Spatial interpolation analysis algorithm is a kind of algorithm applied to transform measurement data of discrete points into continuous data surface. It can compare the distribution of continuous data surfaces with other spatial phenomena, and it has a wide range of applications in spatial information, especially in terms of geographic information. The interpolation principle and application scenarios of spatial interpolation algorithms such as Thiessen polygon method, inverse distance weight interpolation method, spline function interpolation method and Kriging interpolation method are reviewed. The progress and future research direction of spatial interpolation analysis algorithm is discussed.