There is growing support for investments to promote pedestrian travel. Metropolitan planning organizations (MPOs) are improving travel demand forecasting models to better address policy-relevant issues like air quality, public health, and the smart allocation of infrastructure. This report describes an innovative method to integrate walking activity into trip-based travel models. Using data for the Portland, OR, metropolitan area, the method applies trip generation at a new micro-scale spatial unit: a pedestrian analysis zone (PAZ). Next, a binary logit walk mode split model estimates the number of walk trips generated. Non-walk trips are aggregated up to transportation analysis zones (TAZs) for destination choice, mode choice, and traffic assignment. This method improves travel modelsÕ sensitivity to walking influences, and it could operate as a standalone tool for rapid scenario analysis. Care must be taken when applying this method with respect to scalability, forecasting, and operational challenges.