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Conference Paper: An Iterative Temperature Inversion Method for Nonisothermal Land Surfaces

TitleAn Iterative Temperature Inversion Method for Nonisothermal Land Surfaces
Authors
KeywordsInversion algorithm
Land surface temperature
Statistical analysis
Vegetation canopy
Issue Date2003
Citation
International Geoscience and Remote Sensing Symposium (IGARSS), 2003, v. 6, p. 3866-3868 How to Cite?
AbstractWe propose an iterative multistage inversion (IMI) algorithm to retrieve the land surface component temperatures for nonisothermal vegetation canopy. Our algorithm is based on a thermal emission model that can simulate the directional effects from the nonisothermal surfaces. Our IMI algorithm just inverts the most uncertain and most sensitive parameters at each step using the most sensitive observation samples, and then adjusts the initial values based on the retrieval results. This inversion process is repeated until convergence condition is satisfied. Compared with the inversion method that try to invert all of the parameters at the same time, the IMI algorithm tends to give more accurate mean values for the parameters and is more stable when the noise level is relative low.
Persistent Identifierhttp://hdl.handle.net/10722/330046

 

DC FieldValueLanguage
dc.contributor.authorYan, Guangjian-
dc.contributor.authorZhou, Yuyu-
dc.contributor.authorWang, Jindi-
dc.contributor.authorLi, Xiaowen-
dc.date.accessioned2023-08-09T03:37:24Z-
dc.date.available2023-08-09T03:37:24Z-
dc.date.issued2003-
dc.identifier.citationInternational Geoscience and Remote Sensing Symposium (IGARSS), 2003, v. 6, p. 3866-3868-
dc.identifier.urihttp://hdl.handle.net/10722/330046-
dc.description.abstractWe propose an iterative multistage inversion (IMI) algorithm to retrieve the land surface component temperatures for nonisothermal vegetation canopy. Our algorithm is based on a thermal emission model that can simulate the directional effects from the nonisothermal surfaces. Our IMI algorithm just inverts the most uncertain and most sensitive parameters at each step using the most sensitive observation samples, and then adjusts the initial values based on the retrieval results. This inversion process is repeated until convergence condition is satisfied. Compared with the inversion method that try to invert all of the parameters at the same time, the IMI algorithm tends to give more accurate mean values for the parameters and is more stable when the noise level is relative low.-
dc.languageeng-
dc.relation.ispartofInternational Geoscience and Remote Sensing Symposium (IGARSS)-
dc.subjectInversion algorithm-
dc.subjectLand surface temperature-
dc.subjectStatistical analysis-
dc.subjectVegetation canopy-
dc.titleAn Iterative Temperature Inversion Method for Nonisothermal Land Surfaces-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0242709458-
dc.identifier.volume6-
dc.identifier.spage3866-
dc.identifier.epage3868-

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