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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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Maximizing the pedestrian radiative cooling benefit per street tree
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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- Award ID(s):
- 1828010
- PAR ID:
- 10514447
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Landscape and Urban Planning
- Volume:
- 230
- Issue:
- C
- ISSN:
- 0169-2046
- Page Range / eLocation ID:
- 104608
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Abstract Cities increasingly recognize the importance of shade to reduce heat stress and adopt urban forestry plans with ambitious canopy goals. Yet, the implementation of tree and shade plans often faces maintenance, water use, and infrastructure challenges. Understanding the performance of natural and non-natural shade is critical to support active shade management in the built environment. We conducted hourly transects in Tempe, Arizona with the mobile human-biometeorological station MaRTy on hot summer days to quantify the efficacy of various shade types. We sampled sun-exposed reference locations and shade types grouped by urban form, lightweight/engineered shade, and tree species over multiple ground surfaces. We investigated shade performance during the day, at peak incoming solar, peak air temperature, and after sunset using three thermal metrics: the difference between a shaded and sun-exposed location in air temperature ( ΔT a ), surface temperature ( ΔT s ), and mean radiant temperature ( ΔT MRT ). ΔT a did not vary significantly between shade groups, but ΔT MRT spanned a 50°C range across observations. At daytime, shade from urban form most effectively reduced T s and T MRT , followed by trees and lightweight structures. Shade from urban form performed differently with changing orientation. Tree shade performance varied widely; native and palm trees were least effective, while non-native trees were most effective. All shade types exhibited heat retention (positive ΔT MRT ) after sunset. Based on the observations, we developed characteristic shade performance curves that will inform the City of Tempe’s design guidelines towards using “the right shade in the right place” and form the basis for the development of microclimate zones (MCSz).more » « less
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Abstract Tree cover is generally associated with cooler air temperatures in urban environments but the roles of canopy configuration, spatial context, and time of day are not well understood. The ability to examine spatiotemporal relationships between trees and urban climate has been hindered by lack of appropriate air temperature data and, perhaps, by overreliance on a single ‘tree canopy’ class, obscuring the mechanisms by which canopy cools. Here, we use >70 000 air temperature measurements collected by car throughout Washington, DC, USA in predawn (pd), afternoon (aft), and evening (eve) campaigns on a hot summer day. We subdivided tree canopy into ‘soft’ (over unpaved surfaces) and ‘hard’ (over paved surfaces) canopy classes and further partitioned soft canopy into distributed (narrow edges) and clumped patches (edges with interior cores). At each level of subdivision, we predicted air temperature anomalies using generalized additive models for each time of day. We found that the all-inclusive ‘tree canopy’ class cooled linearly at every time (pd = 0.5 °C ± 0.3 °C, aft = 1.8 °C ± 0.6 °C, eve = 1.7 °C ± 0.4 °C), but could be explained in the afternoon by aggregate effects of predominant hard and soft canopy cooling at low and high canopy cover, respectively. Soft canopy cooled nonlinearly in the afternoon with minimal effect until ∼40% cover but strongly (and linearly) across all cover fractions in the evening (pd = 0.7 °C ± 1.1 °C, aft = 2.0 °C ± 0.7 °C, eve = 2.9 °C ± 0.6 °C). Patches cooled at all times of day despite uneven allocation throughout the city, whereas more distributed canopy cooled in predawn and evening due to increased shading. This later finding is important for urban heat island mitigation planning since it is easier to find planting spaces for distributed trees rather than forest patches.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.landurbplan.2022.104608
