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Lin, SP; Moore, NJ; Messina, JP; DeVisser, MH; Wu, JP (2012). Evaluation of estimating daily maximum and minimum air temperature with MODIS data in east Africa. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 18, 128-140.

Real time and spatially distributed T-a (air temperature) data are desired for many applications. T-s (land surface temperature) derived from remote sensors has been used to estimate T-a in previous studies. Exploring MODIS Aqua T-s and station measured daily maximum and minimum T-a over east Africa, we found that T-s did not agree well with T-a during the day (MAE (Mean Absolute Error) = 6.9 +/- 5.0 degrees C) but had better agreement during the night (MAE = 1.9 +/- 1.7 degrees C). A stepwise linear regression method was applied to construct possible models to predict T-a based on MODIS data. Our results showed that, only considering elevation, high spatial resolution T-a could be obtained by simple linear models, with MAE=1.9 degrees C, agreement index = 0.79 for daily maximum T-a. and MAE = 1.9 degrees C, agreement index=0.92 for daily minimum T-a. MODIS T-s data could provide temporal variation information and slightly improve the accuracy of model predictions (by 0.2 degrees C of MAE). However, considering (i) major absences (about 2/3 of days) of T-s data due to cloud cover and (ii) small T-a variations in time (sigma = 2.1 degrees C) over east Africa, models without T-s might be more practical in particular applications such as tsetse fly distribution models. Other variables including solar zenith angle, low level precipitable water content, and vegetation index (NDVI and EVI) were insignificant in the daily maximum and minimum T-a estimation models after elevation and T-s had already been considered as predictors. (C) 2012 Elsevier B.V. All rights reserved.



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