att_abstract={{In the past, sensors networks in cities have been limited to fixed sensors,
embedded in particular locations, under centralised control. Today, new
applications can leverage wireless devices and use them as sensors to develop
aggregated information. In this paper, we show that the emerging patterns
unveiled through the analysis of large sets of aggregated digital footprints can
provide novel insights into how people experience the city and into some of the
drives behind these emerging patterns. This information has uses for local
authorities, researchers, as well as service providers such as mobile network
operators. To explore this capacity for quantifying urban attractiveness, we
performed a case study using the distribution and density of digital footprints in
the area of the New York City Waterfalls, a public art project of four man-made
waterfalls rising from the New York Harbor. Methods to study the impact of an
event of this nature are traditionally based on the collection of static information
such as surveys and ticket-based people counts, which allow to generate
estimates about visitors´┐Ż presence in specific areas over time. In contrast, our
contribution makes use of the dynamic data that visitors generate, such as the
amount and distribution of aggregate phone calls and photos taken in different
areas of interest and over time. Our analysis provides novel ways to quantify the
impact of the public art exhibit on the distribution of visitors and the attractiveness
of points of interest in the proximity of the event.}},
	att_copyright={{This work is licensed under the Creative Commons Attribution-Non-commercial Works 3.0 License}},
	att_tags={digital earth, digital footprints, urban studies, reality mining},
	author={Fabien Girardin and Andrea Vaccari and Alexandre Gerber and Assaf Biderman and Carlo Ratti},
	institution={{International Journal of Spatial Data Infrastructures Research, Volume 4 (2009) pp. 175-200}},
	title={{Quantifying urban attractiveness from the distribution and density of digital footprints}},