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.

This study seeks to determine the role of land architecture—the composition and configuration of land cover—as well as cadastral/demographic/economic factors on land surface temperature (LST) and the surface urban heat island effect of Phoenix, Arizona. It employs 1 m National Agricultural Imagery Program data of land-cover with 120mLandsat-derived land surface temperature, decomposed to 30 m, a new measure of configuration, the normalized moment of inertia, and U.S. Census data to address the question for two randomly selected samples comprising 523 and 545 residential neighborhoods (census blocks) in the city. The results indicate that, contrary to most other studies, land configuration has a stronger influence on LST than land composition. In addition, both land configuration and architecture combined with cadastral, demographic, and economic variables, capture a significant amount of explained variance in LST. The results indicate that attention to land architecture in the development of or reshaping of neighborhoods may ameliorate the summer extremes in LST.

Interdependent systems providing water and energy services are necessary for agriculture. Climate change and increased resource demands are expected to cause frequent and severe strains on these systems. Arizona is especially vulnerable to such strains due to its hot and arid climate. However, its climate enables year-round agricultural production, allowing Arizona to supply most of the country's winter lettuce and vegetables. In addition to Phoenix and Tucson, cities including El Paso, Las Vegas, Los Angeles, and San Diego rely on Arizona for several types of agricultural products such as animal feed and livestock, meaning that disruptions to Arizona's agriculture also disrupt food supply chains to at least six major cities.

Arizona's predominately irrigated agriculture relies on water imported through an energy intensive process from water-stressed regions. Most irrigation in Arizona is electricity powered, so failures in energy or water systems can cascade to the food system, creating a food-energy-water (FEW) nexus of vulnerability. We construct a dynamic simulation model of the FEW nexus in Arizona to assess the potential impacts of increasing temperatures and disruptions to energy and water supplies on crop irrigation requirements, on-farm energy use, and yield.

We use this model to identify critical points of intersection between energy, water, and agricultural systems and quantify expected increases in resource use and yield loss. Our model is based on threshold temperatures of crops, USDA and US Geological Survey data, Arizona crop budgets, and region-specific literature. We predict that temperature increase above the baseline could decrease yields by up to 12.2% per 1 °C for major Arizona crops and require increased irrigation of about 2.6% per 1 °C. Response to drought varies widely based on crop and phenophase, so we estimate irrigation interruption effects through scenario analysis. We provide an overview of potential adaptation measures farmers can take, and barriers to implementation.

Recent developments in computational software and public accessibility of gridded climatological data have enabled researchers to study Urban Heat Island (UHI) effects more systematically and at a higher spatial resolution. Previous studies have analyzed UHI and identified significant contributors at the regional level for cities, within the topology of urban canyons, and for different construction materials.

In UHIs, air is heated by the convective energy transfer from land surface materials and anthropogenic activities. Convection is dependent upon the temperature of the surface, temperature of the air, wind speed, and relative humidity. At the same time, air temperature is also influenced by greenhouse gases (GHG) in the atmosphere. Climatologists project a 1-5°C increase in near-surface air temperature over the next several decades, and 1-4°C specifically for Los Angeles and Maricopa during summertime due to GHG effects. With higher ambient air temperatures, we seek to understand how convection will change in cities and to what ends.

In this paper we develop a spatially explicit methodology for quantifying UHI by estimating the daily convection thermal energy transfer from land to air using publicly-available gridded climatological data, and we estimate how much additional energy will be retained due to lack of convective cooling in scenarios of higher ambient air temperature.

The impacts of land-cover composition on urban temperatures, including temperature extremes, are well documented. Much less attention has been devoted to the consequences of land-cover configuration, most of which addresses land surface temperatures. This study explores the role of both composition and configuration—or land system architecture—of residential neighborhoods in the Phoenix metropolitan area, on near-surface air temperature. It addresses two-dimensional, spatial attributes of buildings, impervious surfaces, bare soil/rock, vegetation and the “urbanscape” at large, from 50 m to 550 m at 100 m increments, for a representative 30-day high sun period. Linear mixed-effects models evaluate the significance of land system architecture metrics at different spatial aggregation levels. The results indicate that, controlling for land-cover composition and geographical variables, land-cover configuration, specifically the fractal dimension of buildings, is significantly associated with near-surface temperatures. In addition, statistically significant predictors related to composition and configuration appear to depend on the adopted level of spatial aggregation.