Dr. Jiangping Zhou is Associate Professor and Deputy Director of the Master of Urban Planning program at University of Hong Kong (HKU). He is Chief Examiner of Master of Transport Policy and Planning at HKU. He regularly delivers sessions on big data analytics on public transportation for HKU’s Master of Urban Analytics program. His research focuses on transport/transit systems and land use connections and how to improve their performance. He has published more than 70 articles in English in leading journals such as Proceedings of National Academy of Sciences of the United States of America, Urban Studies, and Journal of American Planning Association. He also has more than 60 refereed articles in the Chinese language. He is currently leading several research projects exploring the nexus of physical infrastructure, land use, and travel behaviors and how better/new data supply/analytics can produce new insights into it and can inform public policies.

• 1. Transit areas 2. A normative framework for transit-area planning 3. Big and open data in transit-area planning: Theory 4. Traditional approaches to transit-area planning 5. Big and open data meets transit-area planning: Practice 6. Identifying and measuring features of transit areas 7. Defining and measuring performance of transit areas 8. Transit areas: Linking features and performance Conclusion: A future of big and open data in transit-area planning

Dr. Jiangping Zhou is Associate Professor and Deputy Director of the Master of Urban Planning program at University of Hong Kong (HKU). He is Chief Examiner of Master of Transport Policy and Planning at HKU. He regularly delivers sessions on big data analytics on public transportation for HKU’s Master of Urban Analytics program. His research focuses on transport/transit systems and land use connections and how to improve their performance. He has published more than 70 articles in English in leading journals such as Proceedings of National Academy of Sciences of the United States of America, Urban Studies, and Journal of American Planning Association. He also has more than 60 refereed articles in the Chinese language. He is currently leading several research projects exploring the nexus of physical infrastructure, land use, and travel behaviors and how better/new data supply/analytics can produce new insights into it and can inform public policies.

• 1. Transit areas 2. A normative framework for transit-area planning 3. Big and open data in transit-area planning: Theory 4. Traditional approaches to transit-area planning 5. Big and open data meets transit-area planning: Practice 6. Identifying and measuring features of transit areas 7. Defining and measuring performance of transit areas 8. Transit areas: Linking features and performance Conclusion: A future of big and open data in transit-area planning

Dr. Jiangping Zhou is Associate Professor and Deputy Director of the Master of Urban Planning program at University of Hong Kong (HKU). He is Chief Examiner of Master of Transport Policy and Planning at HKU. He regularly delivers sessions on big data analytics on public transportation for HKU’s Master of Urban Analytics program. His research focuses on transport/transit systems and land use connections and how to improve their performance. He has published more than 70 articles in English in leading journals such as Proceedings of National Academy of Sciences of the United States of America, Urban Studies, and Journal of American Planning Association. He also has more than 60 refereed articles in the Chinese language. He is currently leading several research projects exploring the nexus of physical infrastructure, land use, and travel behaviors and how better/new data supply/analytics can produce new insights into it and can inform public policies.

• 1. Transit areas 2. A normative framework for transit-area planning 3. Big and open data in transit-area planning: Theory 4. Traditional approaches to transit-area planning 5. Big and open data meets transit-area planning: Practice 6. Identifying and measuring features of transit areas 7. Defining and measuring performance of transit areas 8. Transit areas: Linking features and performance Conclusion: A future of big and open data in transit-area planning