An Analysis of the Spatial and Temporal Evolution of the Urban Heat Island in the City of Zhengzhou Using MODIS Data

Abstract

A rapid increase in urbanization has caused severe urban heat island (UHI) effects in China over the past few years. Zhengzhou is one of the emerging cities of China where residents are facing strong impact of UHI. By utilizing MODIS data on land surface temperature (LST) and employing 3S technology, this study investigates the UHI phenomenon in Zhengzhou over a 10-year period (2012–2021), aiming to analyze the spatio-temporal evolution characteristics of the UHI effect and the associated land cover changes. To the best of our knowledge, this study represents the first attempt to investigate annual and seasonal changes in different areas of Zhengzhou. It is noted that in the night-time, the intensity of the heat island is stronger than in daytime, which has moderate and weak heat island areas. Seasonal variation showed that in autumn, Zhengzhou has the strong heat island intensity, followed by summer, and the lowest is in winter and spring. The analysis reveals that built-up (construction) areas exhibit the highest LST, whereas forested land and water bodies have the lowest temperature levels. The findings of this study can serve as reference for reducing UHI and increasing thermal comfort in cities.

1. Introduction

The percentage of people living in urban areas has increased from 2.5% to 40% and the world has experienced rapid urbanization in the past century. In the 21st century, urbanization is a significant socioeconomic trend in human society [1]. The most recent statistics show that more than 54% of the population currently resides in urban areas, and this number will increase to 66% by 2050 [2]. Urbanization has severely affected urban climate change more than global climate change [3,4]. Urban heat island (UHI), a phenomenon in which urban areas experience a temperature higher than the nearby suburbs and rural areas, is one of the most significant effects of urbanization [5,6]. It has a significant effect on environmental conditions as well as an impact on human lives and health [7]. Studying the heat island effect in fast-growing cities is meaningful in the development and planning of urbanization. Therefore, it is essential to understand the UHI effects, and urban strategies should be considered for UHI effect mitigation.

The intensity of UHI is directly impacted by the rate of urbanization, land use patterns, and building density [8,9]. The characteristics of UHI have been the subject of extensive research in recent years, and measurements and reports on its impact and causes have been made for the majority of the world’s largest geographical regions [10,11,12,13]. In early studies of UHI, in situ data were used. Although analysis of UHI in situ data shows that they have a long data record and high temporal resolution, they lack spatial resolution [14]. Using satellite remote sensing data in the infrared spectrum, the disadvantage of using in situ data with spatial discontinuity can be overcome with the advancement of thermal remote sensing (RS) technology. Using thermal infrared (TIR) remote sensing pictures, the land surface temperature (LST) can be calculated to represent the surface urban heat island (SUHI). Recently, to study the UHI effect on various spatial and temporal scales, a variety of remotely sensed data have been used for LST retrieval, including Landsat TM/ETM+, MODIS (Moderate Resolution Imaging Spectroradiometer), AVHRR, and ASTER (Advanced Spaceborne Thermal Emission, Reflection Radiometer) [15,16,17,18]. These studies examined the spatiotemporal variations in UHIs and the relationship between the UHI effect and urban parameters such as surface cover characteristics and population.

Large and coastal cities, where UHI impacts are considerable, have been the main focus of previous UHI investigations. Urban heat island intensity (UHII), defined as the difference in air temperatures between urban and nearby rural areas by Oke (1987), is a concept that has since been widely adopted [19]. With data gathered by the National Weather Service Forecast Office in Phoenix Sky Harbor Airport, Balling et al. [20] studied and analyzed day maximum, minimum, and mean temperature data from 1920–1984 from 961 stations in Phoenix, Arizona (located in the southwestern part of the USA). The study indicated that the average yearly increase in summertime temperatures in Phoenix was found to be 0.072 °C, with mean minimum temperatures increasing at a pace of 0.10 °C and mean maximum temperatures rising at a rate of 0.04 °C. After adjusting for ecological conditions, Imhoff et al. [18] discovered that the amplitude of UHI is seasonally asymmetric throughout the 38 most populated urban locations in the contiguous United States, with more significant temperature differences in summer than in winter. Kim and Baik [21] examined the UHII in Seoul, Korea, by collecting data from 31 automatic weather stations (2001–2002). Their study showed that the UHI was more intense at night than during the day and decreased with increasing wind and cloud cover. A maximum UHII of 2.2 °C was the average. Giridharan et al. [22] investigated how design-related factors affected the heat island effect in Hong Kong’s residential developments. The UHII was found to be 1.5 °C, at its highest during summer days, and 1 °C between estates. According to Sharifi and Lehmann [23], Sydney faced severe UHI effects due to its numerous urban development initiatives and climatic changes. The intensity of UHI at night-time was high, and the temperature in urban areas increased from 1.1 °C to 3.7 °C, while in rural areas, it increased from 0.8 °C to 2.6 °C.

Hung et al. [14] collected satellite data from 2001 to 2003, and their study concluded that the UHII in Bangkok was equal to 8 °C during the dry season (November to April), 7 °C in Shanghai, 7 °C in Manila, and 12 °C in Tokyo. Jiahua and Fengmei [21] used MODIS data to investigate the UHI in Beijing, China. They found that in the summer, there is an LST differential of around 4–6 °C between the city and the suburbs and 8–10 °C between the city center and the outer suburbs. Using a combination of Advanced Spaceborne Thermal Emission, Reflection Radiometer (ASTER) and Thematic Mapper (TM) data, Cai et al. [24] also discovered the UHII in Beijing from 2002 to 2006. Their findings demonstrated that urban Beijing has a high UHI effect in the summer, spring, and autumn. Sharma and Joshi [25] examined the seasonal variation in the UHII in the Delhi territory using Landsat TM data (India). They discovered that the highest UHII occurred in the summer at 16.7 °C when most agricultural fields were fallow and solar radiation was high. In winter, a 7.4 °C UHII was recorded, which was when there was low solar radiation and the farmland was covered in crops and had a lot of moisture. The second-highest UHII was observed during the monsoon season (13.8 °C).

Zhou et al. [26] used MODIS data for 2003–2011 in 32 major cities in China to analyze the SUHI. They found higher SUHIIs for the day and night in the southeastern and northern regions. They noted how SUHII varied significantly depending on the season, with a higher daily intensity in the summer than in the winter and the opposite during the night for most places. Lin Zhongli and Xu Hanqiu [3] proposed a classification schema LCZ (local climate zone) study of UHII in Fuzhou, China, using remote sensing technology, and the authors found that Fuzhou City’s UHII LCZ on 27 September 2015, was 6.73 °C, indicating a worsening of the UHI in the city. The UHI in Cairo (Egypt) from 1995 to 2000 at three stations equipped with mercury thermometers was examined by Robaa [27]. He discovered that the urban environment was consistently drier than the suburban environment in the morning and was more humid in the afternoon. Except for November, when a chilly island developed, the urban environment was consistently warmer than its surroundings. From February to September (excluding May), the urban region was drier than the rural area, and the monthly mean UHI ranged from 1.0 °C to 2.2 °C. During the winter season, from October to January, the UHII was equivalent to approximately 1 °C.

The urbanization process has increased rapidly in China due to a significant increase in economic growth. According to a report from the National Bureau of Statistics of China from 2011, urbanization increased by 13.5% in China between 2000 and the end of 2010, increasing the UHI effects [9,28,29,30]. A study conducted by Yang et al. examined the evolution of urban heat islands and vegetation coverage in Zhengzhou City [31]. The findings show that during the past 15 years (2006–2020), a high-temperature zone in the urban area has gradually spread to the nearby districts, worsening the urban heat island as a whole. The heat island area initially increased by 138.72 km² between 2006 and 2014. In order to examine the intensity of the UHI in Zhengzhou, China, over a 39-year period (1981–2019), H Li et al. conducted a study that used long-term observation and statistical data on annual, seasonal, daytime, and nighttime bases [32]. The associations between UHI and signs of rapid urbanization, as well as the temporal variations in the UHI effect, were also examined in this study. According to the findings, Zhengzhou is warming at a rate that is 2.2 times faster than the approximate +0.9 °C average for land warming between 1981 and 2019. Consequently, it is crucial to enhance our understanding of the dynamics and influencing factors of the UHI effect, especially in the context of carbon neutrality and global warming. It is imperative to conduct comprehensive studies and investigations in this field to facilitate timely measures for UHI mitigation with all possible techniques. The existing literature on the urban heat island (UHI) effect in Zhengzhou is based on information up until 2019. In order to provide more up-to-date insights, this study extends the available information by including data from two additional years (2012–2021).

The primary goal of this study is to use remote sensing data to analyze the spatiotemporal variations in the thermal environment and investigate the distribution properties and evolution law of the UHI effect in Zhengzhou City (China). The focus was not only to measure the UHII in the selected regions but also the land types (forest, shrub, grassland, cropland, built-up area, bare soil, wetland, and water body). The inter-annual and seasonal distribution of LST of different land use types in Zhengzhou during the period 2012–2021 was analyzed. This research uses two products of MODIS (MYD11A2 and MCD12Q1) LST data and land use data, using 3S technology (remote sensing (RS), geographic information system (GIS), satellite positioning system (SPS)) and Zhengzhou LST and UHI to study the land cover (LC)and the distribution characteristics and evolution law of the UHI effect in Zhengzhou City and to provide a reference for the next step of urban planning and design. This research focuses on three heat island indicators: (1) ground surface temperature, (2) heat island intensity, and (3) local heat island intensity through four aspects: (i) status, (ii) day and night change, (iii) seasonal change, and (iv) annual change. The goal of this study was to offer a thorough and comparative understanding of the spatiotemporal patterns of UHI intensity by using MODIS.

Study Area

Zhengzhou is the capital and largest city of the central Henan Province of China, located between the longitudes of 112°42′ and 114°14′ east and the latitudes of 34°16′ and 34°58′ north, with a total area of 7446 km² and a population of approximately 12,742,000, meaning it has the second highest population density among Chinese cities (according to the 2020 Chinese census). It is divided into six municipalities (Figure 1). It is bounded to the north by the Yellow River, to the west by the Song Mountains, and to the southeast by the Yellow Huai Plain. With railroads linking it to Europe and an international airport, Zhengzhou is a central hub of China’s national transportation system. According to the Nature Index, Zhengzhou is one of the top 100 cities in the world for scientific research [33]. Zhengzhou City is located in the central plain area, has a temperate monsoon climate, and has four distinct seasons, including a dry spring (March–May) and a hot and rainy summer (June–September). Its topography is southwest and northeast. The type of land use classification technique employed is not specified. The land use data are from the MODIS Land Cover (MCD12Q1) product, with a spatial resolution of 500 m and a coverage range of the entire world. The data are processed based on observations obtained each year to extract the type of land cover for that year. The product data contain 13 sets of classification standards, among which the IGBP classification is widely used and has high classification accuracy, with a global classification accuracy of 73.6%. This article chooses the LC_Type1 (Annual IGBP classification) classification standard.

The rapid increase in the population and unreasonable urban constructions has led to many environmental issues, due to which Zhengzhou City has seen rapid urbanization over the past few decades. Zhengzhou’s rapid urbanization has resulted in significant surface cover changes, particularly regarding issues with the heat island effect. Currently, Zhengzhou City is concentrating on creating a national central city. The urban space layout structure is “once weekly, two-axis multi-centered”, mainly developing Zhengzhou’s capital city district and Zhengzhou Aviation Town. The core regions are relatively dispersed. Research on the UHI effect can provide a theoretical basis for future city planning in Zhengzhou.

2. Materials and Methods

2.1. Datasets

Two products of MODIS (MYD11A2 and MCD12Q1) LST time series data obtained from the National Aeronautics and Space Administration (NASA) from the years 2012–2021 were analyzed to determine the spatiotemporal dynamics of UHI intensity, and the data source is in Hierarchical Data Format (HDF) file format.

2.1.1. MYD11A2

MYD11A2 is an 8-day surface temperature synthesis product produced by NASA, currently the most-used surface temperature product. It synthesizes the MODIS surface temperature product and improves the hiding power in space. The time series of LST was derived using the MYD11A2 data. Both the daytime (local time: 1:30 pm) and nighttime (local time: 1:30 am) temperature data were included in this dataset [34]. To study day and night surface temperatures, the MODIS Reprojection Tool (MRT) was used for preprocessing operations such as data splicing and reprojection; as a result, the extracted bands are LST day 1 km (daytime surface temperature) and LST night 1 km (nighttime surface temperature), and the image processed using MRT is truncated to the area of the Zhengzhou administrative region.

2.1.2. MCD12Q1

MCD12Q1 is a global land use data product produced by NASA with a temporal resolution of 1a and a spatial resolution of 500 m. The MCD12Q1 dataset’s feature of global coverage makes it possible to provide data on land cover worldwide. Secondly, the dataset’s high spatial resolution enables it to deliver information on land cover and coverage that is more precise. Additionally, the MCD12Q1 dataset features yearly updates that give researchers access to the most recent land cover and coverage data. The dataset is free and publicly accessible.

MODIS land use data include a variety of classification systems [28,34]. This study adopts the International Geosphere–Biosphere Programme (IGBP) global vegetation classification scheme for land cover types, which divides the Earth’s surface into 17 land use types. Further processing of these data was conducted in MATLAB to merge these land use types into eight categories: forest, shrub, grassland, cropland, built-up area, bare soil, wetland, and water body. This study analyzed the seasonality and annual variation characteristics of the UHI in Zhengzhou.

To obtain the surface temperature image of Zhengzhou City, the quantitative relationship between the brightness value of the pixels of the image and the surface temperature was used, and conversion of the pixel brightness value B_LST into the surface temperature (°C) value was obtained using the Equation (1):

$$T_{LST}=0.02B_{LST}-273.15$$

(1)

This study used three heat island indicators—ground surface temperature, heat island intensity, and local heat island intensity—to examine the heat island of a populated metropolis in four different ways: current status, day and night change, seasonal change, and year change. According to meteorology, there are four distinct seasons: spring (March–May), summer (June–August), autumn (September–November), and winter (December–February).

2.2. Ground Surface Temperature

The value of ground surface temperature can be obtained using Equation (1). Administrative divisions separate the urban regions into districts, including Zhongyuan District, Erqi District, Guancheng District, Jinshui District, and Huiji District. The suburban areas include Zhongmu County, Xinzheng City, Xinmi City, Dengfeng City, Gongyi City, Xingyang City, and Shangjie District. The locations of administrative centers in the suburbs are indicated on the map by the black dots (see Figure 1).

2.3. Urban Heat Island Intensity

To obtain the value of the UHI intensity $\left(UHII\right),$ the average surface temperature in urban areas ($T_{urban}$) is subtracted from the average surface temperature in suburban areas ($T_{rural}$), as shown in the following equation [32,35]:

$$UHII=T_{urban}-T_{rural}$$

(2)

UHII is, however, only a numerical description of the UHI and cannot reflect the spatial distribution characteristics of the UHI. Therefore, it is necessary to calculate the local UHII to reveal the spatial distribution characteristics of the UHI.

2.4. Local Heat Island Intensity (LHII)

The thermal environment impact of different areas within a city on human health and ecosystems and the temperature difference between a specific area and its surrounding areas can be evaluated through local heat island intensity (LHII).

$$I_{UHILOCAL}=(T_{skin}-T_{mean})/T_{mean}$$

(3)

where $I_{UHILOCAL}$ is the local heat island intensity of a particular pixel in the target area, $T_{skin}$ is the surface temperature of a specific pixel in the target area, and $T_{mean}$ is the average surface temperature of the target area. If $I_{UHILOCAL}>0,$ then the area is considered to be as expected. If it is between 0 and 0.1, then the area is a weak heat island area. The range of medium and robust heat island areas, $I_{UHILOCAL}$, is between 0.1 and 0.2 and 0.2 and 0.3, respectively. An area with $I_{UHILOCAL}<0.3$ is said to be an extreme heat island area.

3. Results

3.1. Current Status of Zhengzhou Heat Island Effect

Based on the information presented in Figure 2, it can be inferred that the surface temperature of Zhengzhou in 2021 varied across the city. The highest average temperature recorded in the town was 28.5 °C, while the lowest temperature was 19.4 °C. This indicates a significant range of temperatures across the city. In addition, the temperature distribution in the suburban areas was quite different from that of the urban areas. While the suburban areas had sporadic point-shaped high-temperature patches, the surface temperature in these regions was generally lower than in urban areas.

On the other hand, the urban areas of the city had higher surface temperatures in general. The difference in temperature patterns between the urban and suburban regions of Zhengzhou is likely due to population density, land use, and infrastructure. Urban areas tend to have higher temperatures due to the presence of buildings, roads, and other man-made structures that absorb and radiate heat. Suburban areas, on the other hand, have more open spaces and vegetation, which can help to reduce the overall temperature. Overall, the data presented in Figure 2 provide insight into the surface temperature of Zhengzhou in 2021 and highlight the differences in temperature patterns between the urban and suburban areas of the city.

Figure 3A shows the variation in temperature in the southeast corner and Figure 3B shows the variation in temperature in the northwest corner. The Jiangang Reservoir is located in the southwest corner and the Yellow River is in the northeast corner of Zhengzhou City. It can be observed that the temperature in the southwest corner is relatively mild. However, a low surface temperature can be seen in the northeast corner. One possible explanation for the relatively lower surface temperature observed in the northeastern region could be the numerous artificial lakes. These water bodies have a cooling effect on the surrounding environment by absorbing and dissipating excess heat, thereby mitigating the UHI effect. Additionally, the presence of water bodies can enhance evaporative cooling and promote the formation of convective breezes, further contributing to the lower surface temperature in the region.

3.2. Local Heat Island Intensity (LHII) Distribution

The LHII of Zhengzhou in 2021 was calculated to observe the spatial distribution characteristics of UHIs, and the results are shown in Figure 4. The results suggest that the Zhengzhou metropolitan area did not exhibit any significant hotspots or regions with elevated levels of UHI effect in 2021. The absence of strong UHI effects can be attributed to several factors, including the city’s relatively low population density, green spaces and water bodies, and effective urban planning and management practices. The findings of this study provide valuable insights into the dynamics of UHI effects in urban areas. They can inform the development of strategies for mitigating the adverse impacts of urbanization on the environment and human health. The depiction in Figure 2 illustrates the areas with a medium heat island effect, as indicated by the gray shading. Specifically, within the urban areas of Zhongmu County and Xinzheng City, there were numerous weak heat island areas, which were identified in several locations, including the western part of Gongyi City, the eastern part of Dengfeng City, the central part of Xinmi City, and the central and east parts of Xingyang City. These observations provide valuable scientific insights into the thermal behavior of these regions, which can inform further investigations into the underlying factors contributing to the observed patterns of UHIs.

3.3. Day and Night Contrast

The LST of Zhengzhou City in 2021 is depicted in Figure 5, which presents the day- and nighttime temperature patterns. As can be seen in Figure 5a, the highest and lowest temperatures recorded during the daytime were 35 °C and 22.1 °C, respectively. Moreover, the average temperature for the city was calculated to be 30.6 °C, with a corresponding UHII of 0.87 °C. These findings highlight the significant influence of urbanization on the thermal characteristics of the city and emphasize the need for effective mitigation strategies to counteract the adverse effects of UHI. Figure 5b presents the nighttime LST of Zhengzhou City in 2021, with the highest and lowest temperatures recorded 24.5 °C and 15.6 °C, respectively. The calculated average temperature for nighttime was 19.4 °C, which is substantially lower than the daytime temperature. However, the corresponding UHII was estimated to be 1.7 °C, indicating the presence of the UHI effect even during the nighttime. These observations underscore the complex dynamics of UHI effects in urban areas and highlight the importance of adopting appropriate urban planning and management strategies to mitigate the adverse impacts of UHI on the environment and human health.

Figure 6 presents the results of the LHII calculation for both day and night in Zhengzhou City. The classification of LHII values provides a spatially resolved analysis of UHI effects within the city. The results indicate that during the nighttime, the central-eastern region of Zhengzhou City had considerably stronger LHII values, indicating the presence of localized hotspots with powerful and robust UHI effects compared to the daytime. It is initially assumed that the concentrated urban heating supply in Zhengzhou is what primarily contributes to the winter urban heat island effect when comparing urban and suburban areas. Urban areas typically experience higher temperatures throughout the winter because of the prevalence of heating pipes and indoor heating, especially at night. This causes a more pronounced winter heat island effect. The assessment of Zhengzhou City’s urban and suburban areas revealed medium heat island areas during the day. In contrast, weak heat island areas were predominantly concentrated in the metropolitan region. Furthermore, our analysis identified localized areas with weak heat island effects in the central and southern parts of Zhongmu County, Xinzheng City, and the majority of Xinmi City. Similarly, weak heat island effects were observed in significant areas of Dengfeng City, the western part of Gongyi City, and eastern Xingyang City. These observations highlight the spatial variability of UHI effects across the region and suggest the potential role of localized environmental factors in modulating the intensity and distribution of UHI effects. Such insights can be leveraged to develop targeted urban planning and management strategies for mitigating the adverse impacts of UHI on the environment and public health. Our analysis identified medium heat island areas during the nighttime in Zhengzhou City’s urban and suburban administrative centers. In contrast, weak heat island effects were predominantly observed in the metropolitan region and the central and southern regions of Xingyang City, Gongyi City, and Xinmi City.

3.4. Change of Seasons

The temperature characteristics of Zhengzhou City across different seasons are illustrated in Figure 7. Our analysis indicates that summer is the season with the highest average, maximum, and minimum temperatures, whereas spring and autumn temperatures are relatively similar. Interestingly, we found that the heat island effect has a more significant impact during autumn when temperatures are at their lowest. These findings underscore the need for developing appropriate strategies to mitigate the effects of heat islands on public health and the environment, particularly during the autumn season.

We investigated the daytime and nighttime variations in the heat island effect across different seasons in Zhengzhou City, and the results are presented in Figure 8. Figure 8 illustrates how the heat island effect changes over a day and throughout various seasons in the city. Based on our findings, the impact of the heat island effect in Zhengzhou City during the daytime tends to be most significant during autumn and least significant during winter. This highlights the seasonality of heat island effects and has important implications for developing effective mitigation strategies. Our analysis reveals no significant difference in the heat island effect between spring and summer (0.69 °C and 0.62 °C, respectively). However, a considerable difference is observed between autumn and winter (2.21 °C and 0.02 °C, respectively). These findings suggest that the heat island effect is most pronounced during autumn, and effective mitigation strategies should focus on this season in particular. Our analysis of Zhengzhou City’s heat island effect reveals interesting seasonal differences. During the nighttime, the heat island effect is most potent in the summer (2.4 °C) and comparatively weaker in the autumn (2.06 °C) and winter (1.7 °C), with the most negligible impact in the spring (0.74 °C).

Interestingly, during the day, the heat island effect is stronger than the nighttime effect in autumn (2.21 °C). During the spring, summer, and winter, the nighttime heat island effect is stronger than the daytime effect. These findings emphasize the importance of season-specific mitigation strategies to address the heat island effect in urban environments.

3.5. Interannual Variation

Our investigation revealed that the intensity of the heat island effect was highest during the autumn nighttime in Zhengzhou. The heat island effect during the autumn nighttime from 2012 to 2021 was examined as a representation of this phenomenon. Figure 9 demonstrates an overall increasing trend in the intensity of the heat island effect in Zhengzhou during this period. The power of the heat island effect was at its lowest point in 2014, with a temperature drop of 0.83 °C, whereas it reached its highest point in 2020, with a temperature rise of 2.27 °C. Although the intensity of the heat islands briefly increased in 2012 and 2013, it continued to decrease in 2014. These findings provide critical scientific insights into the temporal dynamics of heat islands in Zhengzhou, particularly concerning seasonal and yearly variations, which can inform future research efforts to understand the underlying causes and potential mitigative measures for UHIs.

Despite the fluctuations observed between 2012 and 2015, an overall upward trend in local heat island intensity has been evident in Zhengzhou since 2015. To compare the surface temperature and local heat island intensity between 2012 and 2021, the results from an autumn night were analyzed and are presented in Figure 10. High-temperature regions in both years were predominantly located in the city center and administrative centers in the suburbs. In 2012, the average temperature was 17.32 °C, with a heat island intensity of 0.88 °C. In 2021, however, the average temperature increased to 22.29 °C, and the heat island intensity rose to 2.06 °C. These observations highlight the significant changes in the thermal behavior of the region over the past decade, which can provide valuable insights into the dynamics of UHIs and inform potential strategies for mitigating their effects.

Figure 11 shows the nighttime temperature of the spring season in the years 2012 and 2021 in the Zhengzhou City. During the spring of 2012 and 2021, the high local heat island intensity areas at night were primarily observed in the urban area. In 2012, a powerful heat island area was detected in the metropolitan area. However, in 2021, the substantial heat island area was expected to expand significantly, including in Xingyang City’s administrative center and Shangjie District. Medium heat island areas were primarily found in urban areas, such as Dengfeng City and the south, central north, and central south of Xinmi City, among other places. Weak heat island areas were mainly observed in urban areas, such as Gongyi City, the south of Xinmi City, the southeast of Dengfeng City, and other places. Furthermore, the range of moderate heat island intensities increased, further indicating the growth of Zhengzhou’s heat island effect. These findings provide essential scientific insights into the spatial distribution of the heat island effect in Zhengzhou, which can inform potential strategies for mitigating the adverse effects of UHIs.

3.6. Spatiotemporal Variation in Land Cover in Zhengzhou

Figure 12 shows the distribution of Zhengzhou land. For example, some parts of the land consist of forest land, built-up areas, shrubland, etc. Figure 12 presents the spatial distribution of different land types in Zhengzhou between 2012 and 2020. Data from 2020 were used instead of 2021 since they were unavailable during the study. Figure 12 shows that the spatial distribution of UHI corresponds with the trend of urbanization. Moreover, the hostile heat island areas are primarily observed in forest land, water bodies, and wetlands. The IGBP global vegetation classification data were used to combine the land cover types in Zhengzhou City into eight categories: grassland (grassland + tropical sparse woody savanna), crops (crops + crops/natural plant mosaic), forest (deciduous broadleaf forest + evergreen broadleaf forest + deciduous needleleaf forest + evergreen needleleaf forest + mixed forest), shrubland (dense shrubland + sparse shrubland), bare land, water (water + snow + ice), built-up area, and wetland (wetland, grassland). The built-up areas of Zhengzhou City have expanded significantly year after year, demonstrating a clear trend of urban expansion. These findings emphasize the need for sustainable urban development strategies that consider urbanization’s impacts on the natural environment and urban climate.

3.7. Annual Changes in Surface Temperature in Different Types of Land Use Areas in Zhengzhou

The thermal characteristics of different underlying surfaces in Zhengzhou were investigated through statistical analysis of the surface temperature of various land use areas, as depicted in Figure 13. The temperature level is intuitively expressed by the brightness of the image pixels given in Figure 12. The surface temperatures of the eight different types of land that had undergone classification were then examined using comprehensive statistical analysis. The average surface temperature was calculated using Equation (1) in order to determine the relative surface temperature value for each land type. The study revealed that the temperature change trend of each land use type was consistent from 2012 to 2021, with urban areas exhibiting the highest surface temperatures. Over time, there has been a noticeable rise in the overall temperature of various land types. In particular, built-up areas have consistently exhibited higher temperatures over the past decade. For instance, in 2012, the highest recorded temperature in built-up areas was 23.6 °C, which subsequently increased to 26.5 °C by 2020. On the other hand, forested regions experienced relatively lower temperatures compared to other land types. In 2012, the minimum temperature recorded in forested areas was 19.3 °C, while it rose to 21.6 °C in 2020. These findings indicate a discernible trend of increasing temperatures in built-up areas and comparatively lower but still rising temperatures in forested regions over the studied period. This can be attributed to converting natural surfaces into concrete roads and buildings during urbanization, resulting in increased heat absorption by these materials and elevated surface temperatures. On the other hand, wetlands and water bodies had the lowest surface temperatures, followed by woodlands. This can be attributed to vegetation’s transpiration, which has the potential to cool and dissipate a significant amount of heat [36]. These results emphasize the significance of maintaining natural land cover in urban areas to reduce the UHI effect and enhance the general urban climate.

3.8. LST Variation among Different Land Types in the Four Seasons of 2012 and 2020

We comprehensively analyzed the distribution of Zhengzhou’s surface temperature across different terrains between 2012 and 2020. Figure 14 illustrates the surface temperature distribution by terrain type during the four seasons. The analysis results indicate that the ground temperature of build-up areas was consistently the highest in all four seasons, while forest land always had the lowest ground temperature. Seasonal temperature variations were also observed across different underlying surfaces. The highest temperature variations were seen during summer, followed by spring and autumn, while the lowest was during winter. These variations can be attributed to various factors, including differences in solar radiation, air temperature, precipitation, and humidity levels during different seasons. It is worth noting that urbanization significantly impacts surface temperature distribution. Replacing natural surfaces with heat-absorbing materials such as concrete and asphalt in urban areas substantially increases surface temperatures. This study’s results underscore the importance of preserving natural textures, such as forests and wetlands, to mitigate the impact of urbanization on surface temperature distribution.

4. Discussion

This study aimed to investigate the UHI effect in Zhengzhou over the past decade (2012–2021). The results showed that the UHI effect has increased in the city’s urban areas compared to the rural areas. This increase can be attributed to the rapid pace of urbanization that has taken place in Zhengzhou and around the world. Urbanization has led to the construction of more buildings and roads, which absorb and store heat from the sun during the day and release it at night, contributing to higher temperatures in urban areas. In addition, the increase in the population and energy consumption in urban areas generates more heat, exacerbating the UHI effect. The UHI effect significantly impacts human health and the environment, including increased energy consumption for air conditioning, higher air pollution levels, and heat-related illnesses. Therefore, it is essential to understand and mitigate the UHI effect in urban areas through strategies such as green roofs, tree planting, and urban design that promotes natural cooling and reduces the amount of heat absorbed and stored by urban surfaces. Currently, the rate of urbanization around the globe is accelerating [3]. Rapid urbanization has been a critical driver of economic prosperity and social advancement but has also negatively affected the global environment [36]. The UHI effect has emerged as a significant concern among the ecological impacts attributed to urbanization. The intensification of UHI in urban areas can have far-reaching consequences on the climate, human health, and ecosystems. Hence, it is imperative to mitigate the UHI effect through appropriate urban planning and design measures and adopt sustainable development strategies [37,38]. As the area of urban construction increases, many natural surfaces are transformed into impermeable surfaces. Urban regions absorb more heat than suburban areas because built-up areas decrease the evaporation capacity of a city, and the emissions of buildings cannot evaporate as quickly as those of urban vegetation and water bodies, which also raises the city’s temperature [39]. As a result, the urban surface temperature is higher than that of other land types. The built-up area of Zhengzhou City is increasing year by year, and the surface temperature of the built-up area is also gradually rising, which leads to an increase in the intensity of the UHI.

Due to the rapid urbanization and industrialization of human civilization, UHI is one of the significant problems of the 21st century [40,41,42]. To measure the effect of UHI, UHII is used. Previous studies show that researchers have used different metrics to measure UHII. However, limited studies have been carried out to analyze the UHI effect in Zhengzhou. In this study, using a combination of MODIS products and 3S technology, the UHII and LHII in Zhengzhou from 2012 to 2021 have been studied and analyzed to evaluate the thermal environment impact of different areas of Zhengzhou. In 2021, moderate heat islands were distributed in the central part of the city; however, weak heat islands were present in other parts of the urban areas (Figure 4). According to the distribution of the daytime and nighttime LST in Zhengzhou in 2021, the highest temperature and UHII in the day and night are 35 °C and 0.87 °C and 24.5 °C and 1.7 °C, respectively, as shown in Figure 5. Initially, it was hypothesized that the winter urban heat island effect in Zhengzhou is primarily caused by the concentrated urban heating supply when comparing urban and suburban areas. The prevalence of heating pipes and indoor heating contributes to higher temperatures in urban regions, thereby leading to a more pronounced winter heat island effect, particularly during the nighttime (Figure 5 and Figure 10). The thermal properties of Zhengzhou and daytime and nighttime variations during different seasons are shown in Figure 7 and Figure 8. It is evident from the results that the heat island intensity in Zhengzhou was the strongest in autumn, and the summer nights had the highest heat island intensity.

The results of this study show that with the rapid urbanization, the temperature of the land surface and heat island intensity has increased from 2012 to 2021. An apparent increasing trend can be seen in 2012. The heat island intensity was 0.88; in 2021, it was measured to be 2.06. Every type of land exhibits seasonal changes, and Zhengzhou’s UHI effect has prominent seasonal characteristics. More water can be sprayed onto impervious surfaces such as roads in cities in the summer to reduce the surface temperature inside the city and thereby contribute to reducing the UHI, especially in construction areas where the surface temperature is at its highest in the summer. The thermal properties of various underlying surfaces in Zhengzhou were investigated using a statistical surface temperature analysis across different land use types (Figure 13). The temperature change patterns for each land use type remained consistent from 2012 to 2021, with urban areas displaying the highest surface temperatures. This can be attributed to replacing natural surfaces with concrete roads and buildings during urbanization, which results in increased heat absorption and, thus, elevated surface temperatures [43,44]. Conversely, wetlands and water bodies exhibited the lowest surface temperatures, followed by woodlands. This is due to vegetation transpiration’s cooling and dissipation of heat potential [45,46]. These findings emphasize the importance of preserving natural land cover in urban areas to mitigate the UHI effect and improve the overall urban climate.

The findings of this study reveal a clear trend of increasing warmth in the city of Zhengzhou due to urbanization, accompanied by a rise in the intensity of the urban heat island effect. While global warming plays a role in this phenomenon, the rate of urban warming surpasses that of suburban areas. The frequency of heat waves and extreme weather events in recent years underscores the urgency of taking proactive measures in urban planning and development to mitigate the urban heat island effect and counteract the escalating urban warming trend. Based on the findings of this study, we propose the following recommendations:

• Emphasize policy guidance: In the future development of cities, urban planners and policymakers should prioritize the construction of cool cities. This entails implementing policies that focus on mitigating the urban heat island effect and promoting sustainable urban environments.
• Enhance urban blue-green infrastructure: It is crucial to invest in the development of urban blue-green infrastructure, as it serves as an urban cool island. The presence of blue-green spaces and the evapotranspiration process they facilitate play a significant role in alleviating the urban thermal environment.
• Increase surface greenery and reflectivity: Efforts should be made to enhance surface greenery, such as incorporating green roofs and vertical greening. Additionally, increasing surface reflectivity through the use of cooling pavement materials and cool infrastructure can help modify the thermal properties of urban areas, leading to a reduction in the urban heat island effect.
• Implement urban heat island monitoring systems: Establish comprehensive urban heat island monitoring systems to continuously assess and analyze temperature variations across different urban zones. These data can provide valuable insights for urban planning and facilitate targeted interventions.

By implementing these recommendations, we can actively work towards mitigating and minimizing the impacts of the urban heat island effect, thus fostering more sustainable and livable cities.

5. Conclusions

In this study, a comprehensive approach was employed to characterize the urban heat island (UHI) effect. We conducted a thorough analysis of UHI intensity, considering temporal variations, using a decade-long dataset (2012–2021) and information from the study area using 3S technology and MODIS data (MYD11A2 and MCD12Q1). This analysis encompassed annual, seasonal, daytime, and nighttime assessments, providing a comprehensive understanding of the UHI phenomenon of Zhengzhou City. The following conclusions can be drawn from the collected data. (1). The findings of this study demonstrate a substantial increase in the UHI effects over the past decade, coinciding with the rapid pace of urbanization in the study area. (2). It is also observed that the heat island is more intense at nighttime in winter than during the daytime, which might be due to the prevalence of heating pipes and indoor heating in built-up areas. The highest UHII during daytime was 0.8 °C, and at nighttime, it was measured to be 1.7 °C. (3). According to the results, autumn was the season with the highest heat island intensity in Zhengzhou, followed by summer and spring. (4). Additionally, the built-up area of Zhengzhou has the highest surface temperature, mainly contributing to UHI, while the woodland and water areas have lower surface temperatures. The results of this study have significant implications for mitigating the UHI effect in the future. Strategies such as constructing ponds and pools, strengthening urban greening efforts, and implementing summer mitigation measures can effectively slow down the UHI effect. These measures should be considered in urban planning and management to promote a more sustainable urban environment.