Comparison of MODIS land surface temperature and ground-based observed air temperature in complex topography

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Publikace nespadá pod Filozofickou fakultu, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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LAI Yen-Jen LI Ching-Feng LIN Po-Hsiung WEI Tsong-Hue CHANG Cheng-Sheng

Rok publikování 2012
Druh Článek v odborném periodiku
Časopis / Zdroj International Journal of Remote Sensing
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
Doi http://dx.doi.org/10.1080/01431161.2012.700422
Obor Zemský magnetismus, geodesie, geografie
Klíčová slova Agua and Terra Earth observation satellites; elevation; monthly mean temperature; mountain climate; soil moisture
Popis Near-ground air temperature (Ta) and land surface temperature (Ts) are important parameters in studies related to variations in hydrology, biodiversity and climate change. However, complicated mountainous terrain tends to hinder observations in such areas. The scarce observations from mountainous areas can be augmented with data from a 1 km high spatial resolution data set. This data set is obtained from the land surface temperature element of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments installed on the Aqua and Terra Earth observation satellites from NASA. This study used regional monthly mean Ta data for Taiwan as a reference to assess the monthly mean Ts data set. The results showed that the two sets of data had correlation coefficients of 0.91–0.96, and the standard deviations of the differences between the two sets were 1.25–1.77. These results could serve as a reference for research related to climate and ecology. Further analysis indicated some possible sources of bias between Ts and Ta: (1) the significant influences caused by soil moisture between wet and dry seasons; (2) the difference between ground-based weather station elevation and 1 km grid-averaged elevation; and (3) interaction among the satellite view, solar zenith angle and terrain gradient. When the Ts product (V005) is used directly in ecological study and application, it is essential to have a clear knowledge of the bias and its possible causes.
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