Up to date population of an urban area is vital for any planning decision for the urban area as well as intelligence by using open source information. The conventional method of collecting data for population mainly relies on census which is time consuming and costly. A rule of thumb for estimating the census cost in developing countries is given to be $1 USD per enumerated person, which requires allocating more resources for collecting population data for dense urban areas. Although the population data collected by census is more precise and accurate, due to long time intervals between censuses, it becomes outdated a few years after the census. Hence use of remote sensing for urban environments has potential for predicting urban population with low cost and up to date data. Recently, the availability of high spatial resolution satellite imagery provides development of methodologies for accurate and up to date population predictions for urban environments.