The Chinese chestnut (Castanea mollissima Blume) is an essential and highly nutritious nut crop, and income from selling chestnuts is important for small producers. Despite chestnuts being widely planted, chestnut yields are decreasing in northern China. The hypothesis of this paper is that yield reduction is the result of complex topographic conditions, insufficient soil nutrients, unscientific fertilization, and limited availability of productive land. The objective was to create a plant social geospatial model-geographical detector for analyzing the strength of the association between chestnut yields and their potential determinants. In this model system, we used measured data from chestnut to highlight how a geospatial model can be used to identify complex relationships among soil, plants, and geospatial location. Four geographical detectors (i.e., risk, factor, ecological, and interaction) were proposed on the basis of spatial variation analysis. The model was then applied to Qianxi County of Hebei Province in China. Soil parent material, soil texture, and total power of farm machinery were found to be the key factors. The interactive effect of any two factors increased chestnut yield, and the interaction between parent material and total power of farm machinery resulted in the highest yield. The study's approach and findings make it possible to introduce effective and practical measures to increase chestnut yield. Strategies to increase chestnut yield need to be designed with spatial variables being considered.