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.

The relationship between the characteristics of the urban land system and land surface temperature (LST) has received increasing attention in urban heat island and sustainability research, especially for desert cities. This research generally employs medium or coarser spatial resolution data and primarily focuses on the effects of a few classes of land-cover composition and pattern at the neighborhood or larger level using regression models. This study explores the effects of land system architecture—composition and configuration, both pattern and shape, of fine-grain land-cover classes—on LST of single family residential parcels in the Phoenix, Arizona (southwestern USA) metropolitan area. A 1 m resolution land-cover map is used to calculate land architecture metrics at the parcel level, and 6.8 m resolution MODIS/ASTER data are employed to retrieve LST. Linear mixed-effects models quantify the impacts of land configuration on LST at the parcel scale, controlling for the effects of land composition and neighborhood characteristics. Results indicate that parcel-level land-cover composition has the strongest association with daytime and nighttime LST, but the configuration of this cover, foremost compactness and concentration, also affects LST, with different associations between land architecture and LST at nighttime and daytime. Given information on land system architecture at the parcel level, additional information based on geographic and socioeconomic variables does not improve the generalization capability of the statistical models. The results point the way towards parcel-level land-cover design that helps to mitigate the urban heat island effect for warm desert cities, although tradeoffs with other sustainability indicators must be considered.