Seeing differently : cartography for subjective maps based on dynamic urban data

What should maps look like in the information age? This thesis proposes dynamic subjective map - maps that are tailored to the context of the observer - to digitally bridge the gap between man in cities and massive urban data. Maps affect the way people see the world profoundly. Throughout history, maps have been evolving from subjectivity and ideals towards objectivity and accuracy. Cartography has become a precise science that excludes much inspiring narrative, which was commonly seen in ancient maps. On the other hand, during the past two decades, the nature of cities has been undergoing an enormous shift powered by information technology that avails a vast variety of data by tracking people's behavior in the city, such as GPS navigation based on real-time traffic status. As a result, the work, travel and social patterns of urban residents have been gradually transformed. Despite availability of such data, there is no satisfying means to help people in the city interpreting and visualizing them effectively. The maps that designers produce today are still static geographic representations, paying little attention to human activity. The dynamic subjective map in this thesis explores ways to embed narrative and meaning into urban data visualization, and uses animation and interaction to create a more personalized cartography. In this map, space is no longer defined by geographical features alone, but with human-related factors such as transportation time, population density or social connections as well. The thesis starts by looking into the origin and purpose of dynamic subjective maps. Then it describes the principles and methodologies used in producing them. A selection of case studies is used to demonstrate the design process and implementation techniques of such maps in two typical contexts: isochronic maps and relevance-equalizing maps. The dynamic subjective maps presented in this thesis show possibilities of representing cities through the use of the latest computation technology from perspectives that are rarely seen before. The work also delivers a set of toolkits that are useful in visualizing massive urban data streams and is expected to inspire planners, architects and the general public to reflect upon their understanding of cities.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Architecture.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2011

Author dc:creator

• Chen, Xiaoji, S.M. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Takehiko Nagakura and Carlo Ratti.

• Architecture.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/65543

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/65543