Thane, located in the state of Maharashtra, is currently urbanizing at an alarming rate on account of rapid economic growth and migration of the rural population from other parts of India. The total area of Thane is 328 sq km with a population of 3.7 million as per the 2011 census, while the current population is 5.5 million, which is a 50% increase in a decade. Thane floods every year in the monsoon, halting traffic, damaging property, and posing a threat to the lives of people. The availability of historical Earth satellite images combined with modern GIS (Geographic Information System) tools provides a unique opportunity to study the land use land cover (LULC) changes of Thane between the years 1989 and 2025. The research used Landsat 4-5 TM C2 L2 (Thematic Mapper) for the year 1989 and Sentinel-2A Level 2A MSI (Multispectral Instrument) for the year 2025 to classify the land uses into four categories—water bodies, developed land, open land, and forest land, while the changes in these categories were compared for a 36-year period. The accuracy assessments were performed as well for each classification after selecting the 500 ground-truthing points. Overall accuracy exceeded 90%, while the Kappa coefficients remained above 0.85 for all raster classifications. Supervised classification using Maximum Likelihood Classifier (MLC) algorithms shows that there is a significant increase in developed land area while barren and forest land areas are shrinking in Thane. The water bodies dropped from 9% to 6%, and the forest and barren land area diminished by 18%. At the same time, developed land (built-up area) increased from 36% to 56%, that is, a 78 sq km area expansion in the last 36-year period. The change in land use pattern will have a negative impact on soil imperviousness and curve number, which will have a significant impact on urban runoffs in Thane. The study offers strategic oversight to city planners and municipal engineers on land use/land cover changes occurring in the city and their potential consequences for extreme flood events.