Active Transportation: Geoinformatics and Big Data for Sustainable Urban Mobility

Cohen Achituv

Active transportation, such as walking and bicycling, is a crucial element of modern urban planning, significantly influencing the environmental, social, and economic dynamics of cities. Factors like street design, destination proximity, connectivity, and subjective perceptions such as safety and comfort play pivotal roles in shaping walkability and bikeability. However, accurately assessing what drives individuals to choose active transportation remains a challenge.

In this seminar, Dr. Achituv Cohen will share insights from his research and other studies on active transportation, utilizing Geographic Information Systems (GIS) and geospatial data science. He will delve into how innovative methodologies, such as machine learning and deep learning, offer new ways to analyze walking and cycling behavior. Furthermore, he will discuss emerging trends like incorporating subjective perceptions and improving accessibility for vulnerable populations. These approaches not only enhance our understanding of the factors that influence active transportation choices and urban mobility but also contribute to the development of more inclusive and sustainable communities.