Urban community green spaces serve as vital leisure areas for residents and hold significant ecological and aesthetic value. Understanding the characteristics of urban community green space landscape patterns and their key influencing factors is crucial for enhancing the ecological functions, quality, and benefits of these green spaces. However, research in this area is still limited. Therefore, this study selected 35 communities of various types across six typical northern Chinese cities, including Beijing, Qingdao, Xi"an, Shenyang, Xining, and Qian"an. Through field surveys and multi-source remote sensing imagery interpretation, the landscape characteristics of green spaces in different cities and community types were analyzed. We constructed a composite index reflecting the characteristics of community green space landscape patterns (i.e., Comprehensive Landscape Pattern Index) based on landscape metrics using factor analysis, and the partial least squares method. This allowed us to evaluate the current situation of green space landscape patterns in different cities and community types and to identify the key factors influencing the landscape patterns of community green spaces in northern cities. The results showed that: (1) There were no significant differences in diversity, aggregation, patch size, and connectivity of community green spaces landscapes across the six cities overall (P>0.05). However, for different types of communities, high-grade newly-built communities had significantly higher aggregation and number of green spaces compared to ordinary old communities (P<0.05). (2) The comprehensive landscape pattern index of green spaces varied by city, ranked from highest to lowest as follows: Qingdao, Beijing, Xining, Qian"an, Shenyang, and Xi"an. Among different types of communities, the ranking was as follows: high-grade new construction > ordinary new construction > high-grade old > ordinary old communities. (3) Socio-economic indicators such as building density, completion time, per capita GDP, and community area were the primary factors affecting the comprehensive index of community green space landscape patterns. In contrast, natural factors like elevation, precipitation, and temperature had relatively little influence. The findings of this study provide a scientific basis for optimizing community green space landscape patterns and enhancing ecological service functions in northern cities of China.