Urban green space is an important consideration when people purchase housing, and remote sensing technology makes it possible to acquire and analyze urban data on a large scale. The purpose of this article is, using remote sensing data on the Web, to quantify the relationship between urban green space and urban commercial house prices to reflect the increased importance that contemporary urban residents attach to urban green space and the potential economic benefits to real estate that green space enhancement may bring. We establish a model of the impact of urban green space on house prices for three districts in Beijing within the Fifth Ring Road using the hedonic price method, GIS spatial operation, and regression analysis. Then through questionnaire clustering, we summarize the preferences of people of different regions and social attributes in terms of green space accessibility, visibility, and availability indicators. We find that, holding other variables constant, the price of each residence decreases by 0.403 million yuan/m² for each 1 km increase in the distance from the house to the nearest park. Holding other variables constant, each unit increase in the rating of the nearest park increases the price of each residence by 0.144 million yuan/m². Respondents attach more importance to urban green space accessibility than to visibility and availability. Combining these two findings, we propose that the design of green space should take accessibility as the main consideration, that the construction of green space should enhance the coordination between green space and residences, and that the layout of green space should also be differentiated to improve the science of green space system planning. Through this study, we can explore ways to improve the social benefits of public space such as urban green space and help carry out more scientific and reasonable planning of urban green space, so as to promote the sustainable development of environmental and ecological spaces for human settlement.