Search for: All records

Abstract Urban agriculture has significant potential to address food security and nutritional challenges in cities. However, water access for urban food production poses a major challenge in the face of climate change and growing global freshwater scarcity, particularly in arid and semi‐arid areas. To support sustainable urban food production, this study focuses on a hybrid urban water system that integrates two important alternative water resources: a decentralized system of rainwater harvesting (RWH) and a centralized reclaimed water system. A new spatial optimization model is developed to identify the best investment strategy for deploying these two alternative water infrastructures to expand urban food production. The model is applied to the case study in Tucson, Arizona, a semi‐arid city in U.S. Southwest, to address food deserts in the region. Results show that 72%–96% of the investment is allocated to rainwater tanks deployment across all investment scenarios, with the proportion of investment in rainwater harvesting increasing as total investment rises. However, rainwater contributes only about 18%–27% of the total food production. The results of our case study indicate that expanding the reclaimed water network is more effective for urban food production and is also more cost‐efficient compared to implementing rainwater tanks. The new model can be applied to other regions, taking into account factors such as crop types, climate, soil conditions, infrastructure configurations, costs, and other site‐specific variables. The study provides valuable insights for planning urban water systems that incorporate alternative water sources under different investment scenarios. 

Abstract Urban informatics appears to be a suitable area for the application of digital twins. Definitions of the term share some characteristics, but these definitions do not agree on what exactly constitutes a digital twin. The term has the potential to be misleading unless adequate attention is paid to the inherent uncertainty in any replica of a real system. The question of uncertainty is addressed, together with some of the issues that make its quantification problematic. Digital twins for urban informatics pose questions of purpose, governance, and ethics. In the final section the paper suggests some research issues that will need to be addressed if digital twins are to be successful. 

An amendment to this paper has been published and can be accessed via a link at the top of the paper. 

Given widespread concerns over human-mediated bee declines in abundance and species richness, conservation efforts are increasingly focused on maintaining natural habitats to support bee diversity in otherwise resource-poor environments. However, natural habitat patches can vary in composition, impacting landscape-level heterogeneity and affecting plant-pollinator interactions. Plant-pollinator networks, especially those based on pollen loads, can provide valuable insight into mutualistic relationships, such as revealing the degree of pollination specialization in a community; yet, local and landscape drivers of these network indices remain understudied within urbanizing landscapes. Beyond networks, analyzing pollen collection can reveal key information about species-level pollen preferences, providing plant restoration information for urban ecosystems. Through bee collection, vegetation surveys, and pollen load identification across ~350 km of urban habitat, we studied the impact of local and landscape-level management on plant-pollinator networks. We also quantified pollinator preferences for plants within urban grasslands. Bees exhibited higher foraging specialization with increasing habitat heterogeneity and visited fewer flowering species (decreased generality) with increasing semi-natural habitat cover. We also found strong pollinator species-specific flower foraging preferences, particularly for Asteraceae plants. We posit that maintaining native forbs and supporting landscape-level natural habitat cover and heterogeneity can provide pollinators with critical food resources across urbanizing ecosystems. 

Abstract We study the problem of synthesizinglockdown policies—schedules of maximum capacities for different types of activity sites—to minimize the number of deceased individuals due to a pandemic within a given metropolitan statistical area (MSA) while controlling the severity of the imposed lockdown. To synthesize and evaluate lockdown policies, we develop a multiscale susceptible, infected, recovered, and deceased model that partitions a given MSA into geographic subregions, and that incorporates data on the behaviors of the populations of these subregions. This modeling approach allows for the analysis of heterogeneous lockdown policies that vary across the different types of activity sites within each subregion of the MSA. We formulate the synthesis of optimal lockdown policies as a nonconvex optimization problem and we develop an iterative algorithm that addresses this nonconvexity through sequential convex programming. We empirically demonstrate the effectiveness of the developed approach by applying it to six of the largest MSAs in the United States. The developed heterogeneous lockdown policies not only reduce the number of deceased individuals by up to 45 percent over a 100 day period in comparison with three baseline lockdown policies that are less heterogeneous, but they also impose lockdowns that are less severe. 

In this commentary we reflect on the potential and power of geographical analysis, as a set of methods, theoretical approaches, and perspectives, to increase our understanding of how space and place matter forall. We emphasize key aspects of the field, including accessibility, urban change, and spatial interaction and behavior, providing a high‐level research agenda that indicates a variety of gaps and routes for future research that will not only lead to more equitable and aware solutions to local and global challenges, but also innovative and novel research methods, concepts, and data. We close with a set of representation and inclusion challenges to our discipline, researchers, and publication outlets.