Discovering regions of different functions in a city using human mobility and POIs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Inferring land use from mobile phone activity
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
Discovering urban spatial-temporal structure from human activity patterns
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
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Identifying the spatial structure generated by urban movements contributes to a better understanding of urban dynamics and is crucial to urban planning applications. Despite a number of studies concerning functional urban space, related research is still in a development phase, especially using emerging urban movement data. This study proposes a centrality index and attractiveness indices for detecting the urban spatial structure of functional centers and their spatial impacts using transportation data. The basic idea of these indices is to build a relationship between the activity patterns (distribution, density, and diversity) and urban form. Accordingly, measurements, spatial analysis, and clustering methods are presented. Taking Singapore as a case study area, we applied the proposed indices and measurements to travel survey data of different years, through which centers of urban activities as well as the changing urban form are detected and compared quantitatively. Our approach yields important insights into urban phenomena generated by human movements. It represents a novel way of quantitative urban analysis and explicit urban change identification.