Goodspeed and Yan Write Chapter in Big Data for Regional Science
Assistant Professor Robert Goodspeed and Urban Planning PhD student Xiang Yan have contributed a chapter, “Crowdsourcing street beauty: visual preference surveys in the big data era” to the book Big Data for Regional Science.
The book was published on 17 August 2017. A limited preview of the chapter can be read here, including this introduction:
Aesthetic preferences for landscapes have been studied by researchers in many fields, given the importance of the issue to human well-being, ecosystem sustainability and public policy. […] The aim of this chapter is to demonstrate how utilizing new data sources and techniques in the big data era could transform this type of research. The utilizes images from Google Street View to obtain preference data through crowdsourcing, applies the Elo algorithm to transform the pairwise voting data into continuous beauty scores and then relates these scores to urban landscape indicators constructed from publicly available GIS data ( Figure 7.1 ). The remainder of the introduction reviews previous research, and describes how the method described here helps address four problems identified through a methodological review of landscape preference research.
Another closely related article by Goodspeed in Landscape and Urban Planning, “Research note: An evaluation of the Elo algorithm for pairwise visual assessment surveys,” can be accessed on this website.