# Integrating Satellite and Ground Measurements for Predicting Locations of Extreme Urban Heat
## 5 Conclusions  
Emerging tools can further help to apply urban heat assessments across the United States or globally. Climate Engine, an on-demand processor of satellite and climate data, provides an extensive set of variables for examination of climate impacts such as extreme heat, drought, and wildfire [43]. Climate Engine uses remote sensing data from platforms such as Landsat 4, 5, 7, and 8, and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra to quickly assess, analyze, and visualize hazard and population information at various scales over large areas [43; 44]. Moreover, remote sensing data may serve to inform decision-making frameworks, such as the National Oceanic and Atmospheric Administration's (NOAA) Climate Resilience Toolkit. With enhanced informing of hazards and vulnerabilities, communities may be empowered through the Toolkit to better evaluate risks and costs associated with natural disasters such as extreme heat and develop appropriate mitigation and adaptation solutions [45]. Other efforts by civic leaders and organizations aim to coordinate resilience activities across cities and regions while engaging citizens to take action in their communities. The novel framework described in the present study offers researchers the ability to measure and understand community exposure to extreme heat. Using volunteer-based, community science-led urban heat assessments provides a direct means for low-cost, and highly predicative descriptions of temperature. Our in situ observations and model surfaces for three Mid-Atlantic metropolitan regions point to substantial and land-use specific variation in ambient temperatures across time and space, on the order of \(\sim\)10 \({}^{\circ}\)C for the same time period and up to \(\sim\)18 \({}^{\circ}\)C throughout the diurnal cycle (Table 2), addressing research question (1) and, in part, research question (2). Through combining both satellite-derived and in situ data, our heat island model surfaces are shown to be highly predictive within several dense urban environments spanning the Mid-Atlantic region, an area of the USA that is acutely impacted by increasing extreme heat waves [1]. We identified extreme disparity in air temperature maximums within our study areas that is dominantly controlled and amplified by land use features such as dense, sparsely vegetated urban cores and major arterial roadways, regardless of latitude and areal extent. As a result, our study underscores the need for assessments for current climate vulnerabilities, and for potential future climate change exacerbation. We offered the maps as rhetorical tools for public discourse, and as examples of finding mechanisms to develop city-scale resilience plans, one neighborhood at a time. With enhanced information about the scale of worsening hazards and vulnerabilities, communities may be empowered with increasingly precise and accurate heat data to better evaluate exposure, sensitivity, and vulnerability to worsening natural disasters like extreme heat. Additionally, the method described here highlights how civic leaders, resilience boundary organizations, and cultural institutions (such as science centers and museums) can coordinate climate resilience-building activities across cities and regions while engaging community members to take climate action within their neighborhoods. As climate change continues to increase the duration, intensity, and frequency of extreme heat waves, concomitantly with further expansion and densification of urban areas, collaborative informational field campaigns can provide actionable data for decision makers for any region. [PERSON] conceived of and collected the data for the study and contributed to the writing of the full manuscript. [PERSON] participated in the collection of field data from Richmond, V.A., performed the analysis, and wrote parts of the methods and results sections. [PERSON] contributed to the collection of relevant materials and field data from Baltimore and Washington DC field locations, formatting, and some writing of the manuscript.