Satellite-derived subsurface urban heat island

Cooling Effect of Green Spaces on Urban Heat Island in a Chinese Megacity: Increasing Coverage versus Optimizing Spatial Distribution

Enhancing the cooling effectiveness of green spaces (GSs) is crucial for improving urban thermal environments in the context of global warming. Increasing GS coverage and optimizing its spatial distribution individually proved to be effective urban cooling measures. However, their comparative cooling effectiveness and potential interaction remain unclear. Here, using the moving window approach and random forest algorithm, we established a robust model (R2 = 0.89 ± 0.01) to explore the relationship between GS and land surface temperature (LST) in the Chinese megacity of Guangzhou. Subsequently, the response of LST to varying GS coverage and its spatial distribution was simulated, both individually and in combination. The results indicate that GS with higher coverage and more equitable spatial distribution is conducive to urban heat mitigation. Increasing GS coverage was found to lower the city's average LST by up to 4.73 °C, while optimizing GS spatial distribution led to a decrease of 1.06 °C. Meanwhile, a synergistic cooling effect was observed when combining both measures, resulting in additional cooling benefits (0.034-0.341 °C). These findings provide valuable insights into the cooling potential of GS and crucial guidance for urban green planning aimed at heat mitigation in cities.

A Quantitative Study of a Directional Heat Island in Hefei, China Based on Multi-Source Data

Surface urban heat islands (SUHIs) are essential for evaluating urban thermal environments. However, current quantitative studies of SUHIs ignore the thermal radiation directionality (TRD), which directly affects study precision; furthermore, they fail to assess the effects of TRD characteristics at different land-use intensities, on the quantitative studies of SUHIs. To bridge this research gap, this study eliminates the interference of atmospheric attenuation and daily temperature variation factors, in quantifying the TRD based on land surface temperature (LST), from MODIS data and station air temperature data for Hefei (China) from 2010-2020. The influence of TRD on SUHI intensity quantification was evaluated by comparing the TRD under different land-use intensities in Hefei. The results show that: (1) daytime and nighttime directionality can reach up to 4.7 K and 2.6 K, and occur in areas with the highest and medium urban land-use intensity, respectively. (2) There are two significant TRD hotspots for daytime urban surfaces, where the sensor zenith angle is approximately the same as the forenoon solar zenith angle, and where the sensor zenith angle is near its nadir in the afternoon. (3) The TRD can contribute up to 2.0 K to the results of assessing the SUHI intensity based on satellite data, which is approximately 31-44% of the total SUHI in Hefei.

Multi-Time Scale Analysis of Urbanization in Urban Thermal Environment in Major Function-Oriented Zones at Landsat-Scale: A Case Study of Hefei City, China

Urbanization and increasing demand for natural resources and land have affected the urban thermal environment. This is an important hot topic in urban climate research. In this study, we obtained multi-time scale land surface temperatures (LST) at the Landsat scale in Hefei, China, from 2011 to 2020. The evolution of the surface urban heat island (SUHI) was analyzed, and the contribution index (CI), urban thermal field variation index (UTFVI), and landscape pattern were evaluated to analyze the thermal environment mechanism of a major function-oriented zone (MFOZ). In addition, we explored the role and mechanism of different MFOZs in a thermal environment. Our results show that the multi-time scale differences in the SUHI were obvious, with the phenomenon of heat islands being concentrated in the main city zone. There are significant multi-time scale differences in the CI of different landscapes under the MFOZ. The UTFVI analysis of the MFOZ shows that the livability of the cities in the core optimization zone (COZ) and modern urbanization and industrialization cluster development zone (IDZ) is poor. MFOZ planning moderately alleviated the urban thermal environment of the entire study area, especially in the agricultural development zone (ADZ) and ecological conservation zone (ECZ). This study can guide the planning of the MFOZ and guide decision-makers in selecting governance zones when planning policies or dividing the key restoration areas of the thermal environment.

Geothermal Resources and ATES Potential of Mesozoic Reservoirs in the North German Basin

Mesozoic sandstone aquifers in the North German Basin offer significant potential to provide green and sustainable geothermal heat as well as large-scale storage of heat or chill. The determination of geothermal and subsurface heat storage potentials is still afflicted with obstacles due to sparse and partly uncertain subsurface data. Relevant data include the structural and depositional architecture of the underground and the detailed petrophysical properties of the constituting rocks; both are required for a detailed physics-based integrated modeling and a potential assessment of the subsurface. For the present study, we combine recently published basin-wide structural interpretations of depth horizons of the main stratigraphic formations, with temperature data from geological and geostatistical 3D models (i.e., CEBS, GeotIS). Based on available reservoir sandstone facies data, additional well-log-based reservoir lithology identification, and by providing technical boundary conditions, we calculated the geothermal heat in place and the heat storage potential for virtual well doublet systems in Mesozoic reservoirs. This analysis reveals a large potential for both geothermal heating and aquifer thermal energy storage in geologically favorable regions, and in many areas with a high population density or a high heat demand. Given the uncertainties in the input data, the applied methods and the combination of data from different sources are most powerful in identifying promising regions for economically feasible subsurface utilization, and will help decrease exploration risks when combined with detailed geological site analysis beforehand.

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions

Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.

Do industrial parks generate intra-heat island effects in cities? New evidence, quantitative methods, and contributing factors from a spatiotemporal analysis of top steel plants in China

Industrial parks emit large amounts of anthropogenic heat and aggravate the urban heat island effect, which has become a severe environmental problem worldwide. Few studies explored if the warming effect generated by concentrated industrial facilities (i.e., steel plants in this study) produces an intra-heat island effect in urban built-up areas. Sufficient evidence of an industrial heat island (IHI) effect is lacking, and new quantitative methods are urgently needed to address these issues. Therefore, we proposed a new scheme to quantify the warming effect of large, heat-emitting urban objects versus complex surroundings, and the IHI effect was accordingly defined at a finer scale. This study separated the industrial park from other artificial lands and comprehensively estimated the IHI effects' spatiotemporal variation. The IHI intensities were measured based on varied natural and urbanized references, which provided new evidence for the existence of the IHI effect over space and seasons. The land surface temperature (LST) profiles delineated the downward trend in LST variation from inside to surroundings in the IHI cases on both spatial and temporal scales. The time-series analysis revealed that the IHI effects demonstrated more significant disparities regarding the LSTs between the industrial parks and their surrounding backgrounds during warm seasons than in cold seasons. And a more severe IHI effect was observed in spring and summer, and the weakest IHI intensity occurred in winter. Moreover, the IHI intensity is positively associated to the anthropogenic heat, indicating that the industrial activities contribute to the increased LSTs of the industrial park to a great extent. The rationale of the IHI effect can broaden insight for understanding how urban industrial heat sources influence the regional thermal environment, especially at a finer scale.

Impact of simplifications on numerical modelling of the shallow subsurface at city-scale and implications for shallow geothermal potential

Anthropogenic infrastructures in the shallow subsurface, such as heated basements, tunnels or shallow geothermal systems, are known to increase ground temperatures, particularly in urban areas. Numerical modelling helps inform on the extent of thermal influence of such structures, and its potential uses. Realistic modelling of the subsurface is often computationally costly and requires large amounts of data which is often not readily available, necessitating the use of modelling simplifications. This work presents a case-study on the city centre of Cardiff, UK, for which high resolution data is available, and compares modelling results when three key modelling components (namely ground elevation, hydraulic gradient distribution and basement geometry) are implemented either 'realistically', i.e. with high resolution data, or 'simplified', utilising commonly accepted modelling assumptions. Results are presented at a point (local) scale and at a domain (aggregate) scale to investigate the impacts such simplifications have on model outputs for different purposes. Comparison to measured data at individual locations shows that the accuracy of temperature outputs from numerical models is largely insensitive to simplification of the hydraulic gradient distribution implemented, while changes in basement geometry affect accuracy of the mean temperature predicted at a point by as much as 3.5 °C. At the domain scale, ground temperatures within the first 20 m show a notable increase (approximately 1 °C volume-averaged and 0.5 °C surface-averaged), while the average heat flux over the domain is about 0.06 W/m² at 20 m depth. These increased temperatures result in beneficial conditions for shallow geothermal utilisation, producing drilling cost savings of around £1700 per typical household system or about 9% increase in thermal energy potential. Simplifications of basement geometry and (to a lesser degree) the hydraulics can result in an overestimation of these temperatures and therefore over-predict geothermal potential, while the elevation simplification showed little impact.

Spatiotemporal Differentiation of Land Surface Thermal Landscape in Yangtze River Delta Region, China

Advancements in the integrated development of the Yangtze River Delta are changing the structure and function of the surface thermal landscape and triggering a series of ecological and environmental problems. Therefore, examining the spatiotemporal differentiation characteristics and evolution laws of this land surface thermal landscape has great theoretical and practical significance in the context of optimizing functional zoning and realizing the harmonious development of the economy, society and nature. The paper uses the LST (land surface temperature) data retrieved by MODIS (MOD11A2) remote sensing satellites in 2007, 2010, 2013, 2016 and 2019 to extract a land surface thermal rating map of the Yangtze River Delta region, and to analyze the spatiotemporal differentiation in the land surface thermal landscape, combining of the land surface thermal landscape strip profile and thermal landscape pattern indices. The results show that the LST in the Yangtze River Delta region has increased in the past 12 years, the proportion of middle-, sub-high- and high-temperature zones increased by 33.42%, and the high-temperature zone has gradually extended into inland areas. The high-temperature zones in the areas surrounding core cities such as Shanghai, Nanjing, and Hangzhou have expanded. The corridor effect of thermal changes on the surface is obvious. The degree of aggregation in the lower-temperature areas has gradually decreased. The degree of aggregation in the higher-temperature regions has increased. The patch types of thermal landscape pattern increase, and the distribution of landscape area among various types tends to be even. this trend is most significant in optimized development region.

Long-term trends of surface and canopy layer urban heat island intensity in 272 cities in the mainland of China

The canopy layer urban heat island (CLUHI) and surface urban heat island (SUHI) refer to higher canopy layer and land surface temperatures in urban areas than in rural areas, respectively. The long-term trends of CLUHIs are poorly understood at the regional scale. In this study, 1 km resolution air temperature (Ta) data for the 2001-2018 period in the mainland of China were mapped using satellite data and station-based Ta data. Subsequently, the temporal trends of the CLUHI and SUHI intensities (CLUHII and SUHII, respectively) were investigated in 272 cities in the mainland of China. The Ta was estimated with high accuracy, with a root mean square error ranging from 0.370 °C to 0.592 °C. The CLUHII and SUHII increased significantly in over half of the cities in spring and summer, over one-third of the cities in autumn, and over one-fifth of the cities in winter. The trends of the nighttime SUHII were strongly related to the CLUHII calculated using mean and minimum Ta (correlation coefficients ranging from 0.613 to 0.770), whereas the relationships between the trends of the daytime SUHII and CLUHII were relatively weak. Human activities were the major driving forces for the increase in the CLUHII and SUHII. The difference in impervious surfaces between urban and rural areas was significantly correlated with the CLUHII and SUHII in approximately half of the cities. Meteorological factors were significantly correlated with the CLUHII and SUHII in few cities. This study highlights the trends of the significant increase in the CLUHII and SUHII in the mainland of China, which may have negative effects on humans and the environment.

Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives

The surface urban heat island (SUHI), which represents the difference of land surface temperature (LST) in urban relativity to neighboring non-urban surfaces, is usually measured using satellite LST data. Over the last few decades, advancements of remote sensing along with spatial science have considerably increased the number and quality of SUHI studies that form the major body of the urban heat island (UHI) literature. This paper provides a systematic review of satellite-based SUHI studies, from their origin in 1972 to the present. We find an exponentially increasing trend of SUHI research since 2005, with clear preferences for geographic areas, time of day, seasons, research foci, and platforms/sensors. The most frequently studied region and time period of research are China and summer daytime, respectively. Nearly two-thirds of the studies focus on the SUHI/LST variability at a local scale. The Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+)/Thermal Infrared Sensor (TIRS) and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) are the two most commonly-used satellite sensors and account for about 78% of the total publications. We systematically reviewed the main satellite/sensors, methods, key findings, and challenges of the SUHI research. Previous studies confirm that the large spatial (local to global scales) and temporal (diurnal, seasonal, and inter-annual) variations of SUHI are contributed by a variety of factors such as impervious surface area, vegetation cover, landscape structure, albedo, and climate. However, applications of SUHI research are largely impeded by a series of data and methodological limitations. Lastly, we propose key potential directions and opportunities for future efforts. Besides improving the quality and quantity of LST data, more attention should be focused on understudied regions/cities, methods to examine SUHI intensity, inter-annual variability and long-term trends of SUHI, scaling issues of SUHI, the relationship between surface and subsurface UHIs, and the integration of remote sensing with field observations and numeric modeling.

Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan'an City, China

In this study Yan’an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990–2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990–2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon’s diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment.

Linking Surface Urban Heat Islands with Groundwater Temperatures

Urban temperatures are typically, but not necessarily, elevated compared to their rural surroundings. This phenomenon of urban heat islands (UHI) exists both above and below the ground. These zones are coupled through conductive heat transport. However, the precise process is not sufficiently understood. Using satellite-derived land surface temperature and interpolated groundwater temperature measurements, we compare the spatial properties of both kinds of heat islands in four German cities and find correlations of up to 80%. The best correlation is found in older, mature cities such as Cologne and Berlin. However, in 95% of the analyzed areas, groundwater temperatures are higher than land surface temperatures due to additional subsurface heat sources such as buildings and their basements. Local groundwater hot spots under city centers and under industrial areas are not revealed by satellite-derived land surface temperatures. Hence, we propose an estimation method that relates groundwater temperatures to mean annual land-surface temperatures, building density, and elevated basement temperatures. Using this method, we are able to accurately estimate regional groundwater temperatures with a mean absolute error of 0.9 K.