This study studies a method of spatial interpolation of sea state information data in spaces other than the observation point in a grid format based on the sea state information data at the observation point. Due to the limited spatial distribution of observation points, only fragmentary information can be collected. To solve this limitation, this study utilizes an OPEN API to collect sea state information data and through data preprocessing process, data for points without observational data were spatially interpolated into a grid format. In this study, three interpolation methods were employed: Cubic spline interpolation, Linear extrapolation, and Kriging. The accuracy and applicability of each interpolation method for spatial interpolation were evaluated through comparative analysis of the results. Consequently, Kriging is considered a suitable interpolation method for sea state information spatial interpolation because it best reflects the spatial distribution, correlation between observed points and the data structure of sea state information. It demonstrates higher accuracy in interpolating areas outside observed points compared to the other two interpolation methods. The spatially interpolated data allows for precise calculations of critical factors impacting ship maneuverability, such as average wind speeds and directions, current speeds, and directions. These calculations enable the identification of external forces affecting the vessel along its route, facilitating the planning of a path that considers both safety and economic efficiency.