This research identifies places that concentrate a large proportion of activity in Singapore, and explores a methodology to characterize them based on features of the physical environment, demographics and arrangements of activity. The methodology utilizes a spatial-temporal algorithm of pattern detection based on cellphone data aggregated into a “SpotRank” score of hourly relative frequencies within 100×100 meter cells. Our study shows a rich variation in the spatial and temporal scales of popular destinations, as well as their internal distribution and mix of activities. Identifying and characterizing ‘non-work destinations’ requires consideration of several dimensions and scales. However, this blend and spatial structure provide rich information about the character and location of non-work trips.
About the speaker
Roberto Ponce-Lopez is a doctoral candidate in Urban Information Systems in the Massachusetts Institute of Technology (MIT). For the past three years, he has worked as research assistant in the Singapore MIT Alliance for Research (SMART), modelling housing prices and residential choices. His broad area of interest consists of using methods from urban information systems to explore the relationship between urban morphology with spatial sorting of activities and people within cities. Roberto completed a M.Sc. in Public Policy at Carnegie Mellon University. His professional work experience includes Office of the President of Mexico as head of the Geostatistics department.