With the acceleration of urbanization, the relationship between an area's population and its economy has become the main indicator of regional differences. Therefore, a comprehensive study of population-economy spatial dispersion changes and their influencing factors will help identify the driving force of population change and economic development. Moreover, it will facilitate measurement of the coupling and coordination relationship between industrial layout and the environment. Accordingly, based on the 2018 population and economic data of Anhui Province, China, this study used a land use impact model to spatialize socioeconomic indicators, and considered the population–economic spatial relationship of Anhui Province with its terrain. By doing so, the study hopes to promote the construction of new urbanization in Anhui Province and provide a reference for the development of central provinces in China. The results indicated that: 1) The predicted population and economic densities of the study area fit well with the actual statistical values, which suggests that the spatialization results could reflect the actual situation of population and economic distribution. Based on the simulation data, the spatial relationship between the population and economy can be divided into three types: leading, lagging, and coordinating. The overall distribution characteristics of the spatial relationship between population and economy in the study area were as follows: in the mountainous area of Southern Anhui, the lag type was dominant, and economic agglomeration lagged behind that of population; in northern Anhui, the coordination type was dominant, and population and economic development were in balance; finally, in central Anhui, the lead type was dominant, and economic agglomeration was greater than population agglomeration. 2) The correlation between terrain factors and the population was higher than that with the economy, with changes in the terrain factors strengthening the influence of terrain on population, compared to on the economy. The areas with an altitude gradient of > 100 m, a slope > 6?, and a relief of > 50 m can be considered focus areas, where economic agglomeration lags behind population agglomeration. They are mainly distributed in the core areas of the Dabie Mountains such as Jinzhai County, Huoshan County, Yuexi County, and Taihu County, and the mountainous areas of Southern Anhui, such as Chizhou City, Huangshan City, and Xuancheng City. In the future, efforts should be made to improve the economic level of this area. 3) The spatial relationship between the population and economy had a certain spatial correlation with topography. In general, with an increase in altitude, slope, and topographic relief, the proportion of leading-type areas reduced, while that of lagging-type areas grew, with the proportion of coordinating-type areas remaining stable. Specifically, with a rise in elevation from 0 m to 1,800 m, the proportion of leading-type areas increased from 54.46% to 58.06%, and then decreased to 4.17%; that of lagging-type areas increased from 26.11% to 79.17%; while the ratio of coordinating-type areas remained stable. With an increase in slope from 0? to 60?, the proportion of leading-type areas increased from 48.66% to 50.31%, and then decreased to 23.77%; that of lagging-type areas increased from 37.45% to 64.83%; while that of coordinating-type areas remained stable. With a topographic relief increase in fluctuation from 0 m to 450 m, the proportion of leading-type areas decreased from 49.69% to 18.03%, that of lagging-type areas increased from 36.66% to 72.13%, and the proportion of coordinating-type areas remained stable. Combined with the economic development of the primary, secondary, and tertiary industries, the undulating surface characteristics could have a significant barrier effect on agricultural mechanization, reducing the convenience of farming and restricting the development of the primary industry. Moreover, due to the dependence of enterprise profits and industrial layout on location, the secondary and tertiary industries are mostly reluctant to invest in regions with complex terrain. A complex terrain, thus, has a significant impact on infrastructure construction, investment, and industrial layout; hinders the development of the secondary and tertiary industries; and weakens regional economic advantages.