Linna Li, PhD
1. Spatial analysis of cycling patterns in Long Beach using multi-source geographic data.This project will use Geographic Information Science (GIS) and spatial analysis to study cycling patterns in Long Beach and surrounding areas by taking advantage of data from multiple sources, including both authoritative data and crowd-sourced data. The relationship between the actual routes cyclists traveled and existing street conditions will be analyzed and a density map of cycling patterns will be generated. The findings will shed light on cyclists’ route choices, travel behavior, and the conditions of current street bicycle facilities, which are all critical for policy makers who are interested in promoting alternative urban transportation and health- enhancing behaviors.
2. Which place demonstrates the most active lifestyle in the social media?Using geolocated tweets harvested from Twitter API, this project will investigate the spatial patterns of most active places in the US. Tweet messages related to running, biking, walking, dancing, jogging, gym, etc. will be used as an indicator of an active lifestyle. The map of active places will be linked with social and economic factors to find possible correlations.
Skills to develop: public health, geographic information science, data collection, data analysis, programming, writing, communication, map-making, critical and creative thinking.
Office: Peterson Hall 1 Building, Room 229