Orals: Fri, 2 May | Room 2.24
Latin America is among the most urbanized regions in the world. SELPER, a Latin American non profit organization is interested in contributing to a better understanding of climate-related problems using Earth Observation and remote sensing data. This collaborative research by ISPRS and SELPER researchers responds not only to the intensification of the urban heat island (UHI) effect caused by the rapid development of cities in recent decades, but also recognizes the importance of preserving and restoring critical blue-green infrastructure to mitigate the effects of climate change.
During a first stage, the study focused in 16 major Latin American megacities present at 6 countries, collectively home to approximately 73 million people: São Paolo (22.62), Mexico City (22.28), Buenos Aires (15.69), Río de Janeiro (13.73), Bogotá (11.51), Lima (11.2), Santiago (6.9), Belo Horizonte (6.25), Guadalajara (5.42), Monterrey (5.12), Brasilia (4.87), Recife (4.26), Porto Alegre (4.21), Medellin (4.1), Salvador (3.96) and Curitiba (3.81). Each city was mapped and analyzed using Google Earth Engine and remote sensing data. The analysis included Land Surface Temperatures (LST) and Local Climate Zones (LCZ) for the years 2003, 2008, 2018 and 2021. Preliminary results explored the UHI distributions and the impact of different levels of urban development by LCZ.
First-stage acchievements indicate, that these megacities exhibit: (1) a diffuse urban model, (2) urban heat islands are spatially and temporally located, (3) compromised green-blue infrastructure during the last decades, and (4) differences in construction materials and morphological changes among surface structures.
Collaboration is needed. For the second stage the researcher's group is developing green-blue infrastructure models for each city, such as the Urban Canopy Model (UCM), Riparian Infrastructure Model (RIM) and/or Urban Green Areas (UGA). These models will be based on a fusion of Earth Observation, remote sensing data and local knowledge. Moreover, important information will be retrieved, such as meteorological local station data and socioeconomic information.
In summary, collaborative efforts could achieve potential results to create the basis for implementing preventive policies for sustainable planning, promoting climate justice, and adopting nature-based solutions in Latin American megacities.
How to cite: Yépez-Rincón, F. D., Rocha-Salamanca, L. A., Polidori, L., Hernández-Palma, H. J., Antes, M., Cuello, A., Alva-Huayaney, M. E., Ferrerira, H. S., Huerta-Garcia, R. E., Ramirez-Serrato, N. L., Bruster-Flores, J. L., Zapata-Wah, I. G., Guerra-Cobián, V. H., and Ferrino-Fierro, A. L.: ISPRS-SELPER: Tackling Urban Heat Islands in Latin America through Collaborative Research, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11841, https://doi.org/10.5194/egusphere-egu25-11841, 2025.
Over the past decade, there has been a significant increase in studies leveraging satellite-derived land surface temperature (LST) data to evaluate the cooling efficiency of urban vegetation, especially in multi-city studies. This surge reflects growing interest in understanding the role of green infrastructure in mitigating urban heat, and the computational power to easily process global satellite imagery. However, LST differs fundamentally from air temperature, the latter being more directly linked to human thermal comfort and health. Moreover, heat stress is a complex phenomenon that is influenced not only by air temperature but also by humidity, wind, and radiation.
In this presentation, I will provide a comprehensive overview of my past and ongoing research assessing urban vegetation's cooling efficiency. We will explore studies employing satellite-derived LST, gridded urban-resolving air temperature estimates, and crowdsourced air temperature and humidity measurements, highlighting the strengths and limitations of these approaches. Additionally, I will discuss the role of radiation in shaping urban heat stress and examine how vegetation interacts with radiation to modulate the urban microclimate. By synthesizing insights from multiple methodologies and considering the interplay of diverse environmental factors, this talk aims to offer a nuanced understanding of how urban vegetation contributes to thermal regulation and human well-being.
How to cite: Chakraborty, T. (.: How relevant is satellite-derived land surface temperature for assessing the cooling efficiency of urban vegetation?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2592, https://doi.org/10.5194/egusphere-egu25-2592, 2025.
Urban transformative adaptation is increasingly crucial to minimize the adverse impact of climate change, also in the context of the ongoing global urbanization. Street green space (SGS) represents a key strategy in the solution space due to its capacity to reduce urban heat burden through shade and evapotranspiration. Yet, estimating the cooling efficiency of street trees is highly dependent on the location-specific climate zone, the within-city differences in urban form, as well as on the data and metrics used to measure the urban microclimate and green space density. Moreover, the bulk of previous studies have used remotely sensed land-surface temperature, the use of which is widely criticized for quantifying heat stress.
Here we conduct a 100-meter resolution empirical assessment in a globally relevant pool of cities and with a local climate zone (urban form) within-city stratification to re-evaluate the role of street green space in adapting to urban heat in different urban contexts. We measure local heat load using different metrics (wet-bulb globe temperature (WBGT), and average, maximum and minimum 2-meter air temperature), which are calculated from the hourly output of the UrbClim urban climate model for 143 cities across the world, and we use estimates of the Green View Index (GVI) as a street-based measure of tree canopy cover.
Using random-effects regression models and controlling for a set of confounding factors in the statistical relation (such as population density, water bodies, and buildings height), we find that street green space is an effective strategy to reduce urban heat, but its effectiveness is highly context- specific, depending on both the local climate and the urban form. Our results can serve to inform the global discourse on transformative change of cities to achieve both adaptation goals (e.g. by reducing health impacts of urban heat or the risk caused by urban hydrological hazards), as well as energy use reduction and emission mitigation targets (e.g. cooling energy needs), also in the light of the upcoming IPCC AR7 special report on cities and climate change.
How to cite: Falchetta, G., Lohrey, S., Souverijns, N., Schleussner, C.-F., and Niamir, L.: Street green space for urban heat reduction: a globally-relevant, local climate zone-specific empirical assessment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5169, https://doi.org/10.5194/egusphere-egu25-5169, 2025.
Dense and urbanized European capitals under the Austro-Hungarian empire were developed at the end of the 19th century. In both Vienna (Austria) and Budapest (Hungary), the historic city defense structures were developed into dense, prestigious housing areas with at least four stories. While important cultural heritage, many historically built-up areas are now a challenge for heat reduction and urban planning. In Central Europe, nature-based solutions are being eyed as measures to tackle urban heat islands and the unequal distribution of green areas across cities. In Vienna and Budapest, the local populations are facing growing climate change impacts in the form of heatwaves and tropical nights, which are expected to negatively affect health and wellbeing.
Combining the results of urban heat modelling with the results of a survey with an integrated discrete choice experiment conducted in Budapest and Vienna, this study investigated which geographical parts of the cities are more affected than others, which citizens are the most vulnerable and how they perceive their own affectedness. By combining data on actual and perceived impacts of the temperature, urban areas are identified which are in greater need of nature-based solutions. By identifying the residents of these areas, vulnerable social groups requiring city administration’s attention and support are identified and policy recommendations are given.
In both Budapest and Vienna heat is felt more intensely and impacts health to a greater extent in neighborhoods with limited access to and poor-quality green areas, while neighborhoods with ample access to public and private green areas are not as strongly impacted by high temperatures. However, residents of Budapest stated to have more experience with heat waves and respondents indicated much higher rates of heat negatively effecting both their wellbeing and their health. This feeling was not confirmed by the heat models – meaning that the difference between perceived heat and actual temperatures is higher in Budapest.
For urban planners the results of this study translate into setting clear planning priorities and goals specific to their residents’ needs: To gain the greatest possible benefits for residents and reduce urban heat island effects, nature-based solutions targeting heat reduction should be placed in neighborhoods which demonstrate high heat perception based on social analysis and heat modeling. By using this approach, planners will address both climate change and its impacts on the population in urban environments.
How to cite: Wanner, A., Budhiraja, B., Pröbstl-Haider, U., McKinley, J., and Jungnickel, M.: Challenges created by the Austro-Hungarian Empire: Heat reduction through nature-based solutions in Vienna and Budapest, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8046, https://doi.org/10.5194/egusphere-egu25-8046, 2025.
Urbanization induces complex interactions between socioeconomic activities and environmental changes, as reflected in the increase of Night-Time Light (NTL) and the decline of Fractional Vegetation Cover (FVC). While NTL is a key indicator of economic growth and infrastructure expansion, its concurrent association with vegetation loss exacerbates urban heat island (UHI) effects. Although substantial progress has been achieved in examining the individual impact of urbanization on land surface temperature (LST), studies investigating the simultaneous trends of NTL and FVC and their combined effect on LST remain limited.
This study utilized a 20-year (2000–2020) remote-sensed dataset to investigate the spatial and temporal interactions among NTL, FVC, and LST anomalies in East Asian megacities, especially Seoul, Tokyo, Beijing, Shanghai, and Hong Kong. Trends in NTL and FVC were analyzed using the Mann-Kendall test and Sen’s slope methods, while LST anomalies were examined to evaluate relationships with NTL and FVC. The analysis specifically focused on summer months to comprehensively evaluate urban heat island effects. Furthermore, NSGA-II optimization was employed to identify the optimal NTL and FVC ranges that best capture LST trends and explore city-specific urban green space planning patterns.
The results reveal distinct nonlinear relationships between night-time light, fractional vegetation cover, and land surface temperature. LST responses varied depending on the increased balance between NTL and FVC. LST showed a more moderated response in regions where NTL and FVC increased proportionally, suggesting that vegetation can partially mitigate urbanization's thermal impacts through a synergistic effect. Conversely, areas with disproportionately high NTL increases and limited FVC growth exhibited heightened LST sensitivity, reflecting the restricted capacity of vegetation to offset the thermal stress caused by rapid urban expansion.
In Shanghai, rapid urbanization has resulted in a substantial increase in land surface temperature (LST), underscoring the city's heightened vulnerability to urban development. In contrast, both Seoul and Shanghai exhibited more moderate declines in LST in areas where urban green space initiatives were implemented. However, despite Shanghai's extensive urbanization, the expansion of urban green spaces, as quantified by the rate of change in the Fraction of Vegetation Cover (FVC), has been comparatively limited relative to other cities. Furthermore, over the past 20 years, the frequency of FVC and NTL increases demonstrated a more substantial correlation with LST increases than the intensity. These findings highlight the pronounced spatiotemporal heterogeneity in urban environments, emphasizing disparities in environmental stress and recovery potential driven by varying interactions between NTL and FVC.
This research suggests key indicators, such as the balance between NTL and FVC, to guide the development of cooling strategies in urban planning. The findings highlight the potential of integrating vegetation restoration into urban planning as a critical approach to achieving global sustainability goals, particularly SDG 11 (sustainable cities and communities) and SDG 13 (climate action).
How to cite: Kim, E. and Kim, J.: How Do Urban Green Spaces Influence Land Surface Temperature Dynamics in Urbanizing Areas?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14258, https://doi.org/10.5194/egusphere-egu25-14258, 2025.
Urban heat islands significantly challenge environmental sustainability and public health, creating localized areas within cities with higher temperatures. Addressing these issues requires predictive tools for precise temperature forecasts to aid urban planning and policy decisions. Although satellite-based land surface temperature (LST) monitoring has potential, data from the ESA Copernicus Sentinel-3 mission face two key limitations: inadequate spatial resolution for urban-scale differentiation (1 km per pixel bidaily LST measurements) and the disparity between land surface and air temperatures.
This research introduces a machine learning model designed to predict maximum daily air temperatures at a spatial resolution of 20 meters per pixel, sufficient for the recognition of temperature differences between individual city blocks. For each day the inference is run, the model produces a seven-day temperature forecast. Our technology utilizes a visual transformer-based architecture, which distinguishes itself by being more compact and computationally efficient than traditional convolutional neural networks (CNNs), achieving a mean absolute error (MAE) of 2°C across seven-day temperature predictions for three major European cities.
The model uses multiple remote sensing and weather forecast data. The first input is LST data fromSentinel-3. It also uses NDVI data from Sentinel-2, sensitive to vegetation health and density. Meteorological data include forecasted temperature, pressure, humidity, wind, and more. For topographic data, two sources are used: the Digital Elevation Model for terrain altitude and the Copernicus Urban Atlas for land use classification. All input data is resized to the required dimensions and combined into a single 3D tensor for the model. Circular encoding is used to incorporate the day of the year and time of day of the Sentinel-3 passage. All inputs, except for the weather data, are stacked and combined with the weather data for the predicted day, then passed to the model. This process is repeated for each of the seven days to generate the temperature predictions.
Temperature measurements used for target for ML training are sourced from on ground stations and processed into a 2D matrix, with pixel values showing the average maximum temperature recorded by each station within the pixel's area. Pixels with no active stations are marked as invalid. For each valid pixel, the mean squared error (MSE) loss between the model's predicted temperature and the ground truth is computed to update the model weights. An encoder-decoder architecture is used to translate these multidimensional inputs into a set of two-dimensional temperature maps. The chosen encoder is a Mixed Transformer model (MiT), and the decoder is a simple cascade of convolution-upsample.
The model is embedded in a continuous pipeline for uninterrupted operation. Its daily workflow automatically retrieves data, preprocesses it, and generates temperature mappings. Seven-day temperature forecasts are uploaded to a dashboard, presenting predictions as overlays on urban landscapes. This solution is part of UP2030, a project supported by the EU's Horizon Europe program, which guides cities through socio-technical transitions towards climate neutrality.
How to cite: Innocenti, L.: Forecasting Urban Heat Islands: A Neural Network Approach Using Remote Sensing Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6578, https://doi.org/10.5194/egusphere-egu25-6578, 2025.
Urbanization and regional climate change-induced warming, known as the Urban Heat Island effect, result in urban areas experiencing temperatures 1–4 °C higher than their rural counterparts. This phenomenon poses significant risks to biodiversity, human health, and regional climate systems, necessitating an in-depth understanding of its spatiotemporal patterns and characterization to inform effective adaptation strategies. In this study, we investigated the diurnal and seasonal dynamics of Surface Urban Heat Island intensity (SUHII) for 141 Indian cities over two decades (2001-2022) using MODIS satellite-derived Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), evapotranspiration (ET), and Land Use Land Cover (LULC) data. We employed the urban-rural method to calculate SUHII, used the Mann-Kendall Test and Theil-Sen slope estimator to identify trends, while five-year interval analyses captured the evolution of SUHII hotspots. Further, to characterize SUHI variability, we used a Multilevel Modeling (MLM) approach, incorporating time-varying NDVI and ET, alongside city size as a time-invariant factor. Our findings reveal a significant rising trend in nighttime SUHII across most cities, while five-year average change analyses highlight emerging daytime SUHI hotspots during both summer and winter seasons. The MLM approach explained more than 90% of SUHII variability in both seasons. While SUHII generally showed negative associations with ΔNDVI and ΔET across most cities, except in warm deserts, city size exhibited a negative yet weak association. Overall, our findings demonstrate the escalating SUHI effect in Indian cities and underscore the importance of vegetation and water dynamics in regulating urban thermal environments at a regional scale. These insights emphasize the urgent need for sustainable local-scale urban planning to mitigate the adverse impacts of SUHI on ecosystems and human well-being.
How to cite: Thakur, D. and Dhanya, C. T.: Rising Urban-Rural Temperature Gradient in Indian Cities: Analysis and Characterization, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11323, https://doi.org/10.5194/egusphere-egu25-11323, 2025.
Nature-based solutions offer significant potential to mitigate the impacts of urban heatwaves if urban trees and their soils can capture unused stormwater and create evaporative cooling. This study employed the i-Tree Cool Air soil-vegetation-atmosphere transfer model to evaluate the effects of increasing neighborhood tree cover to a minimum of 30% in all neighborhoods of 10 Italian cities during the extreme summer of 2003. The analysis introduced a heatwave degree day (HWDD) metric to quantify reductions in heatwave intensity and duration, which were mapped alongside excess mortality attributed to heatwaves in the baseline scenario. Results reveal that transitioning from the average baseline tree cover of 8.2% to 30% would decrease HWDDs by 32.5%, with reductions varying from 15.8% in Cagliari to 84.1% in Bologna. Correspondingly, excess mortality among adults aged 65 and older would decline by 29.3%, sparing an estimated 574 lives from the 1962 killed by the 2003 heatwaves. The study also highlights spatial variability in mortality reductions, reflecting neighborhood-specific differences in tree cover, developed area, and population density. Enhanced tree cover improved ecosystem services, with a median annual increase in value of $11 million per city, generated by reductions in air pollution (53%) and stormwater runoff (33%), and increases in carbon sequestration (14%). This research underscores the transformative impact of urban greening in mitigating heatwave risks and highlights its utility for informing urban planning policies aimed at climate adaptation and public health.
How to cite: Endreny, T., Ciolfi, M., Endreny, A., Chiocchini, F., and Calfapietra, C.: Modeling Decreased Intensity and Mortality of the 2003 European Heatwave with Nature-based Solutions of Evaporative Cooling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12933, https://doi.org/10.5194/egusphere-egu25-12933, 2025.
Urban Heat Islands (UHIs) significantly impact urban climate resilience, with both beneficial and adverse effects depending on seasonal and spatial factors. This study evaluates the influence of cool roofs and green roofs, designed to mitigate summer UHI intensity, on winter UHI dynamics in Seoul, Korea. A deep learning framework, incorporating temporal and spatial models, was developed to forecast UHI intensity and propose balanced seasonal mitigation strategies.
The temporal model used meteorological data collected from 54 Automatic Weather Stations (AWSs) over a 10-year period (2014–2023) and accounted for variables such as temperature, humidity, wind speed, and solar radiation. The spatial model incorporated GIS-derived data, including building density, vegetation coverage, and road imperviousness, along with satellite-obtained albedo and radiance information. Both models were combined into a hybrid system to predict seasonal UHI patterns.
According to previous research, cool roofs alleviated the urban heat island intensity in summer by an average of 2.5°C, and green roofs showed a mitigation effect of 1.8°C. These two strategies had the greatest impact mainly during the noon hour (12:00–15:00). On the other hand, cool roofs in winter had the side effect of increasing heating energy demand by about 5%, but green roofs offset this effect, limiting temperature drops to an average of 1°C and suppressing additional heating demand to 2%. Spatial analysis indicated that high-density urban areas were the main targets of mitigation strategies, with marked differences in seasonal UHI characteristics.
This research provides actionable insights for urban climate resilience planning, demonstrating the potential of deep learning models to inform policy and design interventions. The findings underscore the importance of spatially and temporally adaptive strategies, such as targeted cool roof and green roof installations, to achieve sustainable urban heat management across seasons.
This work was supported by Korea Environment Industry &Technology Institute (KEITI) through "Climate Change R&D Project for New Climate Regime.", funded by Korea Ministry of Environment (MOE) (RS-2022-KE002102)
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Climate Change R&D Project for New Climate Regime Program, funded by Korea Ministry of Environment(MOE)(RS-2023-00221110)
How to cite: Jun, S., Kim, S. H., and Lee, D. K.: Evaluating the Seasonal Effects of Cool Roofs and Green Roofs on Urban Heat Island effect Using Deep Learning Models in Seoul, Korea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8968, https://doi.org/10.5194/egusphere-egu25-8968, 2025.
Urban Heat Islands (UHIs) exacerbate the challenges of rising temperatures in urban areas, increasing heat stress and thermal discomfort for urban dwellers. This study focuses on Bhubaneswar, a city in eastern India experiencing significant recent urbanisation, to analyse the effectiveness of greening efforts on dynamics of UHIs. For that, Land Surface Temperature (LST) was derived from Landsat 8 and 9 data spanning 2013 to 2024 to evaluate UHI pockets, persistence UHI and reduced UHI areas along with the Normalized Difference Vegetation Index (NDVI) and Bare Soil Index (BSI), to investigate the relationship between vegetation cover, bare surfaces, and influence on UHI dynamics. The analysis identified persistence UHI in industrial zones, including the airport and bare land areas. Conversely, newly formed UHI pockets emerged along national highways and dense built-up areas. The study also identified reduced UHI areas, regions that exhibited intense UHI effects in earlier years but showed no UHI presence by later years. These areas show the positive impact of greening initiatives and surface changes over the past decade. NDVI analysis revealed a significant increase in vegetation in reduced UHI areas, indicating the positive impact of initiatives. In contrast, persistent UHI areas, exhibited lower NDVI values, underscoring the lack of vegetation and its role in sustaining high LSTs. BSI analysis further complemented these findings, showing a notable reduction in bare surfaces within reduced UHI areas compared to persistent UHI zones. The results highlight the critical role of vegetation in moderating UHI effects. This study underscores the importance of integrating green infrastructure into urban planning to address the growing UHI effects in cities. The results highlight the need to expand greening efforts to effectively manage UHI effects in urban areas.
How to cite: Pritipadmaja, P. and Garg, R. D.: The Influence of Vegetation and Surface Changes on Urban Heat Island Dynamics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-782, https://doi.org/10.5194/egusphere-egu25-782, 2025.
Urban heat islands (UHI), which can be exacerbated by extreme heat events, pose a growing risk to metropolitan regions worldwide. Nature-based Solutions (NbS) are an adaptive solution to UHI. However, the equitable distribution of NbS benefits to address UHI can be obstructed if stakeholders are not sufficiently engaged in a participatory and just planning process. Excluding justice considerations weakens the ability of NbS to deliver benefits to those most vulnerable to heat and may create or entrench existing environmental and socioeconomic disparities. In the case of addressing UHI in metropolitan regions, there is a strong need for NbS planning approaches for heat that can account for landscape diversity while strengthening the equitable distribution of NbS benefits. However, planning approaches depend on the decision-making and preferences of relevant stakeholders, who may be more or less interested in ensuring equitable outcomes.
There is a lack of research on understanding how stakeholders are currently integrating climate justice into NbS preferences and decision-making. This research addresses this critical gap by assessing the degree of climate justice consideration in NbS planning for heat across several European metropolitan regions representing different biogeographical and climatic regions. We use surveys to investigate stakeholder preferences for NbS to address urban heat, as well as which NbS benefits and implementation criteria should be prioritized in planning. Participatory geospatial mapping is also deployed to better understand stakeholders’ perceptions of where and why current NbS in their metropolitan regions are effective against heat risk and to identify areas that need NbS benefits. Through these methods, we assess the relative strength of stakeholders’ consideration of climate justice in their preferences and perceptions. We present our methodology and preliminary results which lead to a research agenda on climate justice and participatory NbS planning.
How to cite: Urrutia II, J. M., Anderson, C. C., and Albert, C.: Considering climate justice in NbS planning for metropolitan heat risk reduction? A participatory GIS approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10918, https://doi.org/10.5194/egusphere-egu25-10918, 2025.
Urban Heat Island is a significant urban climate phenomenon, particularly during extreme heat events, with profound impacts on environmental sustainability and human well-being. This study investigates UHI dynamics in the Beijing-Tianjin-Hebei (BTH) region during the summers of 2019–2024 using FY-3D satellite-derived Land Surface Temperature (LST) data. Employing Dynamic Equal-Area UrbanHeat Island Classification (DEA) combined with the Beijing local standards, UHI intensity was quantified and classified into five levels to analyze spatiotemporal variability and transitions across intensity levels. The results reveal a pronounced UHI intensification in 2023, with cities such as Beijing, Tianjin, and Rwanda exhibiting intensity values exceeding 2K. High-intensity UHI zones expanded significantly, particularly in southern Hebei, while 2022 and 2024 showed similar, lower-intensity patterns. These findings provide strong evidence supporting the occurrence of record-breaking localized temperatures in the BTH region during 2023. This study underscores the value of FY-3D data for precise UHI monitoring, offering robust quantitative assessments and spatial distribution insights. The findings lay a foundation for developing effective heat mitigation strategies and sustainable urban planning in rapidly urbanizing regions.
How to cite: Zhou, T.: Multi-level heat island monitoring in the Beijing-Tianjin-Hebei region during the summers of 2019-2024 using FY-3D LST data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19202, https://doi.org/10.5194/egusphere-egu25-19202, 2025.
Urbanization poses significant challenges to climate resilience, particularly in rapidly expanding cities like Kolkata in India. The extensive land use and land cover (LULC) changes resulting from unplanned urban growth have intensified urban climatic issues, notably the Surface Urban Heat Island (SUHI) and Urban Aerosol Pollution Island (UAPI) effects. This study investigates the impact of Kolkata's urbanization over the past 20 years (2000–2020), focusing on the interplay between LULC changes and the exacerbation of SUHI and UAPI phenomena. The findings reveal that the transformation of green spaces into built-up and impervious areas has significantly contributed to rising Land Surface Temperatures (LST) and deteriorating air quality. In contrast, regions with higher vegetation cover consistently recorded lower LST, often remaining below 30 °C, even in densely urbanized zones. Keeping temperatures below 30 °C reduces heat stress and mitigates emissions and are essential for achieving global health priorities and the Paris Agreement goal of limiting temperature rise to 1.5°C above pre-industrial levels. This highlights the critical role of urban greening in mitigating these adverse effects. A tailored vegetation strategy is proposed, categorizing urban areas based on road types—national highways, state highways, and residential roads. Using the i-Tree application, the study identifies suitable tree species for urban greening initiatives, considering Kolkata's unique climatic conditions, including temperature, growing season length and height constraints to achieve desired pollutant removal and eight other environmental factors. By aligning greening efforts with these classifications, the study demonstrates how nature-based solutions can effectively reduce SUHI and UAPI impacts while enhancing urban sustainability. This research underscores the importance of strategic vegetation planning to counteract the negative impacts of urbanization in tropical cities like Kolkata. By addressing LULC changes with targeted urban greening measures, cities can enhance their resilience to extreme climatic events and improve overall environmental quality.
Keywords: LULC, SUHI, UAPI, Urban Greening, Nature-Based Solutions
How to cite: Yenugula, R. and Kuttippurath, J.: Strategic Urban Greening to Mitigate Urban Heat and Pollution Islands: A Nature-Based Approach for the Megacity Kolkata, India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7849, https://doi.org/10.5194/egusphere-egu25-7849, 2025.
Despite the increasing trend of temperatures due to climate change, urban areas often experience higher temperatures than rural areas, a phenomenon commonly referred to as the Urban Heat Island (UHI). Heat waves are becoming more frequent in Turku, Finland (humid continental climate zone), and longer and warmer days are being experienced in summer than in nearby rural areas. The use of heat-absorbing materials in construction, increased impervious surfaces, higher emissions of CO2, and lack of blue-green regions in the urban territory, etc., are found to accelerate this phenomenon. Green infrastructure or urban green parks are expected to moderate temperature fluctuations by absorbing less heat and providing cooling through evapotranspiration, thereby slowing down temperature changes in urban environments.
In this research, the impact of urban greenery to mitigate UHI during heatwaves in the city of Turku, South-West Finland, was studied. We exploited spatially and temporally comprehensive temperature observation data over the urban area, and precise land use data to analyze the relationships between UHI and UG. A total of 22 temperature monitoring stations, recording temperatures every 30 minutes from 2002 to 2024, were used. The land cover in 2022 was obtained from an open 2m resolution land cover dataset produced by SYKE (Finnish Environment Institute). Satellite images were used to detect the change in land cover since 2002.
Statistical methods were used to find temperature-increasing trends at each logger station point to observe and analyze how urban greenery can influence or control temperature fluctuations. The neighborhood of several logger stations underwent changed land use (forestry to residential blocks with impervious surfaces). How this urbanization influenced the microclimate change in the city will be analyzed. Also, changes in the duration and magnitude of heat waves from 2002 to 2023 are expected to be studied.
Nature-based Solutions (NBS), especially urban green (UG) infrastructures, are becoming popular also in Nordic countries to increase climate change resilience, reduce the risk of urban flooding, improve public well-being, better immune systems, and urban biodiversity. However, not many studies have been done examining urbanization, UG, heatwaves, and UHI, especially in humid continental climate zones. This study aims to deepen the understanding of the effect of urban greenery on UHI, and how they control temperature in neighborhoods during heatwaves in Turku. The outcomes of these results may help city planners design city expansion in a way that makes it resilient to future climate change-intensified heatwaves in the same climate zone.
How to cite: Asif Rifat, A., Suomi, J., Sörensen, J., and Kasvi, E.: Assessing the potential of Urban Greenery to adapt to climate change intensified UHI during heatwaves in Humid Continental Climate climate zones using Long-Term Data and Geospatial Analysis., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18768, https://doi.org/10.5194/egusphere-egu25-18768, 2025.
Due to the seriousness of global warming and climate change, climate-related mitigation and adaptation have become one of the biggest concerns worldwide, including Taiwan. Therefore, Urban Heat Island (UHI) mitigation and adaptation are important in Taiwan, which is beneficial for outdoor thermal comfort and citizen’s health. Although there is a different seriousness of the UHI effect in Taiwan’s major cities, most of the news attention is focused on Taipei City, the capital of Taiwan, which may underestimate the climate issues in other cities. Therefore, this study aimed to investigate the UHI effect in the 5 major cities in Taiwan, and also their climate-related news attention, using big data analysis and Geographical Information System (GIS). First of all, meteorological data in the above cities in recent years was collected and the UHI distribution in different cities was interpolated through GIS. Then the UHI intensity (UHII) of different cities in recent years was further calculated, to present the seriousness of the UHI effect in different cities. On the other hand, climate-related news in Taiwan in recent years was obtained and filtered from Google using a web crawler. After that, the relationship between UHII and news attention was further analyzed. For the results, the UHI effects in different cities were investigated, and the hotspots were identified, which were mainly distributed downtown with more commercial and residential areas. Moreover, the UHII in different cities in recent years was further investigated. The strongest UHII can be found in Taipei City in 2023, and the UHII of most of the major cities increased in recent years, which presented the deterioration of climate conditions in different cities. However, there is no strong correlation between UHII and news attention. Although the amount of climate-related news increased with the increasing UHII, most of the news attention focused on the climate issues in Taipei City, which is significantly higher than other cities. The above phenomenon may cause less climate-related policy attention in other cities because of the less news attention. Moreover, policymakers may make UHI mitigation and adaptation strategies based on the climate and urban conditions in Taipei City because of the higher news attention, which may be less suitable for other cities. According to the above findings, spatial and climate injustice can be observed and should be further discussed and addressed, to ensure sustainable development in Taiwan. In summary, this study investigated the UHI effect and UHII in Taiwan’s major cities and further discussed the uneven climate-related news attention distribution in Taiwan. The results can remind the public and policymakers in Taiwan to further concern about the climate issues in cities apart from Taipei City, which is beneficial for UHI mitigation and adaptation in Taiwan.
How to cite: Lau, T. K. and Huang, K.-H.: Distribution of Urban Heat Island effect and News attention in Taiwan’s major cities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2873, https://doi.org/10.5194/egusphere-egu25-2873, 2025.
The accelerating impacts of climate change, including escalating urban temperatures and the heightened occurrence of extreme weather events, present formidable challenges for rapidly growing cities, particularly in the Global South. Nature-based solutions (NBS) present transformative pathways to address these issues, offering sustainable approaches to enhance resilience, mitigate urban challenges, and improve the well-being of urban residents. Urban Green Spaces (UGSs) are central to these solutions, providing climate adaptation and mitigation benefits.
This study investigates the applicability of the 3–30–300 rule—a recently proposed guideline for equitable urban greening—through case studies in two Indian cities, Nagpur and Jaipur. The guideline advocates for three visible trees per residential building, 30% neighborhood UGS cover, and at least one hectare of UGSs within 300 meters of residences. A GIS-based analysis of land cover maps was conducted to assess public UGS availability, proximity, and provisioning gaps, addressing the 30-300 components. Household surveys measured the visibility of trees to evaluate the "three visible trees" component. A zone-specific analysis explored the potential of applying the 3–30–300 rule to mitigate challenges urban areas face, such as the Heat Island phenomenon and increased urban flooding—exacerbated by rapid urbanization and climate change.
This research develops a replicable and scalable methodological framework, enabling its application to other cities undergoing rapid urban transitions. By quantifying the benefits of equitable urban greening, the study provides urban planners and policymakers with actionable insights and tools for informed decision-making. Highlighting the potential of integrating NBS into mainstream urban planning, the study positions the 3–30–300 rule as a practical and effective guideline for addressing urban sustainability and resilience challenges, particularly in resource-constrained cities of the Global South.
How to cite: Lahoti, S., Thomas, M., Kumar, P., Dhyani, S., and Shende, P.: Implementing the 3-30-300 Rule in Indian Cities: A Framework for Addressing Urban Challenges, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14989, https://doi.org/10.5194/egusphere-egu25-14989, 2025.
Strategic urban green infrastructure (UGI) planning is crucial to mitigate heat stress and foster climate-responsive urban areas that promote liveability, especially in hot and humid subtropical regions. However, paucity of empirical data on UGI-based heat mitigation has led to a dearth of effective urban green spaces in most Indian cities. This study, therefore, aims at developing actionable, evidence-based UGI planning strategies to enhance outdoor thermal comfort (OTC) by taking the case of two typical residential typologies in Dehradun, India. The selected neighbourhoods represent 1-2 storeyed plotted individual houses and 3-4 storeyed row block housing, respectively and include three urban settings: housing park, roadside plantation and private gardens or shared courtyards, for a more focussed analysis.
Context-specific ‘Quality and Quantity’ of UGI are critical for its cooling performance. This necessitates a need to understand the performance of subtropical tree species based on their traits, their placement in the aforementioned urban settings and the role of canopy cover in maximising OTC. Moreover, the comparative performance of trees and UGI types like green roofs and green walls needs to be understood in realistic neighbourhood settings particularly in Indian context. Therefore, we investigate the ‘Right: UGI type, Tree species, Planting arrangement and Canopy cover’ approach using microclimatic simulations on validated ENVI-met software.
The simulation results indicate that trees are significantly more effective in improving human outdoor thermal comfort as compared to green roofs and green walls. The existing trees on the study sites reduce average PET (Physiological Equivalent Temperature) between ~2-9°C under dry and well-irrigated soil conditions during the daytime heat hours (10 a.m. -5 p.m.). Besides, the cooling potential of different tree species varies with their morphological characteristics, and the dense canopy (high LAD) trees have maximum cooling impact during peak heat stress. The impact of LAD becomes even more pronounced in combination with tree height and canopy width due to more widespread shade and evapotranspiration. The simulation results also highlight the influence of planting arrangement on shade, wind speed, and direction on the site. The tree arrangements parallel to the wind and facilitating evenly distributed shade have greater impact on enhancing OTC. Another finding substantiates the beneficial role of increasing overall canopy cover on the site. However, the combined impact of greening strategies like ‘right tree in the right place’ is more beneficial, even in the case with lesser canopy cover than the existing one. This could be particularly beneficial in urban areas with land scarcity.
Therefore, the study provides several empirical evidences that confirm the significance of UGI in improving OTC, as well as a holistic approach for strategizing UGI planning for neighbourhood climate adaptation. The findings of this study can be useful for landscape planners, policymakers and similar actors in comparable urban and climatic contexts. Future research can also test the impact of vegetation diversity on heat stress mitigation to further promote biodiversity and resilience in urban areas. Role of all the UGI types can also be assessed for other ecosystem services, such as stormwater management, for comprehensive climate adaptation.
How to cite: Javaid, S., Sista, K. Y., Mohamed, H., and Pauleit, S.: Evidence-based urban green infrastructure planning in humid subtropical neighbourhoods to enhance outdoor thermal comfort, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18144, https://doi.org/10.5194/egusphere-egu25-18144, 2025.
The increasing frequency of heat waves due to global warming, coupled with the urban heat island effect (UHI), poses significant risks to human health in cities, particularly in highly frequented areas such as public squares. As urbanization continues and temperatures rise, effective heat mitigation strategies are essential. Trees, with their cooling effects through shading and evapotranspiration, offer a key solution by reducing air and surface temperatures, thereby improving thermal comfort in urban environments.
This study investigates the cooling potential of trees in public spaces in Karlsruhe, Germany, a region in the heat-prone Upper Rhine Valley. It examines how tree characteristics - such as trunk height, diameter at breast height, and crown volume - and site factors - such as sky view factor, tree view factor, and leaf area index - influence the heat index, which measures thermal comfort. An essential aspect of the study was to assess the correlation between surface temperature and heat index, allowing the prediction of heat index from satellite-derived land surface temperatures. The novelty of this research lies in its integrative approach, combining tree characteristics and site factors and focusing on an under-researched region.
Field measurements were taken at eight public squares with varying tree cover and size during July and August 2024. Data collected included surface temperatures, tree-level variables, and site metrics, which were statistically analyzed with the heat index using correlations and simple linear regressions.
The results showed that squares with higher tree cover had significantly lower heat index values, indicating improved thermal comfort. Larger trees with higher trunk heights were particularly effective in reducing heat stress. The study also found that a lower sky view factor and a higher tree view factor correlated with reduced heat stress, highlighting the critical role of tree canopies in cooling public squares through shading. In addition, surface temperature was strongly correlated with heat index, suggesting that satellite-derived temperature data could be used to estimate thermal comfort in urban squares.
In conclusion, this research highlights the critical role of trees in mitigating the UHI effect in public squares, where heat stress can significantly impact public health. The results provide valuable insights for urban planning, demonstrating that targeted greening strategies, such as maintaining large trees, increasing canopy cover and frequency of large trees, can improve thermal comfort in public squares. In the future, cities can use satellite-derived land surface temperatures to accurately model and predict heat index, enabling more efficient and cost-effective planning to address heat-related challenges and create more sustainable, liveable public spaces.
How to cite: Saha, S. and Guenzel, M.: Research on the cooling effect of trees at public squares in Germany, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11884, https://doi.org/10.5194/egusphere-egu25-11884, 2025.
Climate change is leading to an increase in urban heat, posing a threat to both humans and biodiversity. Urban green spaces (UGS), such as parks and gardens, have been shown to be cooler than surrounding areas, providing respite for city residents and habitat for many species. However, in a future, hotter climate, it is unclear whether UGS will maintain temperatures cool enough to support both species and human tolerances. The goal of this study is to evaluate how the microclimate conditions of UGS will be altered under climate change and what strategies are most effective to maintain their cooling effect under such conditions. To do so, we used a microclimate model (UT&C) to simulate air temperature, thermal comfort and other relevant variables within 15 urban green spaces across three Swiss cities (Zurich, Geneva and Lugano) under historical and future climate conditions. All models, validated using data collected summer of 2023, show good predictive performance for air temperature and surface temperature (R2 = 0.61 to 0.97). Future climate data for the 2080 decade was obtained from the COSMO-CLM convection permitting model under RCP 8.5 and bias-corrected to the station scale. Scenarios incorporating the five vegetation parameters most relevant to thermal comfort - leaf area index, ground vegetation coverage, albedo, tree height, and tree coverage - were developed and assessed for their effectiveness in mitigating temperature increases in a future climate.
Preliminary results for Zurich show that the ambient air temperature in the summer months is expected to increase by 1.6°C on average by 2080 compared to 2023. The UGS with current vegetation properties is expected to cool the air temperature by 0.2 °C on average. Although unable to offset the increase in temperature due to climate change, increasing the fraction of ground vegetation is the most effective solution, cooling by up to 1.3 °C. The remaining alterations were less effective, with some even increasing the temperature with respect to the baseline scenario (no change in vegetation properties). Future work will confirm the generalizability of these findings with a comparison across all UGS and cities. Overall, this study provides insights into the adaptive management of urban green spaces for both humans and biodiversity in the face of climate change.
How to cite: Yin, Y., Manoli, G., and Cook, L.: Cooling down urban green spaces in a future climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10425, https://doi.org/10.5194/egusphere-egu25-10425, 2025.
İstanbul is located in the northwest of Türkiye and is the largest city in the country by population, with an estimated 16 million inhabitants. It also serves as the country's principal economic hub. Consequently, the city is experiencing significant migration both from other regions within Türkiye and from abroad. Moreover, urbanization in İstanbul is accelerating, driven in part by the increasing influx of refugees. As urbanization and population growth continue, the Urban Heat Island (UHI) effect has significantly intensified, leading to increased precipitation and more frequent heat waves. To investigate this phenomenon, a set of criteria was applied to select meteorological stations from the 44 stations across Istanbul. Six stations were chosen for analysis: Florya, Kireçburnu, Kumköy, Şile, Göztepe, and Kumköy station. These stations were selected to represent urban and rural environments, allowing for a comparative analysis of UHI. The temperature differences between urban and rural stations were analyzed to investigate the UHI effect. A non-parametric Mann-Kendall test was conducted to assess long-term trends in temperature data from these stations, covering the period from 1965 to 2023. For Florya, an urban station in Istanbul, the lowest recorded temperature was 10.18 °C in 1965, which increased to 11.4 °C in 2006, and further rose to 13.51 °C in 2023. In contrast, for Şile, a rural station, the lowest temperature was 10.19 °C in 1965, rising to 10.34 °C in 2006, and increasing substantially to 12.16 °C in 2023. The Mann-Kendall test for the period between 1965 and 2023 indicated a significant upward trend, with a critical value of 1.96 for the 95% confidence level. These results suggest that temperature increases in both urban and rural areas are statistically significant, with both Florya and Şile stations showing a significant increase in temperature during the mid to late 1990s. This study will continue by investigating each station using Mann-Kendall statistical analyses and examining the UHI effect. By summarizing these findings across all sections, the study will also contribute to understanding the potential climate cooling effects associated with UHI migration measures.
Keywords: Urban Heat Island; Climate Change; İstanbul; Urbanization; Refugee Influx; Mann-Kendall Test
How to cite: Birinci, E., Ozdemir, H., and Deniz, A.: Evolution of the Urban Heat Island in İstanbul from 1965 to 2023: Trends, Migration, and Climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5898, https://doi.org/10.5194/egusphere-egu25-5898, 2025.
