Cities and metropolitan areas are increasingly vulnerable to the effects of climate change, including rising temperatures and extreme weather events. One of the most significant impacts of climate change on urban areas is the urban heat island effect, which occurs when a particular area in cities experiences higher temperatures than its surrounding areas owing to human activity and the built environment. Urban greenspaces play an influential role in regulating and mitigating to eliminate these adverse effects. This study presents a novel approach to develop a mathematical model to estimate the greenspace requirements based on the reduction of land surface temperature. This mathematical model is developed to estimate the greenspace requirement based on literature-based evidence and an observed data set considering the impact of green spaces on reducing the average land surface temperature. The study employed the curve fitting method to generate the coefficient of the twenty equations on the observed data set. Out of the generated equations, 14 equations are selected based on a high R² value. To predict greenspace area based on temperature drop, these 14 equations are further validated. The best-fitted equation is selected based on a high r² value, lower root means square value (RMSE) and mean absolute error value (MAE). As a result, the third Order Polynomial Equation is considered as the greenspace area is the function of land surface temperature based on its High r² Value (0.89), RMSE value i.e.,14.49 and MAE value, i.e., 9.61. The equation can then be used to estimate the required greenspace area to achieve a desired LST reduction in a given area. The resulting model provides valuable information for urban planners and policymakers to create liveable and sustainable cities that incorporate sufficient green spaces for temperature regulation. The paper concludes by highlighting the need for further research to better understand the effectiveness of urban greenspaces in mitigating temperature drop.