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Resilience-Oriented Urban Planning
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Table of Contents

Section 1. Introduction, Ayyoob Sharifi and Yoshiki Yamagata.- Section 2. Planning and decision making process.- Section 3. Urban form and typologies.- Section 3. Resilience measurement methodologies.- Section 5. Case studies.- Section 5. Future directions, Yoshiki Yamagata Ayyoob Sharifi.

About the Author

Yoshiki Yamagata graduated from the University of Tokyo (PhD in System Science). Since 1991, he works at the National Institute for Environmental Studies (NIES, Tsukuba). Currently, he is studying about the climate risk management as Principal Researcher of Center for Global Environmental Research (CGER). He is also affiliated with IIASA (Vienna) and Institute of Statistical Mathematics (ISM, Tokyo). His recent research topics include: Land use scenarios, resilient urban planning and International regime networks. He has lecture series at the University of Tokyo, University of Tsukuba and Hokkaido University. Internationally, he has served as Lead author of IPCC, Steering committee of "Global Carbon Project" and Editorial board of "Applied Energy" etc.

Ayyoob Sharifi is a research associate at the Center for Global Environmental Research, National Institute for Environmental Studies and also one of the two Executive Directors of the Global Carbon Project (GCP), a Future Earth core project. As part of his duties as the executive director of the GCP, he is leading the urban flagship activity of the project which is focused on conducting cutting-edge research for supporting climate change mitigation and adaptation in cities. He holds a bachelor's degree in Civil Engineering (Surveying), a master's degree in Urban and Regional Planning, and a doctorate in Environmental Engineering. Ayyoob is interested in pursuing research at the interface of climate change and urban planning. The ultimate goal of his research is to provide further insights into how to develop sustainable and resilient urban communities. He is also interested in developing assessment tools that can be used as decision support systems at the local scale.

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