Visual extraction of spatial data is an important part of the process of spatial data analysis and decision-making. The traditional data extraction method has the problem of low accuracy and stability. The purpose of this research is to design a spatial data visualization extraction system based on genetic algorithms to improve the accuracy and stability of data extraction results. In this study, genetic algorithm is used as the optimization algorithm, and a spatial data visualization extraction system based on genetic algorithm is designed. Through the search and optimization capabilities of genetic algorithms, the system automatically adjusts parameter settings and selects appropriate genetic operators and fitness functions to maximize the accuracy and stability of data extraction. Through experimental evaluation and comparative analysis, the results show that the system accuracy rate of this method is between 89 and 96%, the system can produce high-quality and consistent data extraction results, and has good noise resistance.