The population burst has become a very important topic for discussions during recent periods. Migration has also become one of the most problematic issues and has become an environmental issue. Remote sensing-based error assessment is a critical method for enhancing the reliability of mathematical models for the prediction of urban sprawl. The integration of high-resolution satellite imagery with stochastic approaches quantifies the uncertainties to detect discrepancies in spatial simulations. The technique provides planners with robust data for decision-making, enabling the optimization of land use and infrastructure planning. Error quantification expands model calibration for stochastic simulations to capture inherent variability. These factors play a major role in case of expansion of urban sprawls. The same scenario may be applied here to make urban centers sustainable, first we must assess the sustainability. It is well known that economic, social, and environmental aspects play a major role in the assessment of overall sustainability. These urban sprawls are very important in assessing for environmental well-being in urban life. These may affect the social and economic aspects of the centers negatively. Remote sensing offers error assessment for sustainable urban design and management, ensuring resilient planning under environmental and societal influences while driving innovation.