Search Results (112)

Amman’s rapid population growth and sprawling urbanization have resulted in car-centric, fragmented neighborhoods that lack social cohesion and are vulnerable to the impacts of climate change. This study reframes walkability as a climate adaptation strategy, demonstrating how pedestrian-oriented spatial planning can reduce vehicle emissions, mitigate urban heat island effects, and enhance the resilience of green infrastructure in peri-urban contexts. Using Deir Ghbar, a rapidly developing marginal area on Amman’s western edge, as a case study, we combine objective walkability metrics (street connectivity and residential and retail density) with GIS-based spatial regression analysis to examine relationships with residents’ sense of community. Employing a quantitative, correlational research design, we assess walkability using a composite objective walkability index, calculated from the land-use mix, street connectivity, retail density, and residential density. Our results reveal that higher residential density and improved street connectivity significantly strengthen social cohesion, whereas low-density zones reinforce spatial and socioeconomic disparities. Furthermore, the findings highlight the potential of targeted green infrastructure interventions, such as continuous street tree canopies and permeable pavements, to enhance pedestrian comfort and urban ecological functions. By visualizing spatial patterns and correlating built-environment attributes with community outcomes, this research provides actionable insights for policymakers and urban planners. These strategies contribute directly to several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action), by fostering more inclusive, connected, and climate-resilient neighborhoods. Deir Ghbar emerges as a model for scalable, GIS-driven spatial planning in rural and marginal peri-urban areas throughout Jordan and similar regions facing accelerated urban transitions. By correlating walkability metrics with community outcomes, this study operationalizes SDGs 11 and 13, offering a replicable framework for climate-resilient urban planning in arid regions. Full article

The urban heat island (UHI) effect significantly impacts urban environments, particularly along roads, a phenomenon known as urban linear heat (UHI_ULI). Numerous factors contribute to roads influencing the UHI_ULI; however, effective mitigation strategies remain a challenge. This study examines the relationship between canopy cover percentage, normalized difference vegetation index, land use types, and three road typologies (local, regional, and state) with land surface temperature. This study is based on data from the city of Adelaide, Australia, using spatial analysis, and statistical modelling. The results reveal strong negative correlations between land surface temperature and both canopy cover percentage and normalized difference vegetation index. Additionally, land surface temperature tends to increase with road width. Among land use types, land surface temperature varies from highest to lowest in the order of parkland, industrial, residential, educational, medical, and commercial areas. Notably, the combined influence of the road typology and land use produces varying effects on land surface temperature. Canopy cover percentage and normalized difference vegetation index consistently serve as dominant cooling factors. The results highlight a complex interplay between built and natural environments, emphasizing the need for multi-factor analyses and a framework based on the local climate and the type of roads (local, regional, and state) to effectively evaluate UHI_ULI mitigation approaches. Full article

Parks play a crucial role in mitigating urban heat island effects, a key challenge for urban sustainability. Park cooling intensity (PCI) mechanisms across varying canopy-layer urban heat island (CUHI) gradients remain underexplored, particularly regarding interactions with meteorological, topographical, and socio-economic factors. According to the urban-suburban air temperature difference, this study classified the city into non-, weak, and strong CUHI regions. We integrated causal inference, machine learning and a geographical detector (Geodetector) to model and interpret PCI dynamics across CUHI gradients. The results reveal that surrounding impervious surface coverage is a universal driver of PCI by enhancing thermal contrast at park boundaries. However, the dominant drivers of PCI varied significantly across CUHI gradients. In non-CUHI regions, surrounding imperviousness dominated PCI and exhibited bilaterally enhanced interaction with intra-park patch density. Weak CUHI regions relied on intra-park green coverage with nonlinear synergies between water body proportion and park area. Strong CUHI regions involved systemic urban fabric influences mediated by surrounding imperviousness, evidenced by a validated causal network. Crucially, causal inference reduces model complexity by decreasing predictor counts by 79%, 25% and 71% in non-, weak and strong CUHI regions, respectively, while maintaining comparable accuracy to full-factor models. This outcome demonstrates the efficacy of causal inference in eliminating collinear metrics and spurious correlations from traditional feature selection, ensuring retained predictors reside within causal pathways and support process-based interpretability. Our study highlights the need for context-adaptive cooling strategies and underscores the value of integrating causal–statistical approaches. This framework provides actionable insights for designing climate-resilient blue–green spaces, advancing urban sustainability goals. Future research should prioritize translating causal diagnostics into scalable strategies for sustainable urban planning. Full article

Urbanization, habitat fragmentation, and intensifying urban heat island (UHI) effects accelerate biodiversity loss and diminish ecological resilience in cities, particularly in climate-vulnerable regions. To address these challenges, we developed TreeGrid, a functionality-based spatial tree planning tool designed specifically for urban settings in the Northern Plains of India. The tool integrates species trait datasets, ecological scoring metrics, and spatial simulations to optimize tree placement for enhanced ecosystem service delivery, biodiversity support, and urban cooling. Developed within an R Shiny framework, TreeGrid dynamically computes biodiversity indices, faunal diversity potential, canopy shading, carbon sequestration, and habitat connectivity while simulating localized reductions in land surface temperature (LST). Additionally, we trained a deep neural network (DNN) model using tool-generated data to predict bird habitat suitability across diverse urban contexts. The tool’s spatial optimization capabilities are also applicable to post-fire restoration planning in wildland–urban interfaces by guiding the selection of appropriate endemic species for revegetation. This integrated framework supports the development of scalable applications in other climate-impacted regions, highlighting the utility of participatory planning, predictive modeling, and ecosystem service assessments in designing biodiversity-inclusive and thermally resilient urban landscapes. Full article

A simple statistical model capturing the degree to which different patterns of urban development intensify urban heat islands (UHIs) and stress human health would be useful but has remained elusive. Accurately predicting street-level urban air temperatures from land cover and thermal data is difficult due to (1) the coarse scale of common remote sensing data, which do not observe the key environments beneath urban tree canopies, and, (2) conversely, the immense labor of intense, location-specific, ground-based survey campaigns. This work tested whether remotely sensed urban heat merged with land cover heterogeneity and shade/sun fractions, if combined at a sufficiently fine scale so as to be linearly additive, would enable simple and accurate statistical modeling of street-scale urban air temperatures with minimal empirical fitting. We used ground-based thermography of a sample of 12 residential streetscapes in Portland, Oregon, to characterize the land surface temperatures (LST_g) of eleven common urban surface cover types when sun-exposed and in shade. Surfaces were cooler in shade than sun, but with surface-specific differences not explained by greenery nor (im)perviousness. Also, surfaces on streetscapes with more canopy cover, even when sun-exposed at midday, remained significantly cooler than comparable sun-exposed surfaces on streets with less canopy cover, indicating the key significance of partial diurnal shading, not typically accounted for in urban thermal statistical models. We used high-resolution orthoimagery to quantify the area of each surface cover type within each streetscape and computed an area-weighted average surface temperature (T_s), accounting for sun/shade heterogeneity. The data revealed a significant, nearly 1:1 relationship between calculated T_s values and sun-shielded air temperatures (T_a). In contrast, relationships of T_a to tree coverage, impervious area, or the LST_g of dominant surface cover types were all statistically insignificant. These results suggest that statistical models may more reliably bridge the gap between remote sensing urban surface temperatures and reliable predictions of street-scale air temperatures if (1) analysis is at a sufficiently high resolution (e.g., <10 m) to avoid some of the known scale-dependence of urban thermal environments and enable simple weighted linear models, and (2) distinctions between thermal contributions of sunlit and shaded surfaces are included along with the influence of diurnal shading. Such models may provide effective and low-cost predictions of local UHIs and help inform effective street-level approaches to mitigating urban heat. Full article

Numerical models were employed to simulate the effects of urban infrastructure on the city-scale precipitation distribution during multiple closely occurring convective squall line events over Chicago. Two high-resolution simulations were inter-compared, one using standard land use databases to initialize the WRF-ARW numerical model and the other using a high-resolution urban canopy formulation and detailed land use databases to initialize the WRF-UCM numerical model. Two squall lines organized and propagated over Chicago during an eight-hour period. The (1 km) spatio-temporal evolution of the first squall line was more accurately simulated by the WRF-UCM than that simulated by the WRF-ARW. The WRF-UCM captures more realistic urban heat island-induced buoyancy forcing when validated against multiple airport meteograms and Doppler radar-derived reflectivity and precipitation. The WRF-UCM increases surface heating, substantially strengthening the surface-based convective available potential energy (SBCAPE) and subsequent cold downdrafts. Additionally, the increased surface heating acts to strengthen and bifurcate the upper-level divergence and energize three low-level jets that converge upon the city and shape the convective organization. While the effect of this additional buoyancy on the first squall line was critical, the second line’s dissipation was not substantially different in the two simulations because of diminishing tropospheric forcing. Full article

This research addresses the critical issue of urban heat islands (UHI), in which urban areas experience significantly higher temperatures than their surroundings, adversely affecting human comfort and well-being. Focusing on Inglewood, a city neighboring Los Angeles, California, and Phoenix, Arizona, this study uses a comprehensive methodology involving microclimate analysis-based Universal Thermal Climate Index (UTCI) calculations to assess the impact of horizontal green surfaces and different levels of tree canopies on outdoor thermal stress mitigation. Phoenix was selected due to its hyper-arid desert climate, providing a contrasting context to assess the effectiveness of green infrastructure under extreme heat conditions. The results demonstrate that these interventions effectively reduce strong and moderate heat stress levels (32 °C < UTCI < 38 °C and 26 °C < UTCI < 32 °C); the model with maximum tree canopy achieved an 18.48% reduction in strong heat stress in Inglewood, while combined interventions led to a maximum reduction of 18.92%. However, the findings also reveal that under extreme heat conditions, particularly in hyper-arid environments such as Phoenix, the interventions may have a limited effect, with localized increases in extreme heat stress attributed to microclimate dynamics, reduced vegetation cooling efficiency, and modeling limitations. Despite these challenges, the overall reduction in average UTCI values underscores the potential of integrated green infrastructure strategies for mitigating urban heat stress. This study provides urban planning strategies for integrating these interventions to create more sustainable and resilient urban environments, supporting policymakers and urban planners in their efforts to reduce the effects of UHI. Full article

We model and describe the combined effect of a series of urban heat islands (UHIs), generated by nearby cities aligned as an archipelago, on the vertical diffusion of heat and the temperature structure in the lower atmosphere over an urban chain in northwestern Morocco. We use the Weather and Forecasting Model (WRF) coupled to an urban canopy model to run simulations during the northern summer. We show that when the land surface is characterized accurately, the WRF model can effectively resolve the scale of the urban archipelago effect and describe its detailed diurnal structure. Our results indicate that the combined effect of multiple UHIs in proximity is more impactful than the sum of their parts. Specifically, the urban archipelago’s effect alters the vertical temperature structure through upward diffusion of heat and extends its scale from local to meso-scale. This alters the wind pattern and may affect local weather conditions and air quality. These results underline the importance of considering the urban archipelago effect when studying urban climate. They also extend beyond academic research to offer valuable insights for urban planners in emphasizing the importance of urban typology and spatial proximity in city design and balancing cities’ interconnectivity with sustainable development and resilience. Full article

Intensifying heat from warming climates regularly concentrates in urban areas lacking green infrastructure in the form of green space, vegetation, and ample tree canopy cover. Nature-based interventions in older U.S. city cores can help minimize the urban heat island effect, yet neighborhoods targeted for cooling interventions may remain outside the decisional processes through which change affects their communities. This translational research seeks to address health disparities originating from the absence of neighborhood-level vegetation in core urban areas, with a focus on tree canopy cover to mitigate human susceptibility to extreme heat exposure. The development of LiDAR-based imagery enables communities to visualize the proposed greening over time and across seasons of actual neighborhood streets, thus becoming an effective communications tool in community-engaged research. These tools serve as an example of how visualization strategies can initiate unbiased discussion of proposed interventions, serve as an educational vehicle around the health impacts of climate change, and invite distributional and participatory equity for residents of low-income, nature-poor neighborhoods. Full article

The thermal environment of urban riverside open spaces is crucial for enhancing outdoor comfort and well-being, especially amid extreme heat events caused by global warming and Urban Heat Islands (UHIs). Although significant progress has been made in this area, existing research still has some limitations. This study employed a scenario-based numerical simulation approach to investigate the combined impacts of spatial morphology and wind direction on the thermal environment and thermal comfort (TETC) in riverside districts along the Huangpu River in Shanghai. Focusing on two prototypes—O and SO types—we identified key factors influencing TETC, including tree canopy coverage, vegetation layout, building density, and building height. The findings also reveal that dense canopies and thoughtful building layout significantly enhance daytime thermal comfort, while controlled building height and increased riverbank distance are effective strategies for nighttime comfort. This study highlights the importance of considering both landscape morphology and wind conditions in climate-adaptive planning and design for urban riverside areas. Full article

Urban squares in historic neighborhoods are vital public spaces, often the only nearby option available for an aging population. However, these spaces face increasing thermal discomfort exacerbated by urban heat island (UHI) effects. This research focuses on improving thermal comfort for two case studies located in Seville’s high-density and historically rich Casco Antiguo neighborhood. Although their significance and social value make them central meeting points for locals and visitors, these squares face major challenges regarding thermal comfort, mainly due to a lack of greenery or adequate shading. This study examines the conditions by conducting in-person monitoring and simulations, identifying factors contributing to discomfort. On the basis of this, the research proposes mitigation strategies to address these issues. These solutions include the installation of green walls, the addition of canopies, and the application of specific surface materials to improve the conditions of these squares. Canopies provided the most significant cooling, reducing universal thermal climate index (UTCI) values by up to 6.5 °C. Green walls delivered localized cooling, lowering the mean radiant temperature (MRT) by up to 5 °C. The results reveal how these approaches can bring about changes in thermal comfort in a way that benefits historic city environments. Full article

In the face of global warming, mitigating the urban heat island effect has become an important concern worldwide. This study applies the principle of buoyancy ventilation formed by sunlight in double skin façades (DSFs) to improve the thermal environment outside buildings by discharging heat through temperature and pressure differences. The study subject is a 15 × 30 × 40 m residential concrete building situated in a subtropical climate. The lower opening of the DSF faces the outdoor environment; heat is absorbed through this opening from the ground environment and then evacuated up to above the urban canopy layer heat island in order to cool pedestrian environments on the ground. We used numerical simulation to analyze the cooling potential of this DSF in summer daytime conditions. The results show that the DSF can successfully transport heat energy and discharge it above the urban canopy layer. Significant cooling effects were observed in both the horizontal and vertical spaces on the leeward side of the building DSF through the passage of surface heat, thereby reducing the load of indoor air conditioning. Full article

With the acceleration of global climate change and urbanization, the urban heat island effect has significantly impacted the quality of life of urban residents. Although numerous studies have focused on macro-scale factors such as air temperature, surface albedo, and green space coverage, relatively little attention has been paid to micro-scale factors, such as shading provided by building facades and tree canopy coverage. However, these micro-scale factors play a significant role in enhancing pedestrian thermal comfort. This study focuses on a city community in China, aiming to assess the thermal comfort of urban streets during the summer. Utilizing high-resolution 3D geographic data and street view images extracted from drone data, this study comprehensively considers the mechanisms affecting the urban street thermal environment and the human comfort requirements for shading and greening. By proposing quantitative indicators from multiple scales and dimensions, this study thoroughly quantifies the impact of the surrounding environment, greening, shading effects, buildings, and road design on the thermal comfort of summer streets. The results show that increasing tree canopy coverage by 10 m can significantly reduce the surrounding temperature, and a building layout extending 200 m can regulate temperature. The distribution of shadows at different times significantly affects thermal comfort, while the sky view factor negatively correlates with thermal comfort. Environments with a high green view index enhance visual comfort. This study reveals the specific contributions of different environmental characteristics to street thermal comfort and identifies factors that significantly impact thermal comfort. This provides a scientific basis for urban green space planning and thermal comfort improvement, holding substantial practical significance. Full article

The implementation of sponge cities in China modifies the hydrological conditions of the underlying surface, effectively alleviating the urban heat island effect. However, in planning and construction, heat island mitigation targets are difficult to quantify and lack quantitative design and evaluation methods. To address this issue, two planning schemes were proposed based on sponge city management and control indicators. The WRF-UCM model was used to conduct numerical simulations of the current conditions (case 1) and the sponge city planning schemes (cases 2 and 3), analyzing the impact of sponge city initiatives on the mitigation of the heat island effect. The results indicated that by changing the structure of the underlying surface and increasing the water content of the underlying surface, the sponge city affects the urban energy distribution process and regional horizontal advection pattern. This not only reduces heat accumulation within the urban area but also suppresses regional convection during high-temperature periods, thereby mitigating the urban heat island effect. Moreover, different schemes following the same sponge city design requirements have varying impacts on urban microclimate elements and heat island distributions. Notably, a higher subsurface water content yields a more pronounced inhibition of the heat island effect. Finally, a sponge city planning method with the consideration of heat island mitigation was proposed, facilitating pre-simulation optimization and decision-making in sponge city planning. Full article

The combination of global climate change and the urban heat island effect has given rise to a deterioration in the livability of residential districts within cities, posing challenges to enhancing the health quality of urban environments. Meanwhile, the intensification of daytime changes in temperature and humidity in residential districts has rendered the sensory representation of the urban heat island effect more pronounced. This study selects the residential districts in Fuzhou City as the research case area, which have witnessed a discernible warming trend in recent years, and acquires temperature and humidity parameter data at three time periods (early morning, noon, and evening) to represent the daytime temperature and humidity change phase. Through aerial photography and field research, three types of spatial morphological indicators (buildings I, vegetation II, and the combination of buildings and vegetation II) of residential districts are quantified to represent the three-dimensional spatial form of the case study area. The analysis results show the following: ➀ Residential districts experience two phases of daytime changes in temperature and humidity: a warming and drying phase (WDP) in the morning and a cooling and humidifying phase (CHP) in the afternoon. The characteristics of changes in temperature and humidity show a spatial correlation with each other. ➁ The impact of urban three-dimensional morphology on changes in temperature and humidity in WDP is minor, whereas, in CHP, it is influenced by Class II and Class III indicators. The two types of urban morphology exert a synergistic regulatory effect on changes in temperature and humidity. ➂ Vegetation has a significant regulatory effect on temperature and humidity variations in residential areas through changes in its three-dimensional form. Enlarging the area of individual trees while reducing their canopy volume can restrain the warming and dehumidification of residential districts and promote cooling and humidification. In contrast to only planting trees, a vegetation configuration combining trees, shrubs, and grass can bring a more obvious cooling effect to residential districts. The research results can provide a reference for urban planners in the planning and design of residential areas as well as the optimization and improvement of urban living environments. Full article