# Integrating Satellite and Ground Measurements for Predicting Locations of Extreme Urban Heat
## 2 Materials and Methods
### Temperature Collection and Data  
Data on temperatures were collected through vehicular traverses across the study area(s). This method uses vehicle-mounted temperature sensors along with a global positioning system (GPS), and has been used successfully in the past for UHI assessments [9; 10; 11; 12; 13; 14; 15; 19; 20]. Temperatures were collected at a one-second interval using a type \"T\" thermocouple and data logger. In order to track positionality of the recorded temperatures, we recorded latitudes and longitudes at a one-second interval using GPS devices. We divided individual study areas into sub-areas of varying sizes in which drivers had the ability to access a wide range of unique land uses/land covers (LULCs) within a one hour driving period. This maximization of traversing unique LULCs is important for subsequent modeling and analysis, as we wish to train our models on as many configurations of LULCs as exist in our study area. The focus on one-hour traverses aimed to capture a'snapshot' of temperatures through the city, while allowing enough time for drivers to cover their assigned sub-areas. One-hour collection windows have proven to be adequate in previous analyses [9; 12]. Statistics on the traverse-based data collection are found in Table 1.  
Temperature observations collected during these campaigns were not conducted entirely by the authors but rather by a group of volunteers in each of the cities. Before each campaign was initiated, systematic community outreach to potential program partners was undertaken for each city through identifying and contacting \"boundary organizations\" whose mission and/or community-level work aligns with resilience building to climate change. This practice (loosely considered here as a form of collective leadership) enabled each of the organizations to then form collective and shared goals for the urban heat island data, while also allowing them reach out to their social and professional networks to gather sufficient volunteer interest to build the collection teams (usually one to two people per vehicle, though sometimes as many as four per vehicle in Richmond, VA). These volunteers, owing to their extensive backgrounds of working within the environmental, equity, and/or civic engagement  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Study Area**} & \multirow{2}{*}{
\begin{tabular}{c} **Area Covered** \\ **(km\({}^{2}\))** \\ \end{tabular} } & \multirow{2}{*}{**Date**} & \multirow{2}{*}{**\(n\)**} & \multirow{2}{*}{**Number of Drivers**} & \multicolumn{3}{c}{**Observed Temperatures (\({}^{\circ}\)C)**} \\ \cline{6-9}  & & & & & & _Min._ & _Mean_ & _Med._ & _Max._ \\ \hline Richmond, VA & 851 & 13 July 2017 & 103,971 & 12 (9 cars, 3 bicycles) & 24.8 & 31.8 & 33.6 & 39.5 \\ Washington, D.C. & 476 & 28 August 2018 & 74,048 & 9 cars & 20.5 & 30.5 & 32.0 & 39.5 \\ Baltimore, MD & 679 & 29 August 2018 & 79,306 & 9 cars & 22.4 & 30.8 & 31.8 & 40.3 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Overview of temperature collections and data.  
landscape of their cities, were able to then offer each campaign a form of indigenous knowledge and experience of each city's unique LULCs that the authors could never independently integrate before undertaking the projects.  
After assembling this network of campaign volunteers and organizations in each city, a two-hour campaign orientation session on either the evening before or the day of temperature observation traverses was conducted. These orientation sessions introduced the volunteer teams to the physical phenomenon of urban heat islands, outlined several case studies of previous successful campaigns in other cities and their outcomes, and gave detailed explanations of and hands-on experiences with the campaign technology, as well as shared and collective construction of traverse routes through areas of interest. The volunteer teams then completed the traverses independent of each other and returned the temperatures sensors and GPS unit to the analysis team.