Urban freight transportation plays a vital role in meeting the cargo needs of citizens' lives and business operations. Using establishment factors to analyze urban freight generation does not effectively aid the government in developing urban freight management policies to guarantee economic growth and reduce negative externalities of urban freight. This paper explores the impact of the built environment factor on urban freight generation by creating regression models using goods transported by light freight vehicles in the central city of Shanghai. The models are constructed separately for all traffic analysis zones and the three types of traffic analysis zones after classification. The results show that the models for the classified three types of traffic analysis zones have higher accuracy and that land areas of different uses can be combined with population and employment to jointly predict the size of freight generation for residential life, commercial activities, and production activities.

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