Document Type

Conference Proceeding

Publication Date

4-10-2015

Abstract

The rate of urbanization in developing countries, defined as the speed with which a population shifts from rural to urban areas, is among the highest in the world. The disproportionate number of citizens that live in a small numbers of cities places incredible pressure on the largest cities in these countries, which may already be faced with limited resources, weak industrialization, and underdeveloped infrastructures. Urban planning researchers as well as policy makers have suggested that governments in developing countries make capital investments within and surrounding smaller cities to attract citizens away from large urban centers, thereby lowering the pressure placed on overpopulated urban centers and making it more attractive for citizens to migrate to the smaller cities. This paper proposes a methodology that maps signals in mobile phone usage data to longstanding urban planning theories. These signals are subsequently combined in an unsupervised learner to discover regions within which city investments should be made. Qualitative evaluations of the selected arrondissements illustrate the promise of our approach.

Comments

Presented at the International Conference on the Analysis of Mobile Phone Datasets Data for Development Challenge, April 10, 2015.

The accompanying poster can be found at http://www.netmob.org/assets/img/NetMob%202015_D4D%20Challenge%20Senegal_Sessions_Posters.pdf on page 43.

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