Impacts of Land Cover/Use on the Urban Thermal Environment: A Comparative Study of 10 Megacities in China

Modelling future land use land cover changes and their impacts on urban heat island intensity in Guangzhou, China

During rapid urbanization in developing countries, changes in land use and land cover (LULC) can significantly alter urban land surface temperatures (LST), exacerbating the urban heat island (UHI) effect and degrading the outdoor environment. In this study, taking Guangzhou, China, as an example, we used Landsat series satellite data from 1992 to 2022, classified the LULC of the study area by the Support Vector Machine (SVM) method, estimated the LST of the area by the mono-window algorithm, and classified the LST of the study area into five UHI intensity classes based on the normalized values of the LST, and explored the influence of the LULC on the distribution of the UHI intensity. The CA-ANN (cellular automata-artificial neural network) model in QGIS software was employed to forecast the distribution of LULC and UHI intensity in Guangzhou for 2032. The findings reveal a strong correlation between UHI intensity and LULC, with water bodies and vegetation primarily exhibiting low and sub-low temperatures, while urban areas exhibit sub-high and high temperatures. The prediction results show that, according to the current development trend, compared with 1992, the water body and vegetation cover in 2032 will decrease by 46.97% and 34.24%, the building land will increase by 263.71%, and the sub-high and high temperature areas will increase by 127.76% and 375.92%. By analysing the spatial and temporal changes in LULC and its relationship with the distribution of UHI intensity during urbanization, this study assists government administrations and urban planners in devising sensible urban development strategies and implementing effective measures to plan LULC rationally. This approach aims to mitigate the impacts of the urban heat island and foster sustainable urbanization.

Regional thermal environment changes: Integration of satellite data and land use/land cover

Land surface temperature (LST) is subject to location and environmental influences, which makes quantification difficult in terms of timeliness. Based on 10-d geostationary satellite LST TCI products, we quantitatively evaluated the thermal environment differentiation of various ground objects in North, South, and Northwest China from 2017 to 2021. We found that the thermal condition index (TCI) in Northwest China decreased, whereas it increased in North and South China. In contrast, Moran's I index increased in Northwest and South China, with strong spatial agglomeration. The TCI for artificial surfaces decreased from North (0.633) to Northwest (0.554) and South China (0.384). The bare land TCI was always the lowest among the land use/land cover (LULC) types in each region. Our results reflect the LULC thermal environment of China against the background of new urbanization and provide theoretical support for scientific planning to improve the ecological environment.

Surface urban heat island and its relationship with land cover change in five urban agglomerations in China based on GEE

The development of urbanization has changed the original land cover and exacerbated the urban heat island effect, seriously affecting the sustainable development of the ecological environment. Research on urban heat island characteristics and land cover changes in five major urban agglomerations in China to provide a reference for preventing thermal environmental risks and urban agglomeration construction planning. This paper estimates the surface urban heat island intensity (SUHII) of the five major urban agglomerations in China from 2003 to 2019 based on Google Earth Engine (GEE) through the urban-rural dichotomy, analyzes their trends through the Sen + M-K trend analysis method, and combines the detrending rate matrix to analyze the impact of land cover type shift on urban heat island change. Research shows that (1) the land cover types of the five major urban agglomerations in China have changed considerably from 2003 to 2019, and all five major urban agglomerations in China experienced varying degrees of urban expansion. (2) The annual average value of SUHII decreases in Beijing-Tianjin-Hebei, Yangtze River Delta, and middle reaches of the urban agglomerations, while the annual average value of SUHII increases in Chengdu-Chongqing and Pearl River Delta urban agglomerations. (3) The spatial composition of land cover types in the five major urban agglomerations in China is highly spatially correlated with urban heat islands, with urban land and bare land urban heat islands being the most pronounced. (4) The land cover type shift has the most significant heat island impact on Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengdu-Chongqing urban agglomerations. (5) The land cover change (LCC) with an increasing trend in SUHII is mainly bare land converted to arable land, and water bodies, grassland, forest land, and arable land converted to urban land.

RSEDM: A New Rotational-Scan Exponential Decay Model for Extracting the Surface Urban Heat Island Footprint

Surface urban heat islands are widely focused on due to their close relationship with a series of environmental issues. Obtaining a precise footprint is an important prerequisite for heat island research. However, the land surface temperature curves used for calculating footprint are affected by factors such as the complexity of land-use types, thereby affecting the accuracy of footprint. Therefore, the rotational-scan exponential decay model is developed in this paper, which first takes the gravity center of an urban area as the origin of polar coordinates, specifies due north as the starting direction, and rotationally scans the suburbs that are within 20 km outside urban areas in a clockwise direction at an angle of 1°. The eligible suburbs are screened out according to the built-up area rate, water body rate, and merge tolerance. Then, exponential decay fitting of the temperature curve is performed to obtain the extension distance of the heat island and the background temperature, which are used to determine the final footprint. Based on the method, the footprints of 15 cities were calculated and compared with those of the traditional method. The results show that: (1) this method could effectively eliminate the influence of a large number of contiguous built-up areas and water bodies in the suburbs on the footprint calculation, thus greatly improving the accuracy of the temperature curve and footprint. (2) Three of four cities had the largest footprint boundary in spring. All four cities had the strongest heat island intensity in summer and the smallest footprint boundary and intensity in winter. (3) Coupling effect would aggravate the negative impact of heat islands in the suburbs and threaten the suburban environment. As a state-of-the-art method, it can enhance the calculation accuracy and precisely reflect the spatial pattern of footprint, which is of great significance for the sustainable development of cities.

Spatial differentiation of neighborhood climates and their response to surrounding land cover composition: A case study in Beijing, China

Heterogeneous land cover affects near-surface heat and humidity distribution in urban areas. Effective land cover arrangements can create a more sustainable local thermal environment. However, spatial differentiation in neighborhood climates and their spatial response range to the surrounding land cover composition (LCC) in high-density urban environments remains unclear. In this study, field monitoring of the air temperature (Ta) and relative humidity (Rh) was conducted in summer (August 2016) and winter (December 2016 and January 2017) in a neighborhood in Beijing, China. A multi-radius approach was developed to quantify the effective response range of Ta and Rh at unshaded measuring points to the surrounding LCC. Our results demonstrated that the: (1) spatial distribution of Ta and Rh in a typical neighborhood varies significantly in both summer and winter and is dependent on the local land cover; (2) Ta at measurement points generally increases with growing surrounding vegetation coverage and decreases with less impervious pavement and building coverage, whereas the opposite applies to Rh; (3) response of Ta and Rh to land cover composition is spatially dependent; and (4) Ta and Rh have an effective response range of up to 200-m to surrounding vegetation coverage in both seasons, whereas their response range to pavement coverage is 150- and 100-m in summer and winter, respectively. Overall, LCC within a radius of 100-150-m has a significant impact on the Ta and Rh of the measuring points in a high-density urban neighborhood. These findings elucidate the spatial response of a neighborhood climate to surrounding land cover and demonstrate that landscape infrastructure intervention is an effective means of improving urban thermal environments.

Synchronization, Decoupling, and Regime Shift of Urban Thermal Conditions in Xi’an, an Ancient City in China under Rapid Expansion

Urbanization has profound impacts on economic development and environmental quality. Some of the serious consequences of urbanization are the changes in the thermal environment, which directly affect the greater environment and quality of life. Although many studies have been performed on urban heat islands, few have specifically examined the thermal evolution of rapidly expanding ancient cities and the impacts of urbanization on the thermal environments of important heritage sites. In this study, we analyzed the temporal and spatial patterns of the thermal environment quantified as the surface urban heat island (SUHI) and land surface temperature (LST) values from 2000 to 2018 in Xi’an, an ancient city with rich cultural heritage in China. Specifically, we analyzed the temporal evolution of the thermal environments of the functional zones and heritage sites and explore their coupling relationships with the overall temperature of the study area using a statistical analysis approach. Furthermore, we revealed time-sensitive changes in temperature regimes using the newly proposed double temperature curve approach (DTCA). The results showed that the heat island phenomenon has been intensifying in Xi’an, as evidenced by the summer daytime mean SUHI values being greater than 7 °C continuously since 2010 and the increased frequency of high-intensity SUHI effects. Extreme heat conditions were more frequent in the old urban area (built-up and in existence before 2000) than in the new urban area, while SUHI values in the new area deteriorated more rapidly. The changes in temperature in the functional zones were strongly synchronized with the overall temperature changes in Xi’an, and the temperature differences increased linearly with the overall temperature. The LST values in the four major historical heritage sites investigated in this study were 2–8 °C higher than the background temperature and were decoupled from background temperature changes. From the DTCA, we found the time periods of the thermal environment regime changes for each functional zone or heritage site, which were largely the result of policy guidance. Regional synchronization, site decoupling, and regime shifts in LST suggest opportunities for regional planning and urban landscape optimization to reduce adverse effects of urbanization on the urban environment, particularly in cities with rich historical heritage sites.

A Novel Composite Index to Measure Environmental Benefits in Urban Land Use Optimization Problems

In urban land use optimization problems, different conflicting objectives are applied. One of the most significant goals in urban land use optimization problems is to maximize environmental benefits. To quantify environmental benefits in land use optimization, many researchers have employed a variety of methodologies. According to previous studies, there is no standard approach for calculating environmental benefits in urban land use allocation problems. Against this background, this study aims to (a) identify indicators of environmental benefits and (b) propose a novel composite index to measure environmental benefits in urban land use optimization problems. This study identified four indicators as a measure of environmental benefits based on a literature assessment and expert opinion. These are spatial compactness, land surface temperature, carbon storage, and ecosystem service value. In this work, we proposed a novel composite environmental benefits index (EBI) to quantify environmental benefits in urban land use allocation problems using an ordered weighted averaging (OWA) method. The study results showed that land surface temperature (LST) is the most influential indicator of environmental benefit while carbon storage is the least important factor. Finally, the proposed method was applied in Rajshahi city in Bangladesh. This study identified that, in an average-risk decision, most of the land (64.55%) of the study area falls within the low-environmental-benefit zone due to a lack of vegetated land cover. The result suggests the potential of using EBI in the land use allocation problem to ensure environmental benefits.

A comparative study of land development patterns and regional thermal environments (RTEs) in typical urban agglomerations of China and America: A case study of Beijing-Tianjin-Hebei (BTH) and Boswash

Currently, most regional thermal environment (RTE) studies in urban agglomerations focus on developing countries, especially China. However, there is still a lack of comparative studies on the RTEs of urban agglomerations between China and other developed countries, such as the United States. This paper used the Beijing-Tianjin-Hebei (BTH) agglomeration in China and Boswash (the highly urbanized area extending from Boston to Washington) in the United States as examples to investigate the differences in land development patterns, RTEs and their relationship between the agglomerations of China and America. The results showed that the land development patterns of BTH and Boswash were different, as evidenced by the spatial pattern of land development intensity (LDI) and impervious surface configuration. In terms of the RTE, the sub-high land surface temperature (LST) zones were aggregated in a large and compact patch in central and northern BTH. However, the sub-high zones of the cities in Boswash were relatively separate. Moreover, the land development pattern of Boswash showed a stronger relationship with the RTE than that of BTH did. Global Moran's I between the LDI and LST in Boswash was higher than that in BTH. In addition, the correlation between impervious surface configuration and LST in Boswash was stronger than that in BTH, and this correlation was more controlled by LDI in Boswash. This study also indicated that BTH should change the land development pattern to prevent the further expansion of aggregated sub-high LST zones and control the proximity of high LST zones in cities in central and southern BTH, however, Boswash should adopt some local heat management approaches (installing cool and green roofs and creating more green space) in the core areas to help reduce the very high temperatures in the already highly developed areas where the largest fraction of people live.

Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China

The changes of land use/land cover (LULC) are important factor affecting the intensity of the urban heat island (UHI) effect. Based on Landsat image data of Wuhan, this paper uses cellular automata (CA) and artificial neural network (ANN) to predict future changes in LULC and LST. The results show that the built-up area of Wuhan has expanded, reaching 511.51 and 545.28 km2, while the area of vegetation, water bodies and bare land will decrease to varying degrees in 2030 and 2040. If the built-up area continues to expand rapidly, the proportion of 30~35 °C will rise to 52.925% and 55.219%, and the affected area with the temperature >35 °C will expand to 15.264 and 33.612 km2, respectively. The direction of the expansion range of the LST temperature range is obviously similar to the expansion of the built-up area. In order to control and alleviate UHI, the rapid expansion of impervious layers (built-up areas) should be avoided to the greatest extent, and the city’s “green development” strategy should be implemented.

Dynamics of urban landscape nexus spatial dependence of ecosystem services in rapid agglomerate cities of Ethiopia

Understanding the dependence of ecosystem services (ESs) on the dynamics of human-semi nature-coupled ecosystems is crucial for urban ecosystem resilience. In the present study, the responses of ESs to land use land cover transitions were explored and compared, selecting Addis Ababa, Adama, Hawassa, and Bahir Dar cities in Ethiopia. The geospatial data and benefit transfer approach was used to estimate the nexus over a three-decade period (1990-2020). Moreover, the bivariate Moran's I and spatial regression models were employed to analyze the spatial dependence of ESV on urbanization. The findings showed that the built-up increased by 17,341.0 ha (32.2%), 2151.3 ha (19.6%), 2715.2 ha (12.2%), and 2599.7 ha (15.7%) for Addis Ababa, Adama, Bahir Dar, and Hawassa cities, respectively over the investigated periods. Besides, the total ESV weighed by 24.8%, 8.9%, 0.7%, and 3.9% from the US$ 277.9, 55.5, 100.3, and 90.9 million for Addis Ababa, Adama, Bahir Dar, and Hawassa cities, respectively from1990 to 2020. Synergies occurred among local climate regulation and recreation services, and trade-offs existed among other services. A persistent rising trend in the ESVt was found for all cities the upsurge in Addis Ababa being much sturdier than in others. However, the elasticity of ecosystem of land use (EEL) showed that 1% of the LULC transformation was caused by 8.9% changes in ESV. Besides, the results from the global bivariate Moran's I show substantial positive spatial correlations between ESV, and Integrated Land use Dynamic Degree (ILUDD), Land-Use Intensity (LUI), and Land Use Diversity (LUD) (p < 0.001). Spatial lag model and special error model were shown to be fitting more than the Ordinary Least Square in establishing relationships among the spatial dependence of ESV on urbanization. In contrast, the aggregated ESV is significantly influenced not only by LULC dynamics but also by the spatial spillover effect. Thus, overall findings suggested an antagonistic nexus between the aggregated ESV and ESVf, since 98% of individual ESs were negatively declined as the built-up ecosystem expanded.

A land-use decision approach integrating thermal regulation, stormwater management, and economic benefits based on urbanization stage identification

Driven by global climate change and urbanization, urban heat island (UHI) and urban storm flood (USF) have become the most frequent and influential hazards in recent decades. Land-use optimization can effectively cope with these hazards. However, the trade-offs between multi-hazard mitigation and economic development impose many limitations in practice. Furthermore, current region-based optimization methods no longer meet the precise management demand, and both subdivision and spatial heterogeneity identification have the potential for wider applicability. Hence, a systematic integration of climate adaptation and urban construction through land-use planning is urgently required. This paper proposes a new land-use decision approach for improving climate adaptability of urbanization. This approach involves multi-objective optimization, spatial subdivision, and urbanization stage identification, which enable the simultaneous achievement of environmental and economic benefits. Taking Xiamen as case study, the results showed that excessive pursuit of land economic output (LEO) limits the chance of mitigating UHI and USF. Improving the LEO per unit area of construction land could disrupt the link between land exploitation and the increasing side effects of climate hazards. Future urbanization hotspots in Xiamen will likely emerge at the urban fringe in Tong'an District and Xiang'an District. Within each developing unit, the upper limit of construction land was 81.06 hm² and the green space was recommended to be 7.29-21.94 hm². Construction land and bare land contributed most to UHI and USF, while forest and grassland were highly efficient in heat and runoff mitigation. The developed approach proved to be effective and practicable, especially for reducing the impacts of extreme UHI and USF.

Capturing urban heat island formation in a subtropical city of China based on Landsat images: implications for sustainable urban development

Land use/cover change is the main driving force of urban expansion which influences human-environment interactions. Generally, the formation of urban heat islands (UHIs) can be referred to as a negative "by-product" of urbanization. In the context of rapid urbanization, the present paper aims to capture the landscape changes and three patterns of urban expansion (i.e., infill, extension, and leapfrog), and provide a better understanding of the formation of the surface urban heat island (SUHI) in Dongguan, China, during the past 20+ years. Urban land increased from 28.87 × 10³ ha in 1994 to 78.89 × 10³ ha in 2005 and 101.05 × 10³ ha in 2015, with a compound annual urban growth rate of 9.57% (1994-2005) and 2.51% (2005-2015), respectively. Based on the mean land surface temperature difference (Δ mean LST) between urban land (UL) and green space (GS), the SUHI intensity (SUHII) increased from 1.46 °C in 1994 to 2.32 °C in 2005 and 3.83 °C in 2015 in Dongguan. Overall, the Δ mean LST of urban areas increased from 2.61 °C (1994-2005) to 4.78 °C (2005-2015). The Δ mean LST between the city center and its surrounding areas decreased from 1994 to 2015, and the Δ mean LST between the city center and the suburbs gradually increased, primarily in 2015. In particular, both dense urban and the infill pattern of urban expansion had high mean LSTs in Dongguan, thus having negative impacts on sustainable urban development. The limited green space and open land should be strictly controlled or prohibited for transformation in urban areas. Particularly in dense regions, green roofs, green areas, and urban renewal actions could be considered for mitigating the urban heat island effect.

Spatial Interconnections of Land Surface Temperatures with Land Cover/Use: A Case Study of Tokyo

As one of the most populated metropolitan areas in the world, the Tokyo Metropolitan Area (TMA) has experienced severe climatic modifications and pressure due to densified human activities and urban expansion. The surface urban heat island (SUHI) phenomenon particularly constitutes a significant threat to human comfort and geo-environmental health in TMA. This study aimed to profile the spatial interconnections between land surface temperature (LST) and land cover/use in TMA from 2001 to 2015 using multi-source spatial data. To this end, the thermal gradients between the urban and non-urban fabric areas in TMA were examined by joint analysis of land cover/use and LST. The spatiotemporal aggregation patterns, variations, and movement trajectories of SUHI intensity in TMA were identified and delineated. The spatial relationship between SUHI and the potential driving forces in TMA was clarified using geographically weighted regression (GWR) analysis. The results show that the thermal environment of TMA exhibited a polynucleated spatial structure with multiple thermal island cores. Overall, the magnitude and extent of SUHI in TMA increased and expanded from 2001 to 2015. During that time, SUHIs clustered in the compact residential quarters and redevelopment/renovation areas rather than downtown. The GWR models showed better performance than ordinary least squares (OLS) models, with Adj R2 > 0.9, indicating that the magnitude of SUHI significantly depended on its neighboring geographical setting, including land cover composition and configuration, population size, and terrain. We suggest that UHI mitigation in Tokyo should be focused on alleviating the magnitude of persistent thermal cores and controlling unstable SUHI occurrence based on partitioned or location-specific landscape design. This study’s findings have immense implications for SUHI mitigation in metropolitan areas situated in bay regions.

The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

Although research relating to the urban heat island (UHI) phenomenon has been significantly increasing in recent years, there is still a lack of a continuous and clear recognition of the potential gradient effect on the UHI—landscape relationship within large urbanized regions. In this study, we chose the Beijing-Tianjin-Hebei (BTH) region, which is a large scaled urban agglomeration in China, as the case study area. We examined the causal relationship between the LST variation and underlying surface characteristics using multi-temporal land cover and summer average land surface temperature (LST) data as the analyzed variables. This study then further discussed the modeling performance when quantifying their relationship from a spatial gradient perspective (the grid size ranged from 6 to 24 km), by comparing the ordinary least squares (OLS) and geographically weighted regression (GWR) methods. The results indicate that: (1) both the OLS and GWR analysis confirmed that the composition of built-up land contributes as an essential factor that is responsible for the UHI phenomenon in a large urban agglomeration region; (2) for the OLS, the modeled relationship between the LST and its drive factor showed a significant spatial gradient effect, changing with different spatial analysis grids; and, (3) in contrast, using the GWR model revealed a considerably robust and better performance for accommodating the spatial non-stationarity with a lower scale dependence than that of the OLS model. This study highlights the significant spatial heterogeneity that is related to the UHI effect in large-extent urban agglomeration areas, and it suggests that the potential gradient effect and uncertainty induced by different spatial scale and methodology usage should be considered when modeling the UHI effect with urbanization. This would supplement current UHI study and be beneficial for deepening the cognition and enlightenment of landscape planning for UHI regulation.

Modulations of surface thermal environment and agricultural activity on intraseasonal variations of summer diurnal temperature range in the Yangtze River Delta of China

Compared with interdecadal, interannual, or seasonal scales, the variations of diurnal temperature range (DTR) at the intraseasonal scale and their driving forces are less understood. Using surface meteorological observations and multi-source satellite retrievals during 2013-2017, together with Random Forest modeling, this study examines the intraseasonal variation of summer DTR in the Yangtze River Delta (YRD) region, China, and determines its potential driving factors [i.e., daily maximum/minimum surface air temperature (SAT_max/SAT_min), sunshine duration (SSD), rainfall, altitude, land vegetation cover, and land surface thermal environment including daytime/nighttime land surface temperature (LST_D/LST_N) and anthropogenic heat flux (AHF)]. It is found that the intraseasonal variation of DTR at both 8-day and monthly scales in the YRD exhibits regional differences and is modulated by different primary factors across the region. The evident intraseasonal variation of DTR, with a peak in June, in the northern YRD, is largely attributable to nighttime temperatures (SAT_min and LST_N), which in turn are mainly attributable to different LST_N responses to the underlying surface cover changes associated with crop rotation. In contrast, as the YRD metropolitan area (MYRD) is covered by a large proportion of built-up surfaces, and the weather stations there are surrounded by a higher surface thermal environment and AHF, the MYRD has stably higher LST and SAT_min in the whole summer season. Thus, the summer DTR in the MYRD exhibits marginal intraseasonal variations. In the southern YRD, there is also a distinct DTR characteristic, with a maximum in July and minimum in June, since this region is largely covered by forests with constantly high-density vegetation cover, and its DTR variation is mainly forced by SSD, which directly affects SAT_max. The findings reported here have important implications for understanding the influences of human activities on regional climate and environmental change for other regions of the world that experience various external forcings.

Investigating Seasonal Effects of Dominant Driving Factors on Urban Land Surface Temperature in a Snow-Climate City in China

Land surface temperature (LST) is a crucial parameter in surface urban heat island (SUHI) studies. A better understanding of the driving mechanisms, influencing variations in LST dynamics, is required for the sustainable development of a city. This study used Changchun, a city in northeast China, as an example, to investigate the seasonal effects of different dominant driving factors on the spatial patterns of LST. Twelve Landsat 8 images were used to retrieve monthly LST, to characterize the urban thermal environment, and spectral mixture analysis was employed to estimate the effect of the driving factors, and correlation and linear regression analyses were used to explore their relationships. Results indicate that, (1) the spatial pattern of LST has dramatic monthly and seasonal changes. August has the highest mean LST of 38.11 °C, whereas December has the lowest (−19.12 °C). The ranking of SUHI intensity is as follows: summer (4.89 °C) > winter with snow cover (1.94 °C) > spring (1.16 °C) > autumn (0.89 °C) > winter without snow cover (−1.24 °C). (2) The effects of driving factors also have seasonal variations. The proportion of impervious surface area (ISA) in summer (49.01%) is slightly lower than those in spring (56.64%) and autumn (50.85%). Almost half of the area is covered with snow (43.48%) in winter. (3) The dominant factors are quite different for different seasons. LST possesses a positive relationship with ISA for all seasons and has the highest Pearson coefficient for summer (r = 0.89). For winter, the effect of vegetation on LST is not obvious, and snow becomes the dominant driving factor. Despite its small area proportion, water has the strongest cooling effect from spring to autumn, and has a warming effect in winter. (4) Human activities, such as agricultural burning, harvest, and different choices of crop species, could also affect the spatial patterns of LST.