Search Results (15)

Urban heat mitigation in megacities depends not only on cooling sources, but also on the connectivity through which cooling effects are transmitted across heterogeneous landscapes. However, existing studies have mainly focused on the static patterns of urban cold islands (UCIs), while the connectivity and disturbance response of urban cooling systems remain poorly understood. Taking Landsat-based summer thermal observations in Beijing, this study developed an integrated framework to assess the structure and resilience of the urban cold island network (CIN) by combining thermal source identification, resistance-surface construction, connectivity modeling, and disturbance simulations. Land surface temperature (LST) was extracted from Landsat 8 OLI/TIRS Collection 2 Level-2 surface temperature products acquired in July–August 2022, and cold island core sources (CICS) were subsequently identified by integrating thermal conditions with land-use characteristics. GeoDetector was used to quantify the explanatory power and interaction effects of natural, land-use, and socio-economic factors on LST spatial heterogeneity, serving as an attribution tool for interpreting thermal-environment drivers. These factors were then integrated into a resistance surface for circuit-theory-based connectivity analysis. Under the summer heat-stress scenario, 202 CICS covering 6416.95 km² were identified, mainly concentrated in peripheral mountainous areas. A total of 401 corridors were identified, including 70 primary corridors forming the structural backbone of the CIN. This spatial distribution reveals a mountain–plain cooling structure in Beijing, in which mountainous CICS constitute the regional cooling-supply base, while potential cooling transmission toward the urban core mainly depends on a limited number of backbone corridors. LULC was the dominant driver of LST, and its interactions with PD, NTL, and vegetation-related factors substantially enhanced explanatory power. Compared with random disturbance, targeted node removal led to an earlier and sharper decline in network resilience, with substantial deterioration already evident after approximately 20–30% of critical nodes were removed. These summer-based findings provide spatially explicit evidence for prioritizing cooling corridors, critical nodes, and restoration areas in connectivity-oriented urban heat mitigation and climate-responsive planning, thereby supporting hierarchical maintenance and restoration strategies based on their relative importance within the cooling network. Full article

The rapid urbanization of Jaipur has profoundly altered its urban climate, driven by anthropogenic heat flux (A_F) and shifts in surface energy dynamics. This study leverages remote sensing techniques, utilizing Landsat data, to quantify A_F and assess its influence on the city’s climate. The findings reveal a striking paradox; despite a significant rise in A_F from 127.31 W/m² in 1993 to 201.82 W/m² in 2020, Jaipur exhibits an anomalous urban cool island (UCI) effect during the daytime. In this phenomenon, surrounding fallow lands experience higher land surface temperatures (LSTs) than the urban core, defying the typical urban heat island (UHI) effect observed in most cities worldwide. This paradox is especially pronounced in semi-arid urban environments, where factors such as limited vegetation, arid conditions, and water scarcity intricately shape peculiar thermal behaviour. This study further highlights the role of urban expansion, with built-up areas growing from 11.95% in 1993 to 19% in 2020, intensifying A_F. Notably, the latent heat flux was highest in vegetated areas, significantly reducing LSTs by facilitating evapotranspiration. Daytime surface temperatures have surged significantly, with temperatures ranging from 26–46.9 °C in 1993 to 31–56.5 °C in 2020, indicating an overall increase in surface heat intensity. Despite these increases, the UCI effect remains observable, further illustrating the cooling potential of urban vegetation. This study offers novel insights into the intricate dynamics of urban heat in semi-arid cities, providing refined perspectives on urban heat mitigation strategies and climate adaptation, with implications for future sustainable urban planning and environmental management. Full article

This study pioneers the comprehensive evaluation of the spatiotemporal evolution of land use/land cover (LULC) in Hangzhou city, introducing the novel water body shape index (WBSI) to analyze its seasonal impacts on the urban thermal environment and urban cool island (UCI) effects, uncovering distinct patterns of thermal regulation. It particularly investigates how distance gradients and the water body shape index (WBSI) influence land surface temperature (LST) in the urban core. The region’s climate, featuring hot summers and cold winters, highlights significant seasonal LST variations. Addressing a gap in existing UCI research, the analysis extends beyond the typical large-scale planning focus to include small-scale, high-resolution aspects. Employing remote sensing and geographic information system (GIS) analysis techniques, this study analyzes the seasonal dynamics in Hangzhou’s central urban area. High-resolution LST data, obtained through single-channel inversion and resolution enhancement algorithms, are crucial to this analysis. This study employs the maximum likelihood classification method to analyze land use and land cover changes from 1990 to 2020. This analysis reveals potential drivers of urban thermal environment changes, such as the expansion of residential and commercial areas and the reduction in green spaces. Different regions in LST data are delineated to assess the cool island effect, and the complexity of water body boundaries is quantified using the water body shape index. Spatial and temporal patterns of LST changes are investigated using multivariate regression and time-series analysis models. We identified significant changes in LULC over the past 30 years in Hangzhou, closely correlating with a continuous rise in LST. This observation underscores a clear finding: the strategic importance of blue–green infrastructure in mitigating urban heat, a novel insight that extends the current understanding of urban thermal dynamics. A clear and novel finding of this study is that the intensity of the cool island effect from large water bodies not only diminishes with distance but is intricately influenced by the complexity of their shapes, as quantified by the WBSI, whereas the complexity of their boundaries enhances this effect. Additionally, the regulatory role of the cool island effect is observed to vary seasonally, being most pronounced in summer and less so in autumn and winter, thereby demonstrating a positive impact. In conclusion, our findings innovatively highlight how the specific shapes of water bodies, quantified through the water body shape index (WBSI), emerge as critical, yet previously underappreciated, drivers in modulating the urban thermal environment. This underscores a new avenue for urban planning, advocating for the strategic design of water bodies within urban landscapes. It also finds that spatial factors and seasonal variations significantly affect the intensity of the cool island effect. These findings offer valuable evidence for urban planning and climate change adaptation, emphasizing balancing natural elements with the built environment in urban design. Full article

Blue–green space refers to blue space (rivers and lakes) and green space (lawns and trees), which have the cooling island effect and are increasingly acknowledged as a potential and effective way to help alleviate the urban heat island effect. Scientific and flexible blue–green space planning is required, especially for medium- and large-scale urban agglomerations in the face of climate change. However, the temporal evolution and spatial patterns of the cooling island effect in the blue–green space under different future scenarios of climate change have not been fully investigated. This would impede long-term urban strategies for climate change adaptation and resilience. Here we studied the relationship between future climate change and blue–green spatial layout with Weather Research and Forecasting (WRF), based on the numerical simulation data of 15 global climate models under different extreme Shared Socioeconomic Pathway (SSP) scenarios. As a result, future changes in urban cooling island (UCI) magnitudes were estimated between historical (2015–2020) and future timelines: 2030s (2021–2040), 2050s (2041–2060), 2070s (2061–2080), and 2090s (2081–2100). Our results showed different land use types in blue and green space across the study area were predicted to present various changes in the next 80 years, with forest, grassland, and arable land experiencing the most significant land use transfer. The future UCI intensity of cities under SPP5-8.5 (12) was found to be lower than that under SPP2-4.5 (15), indicating that cities may be expected to experience decreases in UCI magnitudes in the future under SSP5-8.5. When there is no expansion of urban development land, we found that the conversion of different land use types into blue and green space leads to little change in future UCI intensity. While the area growth of forests and water bodies is proportional to the increase in UCI, the increase of farmland was observed to have the most significant impact on reducing the amplitude of urban UCI. Given that Huai’an City, Yancheng City, and Yangzhou City have abundant blue–green space, the urban cooling island effect was projected to be more significant than that of other cities in the study area under different SSP scenarios. The simulation results of the WRF model indicate that optimizing the layout of urban blue–green space plays an important role in modulating the urban thermal environment. Full article

Park green spaces (PGSs) are an important component of urban natural carbon sinks, while their spatial morphological patterns can affect the carbon sequestration capacity themselves. This study selected six typical urban parks in the central district of Shanghai and analyzed the correlation between spatial morphological indices and CO₂ concentration distribution of the PGSs based on ENVI-met and BRT models. It further explored the interaction mechanisms in the carbon cycling process of urban PGSs under the influence of different spatial morphology. The results shows that urban PGSs play the role of carbon sink in diurnal period, and the difference of CO₂ concentration distribution in green space is the largest at 11 a.m. The green biomass (Gb) and arboreal area ratio (Ar) are the most important indices affecting the distribution of carbon concentration. The two indices describing spatial patterns, namely, Cohesion (Co) and canopy density (CanopyD) also significantly impact CO₂ concentration. These indices have a positive impact on carbon sinks. The parkway area ratio (Pr) is a disturbing index that also has an obvious negative impact on the distribution of CO₂ concentration. The moderate herbs area ratio (Hr) and open land area ratio (Or) are conducive to regulating the microclimate environment and enhancing carbon sink capacity. There is an interactive relationship between spatial indices and microclimate environment indices, as well as physical and physiological indices in the carbon sink process of green areas. The study suggested that in green space management aiming at carbon reduction, combined with the influence threshold of Gb on carbon reduction and paying attention to the importance of green amount on carbon sequestration, the vegetation density and allocation ratio should be rationally distributed to form a park green space landscape with efficient carbon fixation. Full article

Blue-green space commonly provides multiple ecological service functions, especially thermal environment comfort for citizens. The greenspace of the riparian buffers along 22 river channels in Shanghai was selected as the study object, and remote sensing and GIS technologies were used to obtain the quantitative composition and morphological indices of riverfront greenspace and the spatial distribution data of the land surface temperature in the study area. Through BRT modelling and statistical analyses, the interactive correlations among the three aspects, namely, the spatial patterns of riverfront greenspace, their specific functional zoning, and cooling island differentiation characteristics, were explored. The results showed that different river types served for different functional zones of the city, namely, high-density built-up zoning, new urban-growth zoning in built-up areas, suburban areas, and rural areas, and had specific regular patterns of morphosis and service function of riverfront greenspace. These also led to a significant spatial differentiation pattern of cooling intensity levels, which generally appeared in the approximate circle differentiation structure of the cooling island in the city riverfront area. The study further proposed the key factors and corresponding strategies for optimizing the greenspace pattern to strengthen the cooling intensity levels of different river types. This study summarizes the landscape composition paradigm of riverfront greenspaces at the urban mesoscale and provides adaptive planning methods for better local microclimate conditions. Full article

Urban Heat Islands increase surface temperatures which impact the health and well-being of urban populations. Radiative forcing is impacted by changes to the land surface associated with urbanization that are particularly significant immediately after sunset. This paper aimed to analyze the behavior of UHI in different Local Climate Zones (LCZ) in Bragança city (Portugal), using Air Temperature (Ta), satellite images (Landsat 8), and on-site data. The methodology included a seasonal approach, integrating data with different scales (spatial, radiometric, and spectral) and qualitative and quantitative analyses. Google Earth Engine (GEE) optimized the processing time and computation requirement to generate the Land Surface Temperature (LST) maps. The integration of data with different scales corroborated the complementation of information/analysis and detected the correlation between the Ta and LST. However, the identification of the UHI was compromised due to the time of the passage of Landsat 8, and it was identified as the Urban Cool Island (UCI), a complementary effect of UHI, supporting the results of previous studies and for the use of Remote Sensing (RS) for thermal effects analysis. Full article

The patterns of green corridors in urban riverfront districts provide different synergistic cooling effects of blue-green space in urban areas. The purpose of this study is to quantify the spatial morphological impact of green corridors in riverfront block-scale area on the cooling effect. Three representative patterns (radiate, grid and dendritic) were selected in the study. The comprehensive influences analysis between multi-dimensional factors of spatial structure and morphology of green corridors and Ta (air temperature) distribution are processed by Envi-met4.4.5 simulation data and statistical analysis methods, such as regression tree model (BRT), were combined. The results showed that the D (distance from riverbank) has the greatest impact on the cooling effect of each belt green space. The D in the range of 600–750 m was affected by the cooling effect of blue-green space; The orientation with parallel to (southeast–northwest) or roughly the same as the prevailing wind direction (north–south) green corridors had relatively better cooling effect. When the width of green corridor was 20–25 m, the ME (marginal effect) of cooling was the largest; at 30–35 m (corridor width), the overall ME of cooling was the best; When the dPC (decreased probability connectivity, here the index was adapted to describe the connectivity degree) of green corridors was in the range of 0.5–1.5, the cooling effect of green corridor could be significantly improved. When dPC is 1.5, its marginal effect on temperature reached the maximum. The study provided a quantitative correlation technology for the morphological influence of blue-green space on the distribution of UCI (urban cooling island), which can guide the spatial layout control of green corridors in the planning and design of urban riverfront district. Full article

The spatial morphology of waterfront green spaces helps generate cooling effects to mitigate the urban heat island effect (UHI) in metropolis cities. To explore the contribution and influence of multi-dimensional spatial indices on the mitigation of UHIs, the green space of the riparian buffer along 18 river channels in Shanghai was considered as a case study. The spatial distribution data of the land surface temperature (LST) in the study area were obtained by using remote sensing images. By selecting the related spatial structure morphological factors of the waterfront green space as the quantitative description index, the growth regression tree model (BRT) was adapted to analyze the contribution of various indexes of the waterfront green space on the distribution of the LST and the marginal effect of blue–green synergistic cooling. In addition, mathematical statistical analysis and spatial analysis methods were used to study the influence of the morphological group (MG) types of riparian green spaces with different morphological characteristics on the LST. The results showed that in terms of the spatial structure variables between blue and green spaces, the contribution of river widths larger than 30 m was more notable in decreasing the LST. In the case of a larger river width, the marginal effect of synergistic cooling could be observed in farther regions. The green space that had the highest connectivity degree and was located in the leeward direction of the river exhibited the lowest LST. In terms of the spatial morphology, the fractional cover values of the vegetation (Fv) and area (A) of the green space were the main factors affecting the cooling effect of the green space. For all MG types, a large green patch that had a high green coverage and connectivity degree, as well as was distributed in the leeward direction of the river, corresponded to the lowest LST. The research presented herein can provide methods and development suggestions for optimizing spatial thermal comfort in climate adaptive cities. Full article

Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) can be measured by means of in situ measurements and interpolation methods, which often require densely distributed networks of sensors and can be time-consuming, expensive and in many cases infeasible. The use of satellite data to estimate Land Surface Temperature (LST) and spectral indices such as the Normalized Difference Vegetation Index (NDVI) has emerged in the last decade as a promising technique to map Surface Urban Heat Islands (SUHIs), primarily at large geographical scales. Furthermore, thermal comfort, the subjective perception and experience of humans of micro-climates, is also an important component of UHIs. It remains unanswered whether LST can be used to predict thermal comfort. The objective of this study is to evaluate the accuracy of remotely sensed data, including a derived LST, at a small geographical scale, in the case study of King Abdulaziz University (KAU) campus (Jeddah, Saudi Arabia) and four surrounding neighborhoods. We evaluate the potential use of LST estimates as proxy for air temperature (T_air) and thermal comfort. We estimate LST based on Landsat-8 measurements, T_air and other climatological parameters by means of in situ measurements and subjective thermal comfort by means of a Physiological Equivalent Temperature (PET) model. We find a significant correlation (r = 0.45, p < 0.001) between LST and mean T_air and the compatibility of LST and T_air as equivalent measures using Bland-Altman analysis. We evaluate several models with LST, NDVI, and Normalized Difference Built-up Index (NDBI) as data inputs to proxy T_air and find that they achieve error rates across metrics that are two orders of magnitude below that of a comparison with LST and T_air alone. We also find that, using only remotely sensed data, including LST, NDVI, and NDBI, random forest classifiers can detect sites with “very hot” classification of thermal comfort nearly as effectively as estimates using in situ data, with one such model attaining an F1 score of 0.65. This study demonstrates the potential use of remotely sensed measurements to infer the Physiological Equivalent Temperature (PET) and subjective thermal comfort at small geographical scales as well as the impacts of land cover and land use characteristics on UHI and UCI. Such insights are fundamental for sustainable urban planning and would contribute enormously to urban planning that considers people’s well-being and comfort. Full article

Climate change and rapid urbanization are adversely affecting the urban environment by exacerbating the widely reported urban heat island effect in Dhaka, Bangladesh. Two wetland areas with variable riparian shadings in the warm-humid conditions of urban Dhaka were investigated through field campaigns on microclimatic parameters for their cooling potential on the surrounding urban fabric. It was observed that an inversion layer of fully saturated air develops over the water surface of wetland, suppressing evaporation from the wetland water surface layer, which was effectively reducing the heat exchange between the water surface and the air layer above it through its action as an insulating vapor blanket. Due to this effect, the wetland was unable to render as a source of coolth for the surrounding overheated urban area. This effect of the inversion layer was more pronounced in the urban wetland without riparian shading either by the urban form or tree canopy. A multiphysics simulation study conducted on the selected urban wetlands indicates the effect of differential shading pattern on the relation between fetch and inversion layer thickness. This research hypothesizes that the wetland can act as an urban adaption measure against the urban heat island effect by potentially transforming them into an urban cooling island (UCI) towards a favorable urban bioclimate. Full article

The urban heat island (UHI) concept describes heat trapping that elevates urban temperatures relative to rural temperatures, at least in temperate/humid regions. In drylands, urban irrigation can instead produce an urban cool island (UCI) effect. However, the UHI/UCI characterization suffers from uncertainty in choosing representative urban/rural endmembers, an artificial dichotomy between UHIs and UCIs, and lack of consistent terminology for other patterns of thermal variation at nested scales. We use the case of a historically well-enforced urban growth boundary (UGB) around Portland (Oregon, USA): to explore the representativeness of the surface temperature UHI (SUHI) as derived from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data, to test common assumptions of characteristically “warm” or “cool” land covers (LCs), and to name other common urban thermal features of interest. We find that the UGB contains heat as well as sprawl, inducing a sharp surface temperature contrast across the urban/rural boundary. The contrast ranges widely depending on the end-members chosen, across a spectrum from positive (SUHI) to negative (SUCI) values. We propose a new, inclusive “urban thermal deviation” (UTD) term to span the spectrum of possible UHI-zero-UCI conditions. We also distinguish at finer scales “microthermal extremes” (MTEs), discrete areas tending in the same thermal direction as their LC or surroundings but to extreme (hot or cold) values, and microthermal anomalies (MTAs), that run counter to thermal expectations or tendencies for their LC or surroundings. The distinction is important because MTEs suggest a need for moderation in the local thermal landscape, whereas MTAs may suggest solutions. Full article

The thermal environment is an important aspect of the urban environment because it affects the quality of life of urban residents and the energy use in buildings. Urban Heat Island (UHI) and Urban Cold Island (UCI) are complementary effects that are the consequence of cities’ structures interference with the local climate. This article presents results from five years of urban climate monitoring (2012–2016) in a small Portuguese city (Bragança) using a dense meteorological network of 23 locations covering a wide array of Local Climate Zones (LCZ), from urban areas to nearby rural areas. Results show the presence of both the UHI effect, from mid-afternoon until sunrise, and the UCI after sunrise, both being more intense under the dense midrise urban context and during the summer. Urban Green Spaces had an impact on both UHI and UCI, with an important role in cooling areas of the city during daytime in the summer. Other LCZs had less impact on local thermal conditions. Despite the small size of this city, both effects (UHI and UCI) had a relevant intensity with an impact on local climate conditions. Both effects tend to decrease in intensity with increasing wind speed and precipitation. Full article

The urban heat island effect (UHI) for inner land regions was investigated using satellite data, ground observations, and simulations with an Single-Layer Urban Canopy Parameterization (SLUCP) coupled into the regional Weather Research Forecasting model (WRF, http://wrf-model.org/index.php). Specifically, using the satellite-observed surface skin temperatures (T_skin), the intensity of the UHI was first compared for two inland cities (Xi’an City, China, and Oklahoma City (OKC)), which have different city populations and building densities. The larger population density and larger building density in Xi’an lead to a stronger skin-level UHI by 2 °C. However, the ground observed 2 m surface air temperature (T_air) observations showed an urban cooling island effect (UCI) over the downtown region in OKC during the daytime of 19 July 2003, from a DOE field campaign (Joint Urban 2003). To understand this contrast between satellite-based T_skin and ground-based T_air, a sensitivity study using WRF/SLUCP was analyzed. The model reproduced a UCI in OKC. Furthermore, WRF/Noah/SLUCM simulations were also compared with the Joint Urban 2003 ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLUCM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions, and energy fluxes reasonably well. Full article

The variation between land surface temperature (LST) within a city and its surrounding area is a result of variations in surface cover, thermal capacity and three-dimensional geometry. The objective of this research is to review the state of knowledge and current research to quantify surface urban heat islands (SUHI) and surface urban cool islands (SUCI). In order to identify open issues and gaps remaining in this field, we review research on SUHI/SUCI, the models for simulating UHIs/UCIs and techniques used in this field were appraised. The appraisal has revealed some great progress made in surface UHI mapping of cities located in humid and vegetated (temperate) regions, whilst few studies have investigated the spatiotemporal variation of surface SUHI/SUCI and the effect of land use/land cover (LULC) change on LST in arid and semi-arid climates. While some progress has been made, models for simulating UHI/UCI have been advancing only slowly. We conclude and suggest that SUHI/SUCI in arid and semi-arid areas requires more in-depth study. Full article