Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data
The importance of land surface temperature (LST) retrieved from high to medium spatial resolution remote sensing data for many environmental studies, particularly the applications related to water resources management over agricultural sites, was a key factor for the final decision of including a th...
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| Veröffentlicht in: | IEEE geoscience and remote sensing letters 2014-10, Vol.11 (10), p.1840-1843 |
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| container_title | IEEE geoscience and remote sensing letters |
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| creator | Jimenez-Munoz, Juan C. Sobrino, Jose A. Skokovic, Drazen Mattar, Cristian Cristobal, Jordi |
| description | The importance of land surface temperature (LST) retrieved from high to medium spatial resolution remote sensing data for many environmental studies, particularly the applications related to water resources management over agricultural sites, was a key factor for the final decision of including a thermal infrared (TIR) instrument on board the Landsat Data Continuity Mission or Landsat-8. This new TIR sensor (TIRS) includes two TIR bands in the atmospheric window between 10 and 12 μm, thus allowing the application of split-window (SW) algorithms in addition to single-channel (SC) algorithms or direct inversions of the radiative transfer equation used in previous sensors on board the Landsat platforms, with only one TIR band. In this letter, we propose SC and SW algorithms to be applied to Landsat-8 TIRS data for LST retrieval. Algorithms were tested with simulated data obtained from forward simulations using atmospheric profile databases and emissivity spectra extracted from spectral libraries. Results show mean errors typically below 1.5 K for both SC and SW algorithms, with slightly better results for the SW algorithm than for the SC algorithm with increasing atmospheric water vapor contents. |
| doi_str_mv | 10.1109/LGRS.2014.2312032 |
| format | Article |
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(IEEE) Oct 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c341t-d5acc6d43eac5913a6b9fdf56fedb20b11804e4e16354b58bb57151a86f59f103</citedby><cites>FETCH-LOGICAL-c341t-d5acc6d43eac5913a6b9fdf56fedb20b11804e4e16354b58bb57151a86f59f103</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6784508$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6784508$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Jimenez-Munoz, Juan C.</creatorcontrib><creatorcontrib>Sobrino, Jose A.</creatorcontrib><creatorcontrib>Skokovic, Drazen</creatorcontrib><creatorcontrib>Mattar, Cristian</creatorcontrib><creatorcontrib>Cristobal, Jordi</creatorcontrib><title>Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data</title><title>IEEE geoscience and remote sensing letters</title><addtitle>LGRS</addtitle><description>The importance of land surface temperature (LST) retrieved from high to medium spatial resolution remote sensing data for many environmental studies, particularly the applications related to water resources management over agricultural sites, was a key factor for the final decision of including a thermal infrared (TIR) instrument on board the Landsat Data Continuity Mission or Landsat-8. This new TIR sensor (TIRS) includes two TIR bands in the atmospheric window between 10 and 12 μm, thus allowing the application of split-window (SW) algorithms in addition to single-channel (SC) algorithms or direct inversions of the radiative transfer equation used in previous sensors on board the Landsat platforms, with only one TIR band. In this letter, we propose SC and SW algorithms to be applied to Landsat-8 TIRS data for LST retrieval. Algorithms were tested with simulated data obtained from forward simulations using atmospheric profile databases and emissivity spectra extracted from spectral libraries. Results show mean errors typically below 1.5 K for both SC and SW algorithms, with slightly better results for the SW algorithm than for the SC algorithm with increasing atmospheric water vapor contents.</description><subject>Algorithms</subject><subject>Atmospheric modeling</subject><subject>Earth</subject><subject>Land surface temperature</subject><subject>Land surface temperature (LST)</subject><subject>Landsat Data Continuity Mission (LDCM)</subject><subject>Landsat satellites</subject><subject>Landsat-8</subject><subject>Meteorology</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>single-channel (SC) algorithm</subject><subject>split-window (SW) algorithm</subject><subject>Temperature sensors</subject><subject>thermal infrared (TIR)</subject><issn>1545-598X</issn><issn>1558-0571</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEFLw0AQhRdRsFZ_gHhZ8Jy6k91NN0dRWwsRoa3ibdkks7SlSepsIvjvTWjxNAPz3hvex9gtiAmASB-y-XI1iQWoSSwhFjI-YyPQ2kRCT-F82JWOdGq-LtlVCDshYmXMdMQ-M1eXfNWRdwXyNVYHJNd2hHyJLW3xx-35G7abpgx8Rk3FB31wbWT4eoNU9edF7ckR9ilYh4b4s2vdNbvwbh_w5jTH7GP2sn56jbL3-eLpMYsKqaCNSu2KIimVRFfoFKRL8tSXXiceyzwWOYARChVCIrXKtcnzvo0GZxKvUw9Cjtn9MfdAzXeHobW7pqO6f2n7xqlWYJK4V8FRVVATAqG3B9pWjn4tCDvgswM-O-CzJ3y95-7o2SLivz6ZGqWFkX_TvWtX</recordid><startdate>20141001</startdate><enddate>20141001</enddate><creator>Jimenez-Munoz, Juan C.</creator><creator>Sobrino, Jose A.</creator><creator>Skokovic, Drazen</creator><creator>Mattar, Cristian</creator><creator>Cristobal, Jordi</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Atmospheric modeling Earth Land surface temperature Land surface temperature (LST) Landsat Data Continuity Mission (LDCM) Landsat satellites Landsat-8 Meteorology Remote sensing Satellites single-channel (SC) algorithm split-window (SW) algorithm Temperature sensors thermal infrared (TIR) |
| title | Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data |
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