Phoenix Regional Heat and Air Quality Knowledge Repository

Context:
With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives:
We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA.

Methods:
We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey.

Results:
Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures.

Conclusions:
Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

This study examines the impact of spatial landscape configuration (e.g., clustered, dispersed) on land-surface temperatures (LST) over Phoenix, Arizona, and Las Vegas, Nevada, USA. We classified detailed land-cover types via object-based image analysis (OBIA) using Geoeye-1 at 3-m resolution (Las Vegas) and QuickBird at 2.4-m resolution (Phoenix). Spatial autocorrelation (local Moran’s I ) was then used to test for spatial dependence and to determine how clustered or dispersed points were arranged. Next, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired over Phoenix (daytime on 10 June and nighttime on 17 October 2011) and Las Vegas (daytime on 6 July and nighttime on 27 August 2005) to examine day- and nighttime LST with regard to the spatial arrangement of anthropogenic and vegetation features. Local Moran’s I values of each land-cover type were spatially correlated to surface temperature. The spatial configuration of grass and trees shows strong negative correlations with LST, implying that clustered vegetation lowers surface temperatures more effectively. In contrast, clustered spatial arrangements of anthropogenic land-cover types, especially impervious surfaces and open soil, elevate LST. These findings suggest that city planners and managers should, where possible, incorporate clustered grass and trees to disperse unmanaged soil and paved surfaces, and fill open unmanaged soil with vegetation. Our findings are in line with national efforts to augment and strengthen green infrastructure, complete streets, parking management, and transit-oriented development practices, and reduce sprawling, unwalkable housing development.

Cities are developing innovative strategies to combat climate change but there remains little knowledge of the winners and losers from climate-adaptive land use planning and design. We examine the distribution of health benefits associated with land use policies designed to increase vegetation and surface reflectivity in three US metropolitan areas: Atlanta, GA, Philadelphia, PA, and Phoenix, AZ. Projections of population and land cover at the census tract scale were combined with climate models for the year 2050 at 4 km × 4 km resolution to produce future summer temperatures which were input into a comparative risk assessment framework for the temperature-mortality relationship. The findings suggest disparities in the effectiveness of urban heat management strategies by age, income, and race. We conclude that, to be most protective of human health, urban heat management must prioritize areas of greatest population vulnerability.

We use the Northeast US Urban Climate Archipelago as a case study to explore three key limitations of planning and policy initiatives to mitigate extreme urban heat. These limitations are: (1) a lack of understanding of spatial considerations—for example, how nearby urban areas interact, affecting, and being affected by, implementation of such policies; (2) an emphasis on air temperature reduction that neglects assessments of other important meteorological parameters, such as humidity, mixing heights, and urban wind fields; and (3) too narrow of a temporal focus—either time of day, season, or current vs. future climates. Additionally, the absence of a direct policy/planning linkage between heat mitigation goals and actual human health outcomes, in general, leads to solutions that only indirectly address the underlying problems. These issues are explored through several related atmospheric modeling case studies that reveal the complexities of designing effective urban heat mitigation strategies. We conclude with recommendations regarding how policy-makers can optimize the performance of their urban heat mitigation policies and programs. This optimization starts with a thorough understanding of the actual end-point goals of these policies, and concludes with the careful integration of scientific knowledge into the development of location-specific strategies that recognize and address the limitations discussed herein.