In ancient China, where was frequently troubled by invaders, the government set up many beacon towers for alerting and transmitting military information along the border and the coast. Many beacon sites still exist in some areas, which are generally located in dangerous places with high mountains and rough terrain, bringing great difficulties to archaeological discovery. Therefore, it is particularly important to develop a predictive model applicable to the distribution of mountain beacon sites. Taking 68 beacon sites found in Wenzhou as research samples, this study used the superimposed method of logistic regression and viewshed analysis, forming a high-precision, scientific and operational predictive model for the distribution of beacon sites, which was verified by the cross-validation method. The results showed that the beacon site predictive model simulated in this study could reduce the probability scope of site location by 90% compared with the common logistic regression predictive model, which greatly improved the accuracy and ability of site prediction. At the same time, it could also be used to understand the relationship between the known sites and their surroundings to assist in decision-making about conservation and management.
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