Abstract: In the monitoring and warning system for crop diseases and insect pests, the amount of monitoring spots is smaller and the monitored data are very limited. Therefore, How to use the limited data to show the general spatial distribution and time-spatial change of crop diseases and insect pests is the key to build the efficient spatial interpolation model. By analyzing the advantages of all kinds of spatial interpolation algorithms and considering the particularity of spatial interpolation on the crop diseases and insect pests in agriculture, the authors bring forward one new method: multi-factor spatial interpolation model. It refers to many factors, such as spatial orientation relationship, topological relationship, distance relationship and national weather conditions. Moreover, the model is applied to the interpolation of crop diseases and insect pests in Guangdong Province. First, the spatial relationships, such as orientation relationship, topological relationship, distance relationship, were used to build up the spatial influencing factors between various counties in Guangdong Province. Then, the national weather conditions, such as air temperature, climate, wind direction and wind speed, are introduced into the influencing factors in order to construct the spatial interpolation model. At last, on the basis of the raw data of crop diseases and insect pests, the other data of crop diseases and insect pests are gained by using the multi-factor spatial interpolation model, which shows the effluence and spread speed of crop diseases and insect pests and implements the monitoring and warning of crop diseases and insect pests.