This research work focused on the development of specialized techniques of Machine Learning to understand satellite image for the extraction of socio-economic indicators. In this study the approach that is employed draws on McKinsey’s concept of “Government for Design” which explicates the importance of merging Big Data Analytics with local insight in order to promote the design and development of locally-relevant interventions. Hence, the availability of cost effective satellite imagery captured at different time frames and availability of huge data gathered by different agencies provide a solution to this age-old problem, opening an avenue for policy makers and researchers. Nonetheless, some work has been done in this country by researchers in the past on using satellite imagery for visualization separately at different intervals which is highly cumbersome, expensive, ineffective and lacking holistic view but there is no such major research on how to solve this problem with temporal analysis portal having smart algorithms to deduct different socio-economic indicators. The portal facilitates policy maker/researcher to make correlation at different time intervals on different social and economic parameters, promoting new means of monitoring and evaluating results.