Urban Heat Island Intensity Research Articles

Seasonal Variations of the Relationship between Spectral Indexes and Land Surface Temperature Based on Local Climate Zones: A Study in Three Yangtze River Megacities

Urban heat islands are representative problems in urban environments. The impact of spectral indexes on land-surface temperature (LST) under different urban forms, climates, and functions is not fully understood. Local climate zones (LCZs) are used to characterize heterogeneous cities. In this study, we quantified the contribution of three cities to high-temperature zones and surface urban heat island intensity (SUHII) across LCZs and seasons, used Welch and Games–Howell tests to analyze the difference in LST, then described the spatial pattern characteristics of LST, and used a geographically weighted regression model to analyze the relationship between spectral indexes and LST. The results showed that compact midrise, compact low-rise (LCZ 3), large low-rise (LCZ 8), heavy industry (LCZ 10), and bare rock or paved (LCZ E) contributed greatly to high-temperature zones and had strong SUHII. There were 92–98% significant differences between different LCZs. The spatial aggregation of LST gradually weakened with a decrease in temperature. The modified normalized difference water index (MNDWI) in most LCZs of all seasons for Wuhan could reduce LST well, while MNDWI only had cooling effects in winter for Nanjing and Shanghai. Normalized difference vegetation index (NDVI) in most LCZs performed a cooling role during summer and transition seasons (spring and autumn), while it showed a warming effect in winter. The cooling effect of NDVI in open building types was stronger than that of compact building types, while the cooling effect of MNDWI was better in compact building types than in open building types. With the increase of normalized difference built-up index (NDBI), all LCZs showed warming effects, and the magnitude of LST increase varied in different cities and seasons. These results contribute further insight into thermal environment in heterogeneous urban areas.

The Impact of Urbanization on Urban Heat Island: Predictive Approach Using Google Earth Engine and CA-Markov Modelling (2005-2050) of Tianjin City, China.

Urbanization has adverse environmental effects, such as rising surface temperatures. This study analyzes the relationship between the urban heat island (UHI) intensity and Tianjin city's land cover characteristics. The land use cover change (LUCC) effects on the green areas and the land surface temperature (LST) were also studied. The land cover characteristics were divided into five categories: a built-up area, an agricultural area, a bare area, a forest, and water. The LST was calculated using the thermal bands of spatial images taken from 2005 to 2020. The increase in the built-up area was mainly caused by the agricultural area decreasing by 11.90%. The average land surface temperature of the study area increased from 23.50 to 36.51 °C, and the region moved to a high temperature that the built-up area's temperature increased by 1.5%. Still, the increase in vegetation cover was negative. From 2020 to 2050, the land surface temperature is expected to increase by 9.5 °C. The high-temperature areas moved into an aerial distribution, and the direction of urbanization determined their path. Urban heat island mitigation is best achieved through forests and water, and managers of urban areas should avoid developing bare land since they may suffer from degradation. The increase in the land surface temperature caused by the land cover change proves that the site is becoming more urbanized. The findings of this study provide valuable information on the various aspects of urbanization in Tianjin and other regions. In addition, future research should look into the public health issues associated with rapid urbanization.

Study of the urban heat island intensity using Landsat 8 in Da Nang in 2020

Monitoring spatiotemporal changes in land surface temperature in metropolitan areas is important to obtain the necessary information about environmental conditions and promote sustainable cities. Da Nang is a big city and is considered one of the tourist centers of Vietnam. Economic development and population growth lead to the expansion of urban land there. That affects the environment, especially resulting in the increase in surface temperature of the core city compared to the surrounding areas. The application of remote sensing data and techniques using thermal sensors for the estimation of land surface temperature and the formation of urban heat islands. This research aims to determine land surface temperature (LST) values and urban heat island (UHI) intensity distribution using Landsat 8 images. UHI is calculated in two steps: first, LST is calculated, and then the temperature threshold for UHI and none UHI is determined by the mean and standard deviation statistics of LST in the study area. To compute the LST, two levels of data must be processed: the NIR and RED bands from level 1 and the thermal band from level 2. The results showed the temperature in Da Nang varies from 15.7÷46.8 0C, with a significant regional temperature variance. The areas with high vegetation index had low temperatures while areas with low vegetation index had high temperatures. Non-UHI areas are present in areas with dense vegetation, dominated by Hoa Vang district and Son Tra peninsula. UHI is found in areas with temperatures more than or equal to 34.2 0C. The urban heat island has been taken play in the core of Da Nang, where the densely populated areas, industrial zones, airports, and landfill are located.

Impact of land use land cover on variation of urban heat island characteristics and surface energy fluxes using WRF and urban canopy model over metropolitan cities of India

The present study focuses on the assessment of urban heat island (UHI) and urban energy fluxes over Indian metropolitan cities. For this purpose, a high-resolution numerical Weather Research and Forecasting (WRF) model and a coupled single-layer urban canopy model (WRF-UCM) has been implemented over Delhi, Kolkata and Hyderabad to evaluate the performance of these models in capturing the impact of urban areas in simulating the UHI over different land use land cover (LULC) classes. The model initial conditions are obtained from NCEP-FNL reanalysis data. The model simulations reveal that the air temperature at 2 m height (T2) and UHI intensity are overestimated by WRF whereas the WRF-UCM simulations are matching well with ERA5-Land reanalysis data considered as observations. For the WRF-UCM simulation, the statistical errors in T2 and UHI intensity are within the desirable limits and the index of agreement (IoA) is more than 0.8 over the built-up areas (BAs). By comparing with the satellite observations, the relative surface UHI is noticed to be better captured over the BA by WRF-UCM simulation. The sensible heat flux simulated by WRF is highly overestimated whereas WRF-UCM is in good agreement with the satellite observation over the BA. Interestingly, the latent heat flux is reasonably well simulated over all the LULC classes. The results derived from the present study have shown the performance of WRF-UCM in simulating the spatial variation of UHI and fluxes of sensible and latent heat-related varied LULC classifications over metropolitan cities of India.

The urban climate of the largest cities of the European Arctic

Recent studies have found intense and persistent positive temperature anomalies associated with urban areas in high northern latitudes. However, understanding the intensity and variability of urban heat islands (UHI) in these regions remains limited. Here we study the urban climate of the seven largest cities in the European Arctic. These cities with populations ranging from 50,000 to nearly 300,000 span four countries and three bioclimatic zones in northern Fennoscandia. They include coastal and inland cities—and have complex local geography associated with topography and water bodies. We analyze land surface temperature (LST) satellite remote-sensing data with the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2020. The aim is to assess the intensity and temporal (seasonal and interannual) variability and trends of LST anomalies to learn about surface UHI development over different time frames in the urban Arctic. We observed persistent urban temperature anomalies in every season in the range of 1–5 °C, with the highest values for the largest city Murmansk (Russia). There is a strong inverse relationship between surface UHI intensity and its temporal variability: the more substantial the surface UHI, the more stable it is and the lower its temporal variability. Murmansk and Tromsø (Norway) have the highest thermal anomalies showing relatively low temporal variability, whereas the surface UHI in Bodø (Norway) is low and very volatile. We found no general direction of surface UHI change in the long term, as statistically significant changes were identified for only 10 of 56 cases. The study also suggests that in addition to the size (population) of the city, the presence of compact and dense urban infrastructure causes strong and stable urban temperature anomalies and has a more significant impact than the geographical setting of the city.

Investigating the Impact of Weather Conditions on Urban Heat Island Development in the Subtropical City of Hong Kong

Subtropical monsoon climates, high-density and heterogeneous urban built environments, as well as coastal–mountainous geographical environments influence the development of urban heat island (UHI) effects in Hong Kong. For better weather control of in situ observations and spatial analysis of UHI effects, it is necessary to quantitatively understand the influence of weather conditions on UHI development in Hong Kong and establish weather-based UHI estimation models. Meteorological records of four urban stations, one rural reference station, and one wind reference station at an hourly interval during the period of 2002–2012 were collected from Hong Kong observatory. A frequency analysis of the mean values of multiple meteorological elements and UHI parameters in urban stations was conducted to examine the prevailing and critical weather conditions, as well as the associated UHI conditions in Hong Kong. Multiple Linear Regression (MLR) was used to estimate the daily maximum UHI intensity (UHImax) based on a set of meteorological elements including cloud amount, wind speed, wind direction, relative humidity, and air temperature, as well as a UHI parameter of the daily maximum UHI intensity of the previous day (UHIpre-max). The results showed that MLR-based models can explain 33% and 56% variations of the UHImax in the summer and the whole year, respectively. The relative importance of each meteorological element on UHI development differed in the summer and annual periods, and the UHImax tended to be intensified under high temperature conditions in the summer.

Rural agriculture largely reduces the urban heating effects in China: A tale of the three most developed urban agglomerations

Agriculture, as a widespread high-intensity land use activity in urban surroundings, may dramatically alter urban climate through advection and atmospheric feedbacks. However, it remains unclear how and to what extent agriculture warms or cools the urban temperature. This study investigated the potential impacts of rural croplands on summer and winter urban heat island (UHI) effects in three most developed urban agglomerations (JJJ, Jing-Jin-Ji; YRD, Yangtze River Delta; PRD, Pearl River Delta) of China by the Weather Research and Forecast (WRF) model. Results show that urban lands warm 2-m air temperature substantially relative to natural forests, with a mean intensity of 1.33∼1.70 °C and the strongest in winter night of 2.99∼3.07 °C, but one to two thirds of the warming are canceled by rural croplands, especially in the semi-humid JJJ. The cropland impacts depend strongly on the concurrent UHI effects, with the coupled effects (added impacts due to the UHI effect) are 2.0∼8.7 times the independent effects (assuming no UHI effect), especially in the humid-hot PRD. Consequently, the rapid cropland loss for urbanization during 2000–2020 not only increases the UHI-affected area by 1.5∼4.2 times, but also elevates the UHI intensity of existing urban lands, for example, by 0.43∼0.65 °C in winter night. The cropland impacts on urban climate can be attributed to a range of factors like decreases in ground heat storage and net radiation, an increase in wind speed (turbulent heat mixing), and a change of planetary boundary layer height. Our results highlight the importance of rural agriculture in modulating urban climate and therefore in formulating the coordinated development plans of city clusters. However, the simulated cropland impacts differ greatly between near-surface air and land skin temperatures, and from the satellite-sensed radiant temperature, calling for field observations and more numeric experiments to elaborate the findings from this study.

Spatio-temporal analysis of urban heat island (UHI) and its effect on urban ecology: The case of Mekelle city, Northern Ethiopia

The bio-geophysical effects of land cover classes are considered to be an important factor in land surface temperature variations between urban and suburban areas. This means that major cities are significantly warmer than surrounding suburban or rural areas, which is known as the Urban Heat Island (UHI) effect. The aim of this study was to assess and analyze the spatiotemporal variation, correlation and impact of UHIs on Mekelle city (1990–2020) using remote sensing techniques. The study's primary objective was accomplished using the a number of techniques, including the extraction of LULC classes, estimation of the seasonal LSTs, assessment of UHI and UTFVI, and showing the relationship between LULC and LST as well as the interactions between UHI, UTFVI, and urban LULC classes. By analyzing TIRs/OLI thermal band data after calibrating uncertainty in the images and validating it using the concept of theoretical relationships and least squares fitting method, estimates of local LST, UHI (both in Mekelle and periphery rural areas), and UTFVI were obtained. The result of standard multiple regression models showed that impervious urban land surface, built-up areas, and dry bare soil highly contribute and influence variation at LST intensity caused for the formation of UHI in the study area. The result showed that the maximum UHI value in Mekelle city was 2.73 °C during the dry season in 1990. It decreased slightly to 2.53 °C in 2000 and then increased regularly to 2.83 °C and 2.98 °C in 2010 and 2020, respectively. To determine the city's UHI status in comparison to eight selected peripheral suburban areas, a trend analysis has been done. The UHI intensity of Mekelle city was higher relatively to that of most of the periphery suburban districts, particularly in 2020 (both dry and rainy seasons); this could be due to the city's explosive growth. It's worth noting that the research area affected by the urban heat island effect has grown over time, and as a result, the study area also has severe microclimate conditions that primarily damage the quality of urban life and create the worst conditions for thermal discomfort. The results of this study provide major conceptual understandings of how improper distribution and use of urban land affects the urban environment and fuels the creation of the UHI and thermal discomfort phenomena. Hence policy makers and urban planners should consider the effects of LST and UHI and integrate UHI comprehensive mitigation strategies with urban development patterns, and current and projected local climate changes in order to create sustainable urban environments, cities, and communities. In conclusion, compared to the conventional method, satellite remote sensing provides a faster and more efficient method for researching LST and UHI.

Assessing the intensity of land surface temperature in Thiruvarur district (India).

Nature gives way to the emergence of concrete jungles as cities grow around them. The majority of these concrete masses are highly reflective, changing the surrounding temperature. Hence, urbanized regions often have higher average temperatures than their surrounding rural areas. This phenomenon is termed Urban Heat Island (UHI). The intensity of UHI depends up on Land Surface Temperature (LST). This paper intends to study the intensity of LST in the Thiruvarur district and its correlation with Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) using Landsat 8 Imageries (OLI & TIRS) of January 2018. To calculate the LST, we used the mono-window algorithm. The result shows that LST intensity varies from 20.68°C to 32.3°C, with the maximum being in built-up areas and the minimum being in vegetation areas and water bodies. The Pearson regression shows that there is a negative correlation (r = -0.925, P < 0.5) between LST & NDVI and a positive correlation (r = 0.925, P < 0.5) between LST and NDBI. The strong positive correlation of NDBI confirms the influence of urbanization on Surface Urban Heat Island (SUHI). The negative correlation between LST and NDVI shows that green covers can mitigate it. Hence, this study conclusively demonstrates that urbanization can raise temperatures, showing that sustainable development in cities is essential for sustainable growth.

Assessing urban heat island intensity and emissions with compressed natural gas in non-commercial vehicles

The paradigm to shift toward cleaner fuel in vehicles and upgrade emission norms is a frequent discussion. The current study is a narrative of comparing fuels (gasoline, diesel, and compressed natural gas) in non-commercial four-wheel vehicles on the urban heat island (UHI) and their effects on emissions of greenhouse gases (GHG) and pollutants. We assume all such vehicles are single-fuel driven at a time in the densely populated urban city of Delhi, corresponding to the fiscal year 2017. We estimate that CNG can potentially raise the local temperature due to vehicular heat released and increased power plant load during summer by 1.09 °C and produces ∼1.6 times more heat than gasoline and diesel vehicles for the same distance traveled. CNG lowered the PM2.5 emissions by 81%, NOx by 45%, and VOC by 3%, while CO emissions increased by ∼14% and GHG emissions increased by 15%. For natural gas to become more effective, CNG vehicles' efficiency needs to improve, and the dependence on electricity should be more on cleaner resources. The analysis is based on estimates for Delhi, although the results would apply to other cities in India and globally.

Cause analysis of the extreme hourly precipitation and its relationship with the urban heat island intensity in Shenyang, China

Based on the hourly temperature and precipitation data from China national meteorological stations and regional automatic weather stations in Shenyang, the relationship between extreme hourly precipitation (ExHP) and urban heat island Intensity (UHII) is analyzed. Results show that the UHII is higher at night and in the early morning. The ExHP events mostly occur at night in summer when the UHII is relatively high. The spatial distribution of UHII in Shenyang is consistent with the economic development and the transportation density. Denser population and transportation, and high-rise buildings in the urban center contribute to higher UHII. There are three types of ExHP, namely the abrupt-type ExHP, the growing-type ExHP and the continuous-type ExHP. The overall variation characteristics of the three types of ExHP are relatively consistent. Their UHII values are positive and relatively stable in 6–12 h before the start of ExHP. The UHII begins to increase dramatically about 6 h before the ExHP, but decreases obviously and turn negative after the precipitation begins. Before the abrupt ExHP, the UHII is relatively high and can rapidly return to positive after the ending of ExHP. The UHII of the abrupt-type ExHP is remarkably larger than that of the growing-type and continuous-type ExHP. The UHII before and after the abrupt-type ExHP differs greatly. Before the abrupt ExHP, the UHII is high in the center and low at both ends, and the high-value areas of UHII are mainly located in the urban area. After the abrupt-type EXHP, the UHII drops and turn negative in the whole area. The UHII is obviously increasing with urbanization. The diurnal variation of UHII is enormous, which is higher at night than during the daytime. The increasing UHII can cause abnormal air pressure in cities and villages. The air in the lower atmospheric layer of the city can be heated and expanded, hence resulting in lower local air pressure. Then, the lower air pressure can promote the convergence and upward movement of air, hence facilitating the establishment of UHII circulation. This phenomenon is particularly distinct at night, which is conducive to the occurrence of ExHP events.

Urbanization-Induced Increases in Heavy Precipitation are Magnified by Moist Heatwaves in an Urban Agglomeration of East China

Abstract Heavy precipitation (HP) events can be preceded by moist heatwaves (HWs; i.e., hot and humid weather), and both can be intensified by urbanization. However, the effect of moist HWs on increasing urban HP remains unknown. Based on statistical analyses of daily weather observations and ERA5 reanalysis data, we herein investigate the effect of moist HWs on urban-intensified HP by dividing summer HP events into NoHW- and HW-preceded events in the Yangtze River delta (YRD) urban agglomeration of China. During the period 1961–2019, the YRD has experienced more frequent, longer-lasting, and stronger intense HP events in the summer season (i.e., June–August), and urbanization has contributed to these increases (by 22.66%–37.50%). In contrast, urban effects on HP are almost absent if we remove HW-preceded HP events from all HP events. Our results show that urbanization-induced increases in HP are associated with, and magnified by, moist HWs in urban areas of the YRD region. Moist HWs are conducive to an unstable atmosphere and stormy weather, and they also enhance urban heat island intensity, driving increases in HP over urban areas. Significance Statement The contribution of urbanization to increases in heavy precipitation has been widely reported in previous studies. HP events can be preceded by moist heatwaves (hot and humid extremes); however, it is unknown whether moist HWs enhance urban effects on HP. We choose the Yangtze River delta urban agglomeration to explore this question and find that urbanization contributes to the increasing frequency, duration, maximum intensity, and cumulative intensity of HP events in the summer season. However, this urban signal is not detectable if we remove HW-preceded events from all HP events. In other words, moist HWs play a key role in magnifying urbanization-induced increases in HP. Given that urban areas are projected to continue expanding and moist HWs are projected to occur with increasing frequency and intensity in the future, the role of HWs in the urban water cycle merits further investigation.

Analysis of urban form typology using urban heat island indicators: Case study of Ferdous neighborhood of Tabriz

Urbanization, with the acceleration of construction operations in cities, is the main reason for in-creasing the absorption of thermal energy in urban areas, which leads to climate change, especially urban form has responded differently depending on environmental dimension of urban context concerning the urban heat island intensity. In the last Studies, Researchers have not Codified the effect of urban form on heat islands in the form of a comprehensive model. It is necessary to examine each urban context according to its own conditions. Accordingly, this study aims to identify the effect of building form variability on reducing the intensity of heat islands in Ferdous context of Tabriz in the form of comprehensive modelling as a new task. The research gap is the effect of the form of buildings on the intensity of UHI, and the question will be asked whether it is possible to control the intensity of UHI by changing the form by influencing the climatic indicators. Our conceptual framework was based on urban form typologies in microscale affect the amount of energy intake and consumption, especially the intensity of heat islands, and whether the use of desirable types can be responsive to reducing the intensity of these islands? In this regard, using a quantitative analysis method in Rhinoceros software, especially using Grasshopper plugins, urban form is investigated. This analysis includes both the coldest and hottest days of the year. The results show that the optimal model is the cross typology.

Urban heat health risk assessment in Singapore to support resilient urban design — By integrating urban heat and the distribution of the elderly population

Elderly people are more vulnerable than other age groups to the increasing urban heat risk caused by both climate change and urbanization. This study developed a systematic method to assess the urban heat health risk to the aging population in high-density tropical cities. Based on the assessment, the study identifies high heat health risk districts, diagnoses specific reasons in individual districts, and suggests specific solutions. First, we applied an existing GIS model to quantitatively evaluate urban heat island (UHI) intensity, which is influenced by both longwave radiation and anthropogenic heat. Second, the urban heat health risk to the elderly in individual districts was weighted by UHI intensity, density and proportion of the elderly population in different districts. The integrated mapping results showed that the old HDB neighborhoods in the Central Region are at the highest risk, with a higher UHI intensity, density and proportion of the elderly population than other districts. Based on the analysis, we suggest both UHI mitigation strategies, social support, and facilities for the elderly population at Singapore HDB neighborhoods. Research outputs allow different stakeholders to understand various issues of individual neighborhoods regarding the urban heat health risk to the elderly and to develop corresponding solutions. • A new method is developed to assess heat health risks on aging population, by heat, exposure, and vulnerability. • GIS overlapping map is used to identify specific heat health risk reasons at districts. • Nighttime air temperature is used to assess urban heat health issue, rather than land surface temperature. • Older neighborhoods in the Central Region of Singapore are at the highest risk. • Both adaptation and mitigation recommendations are provided to develop systematic and specific strategies.

Временная изменчивость городского острова тепла Екатеринбурга

The article deals with the analysis of temporal variability of the urban heat island (UHI) in the field of surface air temperatures in Yekaterinburg using the data on meteorological observations on weather stations “Yekaterinburg” and “Verkhnee Dubrovo”. The UHI intensity variations have been analyzed for the periods from annual/interannual to diurnal. The sustainable effect of the urban heat island is manifested in all seasons. Annual cycles of monthly averaged UHI values demonstrates “W”-shaped form with maxima of about 1.0 ºС in February/March and in three summer months. Summer maximum is generally determined by maximal diurnal (night) UHI values. The maximum in February/March is related to the increased minimum daily values. From the 50s of the 20th century “W”-shaped annual curve of the UHI intensity remained unchanged under the increase in mean annual UHI values while growing at a rate of 1.31 ºС/100 years to the beginning of the 80s. At the same time, summer maximum increased at a faster rate in comparison with the winter one. Since the beginning of the 80s, the mean annual UHI intensity has stabilized at the level of 0.8 ºС. In a diurnal cycle, the maximal UHI intensity (to 2.4 ºС) is observed in May-July after the sunset. Maximal daily UHI intensity values in summer months are associated with a slower cooling of the city in high-rise building area. The local afternoon maximum (up to 0.8 ºС) caused by the insolation maximum under low albedo value of the urban coverage occurs also from May to July. In the autumn-winter period and at the beginning of spring, the daily amplitude of the UHI intensity decreases due to a decrease in the maximum of UHI and a slight increase in the minimum one. The increase in the minimum UHI values is facilitated by cloudiness, snow cover, calm wind conditions, an increase in the concentration of aerosol and water vapor near the surface and anthropogenic heat emissions. The study results can be used in fundamental and applied climatology, in the development of urban policy.

Examining Relationships between Spatial Pattern of Green Infrastructure and Urban Heat Island (Case Study: Tehran Metropolis)

Green infrastructure (GI) is one factor that reduces the intensity of Urban Heat Islands (UHI). The research results related to the relationship between the spatial pattern (composition/configuration) of urban GI and UHI show contradictory results. Some researchers emphasized the negative relationship between MPS and ED criteria, while other researchers found positive results in these criteria. Based on this, this study was conducted in the metropolis of Tehran, which is located in the center of Iran and has undergone many changes. The method is based on Local Climate Zone (LCZ) classification, measuring the landscape metrics (CA, ED, MPS, LSPI), and analyzing the relationships through Pearson correlation and partial Pearson correlation. These results showed that it is possible to influence the reduction of LST by planning suitable GI spatial patterns, So that urban planners and designers should focus on creating green infrastructure with dense trees in urban centers, and on the other hand, pay attention to air circulation flows in Tehran metropolis based on the height of buildings.

Urban heat islands: a review of contributing factors, effects and data

Urban Heat Island (UHI) is one of the most serious difficulties that humans have faced in the twenty-first century resulted due to urbanization and industrialization. The main causes of UHI are the vast amounts of heat produced by urban structures, which solar energy should be used and re-radiated as well as anthropogenic heat sources. The two heat sources cause an urban area’s temperature to rise in comparison to its surrounding areas, which refers to a phenomenon of the urban heat islands. Large cities and diverse economic activities face even more serious difficulties. This paper defined the concept and types of UHIs. This paper explained a comprehensive review of the phenomenon of UHI from its first appearance with regard to causing factors, its influences on people’s lives and the urban environments, and widely used data for measuring and evaluating the intensity of UHIs. The finding of most studies mentioned that UHI values are different from city to city based on land-use changes. It is revealed that an increasing trend occurred mainly because expand in built-up areas and a reduction in green cover. Also, a number of studies showed that the UHI intensity was low during summer afternoons and high during winter nights in many places around the world.

Time Series Analyses and Forecasting of Surface Urban Heat Island Intensity Using ARIMA Model in Punjab, Pakistan

In the context of rapid urbanization, Urban Heat Island (UHI) is considered as a major anthropogenic alteration in Earth environments, and its temporal trends and future forecasts for large areas did not receive much attention. Using land surface temperature (LST) data from MODIS (Moderate Resolution Imaging Spectro-radiometer) for years 2006 to 2020, we quantified the temporal trends of daytime and nighttime surface UHI intensity (SUHII, difference of urban temperature to rural temperature) using the Mann-Kendall (MK) trend test in six major cities of the Punjab province of Pakistan and estimated the future SUHII for the year 2030 using the ARIMA model. Results from the study revealed that the average mean SUHII for daytime was noted as 2.221 °C and the average mean nighttime SUHII was noted as 2.82 °C for the years 2006 to 2020. The average mean SUHII for daytime and nighttime exhibited increasing trends for all seasons and annually, and for the daytime spring season it showed a maximum upward trend of 0.486 °C/year (p < 0.05) and for the nighttime annual SUHII with an increasing rate of 0.485 °C/year (p < 0.05) which exhibited a maximum upward trend. The ARIMA model forecast suggested an increase of 0.04 °C in the average daytime SUHII and an increase of 0.1 °C in the average nighttime SUHII until 2030. The results from this study highlight the increasing trends of daytime and nighttime SUHII, ARIMA also forecasted an increase in daytime and nighttime SUHII, suggesting various strategies are needed for an effective mitigation of the UHI effect.

Optimization Methods of Urban Green Space Layout on Tropical Islands to Control Heat Island Effects

With the rapid increase in demand for the construction and development of island cities in the South China Sea, the urban heat island phenomenon in such cities should become a key factor to be considered in future urban planning. This paper took Sanya, China as a typical case, and long-term field experiments were conducted in the Mangrove Bay Area in summer and winter. An innovative urban green space cooling model was proposed, using the “green space cooling index” to quantitatively characterize the green space cooling effect, and aiming to minimize the intensity of urban heat islands. This paper studied the optimization method of green space planning and layout under the constraint of a centralized green space total area. Moreover, a genetic algorithm was adopted to optimize the calculation and the layout of the urban green space. The experimental results showed that the urban heat island intensity was more significant at night and was less effective in the daytime during summer. In winter, the urban heat island intensity had a greater effect in the daytime and was less influential at night. Finally, optimization results indicated that the average urban heat island intensity in summer was reduced by 8.8% under the optimal layout urban green space of 0.025 km2. The maximum reduction in heat island intensity occurred at 7:00 am (0.48 °C). When 0.0625 km2 urban green space was planned, the average urban heat island intensity index in summer was reduced to 0.27 °C, with a decrease of 20.5%.

Urban Heat Island Mapping Based on a Local Climate Zone Classification : a Case Study in Strasbourg City, France

The Urban Heat Island (UHI) effect is characterised by higher temperatures in cities than in rural surroundings. This phenomenon leads to increased health risks in urban dwellers, particularly in the context of global climate change. It is essential to consider its spatial variability to propose efficient UHI mitigation strategies. The Local Climate Zone (LCZ) scheme is a climate-based classification that can accurately capture UHI intensities according to the urban area characteristics. In this study, an LCZ classification has been established for the city of Strasbourg by using a vector-based method that relies on a large vector database composed of land cover and cadastral parcels data. LCZ polygons are digitized from cadastral maps, then the different LCZ parameters are calculated for each of them. Six of the ten LCZ parameters proposed in the literature have been obtained. New criteria have been added to improve the classification, i.e. a vegetation parameter (VgSF) and a compactness index (CI). A given LCZ class is then assigned to each polygon using a trapezoidal fuzzy logic model, which is completed by a decision tree. The acquired final LCZ map shows that the developed vector-based method permits obtaining relevant LCZ classification. The LCZ parameters values are subsequently used to determine a multiple linear regression (MLR) aiming to get a UHI intensity for each LCZ polygon. The resulting UHI map of the Eurométropole de Strasbourg (EMS) accurately illustrates the strong spatial heterogeneity of the phenomenon.