It is necessary to establish environmental policies based on data-based analysis in order to solve complex and diverse environmental problems that occur continuously. However, simple analysis of environmental spatial information and data has limitations in establishing effective environmental policies and solving environmental problems. It is necessary to utilize objective analysis using artificial intelligence techniques such as probability/statistics, machine learning, and deep learning through convergence and complex connection with new technologies such as sensors, images, and drones. In particular, location-based spatial information can provide tools and technologies to understand, analyze, and visualize phenomena that appear differently depending on the location of an actual phenomenon. In addition, the convergence of spatial information and various data enables value creation through new knowledge. Therefore, in this study, it is proposed to establish a GeoAI-based environmental policy establishment support system that can converge and link spatial information based on location information and various data. And in order to examine the applicability of this support system, meaningful results could be derived by analyzing the relationship between LST and land use/cover for Seoul. The valuable new knowledge derived through this GeoAI-based environmental policy establishment support system is expected to be utilized as various basic data for future city and environmental planning.