In the context of global warming, to analyse spatial differentiation patterns of carbon emissions from urban residential energy consumption is of great importance. We took the city of Kaifeng as the case area, which is one of the typical small and medium-sized cites in the north of central heating transition zone of China. This study was based on questionnaire surveys, in which there are 1433 valid answers related to 5475 residents. Using the methods as descriptive statistical analysis, spatial autocorrelation analysis as well as the standard deviation ellipse analysis, we studied the spatial characteristics of the carbon emissions in term of the family-based urban resident's energy consumption in the urban area of Kaifeng city for 2015. Our study has achieved the following conclusions: (1) The carbon emissions of urban residents' energy consumption have the positive correlation in terms of spatial distribition, especially in the gathering region of high value. The high carbon emissions were observed in new urban development zone, or in the built-up area expanding faster. This is the area where there are new high- grade commercial housing estates, or the housing zone of the government- affiliated institutions. The low carbon emissions were mainly found in the region where the buildings were built up much earlier, and there is no further or less development. Mostly it is the zone with old commercial housing estate, or small local residential communities; (2) In Kaifeng city, the carbon emissions by household electricity consumption accounted for 67% of the total carbon emissions. The spatial pattern of per capita carbon emissions from residents' energy consumption was subject to heating carbon emissions, and the spatial pattern of per capita heating carbon emissions was subject to spatial pattern of central heating carbon emissions. Therefore, in order to reduce the carbon emissions of residents' energy consumption, it is important to reduce energy consumption from central heating system, and also narrow down the differences of per capita heating energy; (3) The family-based monthly income, the layout of centrally heating facilities and structure of the urban development are the main driving factors for the formation of the spatial dependence and spatial heterogeneity of carbon emissions from residential energy consumption.