Authors: Jiangping Zhou*, University of Hong Kong
Topics: Transportation Geography, Urban and Regional Planning
Keywords: Transit-served area; Feature; Performance; Non-traditional data; Shenzhen
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Poydras, Sheraton, 3rd Floor
Presentation File: No File Uploaded
In this study, transit-served areas (TSAs) are defined as areas within a reasonable distance of transit. Transit-oriented development (TOD) is regarded as a subset of TSAs. TSAs have two key dimensions: physical features (attributes) and performance (regarding human behaviors). It is partially because of the characteristics of input (traditional) data that it is difficult for us to measure both the features and performance of TOD/TSAs and develop useful and replicable indicators/benchmarks to differentiate many TSAs simultaneously. It shows that non-traditional data (NTD) can help overcome the about difficulty. Through a case study of Shenzhen, China, it demonstrates how NTD such as social media check-ins, on-line points of interest and human heatmaps can be used to quantify/assess the features and performance of 167 TSAs. Based on the case study, one can find that: the features (measured by the number of POIs with check-ins) and the performance (measured by the number of popular app users) of different TSAs can vary significantly; even for the same TSAs, their features and the performance can vary across days and the extremely underperforming or performing TSAs can be totally different across days; the POI efficiency, that is, the average app users attracted by each POI) seems to be a useful indicator to further differentiate TSAs’ performance.