1. Introduction
Urbanization is considered as one of the most important processes that affects the environment on local, regional, and global levels [
1]. The construction projects or increasing buildings involved in urbanization often with vegetation removal, lead to increased heat absorption in urban centers. Urbanization transforms natural landscapes into artificial surfaces, altering surface energy budgets, changing physical surface properties, and modifying the hydrological cycle [
2]. As a result, significant landscape changes occur, and one of the outcomes of this process is the creation of the surface urban heat island (SUHI), which refers to areas with higher temperatures than their surrounding regions.
Temperature itself plays a vital role in climate as it influences various human activities, including agriculture, housing, and tourism. Due to its close association with other climate elements, temperature is considered the driving force behind them. The interdependence among these elements means that they significantly impact each other [
3]. When temperature changes, it can trigger a chain reaction of impacts across various climate variables. The combination of rising temperatures or extreme heat events and air pollution in urban areas poses a severe threat to human health, as indicated by [
4]. Furthermore, localized synergies between heat waves and urban heat island effects have significant implications on human thermal comfort and urban heat management [
5]. As it is classified as a localized phenomenon, SUHI is sensitive to local variations in thermal, aerodynamic, moisture [
6], land use dynamics [
7,
8] and urban development and typology [
9]. The challenges posed by urbanization and climate change are diverse and affect cities globally [
10].
The SUHI effect is widely acknowledged as a prominent feature of the urban climate. One crucial parameter in the physical processes of the Earth is Land Surface Temperature (LST), as noted in [
11]. However, obtaining thermal images with high spatial, radiometric and temporal resolution is currently challenging due to the limitations of thermal infrared sensors [
12]. Nonetheless, it is possible to calculate LST using different sources of surface emissivity from thermal infrared sensors such as that on Landsat 5, 7, 8, and 9 [
13,
14], MODIS, ASTER, and ECOSTRESS.
Land use/land cover (LULC) changes in urban settings are a crucial aspect that physically impacts the Earth’s surface. The distinctive physical characteristics of each LULC category regarding radiation and energy absorption contribute to this effect [
15,
16,
17]. Thus, any alterations in LULC patterns will result in a shift in energy exchange between the atmosphere and the ground surface. This, in turn, will bring about modifications in aerodynamic balance, as observed in [
15,
18,
19,
20]. Satellite images are usually used for the registering and mapping of LULC changes [
14,
21,
22]. The use of satellite-derived imagery datasets provides a medium to high-resolution scene and permits continuous monitoring of the Earth’s surface and atmosphere. This has been extensively leveraged to obtain the data required to monitor recent alterations in LULC and its impact on SUHI. Numerous studies have explored the correlation between LST and LULC using remote sensing imagery and geographic information systems (GIS) at the local and global levels [
23,
24,
25,
26,
27,
28,
29]. Recently, spatiotemporal analysis of SUHIs in relation to urban development of different cities was presented [
30,
31,
32,
33,
34].
Jeddah city is located in an arid and semi-arid area, and it receives great governmental attention regarding pelleting and development. In 2021, hoping to achieve high-quality urbanizing trends, a comprehensive development process was initiated in the city of Jeddah, which included removing informal and illegal settlements and buildings without an identity or architectural character, with the aim of serving humanity and ensuring sustainable development. Infrastructure is being developed and services and projects are being created to improve the quality of life in accordance with the Kingdom’s 2030 vision [
35]. Exactly 34 neighborhoods in different areas were removed, with a total area of 37.703 Km
2 [
36], and these areas have become open spaces. As a result, the land cover in Jeddah has been greatly affected. Consequently, LULC dynamics have dramatically altered in the last three years in this city. The main reasons behind choosing Jeddah city as a case for our study are: (1) the comprehensive urban development process for quality-of-life improvement through demolishing the informal and illegal settlements in Jeddah; (2) the investigation of localized synergies between LULC dynamics and LST and its implications on SUHIs formation. The question we aim to address in this study is: to what extent do the new urban strategies influence the LST in Jeddah? Therefore, the objectives of this study are as follows: first, to track the dynamics of LULC changes and their impact on LST within the city of Jeddah; second, to efficiently evaluate the phenomenon of SUHI; and third, to investigate the relationships between LULC changes and SUHI during the period from 2013 to 2023 using remote sensing and GIS techniques.
4. Discussion
4.1. Analysis of the Urban Development Strategies
To improve the quality of life in Jeddah city and to achieve high-quality urbanization trends, a comprehensive development process was initiated in the last years. This, based on the change detection results, may have contributed remarkably to the transition of built areas into barren lands as a first step before installing new urban planning. As mentioned in the introduction to the study, the new urban planning includes developing infrastructure and services and creating new projects to improve the quality of life in accordance with the Kingdom’s 2030 vision [
35]. The first step involves the elimination of certain old, illegal districts in Jeddah, about 34 neighborhoods in different areas were removed [
36], which appeared in the results of change detection. This results in alterations to the land cover characteristics. Since SUHIs are sensitive to explicit factors of LULC and urban development [
5], these modifications subsequently affect the thermal energy balance and are leading to shifts in the local climate, which is represented by a local increase in LST [
31]. Therefore, the main objective of this study was to track the dynamics of LULC changes and associated urban development strategies and their influence on LST within the city of Jeddah.
4.2. Land Use and Land Cover Changes
In today’s era of big data, the availability of advanced robust techniques and cloud computing platforms has made large-scale analysis possible at a low cost [
34,
45]. Thanks to Google Earth Engine (GEE), about 40 different scenes from the Landsat satellite were remotely accessed and classified. Additionally, all the required indices were easily calculated using automatic parallel processing and robust computational abilities provided by GEE. The overall accuracy, using reference data validated by Google Earth, exceeded 95% for all performed classifications.
The heterogeneous spatiotemporal LULC changes from 2013 to 2022 have shown both negative and positive changes in the various LULC classes. Water bodies and vegetation cover, as blue–green spaces, hold significant implications in urban development. However, the percentage of vegetation cover and water bodies in the study area decreased following the commencement of the demolishing project. Remarkably, LST also decreased during this period, suggesting that the influence of these blue–green spaces on LST was minimal. As mentioned earlier, the changes in water and vegetation classes were negligible due to the lower presence of those classes in this arid region. Changes from urban to barren land is attributed to the comprehensive development project in Jeddah to improve the quality of life aligning with the Kingdom’s 2030 vision. Even though, 34 neighborhoods in various regions have been demolished [
36], the results of the change detection indicate that the total urban areas in the study area have increased compared to the total barren land areas from 2013 to 2022. This change from barren land to urban can be attributed to the efforts of the government in providing alternative housing projects for the residents of the demolished neighborhoods through the creation of new urban areas according to a well-planned urban design.
4.3. Impact on LST55
The rise in LST caused by LULC is a widespread phenomenon that occurs all over the world [
30,
31,
32,
33]. A variety of external factors such as latitude, soil type, weather conditions etc. play a big role in determining the degree of change [
34]. In our case, the situation is different for several reasons. Firstly, the study area is arid, so the impact of increased vegetation cover on reducing LST rise is almost nonexistent due to the scarcity of plants in this environment. The percentage of vegetation cover was 4.34% in 2013, 5.33% in 2022, and reached its highest value of 5.51% in 2014. Secondly, the comprehensive development process project, which began the removal of old informal and illegal settlements from the city center, had a significant influence on LST changes. We found that the mean LST began to noticeably decrease starting from 2020 when the project commenced. Thirdly, the geographical location of Jeddah is significant. It extends longitudinally along the Red Sea coast, without a centralized urban area in the city. The presence of the sea acts as a natural cooling mechanism and significantly influences LST. Coastal areas benefit from cooling breezes resulting from the temperature differential between the land and sea. These breezes have a pronounced effect on reducing LST along the coastline, making these regions notably cooler than inland areas. As demonstrated in
Figure 11, the temperature gradients along the cross-sectional profiles A, B, and C illustrate this phenomenon. LST begins at lower values in the coastal area and gradually increases, typically reaching its highest values farther from the sea.
It is clear from the results that LST values varied according to land use and the increase in heterogeneity in land cover features. During the study periods between 2013 and 2022, the barren lands have recorded the most mean LST, followed by the built-up areas, vegetation, and water bodies. While, for maximum LST recorded, the built-up areas have recorded maximum LST, followed by barren lands, vegetation, and water bodies.
The results of the study revealed a clear inverse linear correlation between LST and NDVI throughout the study duration. This indicates that the reduction in vegetation cover significantly contributed to the rise in LST. Moreover, a positive correlation was observed between LST and NDBI, signifying that an expansion of built-up areas leads to an escalation in LST. These outcomes align with results from comparable studies that relied on Landsat data analysis [
52,
53,
58,
59,
60].
4.4. Spatial Analysis of SUHIs
The classification of LST into various classes allowed for the identification of areas with extreme-high temperatures surrounded by sub-high or medium temperatures, which were considered as centers of SUHIs. These centers were tracked and mapped over the years. This provides a comprehensive view of the spatiotemporal dynamics of SUHIs. According to previous studies, heat islands in Jeddah are predominantly concentrated in the southern region [
3]. These areas mostly consist of informal and industrial regions that have been recently removed.
Figure 9 visually illustrates the distribution of these heat islands in Jeddah City from 2013 to 2022. It is apparent from the map that the presence and intensity of SUHIs vary across different years, indicating the dynamic nature of SUHIs in the city. The concentration of UHIs was in the southern part and the middle of the city until 2016, after that the concentration of UHIs decreased. In 2022, complete absence of the SUHIs over the city was noticed. The disappearance of SUHIs can result from various factors, including urban planning, climate change, or mitigation efforts. In our study, it was due to implementation of the new urban development strategy and demolition of old districts. This has a significant positive implication on human thermal comfort, urban heat management, and energy savings.
4.5. Limitations
There are some limitations to this study. First, regarding the data used, on the one hand, The image spatial resolution was 30 m, and this caused inaccuracies in linking the estimated LST with the LULC, especially for the small blocks. On the other hand, the availability of cloud-free data, which is essential to calculate accurate LST, for the required time-points is a major limitation of this study.
In this study, we focus on land use changes as the only factors influencing LST changes. It is important to note that other variables, such as weather changes over the study period, may also impact LST. Future research could yield more insights by extending the study period beyond just the summer months and considering weather variations throughout the year.
5. Conclusions
This study provides a comprehensive assessment of SUHIs in Jeddah City based on LST during a 10-year period (2013–2022), shedding light on their presence, and temporal variations. The spatiotemporal pattern of LULC changes was configured for different time-points and four different LULC classes including: urban, vegetation, barren lands, and water bodies. Average summer LST was calculated, and the variation of LST with NDVI, and NDBI was assessed. Additionally, URI was used to illustrate the variation of the intensity of SUHI in the study area. The results showed notable heterogeneous spatiotemporal LULC changes showing both negative and positive changes in the various LULC classes spatially between urban and barren land classes. Through an examination of the LST distribution pattern and the mapping of SUHIs in Jeddah city over the study duration, it becomes evident that a substantial direct correlation exists between the density of built-up areas and LST. Furthermore, the findings highlight a significant negative association between LST and the NDVI, whereas a positive correlation was consistently observed between LST and NDBI across all time points. From the calculation of the URI, it is seen that the value of URI reached its maximum of 0.24 in 2016 with the presence of SUHIs, then it decreased dramatically to reach 0.12 in 2022 with an absence of SUHI. It was evident that the complete absence of SUHI in 2022 was due to the removal of old informal and illegal settlements from the city. The findings have implications for urban planning, climate adaptation, and further research into the underlying causes of these urban heat phenomena. Understanding and addressing SUHIs is crucial for creating more sustainable and livable urban environments.