A three-month lockdown in the U.S. at the beginning of the COVID-19 outbreak in 2020 greatly reduced the traffic volume in many cities, especially large metropolitan areas such as the San Francisco Bay Area. This research explores the impact of transportation on climate change by using remote sensing technology and statistical analysis during the COVID-19 lockdown. Using thermal satellite data, this research measures the intensity of the urban heat island, the main driver for climate change during the urbanization process. The research team acquired morning and afternoon MODIS data in the same periods in 2019 before the pandemic and 2020 during the pandemic. MODIS imagery provides a wall-to-wall land surface temperature map to precisely measure the dynamics of the urban heat effect. In situ meteorological data were also acquired to build an urban surface energy budget and construct statistical models between solar radiation and the intensity of heat dynamics. The team implemented this urban heat budget in six counties in Northern California. This research quantifies the impact of lockdown policies on heat intensity in urban areas and human mobility in the context of COVID-19 and future pandemics. The quantitative results obtained in this study provide critical information for analyses of climate change impact on an urban scale.
Sustainable Transportation and Land Use, Transportation Technology
Digital Object Identifier
Mineta Transportation Institute URL
Remote sensing, MODIS, Urban heat island, Traffic volume, COVID-19
Structural Engineering | Transportation | Transportation Engineering
My-Thu Tran and Bo Yang. "Using Thermal Remote Sensing to Quantify Impact of Traffic on Urban Heat Islands during COVID" Mineta Transportation Institute Publications (2023). https://doi.org/10.31979/mti.2023.2207