Estimation of minimum and maximum air temperature using MODIS data over Gujarat

Minimum and maximum air temperatures are important input parameters for meteorological and agricultural models. Generally minimum and maximum air temperatures are measured at weather stations on the ground. However these measurements are not available with enough spatial density which makes it difficult to be used in real-time applications. Compensation of this lack of information can be achieved by satellite-based methods. The present study investigates the potential of deriving the spatial distribution of minimum and maximum air temperatures with the help of land surface temperature (Ts) and normalized differential vegetation index (NDVI) products from the moderate resolution imaging spectroradiometer (MODIS) sensor and air temperature (Ta) data from automatic weather stations (AWS) over Gujarat region of India. The minimum Ta was successfully retrieved through a regression analysis between night time MODIS Ts and AWS measured minimum Ta over all stations, since the minimum Ta is strongly associated with night time Ts. While, the maximum Ta was retrieved using a method, namely, temperature vegetation index (TVX) approach based on the linear relationship between Ts and NDVI data. Results showed that MODIS estimated minimum Ta were in good agreement with the measured values by mean absolute error (MAE) of 1.49 degrees C and root mean square error (RMSE) of 1.95 degrees C. While, maximum Ta retrieved through TVX approach showed a good retrieval accuracy with a MAE of 1.96 degrees C and RMSE of 2.46 degrees C.