Surface urban heat islands in Italian metropolitan cities: Tree cover and impervious surface influences

Morabito, Marco; Crisci, Alfonso; Guerri, Giulia; Messeri, Alessandro; Congedo, Luca; Munafò, Michele

doi:10.1016/j.scitotenv.2020.142334

Cited by 133 publications

(71 citation statements)

References 95 publications

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“…This is mainly because in spring and summer, the daytime is long, the height of the sun at noon is high, and the ground receives more solar radiation, which increases the heating differences between different types of surfaces of the city. The SUHI study in Italian metropolitan cities also found that the daytime SUHI increased significantly in summer, especially in inland cities, by increasing the size of areas with low tree cover densities in the metropolitan core (or decreasing areas with low tree cover densities outside the metropolitan core), further increasing its intensity when the impervious density grew [33]. This study revealed that urban green space has a clear impact on the reduction of the urban thermal environment and can effectively mitigate the UHI [66].…”

Section: The Role Of Different Land Covers In Conditioning Lstmentioning

confidence: 87%

“…At present, there are many effective remote sensors for estimating LST [29]. Indeed, since Rao [30] reported the first satellite-based observations of the SUHI phenomenon in the eastern United States in 1972, numerous studies of the UHI effect have been carried out using large-scale satellite LST datasets, such as the Advanced Very High Resolution Radiometer (AVHRR) data of the National Oceanic and Atmospheric Administration (NOAA) satellites [31,32] and the Moderate-Resolution Imaging Spectroradiometer (MODIS) data of the Terra/Aqua satellites [33,34]. However, the spatial resolution of these data is not sufficiently high to detect the LST variations of urban green spaces [29].…”

Section: Introductionmentioning

confidence: 99%

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Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

et al. 2021

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Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

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Section: The Role Of Different Land Covers In Conditioning Lstmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

et al. 2021

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“…The final output is the tree cover binary raster layer (where 0 and 1 are non-tree cover and tree cover surfaces respectively) at 10-m spatial resolution for the summer of 2017. Further information on the workflow methodology is available in Morabito et al [11].…”

Section: Tree Covermentioning

confidence: 99%

“…Understanding the complexity of the spatial heterogeneity of land surface temperature (LST) and its relationship with various influencing factors [8] is of great importance in remote sensing applications and urban climate studies. The urban thermal surface anomalies differ greatly by city [9][10][11] and are due to the inherent characteristics of urban environments (i.e., city size, population density, geometry, topography, characteristics of urban elements and surface materials, vegetation and types of vegetation, and water body distributions) that modify the radiative and thermal properties of urban infrastructures [12]. Dark surfaces with low albedo materials and in general artificial impervious surfaces strongly limit evaporative cooling conditions and "trap" the heat [13].…”

Section: Introductionmentioning

confidence: 99%

“…Thermal analyses in cities should consider all the artificial and natural components interacting with the urban ecosystem. Vegetation [14], tree cover and impervious surfaces [11,15], water bodies [16], surface albedo [17], urban morphology [18] and solar radiation exposure [19] were identified as important indicators able to modify urban microclimatic conditions as they play an important role in the surface energy balance.…”

Section: Introductionmentioning

confidence: 99%

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Thermal Summer Diurnal Hot-Spot Analysis: The Role of Local Urban Features Layers

et al. 2021

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This study was focused on the metropolitan area of Florence in Tuscany (Italy) with the aim of mapping and evaluating thermal summer diurnal hot- and cool-spots in relation to the features of greening, urban surfaces, and city morphology. The work was driven by Landsat 8 land surface temperature (LST) data related to 2015–2019 summer daytime periods. Hot-spot analysis was performed adopting Getis-Ord Gi* spatial statistics applied on mean summer LST datasets to obtain location and boundaries of hot- and cool-spot areas. Each hot- and cool-spot was classified by using three significance threshold levels: 90% (LEVEL-1), 95% (LEVEL-2), and 99% (LEVEL-3). A set of open data urban elements directly or indirectly related to LST at local scale were calculated for each hot- and cool-spot area: (1) Normalized Difference Vegetation Index (NDVI), (2) tree cover (TC), (3) water bodies (WB), (4) impervious areas (IA), (5) mean spatial albedo (ALB), (6) surface areas (SA), (7) Shape index (SI), (8) Sky View Factor (SVF), (9) theoretical solar radiation (RJ), and (10) mean population density (PD). A General Dominance Analysis (GDA) framework was adopted to investigate the relative importance of urban factors affecting thermal hot- and cool-spot areas. The results showed that 11.5% of the studied area is affected by cool-spots and 6.5% by hot-spots. The average LST variation between hot- and cold-spot areas was about 10 °C and it was 15 °C among the extreme hot- and cool-spot levels (LEVEL-3). Hot-spot detection was magnified by the role of vegetation (NDVI and TC) combined with the significant contribution of other urban elements. In particular, TC, NDVI and ALB were identified as the most significant predictors (p-values < 0.001) of the most extreme cool-spot level (LEVEL-3). NDVI, PD, ALB, and SVF were selected as the most significant predictors (p-values < 0.05 for PD and SVF; p-values < 0.001 for NDVI and ALB) of the hot-spot LEVEL-3. In this study, a reproducible methodology was developed applicable to any urban context by using available open data sources.

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Unveiling the complex networks of urban tree diversity research: A global perspective

Xie,

Chen,

Liu

et al. 2024

Ecology and Evolution

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Ecosystem services offered by urban forests must be proactively managed to remain diverse and sustainable. Recent research findings deserve a systematic synthesis to elucidate inherent knowledge structures and dynamics. This study focused on the urban tree diversity theme from 2000 to 2022. Web of Science Core Collection database provided bibliometric details on academic publications. The data‐driven quantitative analysis explored research quantities, emphasis, trends, patterns, linkages, and impacts by countries, institutions, authors, journals, and citations. Publications and research topics have expanded continually, with accelerated growth in recent years. Research activities, outputs and interactions demonstrated conspicuous spatial clustering. A few countries, institutions and researchers generated a notable proportion of publications. Their scholarly contributions were visualized in knowledge graphs as complex networks of nodes and inter‐node links. Keyword analysis generated a network to indicate research hotspots and frontiers to steer and prioritize future studies. Recent findings affirmed that cities can harbor substantial tree diversity due to enhanced habitat heterogeneity and successful species adaptation. Aligning tree traits with environmental conditions and management objectives can improve benefits. Urbanization can filter tree traits to shape community assemblages through stressors: habitat degradation, fragmentation and loss, in conjunction with pollution, climate change, and introduced species. Diversity preservation strategies include protecting remnant natural vegetation, connecting green spaces, and restoring complex canopy geometry and biomass structure. The emerging frontiers are marked by modeling future species distributions, leveraging technologies like remote sensing, linking ecology with human values, and committing to community‐based stewardship. Management can be upgraded by interdisciplinary perspectives integrating ecological science and social engagement. The findings highlight the need for biodiversity enrichment anchored by native species, trait‐matched assemblages, adaptive policies, and community participation to create livable‐green cities. This review synthesizes key advances in urban tree ecology and biodiversity research to inform the planning and stewardship of resilient urban forests.

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Surface urban heat islands in Italian metropolitan cities: Tree cover and impervious surface influences

Cited by 133 publications

References 95 publications

Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

Thermal Summer Diurnal Hot-Spot Analysis: The Role of Local Urban Features Layers

Unveiling the complex networks of urban tree diversity research: A global perspective

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