The project involves combination of Machine Learning along with Satellite Imagery (SIML) which is having potential for addressing major global problems by remotely accessing socioeconomic and meteorological conditions in data poor areas, although SIML’s resource requirements will limits its access and utilization. Combining Machine Learning along with Satellite Imagery (SIML) is enabling better characterizations for population densities and poverty Rates. Further, this ML (Machine Learning) Application proves to be a path which is effective to convert such huge amount of unformed image data into formed assess of conditions of ground.