The spatial distribution of population is essential for both environmental and socio-economic researches. Traditional studies on the spatial distribution of population are mostly based on single scale analysis and ignores scale dependence of population distribution. Analysing the spatial distribution of population at different scales is beneficial to more exactly reveal the spatial distribution law of population. This paper analyzed and compared the spatial autocorrelation of population density using spatial autocorrelation method and statistical correlations between population density and environment-economic factors including DEM, slope, annual average sunshine hours, annual rainfall, average temperature, land use data and GDP at city, county and 1 km?1 km grid scale, and further discussed the spatial distribution patterns of population and the effective or indicative factors to reveal the spatial distribution law of the population at multi-scales. Some conclusions can be drawn as follows. (1) The information at different levels of details can be obtained by multi-scale analysis of the spatial distribution of population. At the city scale, the spatial distribution patterns of the population can be derived. High density districts are in the southeast of Shandong Province including Jinan, Liaocheng, Tai'an, Jining, Zaozhuang and Heze. At the county scale, the spatial distribution patterns of population of some cities can be displayed, and the cases are Jinan, Jining and Dongying. The population density in Jinan is high and unevenly distributed. The population density in Jining is high and evenly distributed. The population density in Dongying is low and evenly distributed. At the 1 km?1 km grid scale, the spatial distribution patterns of population of counties can be obtained. (2) Spatial distribution law differs with scales. Environment-economic factors have a greater impact on population distribution than spatial autocorrelation at city and county levels. At the city level, average sunshine hours, percentage of rural land, and average temperature are the main indicators of population distribution. The level of economic development to some extent affects the population distribution, and the percentages of urban land, and rural land are indicative of population distribution.