Formation Of Urban Heat Island Research Articles

Examining the relationship of major air pollutants with land surface parameters and its monthly variation in Indian cities using satellite data

The relationship of land surface parameters with the air pollutants is worth exploring. The present study investigates the relation of Land Surface Temperature (LST), Normalized Difference Built-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) with six air pollutants such as Aerosol Index (AI), Carbon monoxide (CO), formaldehyde (HCHO), Sulphur Dioxide (SO2), Nitrogen dioxide (NO2) and ozone (O3) from January to December month of year 2022 in four cities situated at varying climatic zones of India. Except for O3, which exhibits lower concentration in winter and greater in summer, the air pollutants concentration showed lower values during monsoon season and higher during summer and post-monsoon seasons. The relationship of LST, NDBI and NDVI with different air pollutants were found to vary throughout the year in the four cities. The magnitude of correlation coefficient (R) was found greater for AI and NO2 as compared to other pollutants depicting greater impact of land surface parameters on concentration of AI and NO2. The surface urban cool island effect in Bikaner showed strong negative relation of LST with NO2 with magnitude of R greater than 0.41. The surface urban heat island formation in Varanasi showed strong positive correlation with the air pollutants such as AI, CO, NO2 and O3 with magnitude of R value greater than 0.61, 0.31, 0.59 and 0.32 for AI, CO, NO2 and O3, respectively. Even though, the correlation of LST with air pollutants varied with seasons and cities, NDVI showed negative correlation with most of the air pollutants in the cities except in Bikaner where vegetation content is negligible. Thus, increasing the amount of vegetation in a city can improve the air quality by lowering the quantity of air pollutants there.

Disproportionate exposure to urban heat island intensity – The case study of Győr, Hungary

Extensive research has shown that urbanisation has a profound effect on the local climate system, leading to the formation of urban heat island. Exposure to urban heat islands poses a major health risk, and there is a growing body of literature recognising that urban population groups with particular demographic characteristics living in specific types of residential environments are disproportionately affected. By combining surface urban heat island data from the Global Surface Urban Heat Island Explorer with neighbourhood-level data on demographics and the type of housing, this study assesses disproportionate exposure to surface urban heat island intensity in the city of Győr, Hungary. Results of the study highlight the importance of targeted interventions for environmental justice, especially in areas characterised by housing estates, high population density and high ageing index.

Mapping impervious surface change from remote sensing and GIS data: A case study in Hochiminh city, Vietnam

Impervious surface is artificial surfaces that prevent water from entering the soil. The increase in impervious surface area has led to negative impacts on the urban environment, including an increase in the risk of flooding, a decrease in vegetation cover, and the formation of urban heat islands. This paper presents the results of building a predictive model of impervious surfaces in Hochiminh city from remote sensing and GIS data. Landsat and Sentinel 2 satellite images for the period 2002–2022 are used to classify impervious surfaces and extract input layers about vegetation cover, land surface temperature, combined with GIS data (elevation, slope, aspect, distance to road, distance to hydrology, population density) for modeling and predicting impervious surface changes in future. 03 machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), Classification and Regression Trees (CART) and maximum likelihood method are used to classify impervious surfaces from Landsat satellite images, then select the method with the highest accuracy. To predict the future distribution of impervious surface, this study uses Cellular Automata (CA) model and 02 artificial intelligence algorithms (Artificial Neural Network - ANN, Logistic Regression - LR). The results obtained in the study can be effectively used for urban planning, minimizing the impact of the process of increasing the impervious surface on the urban environment

Impacts of urbanization on land use, air quality, and temperature dynamics in Dehradun district of Uttarakhand, India: a comprehensive analysis

The present study investigates the impact of urbanization on land surface temperature and air quality in Dehradun district of the Uttarakhand state in India. We utilized data from LANDSAT, TROPOMI, OMI, MODIS, MOPITT, and CHIRPS, for spatio-temporal and trend analyses along with the assessment of correlation matrix. Our findings revealed a significant increase in the built-up area of Dehradun district in 2023 as compared to 2003. This expansion was particularly prominent in the southern and south-eastern regions of the district. The findings highlight the impact of rapid urban expansion on land use and land cover, leading to a rise in land surface temperature (LST) and the formation of surface urban heat islands (SUHI). Notably, the study reveals distinct spatial and temporal patterns, with lower regions of Dehradun district experiencing higher temperatures and pollutant concentrations due to intensified urbanization. Dehradun city also emerged as a hotspot for nitrogen dioxide within the district. Long-term trends indicate a rise in formaldehyde and nitrogen dioxide, attributed to both urbanization and increasing temperatures, while carbon monoxide levels decrease due to reduced biomass burning and the adoption of cleaner household fuels. Correlation matrix analysis underscores the complex relationships between land use, temperature, and pollutants, with built-up areas exhibiting strong positive correlations with all pollutants. This comprehensive study highlights the importance of sustainable urban planning and management to mitigate the adverse effects of rapid urbanization on air quality and overall environmental health in the Dehradun district.

Urban Heat Island and Its Relation to Green Spaces and Built-up Areas: A Study in Delhi, the Capital City of India

Urbanization has brought along with it changes in land use and land cover (LULC), which are not only causing changes in the spatial characteristics of the landscape but also in land surface temperatures, leading to the formation of surface urban heat islands (UHI). This study thus tries to understand the effect of LULC change on land surface temperature (LST) in Delhi between 2013 and 2020 and also tries to see if Delhi has a presence of surface UHI in the year 2020 by comparing the surface temperatures of built-up and green spaces. For collecting data, three geospatial tools were used, namely remote sensing, Google Earth Pro, and the QGIS application. For extracting LST, LULC, and the Normalised Difference Vegetation Index (NDVI), Landsat 8 satellite images were used. The results obtained revealed that change in LULC leads to a change in LST, as all locations which underwent LULC change from non-built-up to built-up and from vegetated to non-vegetated experienced an increase in surface temperatures. Secondly, the results confirmed the presence of a surface UHI in Delhi in the year 2020, as built-up areas recorded more LST than the green spaces. In addition, the low surface temperatures at green spaces highlight the importance of vegetation in mitigating the impact of the urban heat island and recommend city planning with more green spaces.

The analysis of the spatio-temporal changes and prediction of built-up lands and urban heat islands using multi-temporal satellite imagery

Irregular and rapid shifts in built-up lands are among the prime causes of increased Land Surface Temperature (LST) and the subsequent formation of Urban Heat Islands (UHIs). Timely and accurate delineation of built-up lands is fundamental to the understanding of LST variation and environmental changes; however, most of the built-up land maps have coarse resolutions. The present study attempts to develop a combinational index representing the biophysical characteristics of the land surface using exponential functions and Landsat time-series images for accurate built-up land maps on a fine scale. The developed index was used along with the Otsu threshold to categorize different built-up from 2001 to 2021 and then utilized as an input to the CA-Markov model to predict built-up lands in 2031. The corresponding relations between changes in built-up lands and its effects on LST and UHI were also analyzed via partial correlation analysis and bivariate LISA. The accuracy assessments of the proposed model for 2001–2021 revealed an accuracy value of 78 for the period (2001–2021) and a value of 77 when the CA-Markov model was utilized for 2021. The correlation values connecting the built-up land status and LST were also significantly strong and positive (0.86–0.89). The apparent similarities and patterns of clusters linking the built-up lands to UHI were also verified by global bivariate Moran's I index of greater than 0.328, showing how an increase in built-up lands leads to increasing the UHI. These findings are helpful for urban construction planning to minimize the negative environmental impacts of urbanization.

Quantifying the Impact of Urban Growth on Urban Surface Heat Islands in the Bangkok Metropolitan Region, Thailand

The urban built environment, comprising structures, roads, and various facilities, plays a key role in the formation of urban heat islands, which inflict considerable damage upon human society. This phenomenon is particularly pronounced in urban areas characterized by the rapid growth and concentration of populations, a global trend, notably exemplified in megacities such as Bangkok, Thailand. The global trend of urbanization has witnessed unprecedented growth in recent decades, with cities transforming into megametropolises that profoundly impact changes in urban temperature, specifically the urban heat island (UHI) phenomenon induced by the rapid growth of urban areas. Elevated urban concentrations lead to increased city density, contributing to higher temperatures within the urban environment compared to the surrounding areas. The evolving land-use surface has assumed heightened significance due to urban development, necessitating accelerated efforts to mitigate urban heat islands. This study aims to quantify the influence of urban growth on urban surface temperature in Bangkok and its surrounding areas. The inverse relationship between urban temperature and land surface temperature (LST), coupled with urban area density, was examined using Landsat 5 and 8 satellite imagery. The analysis revealed a positive correlation between higher temperatures and levels of urban growth. Areas characterized by high-rise structures and economic activities experienced the most pronounced impact of the heat island phenomenon. The city exhibited a notable correlation between high density and high temperatures (high–high), signifying that increased density contributes to elevated temperatures due to heat dissipation (significant correlation of R2 = 0.8582). Conversely, low-temperature, low-density cities (low–low) with a dispersed layout demonstrated effective cooling of the surrounding area, resulting in a significant correlation with lower local temperatures (R2 = 0.7404). These findings provide valuable insights to assist governments and related agencies in expediting planning and policy development aimed at reducing heat in urban areas and steering sustainable urban development.

The impacts of green spaces on mitigating the urban hot island effect in the city of Tashkent

This article explores the factors contributing to the formation of urban heat islands in Tashkent, their impacts, and the significance of urban green spaces in reducing the intensity of urban heat islands. The study identifies two types of urban heat islands in Tashkent: air and surface hot islands. The cooling effect of green spaces in Tashkent has been quantified using the Invest software, and a heat mitigation index map of Tashkent has been developed. The findings suggest that urban green spaces play a crucial role in mitigating the intensity of urban heat islands in Tashkent.

Spatial Characteristics and Temporal Trend of Urban Heat Island Effect over Major Cities in India Using Long-Term Space-Based MODIS Land Surface Temperature Observations (2000–2023)

The alteration of the Earth’s surface due to urbanization and the formation of urban heat islands is one of the most evident and widely discussed anthropogenic impacts on Earth’s microclimate. The elevated land surface temperature in the urban perimeter compared with the surrounding non-urban area is known as the surface urban heat island (SUHI) effect. India has experienced swift urban growth over the past few decades, and this trend is expected to persist in years to come. The literature published on SUHI in India focuses only on a few specific cities, and there is limited understanding of its geospatial variation across a broader region and its long-term trend. Here, we present one of the first studies exploring the long-term diurnal (daytime, and nighttime), seasonal, and annual characteristics of SUHI in the 20 largest urban centers of India and its neighboring countries. The study highlights a statistically significant (95% confidence interval) rise in nighttime surface temperatures across major cities based on a linear fit over 23 years (2000–2023) of MODIS land surface temperature satellite observations. The nighttime SUHI was found to be more conspicuous, positive, and consistent when compared with daytime satellite observations. The nighttime SUHI for April–May–June representing the pre-monsoon and onset of monsoon months for the top 10 cities, ranged from 0.92 to 2.33 °C; for December–January–February, representing the winter season, it ranged from 1.38 to 2.63 °C. In general, the total change in the nighttime SUHI based on linear fit (2000–2023) for the top ten cities showed warming over the urban region ranging from 2.04 to 3.7 °C. The highest warming trend was observed during the months of May–June–July (3.7 and 3.01 °C) in Ahmedabad and Delhi, cities that have undergone rapid urbanization in the last two to three decades. The study identified strongly positive annual SUHI intensity during nighttime, and weakly negative to moderately positive annual SUHI intensity during daytime, for major cities. Jaipur (India), Lahore (Pakistan), Dhaka (Bangladesh), and Colombo (Sri Lanka) showed a nighttime SUHI intensity of 2.17, 2.33, 0.32, and 0.21 °C, respectively, during the months of April–May–June, and a nighttime SUHI intensity of 2.63, 1.68, 0.94, 0.33 °C, respectively, for the months of December–January–February (2000–2023). It is apparent that the geographical location (inland/coastal) of the city has a high influence on the daytime and nighttime SUHI patterns. The current research is intended to help city planners and policymakers better understand SUHI intensity (day and night/seasonal basis) for developing strategies to mitigate urban heat island effects.

A CORRELATION ANALYSIS OF LAND SURFACE TEMPERATURE AND EVAPOTRANSPIRATION IN AN URBAN SETTING

Abstract. Urbanisation is found to increase the Land Surface Temperature (LST), which results in the formation of Urban Heat Islands (UHI). This effect is a result of the natural land cover being replaced with impermeable surfaces like buildings, roads, and pavements, which absorb and hold onto heat more. As a result, metropolitan regions frequently experience substantially hotter temperatures than their nearby rural counterparts, especially during heat waves. This arises partly due to reduction in Actual Evapotranspiration (AET). AET and LST have a close relationship. AET rates are greatly influenced by the amount of vegetation and their transpiration capacity, which in turn can have an influence on LST in urban regions. The type of Land Use and Land Cover (LULC) has a significant impact on how LST affects the interchange of energy between the earth's surface and the atmosphere. Vegetation AET has a huge potential to reduce both temperatures. The temperature of a water body is lower than that of the nearby urban. The objective of this research is to determine the variation in AET and LST with regards to varying types of land cover by finding correlation between them. The spatio-temporal analysis is done for the summer and winter season of 2020. The correlation is studied between LST and AET for each land cover class and for both seasons for 2020 and results are plotted. The green areas and lakes of the city showed a higher AET and lower LST, whereas the built environment behaved in just the opposite manner. It can be inferred that it is essential to comprehend the local context to effectively determine the relationship between LST and AET in a particular scenario.

Effect of a geothermal heat pump system on cooling residential buildings in a hot, dry climate

ABSTRACT In the last century, electricity demand has doubled due to urban expansion, which has contributed to the formation of more urban heat islands (UHI) and the appearance of environmental hazards such as the global climate change phenomenon. Since residential buildings are considered the main electricity consumer sector in Egypt, they consume up to 42% of total energy consumption, which contributes to increasing temperatures and constitutes UHI in cities. In this context, the research aims to examine the effectiveness of using the closed vertical loop geothermal system (GSHPCV) for cooling residential buildings in a hot, dry climate, such as Cairo, Egypt. In addition to determining its effect on carbon emissions and the amount of energy consumed for cooling, this was done using TRNSYS-17 software as a simulation tool to compare the traditional building in a hot, dry climate before and after adding GSHPCV in Cairo, Egypt. The simulation revealed that using GSHPCV in hot, dry climate zones has a significant impact on residential buildings. It reduced the electricity consumption up to 19.7% of the electricity consumed for cooling, and it reduced temperatures indoors for buildings up to 15.8% on the ground floor, up to 11.3% on the first floor, and up to 3.5% on the roof floor. In addition, it reduced up to 19.7% of the carbon emissions and reached human thermal comfort on the ground floor for the study case at peak times during the summer period. Which provide a solution to reduce UHI and environmental hazards such as climate change.

Effect of Urban Heat Island on Growth Rate of the Convective Boundary Layer Over Baghdad City

Due to human activities and economic growth, in the last decades, urban expansion has increased, and it has a large role in the formation of urban heat island. Urban heat island effects natural physical properties of the air. In this study, data from satellite images included Landsat5 Landsat 9 and reanalysis data from European Centre for Medium-Range Weather Forecasts (ECMWF) by ERA5 model are implemented. ERA5 archives NetCDF file data for many hourly atmospheric elements such as temperature, wind components, sensible heat flux, boundary layer height …etc. All the files were processed by MATLAB, while satellite images processed by ArcGIS to calculate the spectral index such as Normalized difference built up index (NDBI) and supervised classification. Results of composited images and supervised classification show that there is an increase in built up area of about 23% for the periods from July-1994 to July-2022. This change in LULC will create urban heat island for Baghdad and affect heat budget near the surface that will change structure of urban boundary layer, and convective boundary layer (CBL). Near the surface there is an increase in growth rate of convective boundary layer about 0.25m/s at 7AM for July-2022, relative to 0.136 m/s for July-1994. This difference in growth rate is due to urban heat island creation and will increase CBL to about 620m in 2022 relative to 1994 at 10AM.

METHODOLOGICAL PROPOSAL FOR EVALUATING THE TRANSFORMATION OF URBAN MICROCLIMATE IN MEDIUM-SIZED CITIES: A CASE STUDY IN THE URBAN MESH OF THE MUNICIPALITY OF PARACATU, MINAS GERAIS – BR

This work aims to propose a methodological proposal for areas evaluated with potential for the formation of Urban Heat Islands (UHI). Satellite images were used to control surface temperature (Land Surface Temperature - LST) and the Normalized Difference Vegetation Index (NDVI) of the study area. They were also employed in the Annual Mapping of Land Cover and Land Use in Brazil. The city of Paracatu, Minas Gerais (MG) was chosen for application and validation of the proposed method. Images from LANDSAT-5 and 8 satellites were used, which initially underwent resampling and pixel standardization. Subsequently, LST and NDVI calculations were applied, and these data were compared with use and occupation. In general, it was possible to notice that, in the urban area of Paracatu, there was an increase in the average, minimum and maximum LST. The same space-spectral behavior occurred for the NDVI index, which are related to Land Use and Occupancy Changes (LULC). In relation to areas with potential formation of UHI, it was noted that, in the interval of 14 years, they tripled in the city, making it possible to relate the situation with urban expansion and the presence of new subdivisions in peripheral areas. It was also noted that areas with mitigation potential for UHIs were not planned, especially in the most populous neighborhood of the municipality. The results obtained were satisfactory and the proposed methodology can serve as a basis for municipal decision makers in relation to measures to mitigate urban microclimate.

Editorial: Special Issue on Geographical Analysis and Modeling of Urban Heat Island Formation

This Special Issue focuses on the data, methods, techniques, and empirical outcomes of urban heat island studies from a time and space perspective. We showcase research papers, empirical studies, conceptual or analytic reviews, and policy-related tasks to help achieve urban sustainability. We are interested in target methodologies and datasets capturing urban heat island phenomena, including novel techniques for urban heat island monitoring and forecasting with the integration of remote sensing and GIS, the spatial relationship between urban heat island intensity and land use/cover distribution in metropolitan areas, the geographical patterns and processes of urban heat island phenomena in large cities, spatial differences in urban heat island intensity between developing and developed countries, urban heat island disaster mitigation and adaptation for future urban sustainability, and prediction and scenario analysis of urban heat island formation for policy and planning purposes.

Thermal characterization of Ajmer City: Insights into urban heat dynamics

Human development, urbanization, and ongoing environmental issues have led to environmental disturbances and climate changes in Ajmer, a crucial rest station for migrating birds. Congested and poorly planned urban areas, reduced vegetation cover, and increasing emissions from industries and automobiles all contribute to climate challenges. The rise in land surface temperature (LST) has led to the formation of urban heat islands (UHI). The goal of this research is to investigate UHI in Ajmer City, India. Using remotely sensed LANDSAT data and Geographic Information System (GIS), we analyzed LST and Normalized Difference Vegetation Index (NDVI) for the summer months (March to June) in Ajmer from 2015 to 2022, including the period when nationwide curfews were implemented due to Covid-19. The extraordinary measures taken to restrict human activities during the pandemic resulted in remarkable temporary declines in aerosols and atmospheric pollutants (NO2, CO, SO2, and PM) mainly due to restrictions on fossil fuel burning and transportation emissions. The analysis reveals that Urban LST was 312.07 K in 2019 and decreased to 308.228 K in 2020 due to the strict Covid-19 lockdowns. With the gradual easing of restrictions and resumption of human activities, LST slightly increased to 308.27 K in 2021 and further to 311.71 K in 2022. Researchers can now explore the effects of reduced surface vehicle heat and air pollution on LST and UHI intensity in Western Indian cities, providing valuable insights for urban planning and climate mitigation strategies.

Estimation of Turbulent Heat Transfer Rates for Flow Over Buildings Using Openfoam

Formation of Urban Heat Islands is one of the serious issues faced by the cities in India. Due to anthropogenic activities there are abnormal variations in temperature both in day and night in cities as compared to rural areas. When we consider the governing equations the heating coefficients present, which depend on the buildings and local flow, can accelerate or decelerate the effect of temperature in the urban areas. In this paper the coefficient called eddy diffusivity of heat and its influence around high-rise buildings is analyzed using Computational Fluid Dynamics simulations with the OpenFOAM software package.

Correlation Analysis Between Urban Heat Island Intensity and Temperature Criticality Value in Denpasar City

The compactness of buildings in Denpasar resulted in the formation of urban heat islands (UHI), which can be evaluated through the Urban Thermal Field Variance Index (UTFVI) and Environment Criticality Index (ECI). ECI is the ratio of land surface temperature to the Normalized Difference Vegetation Index (NDVI). It can be transformed into Temperature Criticality Value (TCV) using air temperature and Index-based Built-up Index (IBI). This study aims to identify the UHI intensity, the impact of land cover changes, and its association with the TCV. The study employs Landsat 8 imagery and field measurements data, and the findings demonstrate that the study area was mainly composed of built-up areas that had grown from 2015 to 2021. TFVI indicates the most intense UHI (>0.02) in the built-up areas, whereas the mean value of NDVI suggested a reduction in vegetation density. The density of built-up areas (IBI) had increased, while vegetation had decreased. TCV in 2015 ranged from -11.15°C.IBI to 6.42°C.IBI; 2018 between -9.96°C.IBI to 6.79°C.IBI; and 2021 between -10.84°C.IBI to 6.87°C.IBI showed that the environment had become increasingly critical from 2015 to 2021. A transect analysis revealed that more vigorous UHI intensity, denser buildings, and a more critical environment were present in urban centers compared to the suburbs. The correlation coefficient (r) between TCV and UTFVI was relatively robust (0.75–0.82), indicating that the growth of UHI intensity was associated with a more critical environment. TCV has the strongest (r=0.99) and strong correlation (r>0,80) with Built-up Index but inverse correlation with NDVI. Therefore, limiting the expansion of built-up areas and increasing vegetation could help to control the environment's criticality.

Investigating surface UHI using local climate zones (LCZs), the case study of Cairo’s River Islands

The spatial configuration of the built environment influences the thermal behaviour at the local level and may generate the urban heat island (UHI) phenomenon. This impact has been investigated through several physical and climatological approaches. In this respect, the local climate zones (LCZs) scheme is recently adopted to facilitate the spatial study and understanding of UHIs. This research investigates the formation of surface UHIs in the case of the Nile River Islands, Cairo. It adopts the classification scheme of LCZs for selecting and comparing samples and conducting analyses of the distribution of land surface temperature (LST) for the area of interest. The adopted workflow aims at defining the homogenous zones of LCZs by three main steps: (i) the classification of LCZs based on supervised pixel-based classification of geospatial data, using the web-based tool of LCZ Generator, (ii) the detection of UHIs through the estimation of LST, and (iii) spatial statistical tests of Global Moran’s Index and Hotspot analysis for studying the significance of LST distribution within the study area. The adopted workflow successfully assists in estimating the LST and mapping UHI, and it contributes to the understanding of the physical and thermal characteristics of the selected urban areas. The analyses of outputs show reliable results with the recent studies of spatial relations between LCZs and LST.

Potential Effect of the Changing Urban Climate on Non-Communicable Diseases: A Case Study on Barasat City, India

Rapid land use change in urban areas creates a unique climate, which risks the health of its inhabitants. The unique urban climate is attributable to a phenomenon recognized as the Urban Heat Island (UHI). Under such circumstances, the urban regions become hotter than their rural surroundings, creating an island of higher temperatures. Human exposure to excessively warm heat islands, particularly in humid climates like India, is becoming an increasingly serious public health issue. This paper briefly analyses the formation of surface urban heat islands (SUHI), identified by estimating the Land Surface Temperature (LST) and also its potential impacts on the occurrence of heat-related Non-Communicable Diseases (NCD) within a city. Barasat city of India has been chosen to demonstrate this work. LST has been estimated from the Landsat data using a remote sensing platform. It has been observed that the high LST in Barasat city perfectly followed an emitting shape in descending order from the city center to the suburban areas. A primary household survey was conducted in 2018 in the month of March-April, where 200 samples were collected. The information has been collected from the samples regarding their occupation, average hours of exposure to high heat zones, and the NCDs they have suffered from. It has been found that heat cramps, heat stress, heat strokes, and respiratory diseases are common for people exposed to the high heat zone. Although NCDs increase the socioeconomic burden in developing cities, NCD surveillance is limited in India. This study will assist in formulating a better urban neighborhood considering the city’s population exposed to UHI.

Radiation and Temperature of a Tropical Grassland in Summer Times: Experimental Observations

The surface texture of urbanized regions is altered by the replacement of natural vegetated surfaces with hardened pavement surfaces, which have been described as a heat source for the formation of urban heat islands. Grasslands may store rainfall in their roots and leaves for later cooling, but this has received little attention. This study investigated the radiant flux and temperature of a tropical grassland throughout the summer in order to understand the albedo, long-wave radiation, short-wave radiation, and surface temperature of the grassland over 10 days. The grassland had an albedo of 0.13, which did not fluctuate during the day compared to the albedo of other surfaces in metropolitan areas. Even if the local weather changes considerably, this albedo does not alter significantly. The surface temperature and the air temperature above the grassland increase linearly with the upwelling reflectance, incident solar radiation, and upwelling long-wave radiation. These two temperatures do not correspond with downwelling long-wave radiation, which is influenced by cloud cover in the sky. However, the peaks of these temperatures lag behind the incident shortwave radiation and net radiation that reaches the grassland surface. The finding that the thermal properties of grasslands could be harnessed to reduce the heat absorbed by urban surfaces provides valuable insights into the grasslands’ potential to mitigate the impacts of urbanization on temperature.