Makido, Anna2019-10-152020-08-292019-08-30Makido_cornell_0058O_10721http://dissertations.umi.com/cornell:10721bibid: 11050720https://hdl.handle.net/1813/67734Urbanization is rapidly occurring and with this growth in urban populations, it is crucial to plan cities carefully to create a livable and healthy living environment. To better understand human-environment relationships and increase eco-friendly transportation modes, previous studies have discussed the effects of weather variability on urban transportation modes. This study adds to the existing literature by running multiple regressive models to examine the weather-cycling relationship using a variety of temporal scales. Additionally, microclimate simulations were conducted to calculate location specific Universal Thermal Comfort Index (UTCI) values in New York City. Findings indicate that cyclists are more vulnerable to weather variability during the Spring and Fall seasons. The regression results for UTCI suggest that outdoor thermal comfort can be used as a predictor for cycling activity. Furthermore, the simulated location specific UTCI values displayed a stronger effect on bike usage. These findings highlight the importance of conducting microclimate simulations.en-USBig Datacyclingmicroclimate modelingoutdoor thermal comfortUTCISimulationUrban planningEnvironmental sciencesustainabilityExamining How Weather and Outdoor Thermal Comfort Variability Affects Cycling Activity Using Big Data and Microclimate SImulations in New York Citydissertation or thesishttps://doi.org/10.7298/dk8n-bt95