Remote sensing (RS) and Geographic Information System (GIS) has played a major role in the study of different types of drought i.e. agricultural or hydrological drought. The present study on agricultural Drought assessment was carried out in the Patan District of North Gujarat, India. This study focuses on the assessment of climate change and its impact on Agriculture using Remote Sensing (RS) and GIS technology. The Landsat-7 TM and Landsat-8 OLI data of February-2002 and February-2018 covering Patan District was analysed for Land use/Land Cover mapping and monitoring changes in agricultural area over the period of 16-years. The Spectral vegetation index namely Normalized Difference Vegetation Index (NDVI) was computed using Landsat-7 TM and Landsat-8 OLI digital data for assessment of changes in agricultural vegetation during the drought and normal monsoon periods. Meteorological data like Minimum & maximum Temperatures and rainfall was collected from State Data Centre. Various Drought indices like Standardized Precipitation Index (SPI), Potential Evapo-Transpiration (PET) and Aridity Index (AI) were computed using meteorological data of past 16-years.   The results indicate that total agricultural vegetation during drought season was only 21.9 per cent (2002) which has increased to 58.7 per cent during the normal monsoon season of 2018. The rainfall deviations were computed for various years and it was observed that high negative rainfall deviations (-40 to -70%) having low rainfall occurrence were associated with negative SPI values ranging from -0.5 to -1.1 in Patan district. These positive rainfall deviations were associated with positive SPI values of 1.08, 0.57 and 0.62 of respective years indicating moderately wet and mildly wet conditions. During drought year of 2002 total precipitation was very less resulting in Aridity Index of 0.09 which is classified as hyper arid for the Patan District.