Satellite based remote sensing (RS) data at different spatial and temporal scales can provide crop sown area estimates needed by decision makers. Due to conflict of spatial resolution versus temporal frequency of data collection, getting early and accurate crop sown area at large scale is very difficult. This paper presents a methodology of early estimation of crop sown area at large scale by making use of high temporal coarse spatial resolution data and low temporal fine spatial resolution data. It also uses previous years’ data for extracting a-priori knowledge of crop sowing area. Early crop area estimate was made for Gujarat state (India) for 2011-12 rabi season. Multi-date MODIS (MODerate resolution Imaging Spectroradiometer) data and two-date Resourcesat-2 AWiFS (Advance Wide Field Sensor) data upto mid-December were used for crop sown area early estimates. Multi-date MODIS data for previous five years provided a-priori information on crop presence/absence over the previous five crop seasons. While ISODATA was used for classifying multi-date MODIS and AWiFS data; hierarchical decision tree approach was used for integrating multi-source information. Incorporating two date AWiFS data and a-priori information with multi-date MODIS data increased crop sown area early estimates accuracy significantly.