Urban sprawl is considered as a western urban development pattern, which is common in different cities around the world. Although a large number of studies have focused on urban sprawl, modeling urban sprawl has been less emphasized, especially in various geographical contexts. The present study aimed to investigate urban sprawl and its determinants in a post-socialist country and model urban sprawl based on disaggregated data. In addition, the correlations of urban sprawl with travel patterns were examined, along with the socioeconomic characteristics of university students in Krakow, Poland by applying the Weighted Least Square (WLS) regression model. The WLS regression model was fitted based on the data from 1288 online questionnaires targeting university students. Also, urban sprawl around the home and the university for each student who indicated the nearest intersection to their home and university were separately estimated by employing Shannon entropy. Based on the findings, urban sprawl around homes was correlated with 14 transport patterns and socioeconomic features such as gender, age, driving license, financial dependency status, gross monthly income, number of commute trips, mode of transportation for commuting, number of trips for shopping or entertainment, daily shopping area, mode choice for shopping and entertainment trips inside and outside the neighborhoods, frequency of public transport use, attractiveness of shops inside the neighborhoods, and the length of time living in current home. Furthermore, urban sprawl around the university was significantly correlated with age, car ownership, number of commute trips, and sense of belonging to neighborhoods, entertainment place, and residential location choice. Finally, a positive correlation was reported between urban sprawl with higher income, elderly student, financial dependent students, and car dependency trips, while urban sprawl was negatively related to the use of public transit.
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