Urban heat island monitoring and analysis using a non-parametric model: A case study of Indianapolis

A procedure for the monitoring an urban heat island (UHI) was developed and tested over a selected location in the Midwestern United States. Nine counties in central Indiana were selected and their UHI patterns were modeled. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) images taken in 2005 were used for the research. The images were sorted based on cloud cover over the study area. The resulting 94 day and night images were used for the modeling. The technique of process convolution was then applied to the images in order to characterize the UHIs. This process helped to characterize the LST data into a continuous surface and the UHI data into a series of Gaussian functions. The diurnal temperature profiles and UHI intensity attributes (minimum, maximum and magnitude) of the characterized images were analyzed for variations. Skin temperatures within any given image varied between 2–15 ^°C and 2–8 ^°C for the day and night images, respectively. The magnitude of the UHI varied from 1–5 ^°C and 1–3 ^°C over the daytime and nighttime images, respectively. Three dimensional (3-D) models of the day and night images were generated and visually explored for patterns through animation. A strong and clearly evident UHI was identified extending north of Marion County well into Hamilton County. This information coincides with the development and expansion of northern Marion County during the past few years in contrast to the southern part. To further explore these results, an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 2004 land use land cover (LULC) dataset was analyzed with respect to the characterized UHI. The areas with maximum heat signatures were found to have a strong correlation with impervious surfaces. The entire process of information extraction was automated in order to facilitate the mining of UHI patterns at a global scale. This research has proved to be promising approach for the modeling and mining of UHIs from large amount of remote sensing images. Furthermore, this research also aids in 3-D diachronic analysis.     

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.     

Object‐oriented tracking of thematic and spatial behaviors of urban heat islands

Modeling thematic and spatial dynamic behaviors of urban heat islands (UHIs) over time is important for understanding the evolution of this phenomenon to mitigate the warming effect in urban areas. Although previous studies conceptualized that a UHI only has a single life cycle with spatial behaviors, a UHI can be detected to appear and disappear several times periodically in terms of thematic and spatial integrated behaviors. Such multiple behaviors have not yet been illustrated with proof or evidence. This study conceptualizes a UHI as an object which has thematic and spatial behaviors simultaneously and proposes several graphs to depict periodic life‐cycle transitions triggered by behaviors. The conceptualized behaviors have been modeled and implemented in an object‐relational database management system and temperature readings collected from numerous weather stations were interpolated as temperature images per hour. The results of this study indicate that the model could track the spatial and thematic evolution of UHIs continuously and reveal their periodical patterns and abnormal cases.     

A simplified urban-extent algorithm to characterize surface urban heat islands on a global scale and examine vegetation control on their spatiotemporal variability

We develop a new algorithm, the simplified urban-extent (SUE) algorithm, to estimate the surface urban heat island (UHI) intensity at a global scale. We implement the SUE algorithm on the Google Earth Engine platform using Moderate Resolution Imaging Spectroradiometer (MODIS) images to calculate the UHI intensity for over 9500 urban clusters using over 15 years of data, making this one of the most comprehensive characterizations of the surface UHI to date. The results from this algorithm are validated against previous multi-city studies to demonstrate the suitability of the method. The dataset created is then filtered for elevation differentials and percentage of urban area and used to estimate the diurnal, monthly, and long-term variability in the surface UHI in different climate zones. The global mean surface UHI intensity is 0.85 °C during daytime and 0.55 °C at night. Cities in arid climate show distinct diurnal and seasonal patterns, with higher surface UHI during nighttime (compared to daytime) and two peaks throughout the year. The diurnal variability in surface UHI is highest for equatorial climate zone (0.88 °C) and lowest for arid zone (0.53 °C). The seasonality is highest in the snow climate zone and lowest for equatorial climate zone. While investigating the change in the surface UHI over a decade and a half, we find a consistent increase in the daytime surface UHI in the urban clusters of the warm temperate climate zone (0.04 °C/decade) and snow climate zone (0.05 °C/decade). Only arid climate zones show a statistically significant increase in the nighttime surface UHI intensity (0.03 °C/decade). Globally, the change is mainly seen during the daytime (0.03 °C/decade). Finally, the importance of vegetation differential between urban and rural areas on the spatiotemporal variability is examined. Vegetation has a strong control on the seasonal variability of the surface UHI and may also partly control the long-term variability. The complete UHI data are available through this website (https://yceo.yale.edu/research/global-surface-uhi-explorer) and allows the user to query the UHI of urban clusters using a simple interface.     

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.     

A preliminary exploration of the cooling effect of tree shade in urban landscapes

Mitigating urban heat island (UHI) effects, especially under climate change, is necessary for the promotion of urban sustainability. Shade is one of the most important functions provided by urban trees for mitigating UHI. However, the cooling effect of tree shade has not been adequately investigated. In this study, we used a simple and straightforward method to quantify the spatial and temporal variation of tree shade and examined its effect on land surface temperature (LST). We used the hillshade function in a geographic information system to quantify the spatiotemporal patterns of tree shade by integrating sun location and tree height. Relationships between shade and LST were then compared in two cities, Tampa, Florida and New York City (NYC), New York. We found that: (1) Hillshade function combining the sun location and tree height can accurately capture the spatial and temporal variation of tree shade; (2) Tree shade, particularly at 07:30, has significant cooling effect on LST in Tampa and NYC; and (3) Shade has a stronger cooling effect in Tampa than in NYC, which is most likely due to the differences in the ratio of tree canopy to impervious surface cover, the spatial arrangements of trees and buildings, and their relative heights. Comparing the cooling effects of tree shade in two cities, this study provides important insights for urban planners for UHI mitigation in different cities.     

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。     

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.     

Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries

This study assesses surface urban heat island (UHI) and its associated surface physical characteristics using remote sensing approaches. TERRA/MODIS images acquired in 2005 in three different seasons were selected to generate land surface tem-perature and surface characteristics for the Changsha-Zhuzhou-Xiangtan metropolitan area in China. The intensity of urban heat is-land effects and its seasonal variations were examined. The result showed that UHI effects were significant both in the summer and the spri...     

Assessing Greenland ice mass loss by means of point-mass modeling: a viable methodology

Greenland ice mass loss is one of the most serious phenomena of present-day global climate change. In this context, both the quantification of overall deglaciation rates and its spatial localization are highly significant. We have thoroughly investigated the technique of point-mass modeling in order to derive mass-balance patterns from GRACE (Gravity Recovery And Climate Experiment) gravimetry. The method infers mass variations on the Earth’s surface from gravitational signals at satellite altitude. In order to solve for point-mass changes, we applied least-squares adjustment. Due to downward continuation, numerical stabilization of the inversion process gains particular significance. We stabilized the ill-posed problem by Tikhonov regularization. Our simulation and real data experiments show that point-mass modeling provides both rational deglaciation rates and high-resolution spatial mass variation patterns.     

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.     

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.     

Quantitative urban climate mapping based on a geographical database: A simulation approach using Hong Kong as a case study

The urban environment has been dramatically changed by artificial constructions. How the modified urban geometry affects the urban climate and therefore human thermal comfort has become a primary concern for urban planners. The present study takes a simulation approach to analyze the influence of urban geometry on the urban climate and maps this climatic understanding from a quantitative perspective. A geographical building database is used to characterize two widely discussed aspects: urban heat island effect (UHI) and wind dynamics. The parameters of the sky view factor (SVF) and the frontal area density (FAD) are simulated using ArcGIS-embedded computer programs to link urban geometry with the UHI and wind dynamic conditions. The simulated results are synergized and classified to evaluate different urban climatic conditions based on thermal comfort consideration. A climatic map is then generated implementing the classification. The climatic map shows reasonable agreement with thermal comfort understanding, as indicated by the biometeorological index of the physiological equivalent temperature (PET) obtained in an earlier study. The proposed climate mapping approach can provide both quantitative and visual evaluation of the urban environment for urban planners with climatic concerns. The map could be used as a decision support tool in planning and policy-making processes. An urban area in Hong Kong is used as a case study.     

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.     

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。     

地表净辐射通量观测、模拟和同化的研究进展

地表净辐射通量是陆—气相互作用水热交换过程中的一个重要物理参量,在全球变化背景下,定量研究地表净辐射通量的时空变化对气候变化研究具有重要意义。本文总结了目前定量研究地表净辐射通量的主要方法——观测、模拟和同化,分析了观测和模拟的优势和不足,提出利用数据同化方法可以弥补观测和模拟的不足,并比较分析了目前流行的同化算法的优缺点,利用不同的同化算法构建的同化系统可以同化不同来源的观测数据对模型进行校准,获取时空上连续一致的高精度地表净辐射的预报值。最后,探讨了同化多源遥感数据改进地表净辐射通量的研究中存在的问题、发展方向及其在全球变化研究中的意义。     

Monitoring Intraurban temperature patterns and associated land cover in phoenix,Arizona using Landsat thermal data

Abstract

This study investigates urban climatologic modification associated with development and changing land use in the relatively arid urban environment of Phoenix, Arizona. An analysis of surface temperatures, as portrayed on Landsat thermal remotely sensed data, were compared to current land use patterns in regions of the rapidly expanding urban landscape. A second focus of this study involved investigation of the surface temperatures of this environment, as extracted from the radiometric data of the Landsat thermal band, to provide insights into the complexities of the relationship to the near‐surface atmospheric temperature, a parameter used extensively in climate change analyses and in models for energy and water demand in this desert region. The near surface air temperature is usually measured approximately two meters above the ground surface. In general, spatial temperature patterns of the metropolitan region were strongly correlated with the presence of open water or biomass which provide an evapotranspirative heat sink.     

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。     

增强形态学建筑物指数应用于高分辨率影像中建筑物提取

分辨影像是城市地物覆盖分析的重要数据基础,本文提出了一种增强的形态学建筑物指数（EMBI）,利用该指数和地物的几何形状约束来完成高分辨率建筑物的自动提取。本方法首先提取城市的不透水层特征,然后通过建立建筑物属性与形态学运算之间的关系得到了EMBI特征图像以增强对建筑物的描述,随后结合形状特征（长宽比,面积等）采用决策树分析的方法完成对建筑物的最终提取。为了验证本文提出的方法,利用华盛顿商业街的航空高分辨高光谱HYDICE影像和武汉洪山区的两幅QuickBird影像进行实验,实验的精度对比反映本文算法比MBI算法能获得更好的建筑物提取结果,其总体精度分别提高了7.31％,6.48％,7.83％,从而表明EMBI算法更可靠。