Rapid urbanization is a central characteristic of the current world’s globalization and human development. The world’s population is now over 7.8 billion, and the adding of one billion of them only takes the world twelve years; What is more astonishing is that half of world’s population live in cities that only cover three per cent of the earth’s land surface. It is indisputable that the booming population has brought enormous economic prosperities and social changes; however, the skyrocketing number of citizens has also caused many problems that affected the urban environment, lowering the quality of living of citizens. It includes but is not limited to noise, traffic congestion, pollution, and littering. Since cities are a complex system in where millions behave and act differently, it is difficult for scientists and policy makers to extract the correct and right type of data from the population body in order to serve as references in policy making to tackle urbanization problems and optimize urban living environments.
The inherent nature of this problem is the people, but we can only change other factors for improvement as the victim is also people themselves. That is the reason why data science is particularly useful and applicable in solving problems like this for its ever-evolving techniques, methods, and models so we can understand the people and their actions better. In this paper, I will examine some of the geospatial technologies that are applicable under the urbanization context, identify the pros and cons, and discuss future improvements of the technologies in order to address the board research question that how can data science methods and technologies be practically applied to the field of urbanization study, help us understand the population trends and behaviors in this urban complex adaptive system, and finally offer solutions to optimize the urban living environment, contributing to the human development through expanding the environmental freedom of sustainability.