Increased exposure to extreme heat from both climate change and the urban heat island effect—total urban warming—threatens the sustainability of rapidly growing urban settlements worldwide. Extreme heat exposure is highly unequal and severely impacts the urban poor. While previous studies have quantified global exposure to extreme heat, the lack of a globally accurate, fine-resolution temporal analysis of urban exposure crucially limits our ability to deploy adaptations. Here, we estimate daily urban population exposure to extreme heat for 13,115 urban settlements from 1983 to 2016. We harmonize global, fine-resolution (0.05°), daily temperature maxima and relative humidity estimates with geolocated and longitudinal global urban population data. We measure the average annual rate of increase in exposure (person-days/year−1) at the global, regional, national, and municipality levels, separating the contribution to exposure trajectories from urban population growth versus total urban warming. Using a daily maximum wet bulb globe temperature threshold of 30 °C, global exposure increased nearly 200% from 1983 to 2016. Total urban warming elevated the annual increase in exposure by 52% compared to urban population growth alone. Exposure trajectories increased for 46% of urban settlements, which together in 2016 comprised 23% of the planet’s population (1.7 billion people). However, how total urban warming and population growth drove exposure trajectories is spatially heterogeneous. This study reinforces the importance of employing multiple extreme heat exposure metrics to identify local patterns and compare exposure trends across geographies. Our results suggest that previous research underestimates extreme heat exposure, highlighting the urgency for targeted adaptations and early warning systems to reduce harm from urban extreme heat exposure.

We use the Getis/Ord local G statistic and detailed county-level industry employment data from the U.S. Bureau of Labor Statistics to isolate discrete industrial complexes-or groups of nominally linked industries clustered in particular locationsfor two recent years: 1989 and 1997. We describe the characteristics of the complexes in terms of their number, spatial extent, broad regional distribution, and other factors. Data from the two periods help illustrate key shifts in industrial locations, including the continuing concentration of the apparel industry in the Southeast and the ongoing southern shift in U.S. vehicle production.

[1] Dynamic changes in live fuel moisture (LFM) and fuel condition modify fire danger in shrublands. We investigated the empirical relationship between field-measured LFM and remotely sensed greenness and moisture measures from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Moderate Resolution Imaging Spectrometer (MODIS). Key goals were to assess the nature of these relationships as they varied between sensors, across sites, and across years. Most AVIRIS-derived measures were highly correlated with LFM. Visible atmospherically resistant index (VARI) and visible green index (VIg) outperformed all moisture measures. The water index (WI) and normalized difference water index (NDWI) had the highest correlations of the moisture measures. All relationships were nonlinear, and a linear relationship only applied above a 60% LFM. Changes in the fraction of green vegetation (GV) and nonphotosynthetic vegetation (NPV) were good indicators of changes in fuels below the 60% LFM threshold. AVIRIS-and MODIS-derived measures were highly correlated but lacked a 1:1 relationship. MODIS-derived greenness and moisture measures were also highly correlated to LFM but generally had lower correlations than AVIRIS and varied between sites. LFM relationships improved when data were pooled by functional type. LFM interannual variability impacted relationships, producing higher correlations in wetter years, with VARI and VIg showing the highest correlations across years. Lowest correlations were observed for sites that included two different functional types or multiple land cover classes (i.e., urban and roads) within a MODIS footprint. Higher correlations for uniform sites and improved relationships for functional types suggest that MODIS can map LFM effectively in shrublands.

The last decade of the twentieth century was heralded as the 'end of agrarian reform' in Mexico and the initiation of a new era of market-led agricultural policy and practice. The impact of neoliberalism and the North American Free Trade Agreement on smallholder maize production has been widely conceived as negative, associated with ecological degradation, rural emigration and cultural erosion. Yet, some twenty years later, all evidence suggests that smallholder maize production is continuing in Mexico, albeit in evolving structures and forms. This article uses a farm-level survey implemented in three Mexican states to assess the current condition of maize farming in Mexico. The authors revisit past categorizations of Mexican farmers and apply similar approaches to explore what maize-producing households are doing with their maize, and what current patterns of production imply for future Mexican maize policy. They find evidence of greater persistence and adaptability in Mexican maize farming than is often presented. On the basis of their analysis, they advocate for a reconsideration of the underlying assumptions of public policy, highlighting the heterogeneity of the maize landscape and the unrealized and generally unrecognized potential this heterogeneity represents.

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