Data and replication code for analyzing the variation in urban tree canopy and air temperature reduction in New Haven, Connecticut, 2019 - 2021

Urban trees mitigate urban heat, and impervious surfaces increase air temperatures. But the relationships between land cover (tree canopy and impervious) and air temperature changes throughout the day. The tabular data included in this data publication are used to estimate those changing relationships, while controlling for cloud condition, elevation, location, trip, and wind speed per direction. Data were collected by a study coauthor, a university professor, a university staff member, and a group of incoming masters students using bicycle-mounted air temperature sensors in New Haven, Connecticut. The final dataset includes 156 rides taken between June 15 and September 15 in years 2019, 2020, and 2021. Measurements include the time of day, temperature anomaly (which is the outcome of interest; the temperature recorded via bicycle minus a suburban reference station at the same time), tree canopy and impervious cover percentages summarized with multiple buffer sizes ranging from 10 to 90 meters, cloudiness, elevation, and the wind speed and direction from a reference station. Also included in this package is the R code used to analyze these data.
The goal of this study was to answer the research questions, 1) what are the relationships between air temperature and landcover, and how do they change throughout the day with varied cloud conditions? and 2) how do those landcover-air temperature relationships vary or not among the hottest 25th percentile days?
For more information about this study and these data, see Locke et al. (2024; https://doi.org/10.1016/j.heliyon.2024.e25041).