODIS | - |
dc.title | The GLASS Land Surface Temperature Product | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/JSTARS.2018.2870130 | - |
dc.identifier.scopus | eid_2-s2.0-85054237530 | - |
dc.identifier.volume | 12 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 493 | - |
dc.identifier.epage | 507 | - |
dc.identifier.eissn | 2151-1535 | - |
dc.identifier.isi | WOS:000460663600010 | - |