Microwave remote sensing is successfully used for monitoring numerous parameters of the land, ocean and atmosphere. Large volume of active and passive microwave data over the globe is now available and is being used by scientists for deducing various land and ocean parameters. In India, the use of microwave remote sensing data is very much limited. In the present thesis, an effort has been made to analyze  multi frequency scanning microwave radiometer (MSMR) data over Indian sub-continent. MSMR on- board the Indian Remote Sensing (IRS-P4) satellite takes radiometric measurements over the globe with the objective to estimate various land, ocean and meteorological parameters. The brightness temperature data has been analysed over India to deduce the seasonal variations of emissivity and monthly variations of soil moisture. Significant increase in emissivity during summer over all geological terrains of India has been found compared to winter and rainy season and increase in soil moisture during rain and gradual decrease in moisture level from winter to summer seasons. Detailed analysis of MSMR data has also been carried out  prior and after the Gujarat earthquake to deduce various physical parameters of the epicentral region. The brightness temperature, emissivity and the soil moisture of the epicentral region show significant increase after the Gujarat earthquake of January 26, 2001. Using brightness temperature measured at 10 and 18 GHz frequencies in horizontal and vertical polarizations, rainfall rate has been derived. The rain rate deduced from MSMR brightness temperature data shows  high rain rate over ocean during monsoon months June and July. This rain rate gradually decreases and shows very low values during October and November and again it  increases from January to May showing the effect of summer and winter monsoon. The SW monsoon approaches India in June/July  which is responsible for higher rainfall  over the ocean. Due to NE monsoon rain rate increases over ocean during January-February. These results show one-to-one correlation with NCEP monthly averaged rain rate data set. The rain rate is correlated with QuikSCAT wind speed data and probability of rain fall over ocean at a particular time have been deduced which show a good correlation with the actual rain rate.