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1. Comparing land surface temperature and mean radiant temperature for urban heat mapping in Philadelphia

   https://doi.org/10.1016/j.uclim.2023.101615  

   Li, Xiaojiang; Chakraborty, TC; Wang, Guoqing (September 2023, Urban Climate)

   Many cities are experiencing more frequent extreme heat during hot summers. With the rise of global temperature, the thermal comfort in urban areas become even worse. Quantitative information of the spatial distributions of urban heat has become increasingly important for resilience and adaptation to climate change in cities. This study compares satellite-derived land surface temperature (LST) and urban microclimate modeling-based mean radiant temperature (Tmrt) for mapping the urban heat distributions in Philadelphia, Pennsylvania, USA. The LST was estimated based on Landsat 8 thermal imagery with a spatial resolution of around 100 m, while the Tmrt was simulated based on high resolution LiDAR and national aerial imagery program multispectral aerial imageries with a spatial resolution of 1 m. Result shows that both LST and Tmrt show a similar general pattern of the urban heat across the study area, while the Tmrt presents much more details of the heat variations street by street and neighborhood by neighborhood. The LST tends to have a stronger relationship with the Tmrt on building roofs, which are usually not the place for human activities. This studyprovides evidence for choosing more appropriate metrics in urban heat-related studies. 

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2. Maximizing the pedestrian radiative cooling benefit per street tree

   https://doi.org/10.1016/j.landurbplan.2022.104608  

   Lachapelle, Jacob A; Scott_Krayenhoff, E; Middel, Ariane; Coseo, Paul; Warland, Jon (February 2023, Landscape and Urban Planning)

   Outdoor heat stress is a growing problem in cities during hot weather. City planners and designers require more pedestrian-centered approaches to understand sidewalk microclimates. Radiation loading, as quantified by mean radiant temperature (TMRT), is a key factor driving poor thermal comfort. Street trees provide shade and consequently reduce pedestrian TMRT. However, placement of trees to optimize the cooling they provide is not yet well understood. We apply the newly-developed TUF-Pedestrian model to quantify the impacts of sidewalk tree coverage on pedestrian TMRT during summer for a lowrise neighbourhood in a midlatitude city. TUF-Pedestrian captures the detailed spatio-temporal variation of direct shading and directional longwave radiation loading on pedestrians resulting from tree shade. We conduct 190 multi-day simulations to assess a full range of sidewalk street tree coverages for five high heat exposure locations across four street orientations. We identify street directions that exhibit the largest TMRT reductions during the hottest periods of the day as a result of tree planting. Importantly, planting a shade tree on a street where none currently exist provides approximately 1.5–2 times as much radiative cooling to pedestrians as planting the same tree on a street where most of the sidewalk already benefits from tree shade. Thus, a relatively equal distribution of trees among sun-exposed pedestrian routes and sidewalks within a block or neighbourhood avoids mutual shading and therefore optimizes outdoor radiative heat reduction per tree during warm conditions. Ultimately, street tree planting should be a place-based decision and account for additional environmental and socio-political factors. 

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3. Sensitivity and vulnerability to summer heat extremes in major cities of the United States

   https://doi.org/10.1088/1748-9326/ad6c64  

   Li, Xiaojiang; Wang, Guoqing; Zaitchik, Benjamin; Hsu, Angel; Chakraborty, TC (August 2024, Environmental Research Letters)

   Abstract Many cities are experiencing increases in extreme heat because of global temperature rise combined with the urban heat island effect. The heterogeneity of urban morphology also leads to fine-scale variability in potential for heat exposure. Yet, how this rise in temperature and local variability together impacts urban residents differently at exposure-relevant scales is still not clear. Here we map the Universal Thermal Climate Index, a more complete indicator of human heat stress at an unprecedentedly fine spatial resolution (1 m), for 14 major cities in the United States using urban microclimate modeling. We examined the different heat exposure levels across different socioeconomic and racial/ethnic groups in these cities, finding that income level is most consistently associated with heat stress. We further conducted scenario simulations for a hypothetical 1 °C increase of air temperature in all cities. Results show that a 1 °C increase would have a substantial impact on human heat stress, with impacts that differ across cities. The results of this study can help us better evaluate the impact of extreme heat on urban residents at decision-relevant scales. 

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4. Urban Park Usage During the COVID-19 Pandemic

   https://doi.org/10.1142/S2345737621500081  

   Alizadehtazi, Bita; Tangtrakul, Korin; Woerdeman, Sloane; Gussenhoven, Anna; Mostafavi, Nariman; Montalto, Franco A. (December 2020, Journal of Extreme Events)

   null (Ed.)

   Urban parks and green spaces provide a wide range of ecosystem services, including social interaction and stress reduction. When COVID-19 closed schools and businesses and restricted social gatherings, parks became one of the few places that urban residents were permitted to visit outside their homes. With a focus on Philadelphia, PA and New York City, NY, this paper presents a snapshot of the park usage during the early phases of the pandemic. Forty-three Civic Scientists were employed by the research team to observe usage in 22 different parks selected to represent low and high social vulnerability, and low, medium, and high population density. Despite speculation that parks could contribute to the spread of COVID-19, no strong correlation was found between the number of confirmed COVID-19 cases in adjacent zip codes and the number of park users. High social vulnerability neighborhoods were associated with a significantly higher number of COVID-19 cases ([Formula: see text]). In addition, no significant difference in the number of park users was detected between parks in high and low vulnerability neighborhoods. The number of park users did significantly increase with population density in both cities ([Formula: see text]), though usage varied greatly by park. Males were more frequently observed than females in parks in both high vulnerability and high-density neighborhoods. Although high vulnerability neighborhoods reported higher COVID-19 cases, residents of Philadelphia and New York City appear to have been undeterred from visiting parks during this phase of the pandemic. This snapshot study provides no evidence to support closing parks during the pandemic. To the contrary, people continued to visit parks throughout the study, underscoring their evident value as respite for urban residents during the early phases of the pandemic. 

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5. Mapping the walk: A scalable computer vision approach for generating sidewalk network datasets from aerial imagery

   https://doi.org/10.1016/j.compenvurbsys.2023.101950  

   Hosseini, Maryam; Sevtsuk, Andres; Miranda, Fabio; Cesar, Roberto M.; Silva, Claudio T. (April 2023, Computers, Environment and Urban Systems)

   While cities around the world are increasingly promoting streets and public spaces that prioritize pedestrians over vehicles, significant data gaps have made pedestrian mapping, analysis, and modeling challenging to carry out. Most cities, even in industrialized economies, still lack information about the location and connectivity of their sidewalks, making it difficult to implement research on pedestrian infrastructure and holding the technology industry back from developing accurate, location-based Apps for pedestrians, wheelchair users, street vendors, and other sidewalk users. To address this gap, we have designed and implemented an end-to-end open-source tool— Tile2Net —for extracting sidewalk, crosswalk, and footpath polygons from orthorectified aerial imagery using semantic segmentation. The segmentation model, trained on aerial imagery from Cambridge, MA, Washington DC, and New York City, offers the first open-source scene classification model for pedestrian infrastructure from sub-meter resolution aerial tiles, which can be used to generate planimetric sidewalk data in North American cities. Tile2Net also generates pedestrian networks from the resulting polygons, which can be used to prepare datasets for pedestrian routing applications. The work offers a low-cost and scalable data collection methodology for systematically generating sidewalk network datasets, where orthorectified aerial imagery is available, contributing to over-due efforts to equalize data opportunities for pedestrians, particularly in cities that lack the resources necessary to collect such data using more conventional methods. 

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