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“As the world urbanizes, urban planners and policymakers need to make sure urban design and policies adequately address critical issues such as infrastructure and transportation improvements, poverty and the health and safety of urbanites, as well as the increasing inequality within and across cities."
Increasing population shifts from rural to urban areas are resulting in the growth of cities and towns, a process referred to as urbanization. However, this development can put a strain on urban infrastructure, such as transportation, housing, sanitation, and utilities, leading to urban decay. He added that the new machine learning model can provide these professionals with a better understanding of the deterioration of urban space and its significance in future planning by using the tool to identify patterns of neighborhood development and urban inequality.
The model can be a useful and timely tool for public and nongovernmental organizations. It can provide valuable information using data that can be acquired more efficiently and accurately than the traditional standard data used to evaluate urbanization.
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