Mapping and Predicting Land Cover Changes of Small and Medium Size Cities in Alabama Using Machine Learning Techniques

In the southeastern US, Atlanta is always focus of attention, despite rapid expansion small and medium-sized cities (SMSCs) in region. Clearly, larger have more people, resulting loss during disasters. However, SMSCs also face natural calamities must be made robust sustainable. Keeping this mind, study chooses to on ten Alabama (Population > 40,000) which encountered at least a 6% increase population size between 1990 2020, out two large 180,000) experienced same time. This paper examines change urban built-up area 2020 using random forest algorithm Google Earth Engine (GEE) estimates future 2050 scenarios Cellular Automata (CA) Markov model TerrSet’s Land Change Modeler (LCM). The results revealed areas grew rapidly from with some doubling or tripling due growth. growth predicted for most along transportation networks. outcome research showcases importance proper planning building sustainably disaster events.