Estimation of Minimum and Maximum Air Temperature Using MODIS Remote Sensing Imagery and Geographical Information System (GIS)

Abstract

Air temperature is a useful environmental variable in a wide range of applications in areas of ecology, hydrology and atmospheric sciences. Estimating air temperature (T a) is very important in monitoring the environment, estimating precipitation, climatic prediction, determining evapotranspiration, predicting crop yield and climatic changes, etc. Furthermore, it is the most important meteorological and climatological variable, along with radiation, in plant development, determining its spatial distribution, and conditioning agricultural soil suitability. In agro-meteorological, hydrological, hydro-meteorological studies, one of the main issues is the lack of representative temperature data. Density of the meteorological stations network is generally sparse, and installation and running cost of additional meteorological stations are very high. As a result, obtaining high spatial resolution maximum temperature (T max) and minimum temperature (T min) map from meteorological stations data is not possible. Remote sensing data provides synoptic spatial coverage compared to discrete spatial distribution of meteorological stations, thus encouraging researchers to make use of satellite data to fill in the gaps inherent in meteorological station data. Satellite remote sensing image is fundamentally designed to offer spatially distributed information over earth observation. Therefore, this study is carried out with the objectives to select appropriate MODIS data for simulation of temperature and with application of selected imaginary to simulate temperature in the Limkheda watershed located in the semi-arid middle region of Gujarat. Temperature data during the month of October 2010, at two sites of the Limkheda watershed are applied to explore the capabilities of MODIS satellite imagery to simulate the minimum and maximum temperature in the Limkheda watershed. It is found in this study that bands namely Day_view_angle and Emis_32 of MODIS imagery simulate minimum and maximum temperature satisfactorily. It is found in this study that Day_view_angle simulate minimum temperature very well, whereas Emis_32 band simulate both the maximum and minimum temperature very well. From this study, it is recommended that Emis_32 band would be a suitable choice to calculate temperature.