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Separating vegetation and soil temperature using airborne multiangular remote sensing image data

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Liu Q, Yan CY, Xiao Q, Yan GJ, Fang L. Separating vegetation and soil temperature using airborne multiangular remote sensing image data. International Journal of Applied Earth Observation and Geoinformation, 2012, 17: 66-75, doi:10.1016/j.jag.2011.10.003.
Literature information
Type Of Reference JOUR
Title Separating vegetation and soil temperature using airborne multiangular remote sensing image data
Authors Liu, Qiang| Yan, Chunyan| Xiao, Qing| Yan, Guangjian| Fang, Li|
Secondary Title International Journal of Applied Earth Observation and Geoinformation
Abstract Land surface temperature (LST) is a key parameter in land process research. Many research efforts have been devoted to increase the accuracy of LST retrieval from remote sensing. However, because natural land surface is non-isothermal, component temperature is also required in applications such as evapo-transpiration (ET) modeling. This paper proposes a new algorithm to separately retrieve vegetation temperature and soil background temperature from multiangular thermal infrared (TIR) remote sensing data. The algorithm is based on the localized correlation between the visible/near-infrared (VNIR) bands and the TIR band. This method was tested on the airborne image data acquired during the Watershed Allied Telemetry Experimental Research (WATER) campaign. Preliminary validation indicates that the remote sensing-retrieved results can reflect the spatial and temporal trend of component temperatures. The accuracy is within three degrees while the difference between vegetation and soil temperature can be as large as twenty degrees.
Date 2012///
Year 2012
DOI 10.1016/j.jag.2011.10.003
Database Provider ScienceDirect
volume 17
Start Page 66
Alternate Title1 International Journal of Applied Earth Observation and Geoinformation
Issn 0303-2434
Url http://www.sciencedirect.com/science/article/pii/S0303243411001462
Access Date 2013/10/04/06:25:55
Keywords Component temperature| Multiangular remote sensing| WATER|
file_attachments2 http://www.sciencedirect.com/science/article/pii/S0303243411001462
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