Roles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects

The urban heat island (UHI) is increasingly recognized as a serious, worldwide problem because of urbanization and climate change. Urban vegetation is capable of alleviating UHI and improving urban environment by shading together with evapotranspiration. While the impacts of abundance and spatial configuration of vegetation on land surface temperature (LST) have been widely examined, very little attention has been paid to the role of vertical structure of vegetation in regulating LST. In this study, we investigated the relationships between horizontal/vertical structure characteristics of urban tree canopy and LST as well as diurnal divergence in Nanjing City, China, with the help of high resolution vegetation map, Light Detection and Ranging (LiDAR) data and various statistical analysis methods. The results indicated that composition, configuration and vertical structure of tree canopy were all significantly related to both daytime LST and nighttime LST. Tree canopy showed stronger influence on LST during the day than at night. Note that the contribution of composition of tree canopy to explaining spatial heterogeneity of LST, regardless of day and night, was the highest, followed by vertical structure and configuration. Combining composition, configuration and vertical structure of tree canopy can take advantage of their respective advantages, and best explain variation in both daytime LST and nighttime LST. As for the independent importance of factors affecting spatial variation of LST, percent cover of tree canopy (PLAND), mean tree canopy height (TH_Mean), amplitude of tree canopy height (TA) and patch cohesion index (COHESION) were the most influential during the day, while the most important variables were PLAND, maximum height of tree canopy (TH_Max), variance of tree canopy height (TH_SD) and COHESION at night. This research extends our understanding of the impacts of urban trees on the UHI effect from the horizontal to three-dimensional space. In addition, it may offer sustainable and effective strategies for urban designers and planners to cope with increasing temperature.     

Bi-temporal characterization of land surface temperature in relation to impervious surface area,NDVI and NDBI,using a sub-pixel image analysis

As more than 50% of the human population are situated in cities of the world, urbanization has become an important contributor to global warming due to remarkable urban heat island (UHI) effect. UHI effect has been linked to the regional climate, environment, and socio-economic development. In this study, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery, respectively acquired in 1989 and 2001, were utilized to assess urban area thermal characteristics in Fuzhou, the capital city of Fujian province in south-eastern China. As a key indicator for the assessment of urban environments, sub-pixel impervious surface area (ISA) was mapped to quantitatively determine urban land-use extents and urban surface thermal patterns. In order to accurately estimate urban surface types, high-resolution imagery was utilized to generate the proportion of impervious surface areas. Urban thermal characteristics was further analysed by investigating the relationships between the land surface temperature (LST), percent impervious surface area, and two indices, the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results show that correlations between NDVI and LST are rather weak, but there is a strong positive correlation between percent ISA, NDBI and LST. This suggests that percent ISA, combined with LST, and NDBI, can quantitatively describe the spatial distribution and temporal variation of urban thermal patterns and associated land-use/land-cover (LULC) conditions.     

Assessment with satellite data of the urban heat island effects in Asian mega cities

This study focuses on using remote sensing for comparative assessment of surface urban heat island (UHI) in 18 mega cities in both temperate and tropical climate regions. Least-clouded day- and night-scenes of TERRA/MODIS acquired between 2001 and 2003 were selected to generate land-surface temperature (LST) maps. Spatial patterns of UHIs for each city were examined over its diurnal cycle and seasonal variations. A Gaussian approximation was applied in order to quantify spatial extents and magnitude of individual UHIs for inter-city comparison. To reveal relationship of UHIs with surface properties, UHI patterns were analyzed in association with urban vegetation covers and surface energy fluxes derived from high-resolution Landsat ETM+ data. This study provides a generalized picture on the UHI phenomena in the Asian region and the findings can be used to guide further study integrating satellite high-resolution thermal data with land-surface modeling and meso-scale climatic modeling in order to understand impacts of urbanization on local climate in Asia.     

Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation

The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding rural areas. Mitigation of the UHI effects via the configuration of green spaces and sustainable design of urban environments has become an issue of increasing concern under changing climate. In this paper, the effects of the composition and configuration of green space on land surface temperatures (LST) were explored using landscape metrics including percentage of landscape (PLAND), edge density (ED) and patch density (PD). An oasis city of Aksu in Northwestern China was used as a case study. The metrics were calculated by moving window method based on a green space map derived from Landsat Thematic Mapper (TM) imagery, and LST data were retrieved from Landsat TM thermal band. A normalized mutual information measure was employed to investigate the relationship between LST and the spatial pattern of green space. The results showed that while the PLAND is the most important variable that elicits LST dynamics, spatial configuration of green space also has significant effect on LST. Though, the highest normalized mutual information measure was with the PLAND (0.71), it was found that the ED and PD combination is the most deterministic factors of LST than the unique effects of a single variable or the joint effects of PLAND and PD or PLAND and ED. Normalized mutual information measure estimations between LST and PLAND and ED, PLAND and PD and ED and PD were 0.7679, 0.7650 and 0.7832, respectively. A combination of the three factors PLAND, PD and ED explained much of the variance of LST with a normalized mutual information measure of 0.8694. Results from this study can expand our understanding of the relationship between LST and street trees and vegetation, and provide insights for sustainable urban planning and management under changing climate.     

Area Delineation and Spatial-Temporal Dynamics of Urban Heat Island in Lanzhou City,China Using Remote Sensing Imagery

One of the key impacts of rapid urbanization on the environment is the effect of urban heat island (UHI). By using the Landsat TM/ETM+ thermal infrared remote sensing data of 1993, 2001 and 2011 to retrieve the land surface temperature (LST) of Lanzhou City, and by adopting object-oriented fractal net evolution approach (FNEA) to make image segmentation of the LST, the UHI elements were extracted. The G* index spatial aggregation analysis was made to calculate the urban heat island ratio index (URI), and the landscape metrics were used to quantify the changes of the spatial pattern of the UHI from the aspects of quantity, shape and structure. The impervious surface distribution and vegetation coverage were extracted by a constrained linear spectral mixture model to explore the relationships of the impervious surface distribution and vegetation coverage with the UHI. The information of urban built-up area was extracted by using UBI (NDBI-NDVI) index, and the effects of urban expansion on city thermal environment were quantitatively analyzed, with the URI and the LST grade maps built. In recent 20 years, the UHI effect in Lanzhou City was strengthened, with the URI increased by 1.4 times. The urban expansion had a spatiotemporal consistency with the UHI expansion. The patch number and density of the UHI landscape were increased, the patch shape and the whole landscape tended to be complex, the landscape became more fragmented, and the landscape connectivity was decreased. The heat island strength had a negative linear correlation with the urban vegetation coverage, and a positive logarithmic correlation with the urban impervious surface coverage.     

Land surface temperature and emissivity estimation for Urban Heat Island assessment using medium- and low-resolution space-borne sensors: A review

The Urban Heat Island (UHI) phenomenon, a typical characteristic on urban landscapes, has been recognised as a key driver to the transformation of local climate. Reliable retrieval of urban and intra-urban thermal characteristics using satellite thermal data depends on accurate removal of the effects of atmospheric attenuations, angular and land surface emissivity. Several techniques have been proposed to retrieve land surface temperature (LST) from coarse resolution sensors. Medium spatial resolution sensors like the Advanced Space-borne Thermal Emission and Reflection Radiometer and the Landsat series offer a viable option for assessing LST within urban landscapes. This paper reviews the theoretical background of LST estimates from the thermal infrared part of the electromagnetic spectrum, LST retrieval algorithms applicable to each of the commonly used medium-resolution sensors and required variables for each algorithm. The paper also highlights LST validation techniques and concludes by stipulating the requirements for LST temporal and spatial configuration.     

Dynamics and controls of urban heat sink and island phenomena in a desert city: Development of a local climate zone scheme using remotely-sensed inputs

This study aims to determine the dynamics and controls of Surface Urban Heat Sinks (SUHS) and Surface Urban Heat Islands (SUHI) in desert cities, using Dubai as a case study. A Local Climate Zone (LCZ) schema was developed to subdivide the city into different zones based on similarities in land cover and urban geometry. Proximity to the Gulf Coast was also determined for each LCZ. The LCZs were then used to sample seasonal and daily imagery from the MODIS thermal sensor to determine Land Surface Temperature (LST) variations relative to desert sand. Canonical correlation techniques were then applied to determine which factors explained the variability between urban and desert LST.Our results indicate that the daytime SUHS effect is greatest during the summer months (typically ∼3.0 °C) with the strongest cooling effects in open high-rise zones of the city. In contrast, the night-time SUHI effect is greatest during the winter months (typically ∼3.5 °C) with the strongest warming effects in compact mid-rise zones of the city. Proximity to the Arabian Gulf had the largest influence on both SUHS and SUHI phenomena, promoting daytime cooling in the summer months and night-time warming in the winter months. However, other parameters associated with the urban environment such as building height had an influence on daytime cooling, with larger buildings promoting shade and variations in airflow. Likewise, other parameters such as sky view factor contributed to night-time warming, with higher temperatures associated with limited views of the sky.     

Phenology of trees and urbanization: a comparative study between New York City and Ithaca,New York

The ‘global warming’ effect has been found to influence vegetation phenological processes. Heat island phenomenon associated with urbanized area presents a unique place to investigate its local warming effects. This study compares the date of budburst (DOBB) of street London plane trees (Platanus × acerifolia) between highly urbanized New York City (NYC) and relatively less urbanized Ithaca, New York in 2007 and 2008. It also linked DOBB with land surface temperature and fractional vegetation cover derived from Landsat satellite images. The DOBB in NYC and Ithaca differed significantly as budburst occurred 3 and 4 days earlier in NYC than in Ithaca in 2007 and 2008, respectively. The intensity of the heat island effect and its effect on tree phenology were greater in NYC. Results show that DOBB can be explained by temperature, and findings could be extrapolated to make inferences on the potential impact of global warming on vegetation communities.     

基于遥感的长沙市城市热岛与土地利用/覆盖变化研究

基于多时相Landsat TM/ETM+影像,首先计算长沙市地表亮度温度,然后利用NDVI(归一化植被指数)、MNDWI(改进 的归一化水体指数)、NDBI(归一化建筑指数)和NDBaI(归一化裸土指数)4个指数,采用决策树分类方法对长沙市影像进行 土地利用/覆盖分类。在此基础上,对长沙市城市热岛的空间分布特征、时空演变特征以及城市热岛与土地利用/覆盖变化和各种影 响因子之间的关系进行研究。结果表明,随着长沙市城区范围的不断扩张,城市热岛范围也不断增大; 土地利用/覆盖类型的变化 会改变地表温度的空间分布,城市用地和裸地是城市热岛强度的主要贡献因素,水体和林地具有较好的降温作用。地表温度与4种 归一化指数的回归分析表明,它们之间存在明显的相关性,不同土地利用/覆盖类型的地表温度存在较大差异。     

城市热岛空间格局及其变化的图形信息特征分析

热岛效应是城市化进程中产生的特有环境问题。基于Landsat TM/ETM+（1989、2001、2007、2013年）遥感影像完成哈尔滨地面亮温定量反演、标准化和等级划分等处理,并分析城市热岛空间分布特征和时空演变规律。基于地学信息图谱理论,定量分析24 a间热岛效应图谱信息变化特征,探究城市热岛格局的时空演变进程和形成机制,揭示城市化进程与热岛效应之间的响应关系。结果表明,随着哈尔滨城市化进程加速,4级热岛效应呈递增趋势,面积比例分别为4.36%、5.69%、6.29%和7.12%,主要分布在道外区和铁路沿线地带;植被和水体区域的地面温度较低,其边缘温度更低;反复变化型面积最大,后期变化型面积最小,面积比例分别为33.30%和7.30%。地学信息图谱分析可为城市热岛效应随城市化演变趋势提供准确、丰富的信息,对全面分析城市热岛的形成和发展具有重要的意义。     

Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan,China

Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and other remote sensing satellites were compared and analyzed to validate the performance of the HJ-1B. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three landscape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decreases from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment.     

Spatially non-stationary effect of underlying driving factors on surface urban heat islands in global major cities

Urban heat island (UHI) effect is among the most typical characteristics of urban climate. The analysis of surface UHI (SUHI) mechanisms has received the most extensive attention in the world. Here, we quantify the diurnal and seasonal SUHI intensity (SUHII) in global 419 major cities during the period 2003-2013. A geographically weighted regression (GWR) was established to assess the relationships between SUHII and several driving factors, and it further was compared to the ordinary least square (OLS) and stepwise multiple linear regression (SMLR) models. We show that GWR model has higher determination coefficient (R²) than OLS and SMLR models (Time: summer daytime, summer night, winter daytime and winter nighttime; GWR: 0.805, 0.458, 0.699 and 0.582; OLS: 0.732, 0.347, 0.473 and 0.320; SMLR: 0.732, 0.341, 0.468 and 0.316), indicating the spatially non-stationarity in the relationships. During the day, both vegetation activity and tree cover fraction have stronger cooling effect on SUHI in the summer of Asia. At night, there are stronger albedo effects on SUHI in the summer of Eastern Asia and Western North America and in the winter of Eastern Asia. Furthermore, temperature has stronger effect on daytime SUHI in Africa, Europe and South America in summer, and precipitation has stronger effect on nighttime SUHI in Africa and Europe in summer. Our results emphasize the spatial variation of the relationships between SUHII and relevant driving factors across global major cities, further indicating that the spatially non-stationary effect of driving factors on SUHII need to be considered in the future.     

Characterizing bi-temporal patterns of land surface temperature using landscape metrics based on sub-pixel classifications from Landsat TM/ETM+

Landscape patterns in a region have different sizes, shapes and spatial arrangements, which contribute to the spatial heterogeneity of the landscape and are linked to the distinct behavior of thermal environments. There is a lack of research generating landscape metrics from discretized percent impervious surface area data (ISA), which can be used as an indicator of urban spatial structure and level of development, and quantitatively characterizing the spatial patterns of landscapes and land surface temperatures (LST). In this study, linear spectral mixture analysis (LSMA) is used to derive sub-pixel ISA. Continuous fractional cover thresholds are used to discretize percent ISA into different categories related to urban land cover patterns. Landscape metrics are calculated based on different ISA categories and used to quantify urban landscape patterns and LST configurations. The characteristics of LST and percent ISA are quantified by landscape metrics such as indices of patch density, aggregation, connectedness, shape and shape complexity. The urban thermal intensity is also analyzed based on percent ISA. The results indicate that landscape metrics are sensitive to the variation of pixel values of fractional ISA, and the integration of LST, LSMA. Landscape metrics provide a quantitative method for describing the spatial distribution and seasonal variation in urban thermal patterns in response to associated urban land cover patterns.     

光谱指数趋势面的城市地表温度降尺度转换

针对城市及周边区域建造区和自然地表交织分布的特点,探讨了利用归一化植被指数(NDVI)和归一化建造指数(NDBI)构造趋势面的地表温度(LST)降尺度方法,以北京市市区及周边较平坦区域为例实现了LST自960 m向120 m的降尺度转换。分析了LST空间分布特征及NDVI、NDBI对地物的指示性特征;以北京市四至六环为界分析NDVI、NDBI趋势面对地表温度的拟合程度及各自的适用区域;在120 m、240 m、480 m和960 m 4个尺度上评价了NDVI、NDBI和NDVI+NDBI趋势面对LST的拟合程度和趋势面转换函数的尺度效应;对NDVI、NDBI和NDVI NDBI等3种方法的降尺度结果分覆盖类型、分区域对比评价。实验结果表明结合两种光谱指数的NDVI NDBI方法降尺度转换精度有所改善,改善程度取决于地表覆盖类型组合。     

成都平原中等城市的热岛效应动态特征对比研究

城市热岛效应是当前城市气候与城市生态环境的研究热点。研究使用Landsat TM/ETM+遥感影像获取城市建成区信息和反演亮度温度,进而评价成都平原6个中等城市的热岛强度、热岛发育程度以及空间动态演变特征。研究发现,在"评价初期→评价中期→评价末期"过程中,成都平原6个中等城市的热岛强度前期增强、后期减弱;城市旧城区的热岛规模普遍减小,这说明,旧城区热环境有所改善,而城市扩展区的热岛规模普遍增大,是因城市扩展明显改变了地表自然环境,导致热岛效应出现,这与城市化进程的内在规律基本一致。绵阳等城市的研究成果表明,即使城市规模扩大,只要城市规划科学合理,并注重城市生态环境的保护,城市热岛效应也能得到有效缓解。     

Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST)

Land cover changes associated with urbanisation modify microclimate, leading to urban heat islands, whereby cities are warmer than the surrounding countryside. Understanding the factors causing this phenomenon could help urban areas adapt to climate change and improve living conditions of inhabitants. In this study, land surface temperatures (LST) of Aarhus, a city in the high latitudes, are estimated from the reflectance of a thermal band (TIRS1; Band 10; 10.60–11.19 μm) of Landsat 8 on five dates in the summer months (one in 2015, and four in 2018). Spectral indices, modelled on the normalised difference vegetation index (NDVI), using all combinations of the first seven bands of Landsat 8 are calculated and their relationships with LST, analysed. Land cover characteristics, in terms of the percentages of tree cover, building cover and overall vegetation cover are estimated from airborne LiDAR data, building footprints and 4-band aerial imagery, respectively. The correlations between LST, the spectral indices and land cover are estimated.The difference in mean temperature between the rural and urban parts of Aarhus is up to 3.96 °C, while the difference between the warmer and colder zones (based on the mean and SD of LST) is up to 13.26 °C. The spectral index using the near infrared band (NIR; Band 5; 0.85-0.88 μm) and a short-wave infrared band (SWIR2; Band 7; 2.11–2.29 μm) has the strongest correlations (r: 0.62 to 0.89) with LST for the whole study area. This index is the inverse of normalised burn ratio (NBR), which has been used for mapping burnt areas. Spectral indices using different combinations of the infrared bands have stronger correlations with LST than the more widely used vegetation indices such as NDVI. The percentage of tree cover has a higher negative correlation (Pearson’s r: -0.68 to -0.75) with LST than overall vegetation cover (r: -0.45 to -0.63). Tree cover and building cover (r: 0.53 to 0.71) together explain up to 68 % of the variation in LST. Modification of tree and building cover may therefore have the potential to regulate urban LST.     

北京地区陆表温度空间分布特征

利用北京地区1999年的Landsat7/ETM+热红外波段数据反演陆表温度,用热岛比率指数表征陆表温度的空间分布差异。通过计算北京市城区及辖区共15个区、五环路内各环线间区域、以及以故宫为中心的8个方向剖线的缓冲区的热岛比率指数,定量分析其陆表温度空间分布特征。结果表明:北京地区陆表温度空间分布存在明显的差异。总体上城区整体处于次高温区,局部表现为高温区,并且在城区以外的辖区出现了多热岛中心分布的特征;对城区及辖区热岛比率指数分析发现,热岛比率指数最大的区域并不是城区,而是顺义区,为0.6210,其平均地表温度在各区域中也最高,为38.08℃。城区大部分处于次高温区中,热岛比率指数为0.6118,平均陆表温度为37.18℃;五环内区域的平均陆表温度为36.97℃,五环以外区域的平均陆表温度35.18℃;对于五环内各环线间的区域,四环至三环间的区域热岛比率指数最高,为0.6327,其平均地表温度为37.48℃;就8个方向剖线的缓冲区分析总体来看,东向和南向热岛比率指数较高,而西向和北向较低。     

城市热岛的遥感研究进展

系统总结了应用遥感技术开展城市热岛研究的数据、方法与成果。对国内外学者有关城市热岛的形态结构、过程变化及成因分析等方面的研究内容进行了较为详细的评述，在此基础上，对未来城市热岛遥感研究的方向进行了展望。     

On Urban Heat Island of Beijng Based on Landsat TM Data

IntroductionThe scientists have begun to retrieve land sur-face temperature (LST) fromsatellite data sincethe launch of TIROS-Ⅱin 60s of the 20th centu-ry . With the development of remote sensingtechnology and its application, more and moreLST retrieval …     

Spatial and Temporal Dynamics of Urban Heat Island and Their Relationship with Land Cover Changes in Urbanization Process: A Case Study in Suzhou, China

One of the significant environmental consequences of urbanization is the urban heat island (UHI). In this paper, Landsat TM images of 1986 and 2004 were utilized to study the spatial and temporal variations of heat island and their relationships with land cover changes in Suzhou, a Chinese city which experienced rapid urbanization in past decades. Land cover classifications were derived to quantify urban expansions and brightness temperatures were computed from the TM thermal data to express the urban thermal environment. The spatial distributions of surface temperature indicated that heat islands had been largely broadened and showed good agreements with urban expansion. Temperature statistics of main land cover types showed that built-up and bare land had higher surface temperatures than natural land covers, implying the warming effect caused by the urbanization with natural landscape being replaced by urban areas. In addition, the spatial detail distributions of surface temperature were compared with the distribution of land cover by means of GIS buffer analysis. Results show remarkable show good correspondence between heat island variations with urban area expansions.