University campuses provide unique mixed land use, multimodal, and walkable environments to students, faculty, and staff. Often, these campuses are islands of sustainable transport within mostly auto-oriented cities. Campuses are often internally balanced, with most amenities needed by the campus community located within walking distance. Campus populations vary widely but can range from several thousand to tens of thousands, the size of a small town. Universities can also be the largest single employer in many urban areas, providing significant leverage when developing transportation planning strategies. Despite millions of university students and employees, little research has been conducted on best practices and unique methods of transportation and environmental analysis for these unique cases. Universities are increasingly developing comprehensive transportation and environmental plans with little guidance on the best approaches that cater to the unique features of universityrelated travel.Universities have relatively unique many-to-one travel patterns and tend to have central control over transportation and land-use policies (e.g., parking) for the campus community. Moreover, universities tend to keep some household data on all or most campus users (e.g., home address). These features make some traditional transportation and environmental planning and travel demand management (TDM) strategies ill-fitting for campuses.This paper presents a unique methodology with specific cases outlined for exploiting some of the data and travel behaviors that are available to universities. We focus on pairing specific origin (home location) data provided by universities with traditional travel and activity surveys to identify travel demands and opportunities for improved TDM. This is a novel contribution relative to mostly descriptive university-related travel research-allowing more precise policy interventions. We do this in the context of traditional TDM plans and emerging campus greenhouse gas (GHG) inventories and climate action plans.The paper is organized as follows. First, we describe the existing work on campus transportation planning and identify gaps in the literature. Next, we propose a method 781659T RRXXX10.