Urban Surface Temperature Research Articles

Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation

Surface temperature is a key variable in boundary-layer meteorology and is typically acquired by remote observation of emitted thermal radiation. However, the three-dimensional structure of cities complicates matters: uneven solar heating of urban facets produces an “effective anisotropy” of surface thermal emission at the neighbourhood scale. Remotely-sensed urban surface temperature varies with sensor view angle as a consequence. The authors combine a microscale urban surface temperature model with a thermal remote sensing model to predict the effective anisotropy of simplified neighbourhood configurations. The former model provides detailed surface temperature distributions for a range of “urban” forms, and the remote sensing model computes aggregate temperatures for multiple view angles. The combined model’s ability to reproduce observed anisotropy is evaluated against measurements from a neighbourhood in Vancouver, Canada. As in previous modeling studies, anisotropy is underestimated. Addition of moderate coverages of small (sub-facet scale) structure can account for much of the missing anisotropy. Subsequently, over 1900 sensitivity simulations are performed with the model combination, and the dependence of daytime effective thermal anisotropy on diurnal solar path (i.e., latitude and time of day) and blunt neighbourhood form is assessed. The range of effective anisotropy, as well as the maximum difference from nadir-observed brightness temperature, peak for moderate building-height-to-spacing ratios (H/W), and scale with canyon (between-building) area; dispersed high-rise urban forms generate maximum anisotropy. Maximum anisotropy increases with solar elevation and scales with shortwave irradiance. Moreover, it depends linearly on H/W for H/W < 1.25, with a slope that depends on maximum off-nadir sensor angle. Decreasing minimum brightness temperature is primarily responsible for this linear growth of maximum anisotropy. These results allow first order estimation of the minimum effective anisotropy magnitude of urban neighbourhoods as a function of building-height-to-spacing ratio, building plan area density, and shortwave irradiance. Finally, four “local climate zones” are simulated at two latitudes. Removal of neighbourhood street orientation regularity for these zones decreases maximum anisotropy by 3%–31%. Furthermore, thermal and radiative material properties are a weaker predictor of anisotropy than neighbourhood morphology. This study is the first systematic evaluation of effective anisotropy magnitude and causation for urban landscapes.

Impact of Industrial Activities on Land Surface Temperature Using Remote Sensing and GIS Techniques - A Case Study in Jubail, Saudi Arabia

Land Surface temperature (LST) is one of the most important variables for determining the state within the climate system. Thermal infrared (TIR) remote sensing used to monitor air temperature and affecting microclimate in urban areas. TIR remote sensing techniques have been applied for analyzing LST patterns and its relationship with surface characteristics, assessing urban heat island (UHI), and relating LST with surface energy fluxes to characterize landscape properties and processes. In the present study, a remote sensing was combined with a geographic information system (GIS) environment for determine the impact of industrial areas on Surface Temperature using of TIR Remote Sensing through Landsat ETM+ data (band 6.1) and comparing the relationships between urban surface temperature and land cover types in Jubail City in Saudi Arabia. The study showed the increase of urban surface temperature near the industrial area in comparison with suburban areas. The center of the heat island was concentrated above the industrial area and its adjacent urban areas. Iron and steel factories raise the temperature to 80°C which affects air temperature of nearby areas. This effect may extend to the buffer zone area ranging from 500-2000 m

Urban climate change-related effects on extreme heat events in Rostock, Germany

The urban heat island effect poses a challenge in several cities, and may affect human and ecosystem health. It was proven that relatively small urban conglomerations in mid-latitudes, such as the case study region of Rostock, have undergone a considerable effect recently, noticeable particularly in the warm season. Due to climatic changes, these effects are expected to alter in intensity and/or frequency. This was investigated using a model that focuses on interactions between land use and surface temperatures and on specific air conditions in cities. The model enables urban surface temperature differences to be projected with regard to different assumptions of (future or planned) land use/land cover and its specific characteristics. In addition, 99th percentile summer days from the period 1961–1990 and scenario runs from regional climate models (RCMs) were used as an example of extreme heat events. The frequency of occurrence of extreme heat events resembling those occurring in the present day will be up to four (2041–2070) and six (2071–2100) times higher, respectively. Furthermore, the average temperature on defined extreme heat days will rise by 1.6 to 3.4 °C (2041–2070) and 2.2 to 4.4 °C (2071–2100), respectively. The model calculated no significant effects for differences in maximum surface temperatures between land use classes. Some parts of land use change scenarios constructed during scenario workshops in Rostock were integrated into the surface temperature model with regard to climate change adaptation. The results revealed a range of outcomes, from an enlargement of vulnerable areas to the near eradication of climate change-related heat effects in several areas.

Impacts of mesic and xeric urban vegetation on outdoor thermal comfort and microclimate in Phoenix, AZ

Urban vegetation is an effective way in mitigating excessive heat and improving the outdoor thermal environment for residents in cities via evaporative cooling. Different urban vegetation forms (mesic or xeric) alter surface energy and water budgets in different ways, which is further complicated by interactions with buildings and anthropogenic controls. Mesic vegetation such as lawns reduces urban temperatures by evaporative cooling but requires large amounts of water for continuous irrigation. On the other hand, xeric vegetation such as shade trees reduces urban temperatures mainly through shading and has low water demand. The objective of this study is to investigate the impacts of different vegetation forms on microclimate in a hot desert city – Phoenix, AZ. We applied an advanced urban canopy model coupled with a single-column atmospheric model to simulate urban boundary layer dynamics over different landscaping scenarios with different combinations of mesic and xeric vegetation forms. We subsequently compared the urban land surface temperatures, near-surface air temperatures, outdoor thermal comfort in the urban canopy layer, as well as atmospheric dynamics (temperature, humidity) in the overlying boundary layer for a set of different scenarios.

The impact of vegetation on urban microclimate to counterbalance built density in a subtropical changing climate

The purpose of this research is to assess the microscale cooling effects of vegetation in urban environment, especially during daytime, to counterbalance urban warming effects resulting from an increase in built density in a subtropical climate. Considering that Brazil’s climate will be warmer in the coming decades, the paper presents a brief review of planning with high-density and urban greening, having in mind that even low-density land use can contribute to urban heating, depending on the urban occupation pattern. In high-density cities, the most important vegetation effect is to prevent heating in urban canyons, decreasing solar radiation absorption by shading and evapotranspiration. Parametric studies exploring different scenarios of high-density urban blocks and greening have been carried out to investigate different distributions of dense trees to ameliorate urban microclimate using ENVI-met V4 Preview I, previously calibrated with field measurements of local climate and vegetation data. Aiming to benefit urban activities, air, surface and mean radiant temperatures at the pedestrian level are compared among different greening strategies and built densities’ scenarios. Based on the results, two outdoor comfort indexes TEP –Temperature of Equivalent Perception and PET – Physiological Equivalent Temperature were applied to verify the contribution of vegetation to better comfort conditions.

Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ USA

With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems. We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA. We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey. Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures. Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

Spatiotemporal changes of urban impervious surface area and land surface temperature in Beijing from 1990 to 2014

This study examined changes in urban expansion and land surface temperature in Beijing between 1990 and 2014 using multitemporal TM, ETM+, and OLI images, and evaluated the relationship between percent impervious surface area (%ISA) and relative mean annual surface temperature (RMAST). From 1990 to 2001, both internal land transformation and outward expansion were observed. In the central urban area, the high-density urban areas decreased by almost 7 km2, while the moderate- and high-density urban land areas increased by 250 and 90 km2, respectively, outside of the third ring road. From 2001 to 2014, high-density urban areas between the fifth and sixth ring roads experienced the greatest increase by more than 210 km2, and RMAST generally increased with %ISA. During 1990–2001 and 2001–2014, RMAST increased by more than 1.5 K between the south third and fifth ring roads, and %ISA increased by more than 50% outside of the fifth ring road. These trends in urban expansion and RMAST over the last two decades in Beijing can provide useful information for urban planning decisions.

Urban spring phenology in the middle temperate zone of China: dynamics and influence factors.

Urbanization and its resultant urban heat island provide a means for evaluating the impact of climate warming on vegetation phenology. To predict the possible response of vegetation phenology to rise of temperature, it is necessary to investigate factors influencing vegetation phenology in different climate zones. The start of growing season (SOS) in seven cities located in the middle temperate humid, semi-humid, semi-arid, and arid climate zones in China was extracted based on satellite-derived normalized difference vegetation index (NDVI) data. The dynamics of urban SOS from 2000 to 2009 and the correlations between urban SOS and land surface temperatures (LST), precipitation, and sunshine duration, respectively, were analyzed. The results showed that there were no obvious change trends for urban SOS, and the heat island induced by urbanization can make SOS earlier in urban areas than that in adjacent rural areas. And the impact of altitude on SOS was also not negligible in regions with obvious altitude difference between urban and adjacent rural areas. Precipitation and temperature were two main natural factors influencing urban SOS in the middle temperate zone, but their impacts varied with climate zones. Only in Harbin city with lower sunshine duration in spring, sunshine duration had more significant impact than temperature and precipitation. Interference of human activities on urban vegetation was non-negligible, which can lower the dependence of urban SOS on natural climatic factors.

Impact of urbanization on US surface climate

We combine Landsat and MODIS data in a land model to assess the impact of urbanization on US surface climate. For cities built within forests, daytime urban land surface temperature (LST) is much higher than that of vegetated lands. For example, in Washington DC and Atlanta, daytime mean temperature differences between impervious and vegetated lands reach 3.3 and 2.0 °C, respectively. Conversely, for cities built within arid lands, such as Phoenix, urban areas are 2.2 °C cooler than surrounding shrubs. We find that the choice and amount of tree species in urban settings play a commanding role in modulating cities’ LST. At continental and monthly scales, impervious surfaces are 1.9 °C ± 0.6 °C warmer than surroundings during summer and expel 12% of incoming precipitation as surface runoff compared to 3.2% over vegetation. We also show that the carbon lost to urbanization represents 1.8% of the continental total, a striking number considering urbanization occupies only 1.1% of the US land. With a small areal extent, urbanization has significant effects on surface energy, water and carbon budgets and reveals an uneven impact on surface climate that should inform upon policy options for improving urban growth including heat mitigation and carbon sequestration.

Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing

The coupling relationship between urban vegetation and land surface temperature (LST) has been heatedly debated in a variety of environmental studies. This paper studies the urban vegetation information and LST by utilizing a series of remote sensing imagery covering the period from 1990 to 2007. Their coupling relationship is analyzed, in order to provide the basis for ecological planning and environment protection. The results show that the normalized difference vegetation index (NDVI), urban vegetation abundance (UVA) and urban forest abundance (UFA) are negatively correlated with LST, which means that both urban vegetation and urban forest are capable in decreasing LST. The apparent influence of urban vegetation and urban forest on LST varies with the spatial resolution of the imagery, and peaks at the resolutions ranging from 90 m to 120 m.

Exploring the relationships of between land surface temperature, ground coverage ratio and building volume density in an urbanized environment

Abstract. The objective of this study is to explore and compare the relationships between urban land surface temperature (LST), ground coverage ratio (GCR) and building volume density (BVD). Landsat ETM+ data of August 2011 and August 2013 are used to estimate the LST for Wuhan, China, metropolitan area, and maps of GCR and BVD are generated using building census data of 2011 and 2013. Our analysis indicates there is a strong linear relationship between LST and GCR, and when GCR is lower, the linear correlation is more prominent, whereas the relationship between LST and BVD is not straightforward, but seems some underlying pattern. The result suggests GCR and BVD provide complementary metrics to the traditionally applied land use/land cover (LULC) for analysing LST quantitatively for surface urban heat island studies using thermal infrared remote sensing in an urbanized environment. This study is of positive significance to understand today’s urban heat island issues, and contributes to the planning work of urban architectural space.

The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season

The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.

The impact of building density and building height heterogeneity on average urban albedo and street surface temperature

A three-dimensional numerical model (the Model for Urban Surface Temperature – MUST) was used to investigate the impact of urban geometry on average urban albedo and street surface temperature. Satisfactory performance of the model in predicting urban albedo was confirmed. The calculated results for different canyon geometries show that: 1) the medium density urban condition (plan area index λp = 0.44) absorbs the most solar radiation and thus has the lowest urban average albedo; 2) the average urban albedo decreases with increasing building height; and 3) in general, more solar radiation is absorbed as building height differences become much greater. Therefore, the average urban albedo is the least for a medium density city having high-rise buildings with greater building height differences. The relationship between sky-view factor and street surface temperature was also examined. The model predicted a cooler urban street surface temperature with a smaller daily amplitude and earlier occurrence of the daily maximum temperature for a high-rise high density city when compared to a low-rise low density city. Horizontal surfaces in an urban area play an important role in determining the average urban albedo. A linear relationship was found between the average sky-view factor of horizontal surfaces and the average urban albedo.

Urban Surface Temperature Time Series Estimation at the Local Scale by Spatial-Spectral Unmixing of Satellite Observations

The study of urban climate requires frequent and accurate monitoring of land surface temperature (LST), at the local scale. Since currently, no space-borne sensor provides frequent thermal infrared imagery at high spatial resolution, the scientific community has focused on synergistic methods for retrieving LST that can be suitable for urban studies. Synergistic methods that combine the spatial structure of visible and near-infrared observations with the more frequent, but low-resolution surface temperature patterns derived by thermal infrared imagery provide excellent means for obtaining frequent LST estimates at the local scale in cities. In this study, a new approach based on spatial-spectral unmixing techniques was developed for improving the spatial resolution of thermal infrared observations and the subsequent LST estimation. The method was applied to an urban area in Crete, Greece, for the time period of one year. The results were evaluated against independent high-resolution LST datasets and found to be very promising, with RMSE less than 2 K in all cases. The developed approach has therefore a high potential to be operationally used in the near future, exploiting the Copernicus Sentinel (2 and 3) observations, to provide high spatio-temporal resolution LST estimates in cities.

The role of urban green infrastructure in mitigating land surface temperature in Bobo-Dioulasso, Burkina Faso

Green infrastructure in developed countries has been used as a climate change adaptation strategy to lower increased temperatures in cities. But, the use of green infrastructure to provide ecosystem services and increase resilience is largely overlooked in climate change and urban policies in the developing world. This study analyzed the role of urbanization and green infrastructure on urban surface temperatures in Bobo-Dioulasso, Burkina Faso, in sub-Saharan Africa. We use available geospatial data and techniques to spatially and temporally explore urbanization and land surface temperatures (LSTs) over 20 years. The effect of specific green infrastructure areas in the city on LSTs was also analyzed. Results show increased urbanization rates and increased temperature trends across time and space. But, LST in green infrastructure areas was indeed lower than adjacent impervious, urbanized areas. Seasonal phenological differences due to rainfall patterns, available planting space, and site limitations should be accounted for to maximize temperature reduction benefits. We discuss an approach on how study findings and urban and peri-urban agriculture and forestry are being used for policy uptake and formulation in the field of climate change, food security, and urbanization by the municipal government in this city in Burkina Faso.

Planning for cooler cities: A framework to prioritise green infrastructure to mitigate high temperatures in urban landscapes

Warming associated with urban development will be exacerbated in future years by temperature increases due to climate change. The strategic implementation of urban green infrastructure (UGI) e.g. street trees, parks, green roofs and facades can help achieve temperature reductions in urban areas while delivering diverse additional benefits such as pollution reduction and biodiversity habitat. Although the greatest thermal benefits of UGI are achieved in climates with hot, dry summers, there is comparatively little information available for land managers to determine an appropriate strategy for UGI implementation under these climatic conditions. We present a framework for prioritisation and selection of UGI for cooling. The framework is supported by a review of the scientific literature examining the relationships between urban geometry, UGI and temperature mitigation which we used to develop guidelines for UGI implementation that maximises urban surface temperature cooling. We focus particularly on quantifying the cooling benefits of four types of UGI: green open spaces (primarily public parks), shade trees, green roofs, and vertical greening systems (green walls and facades) and demonstrate how the framework can be applied using a case study from Melbourne, Australia.

The Effect of Urban Expansion on Urban Surface Temperature in Shenyang, China: an Analysis with Landsat Imagery

Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images were used to assess the urban expansion dynamics and the corresponding thermal characteristics in Shenyang City, China. Unsupervised classification (ISODATA) and a hierarchy decision tree were applied to eight scenes of the Landsat images to derive the land use/land cover (LULC) around the Shenyang metropolitan region from 1986 to 2007. Landsat TM/ETM+ thermal infrared (TIR) images (band 6) were used to investigate the urban surface thermal patterns by retrieving land surface temperature (LST) using a mono-window algorithm. Results reveal that the built-up area has doubled from 1986 (20.2 %) to 2007 (42.3 %), most of which is converted from croplands around the urban fringe area. The built-up area has close association with the population increase (R 2 = 0.89), the gross domestic production (R 2 = 0.94), and fixed asset investments (R 2 = 0.95). These illustrate the contributions of socioeconomic factors to the rapid urban expansion in Shenyang. Three urban heat island (UHI) indices [i.e., heat effect contribution index (H i ), weighted heat unit index (D 1), and regional weighted heat unit index (D 2)] were used to characterize the urban thermal patterns for removing the phenological effects and to confirm the linkage between UHI and urban expansion. Results show that urban areas have an obvious daytime heating effect (heat source) that is strongly correlated with urban expansion, wherein a higher percentage of an impervious surface is usually associated with a higher surface temperature. Further analyses indicate that urban expansion is fairly correlated to H i ' (R 2 = 0.63) but strongly to D 2 (R 2 = 0.91). Additional research is needed to further quantify the inner urban area to gain a better understanding of UHI resulting from various heat fluxes and urban components.

Understanding the effects of the impervious surfaces pattern on land surface temperature in an urban area

It is well known that urban impervious surface (IS) has a warming effect on urban land surface temperature (LST). However, the influence of an IS’s structure, components, and spatial distribution on LST has rarely been quantitatively studied within strictly urban areas. Using ETM+ remote sensing images from the downtown area of Shanghai, China in 2010, this study characterized and quantified the influence of the IS spatial pattern on LST by selecting the percent cover of each IS cover feature and ten configuration metrics. The IS fraction was estimated by linear spectral mixture analysis (LSMA), and LST was retrieved using a mono-window algorithm. The results indicate that high fraction IS cover features account for the majority of the study area. The high fraction IS cover features are widely distributed and concentrated in groups, which is similar with that of high temperature zones. Both the percent composition and the configuration of IS cover features greatly affect the magnitude of LST, but the percent composition is a more important factor in determining LST than the configuration of those features. The significances and effects of the given configuration variables on LST vary greatly among IS cover features.

The urban heat island of Basel – seen from different perspectives

For decades thermal infrared satellite imagery has been used for climate studies of a variety of geosystems, including urban areas. Additionally, airborne thermal remotely sensed data can provide high resolution information about urban land surface temperatures (LST). Numerous studies make use of these data for the investigation of urban-rural LST differences, commonly known as the urban heat island (UHI) phenomenon. Most of these studies try to analyse the urban heat island by means of the LST distribution. It seems that the UHI is easy to measure, easy to explain, easy to find, and easy to illustrate. Due to this apparent simplicity some people seem to jump into UHI studies without fully understanding the nature of the phenomenon as far as time and spatial scales, physical processes and the numerous methodological pitfalls inherent to UHI studies are concerned. In this study the use of thermal infrared satellite data with respect to the assessment of the surface UHI is investigated. The need to clearly distinguish between different types of UHI is emphasised by recalling the (surface) temperature and the UHI terminology. The pretended simplicity of UHI effects is in reality a result of complex interactions between local radiation conditions, earth surface heat budget, the urban structure and the boundary layer atmosphere. Different methods may provide completely different results. This paper aims to bring more clearness into the subject by assessing the urban heat island of the city of Basel, Switzerland, by the use of thermal data provided by satellites (Landsat TM/ETM+), helicopter-borne infrared camera (InfraTec VarioCAM®) and ground-based measurements of air temperature profiles. It is shown that UHIs vary essentially with the choice of the respective temperature (LST, air temperature) and height (surface level, street/canopy level, roof level).

A systematic approach to model the influence of the type and density of vegetation cover on urban heat using remote sensing

Cities around the world are pursuing increasing green or vegetation cover as a way of managing heat whilst improving beauty, biodiversity and recreational value. However, the pattern of the relationship between vegetation cover and urban temperature can be masked, controlled or exaggerated by vegetation structure, topography and other climate variables. This study examines the relationship between Sydney's urban surface temperature and vegetation cover as defined by two vegetation indices; mixed vegetation cover and tree cover exclusively. The shape of this relationship and relative influence of confounding factors are explored using penalised-likelihood criteria ranked regressions. Overall, increasing tree cover reduces average surface temperatures more dramatically than mixed vegetation cover. This study demonstrates that the extent of influence of greencover on surface temperatures is more accurately defined by identifying and incorporating site specific factors that confound the influence. Best predictor models are significantly improved when the influences of elevation, coastal effects and urban structure are added. Therefore, heat reducing urban greening strategies will be improved if based on local variables and conditions.