With the acceleration of the global urbanization process, the contradiction between urban and rural areas has become increasingly prominent. The rural population is constantly decreasing, but the area of rural areas is increasing. In this regard, studying the global rural boundaries is of great significance for rural planning. In recent years, great progress has been made in products such as global impervious surface area (GISA), which makes it is possible to obtain high-precision, large-scale and long-term rural boundary products. However, the existing rural boundary products still cannot meet the requirements of scientific research in terms of the timeliness, accuracy and quality of data. Obtaining global rural boundary products is of great significance. Therefore, based on multi-source geographic information data, this study adopted kernel density estimation (KDE), convolution operations and post-processing operations to obtain global rural boundary products from 1972 to 2021. This data is named the Global Rural Settlement Boundary Vector (GRSV). By comparing GRSV and Global Urban and Rural Settlement (GURS), the correlation can reach 0.913. The minimum average relative error (MRE) of the two is 0.147.