Identifying commonly used and potentially unsafe transit transfers with crowdsourcing

•We use crowd-sourced ridership data to identify and characterize transit transfers.•We obtain origin-destination ground truth trip data without fare card data.•We identify highly-utilized transfer locations that may need more planning attention.•We merge results with crime data for additional planning insight.•In our Pittsburgh case study, 44% of transfers were less than 10 min.