  How to assess the potential of liking a city or a neighborhood before ever
having been there. The concept of urban quality has until now pertained to
global city ranking, where cities are evaluated under a grid of given
parameters, or either to empirical and sociological approaches, often
constrained by the amount of available information. Using state of the art
machine learning techniques and thousands of geotagged satellite and
perspective images from diverse urban cultures, this research characterizes
personal preference in urban spaces and predicts a spectrum of unknown likeable
places for a specific observer. Unlike most urban perception studies, our
intention is not by any means to provide an objective measure of urban quality,
but rather to portray personal views of the city or Cities of Indexes.
