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1.
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.  相似文献   

2.
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.  相似文献   

3.
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4.
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.  相似文献   

5.
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.  相似文献   

6.
Cairo region is characterized by a range of physiographic features, including: flat agricultural lands, bare sandy deserts, highlands, calcareous terrains and urban land use. A time series data-set (300 images) acquired from the Moderate Resolution Imaging Spectroradiometer for the period July 2002–June 2015 were utilized to retrieve the spatial variations in the mean land surface temperature (LST) for the above-mentioned surface features. Results showed that vegetation, topography and surface albedo have negative correlations with LST. Vegetation/LST correlation has the maximum regression coefficient (R2 = 0.68) and albedo/LST has the minimum (R2 = 0.03). Cultivated lands reveal the lowest mean LST (<32 °C), whereas industrial lands exhibit the highest LST (>40 °C) of Cairo region. There is a considerable urban heat island formed at Helwan south of Cairo, where heavy industries are settled. Industrial activities raised the mean LST of the region by at least 4 °C than the surrounding urban lands.  相似文献   

7.
基于遥感的长沙市城市热岛与土地利用/覆盖变化研究   总被引：9，自引：0，他引：9  
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。  相似文献   

8.
Land surface temperature (LST) of Beijing area was retrieved from Landsat TM thermal band data utilizing a radiative transfer equation and the urban heat island (HUI) effects of Beijing and its relationship with land cover and normalized difference vegetation index (NDVI) were discussed. The result of LST showed that the urban LST was evidently higher than the suburban one. The average urban LST was found to 4. 5°C and 9°C higher than the suburban and outer suburban temperature, respectively, which demonstrated the prominent UHI effects in Beijing. Prominent negative correlation between LST and NDVI was found in the urban area, which suggested the low percent vegetation cover in the urban area was the main cause of the urban heat island.  相似文献   

9.
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.  相似文献   

10.
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.  相似文献   

11.
The knowledge of the surface temperature is important to a range of issues and themes in earth sciences central to urban climatology, global environmental change and human-environment interactions. The study analyses land surface temperature (LST) estimation using temporal ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) datasets (day time and night time) over National Capital Territory Delhi using the surface emissivity information at pixel level. The spatial variations of LST over different land use/land cover (LU/LC) at day time and night time were analysed and relationship between the spatial distribution of LU/LC and vegetation density with LST was developed. Minimum noise fraction (MNF) was used for LU/LC classification which gave better accuracy than classification with original bands. The satellite derived emissivity values were found to be in good agreement with literature and field measured values. It was observed that fallow land, waste land/bare soil, commercial/industrial and high dense built-up area have high surface temperature values during day time, compared to those over water bodies, agricultural cropland, and dense vegetation. During night time high surface temperature values are found over high dense built-up, water bodies, commercial/industrial and low dense built-up than over fallow land, dense vegetation and agricultural cropland. It was found that there is a strong negative correlation between surface temperature and NDVI over dense vegetation, sparse vegetation and low dense built-up area while with fraction vegetation cover, it indicates a moderate negative correlation. The results suggest that the methodology is feasible to estimate NDVI, surface emissivity and surface temperature with reasonable accuracy over heterogeneous urban area. The analysis also indicates that the relationship between the spatial distribution of LU/LC and vegetation density is closely related to the development of urban heat islands (UHI).  相似文献   

12.
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。  相似文献   

13.
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.  相似文献   

14.
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.  相似文献   

15.
Forest fires are one of the most important causes of environmental alteration in Mediterranean countries. Discrimination of different degrees of burn severity is critical for improving management of fire-affected areas. This paper aims to evaluate the usefulness of land surface temperature (LST) as potential indicator of burn severity. We used a large convention-dominated wildfire, which occurred on 19–21 September, 2012 in Northwestern Spain. From this area, a 1-year series of six LST images were generated from Landsat 7 Enhanced Thematic Mapper (ETM+) data using a single channel algorithm. Further, the Composite Burn Index (CBI) was measured in 111 field plots to identify the burn severity level (low, moderate, and high). Evaluation of the potential relationship between post-fire LST and ground measured CBI was performed by both correlation analysis and regression models. Correlation coefficients were higher in the immediate post-fire LST images, but decreased during the fall of 2012 and increased again with a second maximum value in summer, 2013. A linear regression model between post-fire LST and CBI allowed us to represent spatially predicted CBI (R-squaredadj > 85%). After performing an analysis of variance (ANOVA) between post-fire LST and CBI, a Fisher's least significant difference test determined that two burn severity levels (low-moderate and high) could be statistically distinguished. The identification of such burn severity levels is sufficient and useful to forest managers. We conclude that summer post-fire LST from moderate resolution satellite data may be considered as a valuable indicator of burn severity for large fires in Mediterranean forest ecosytems.  相似文献   

16.
Indian geostationary satellite Kalpana-1 (K1) offers a potential to capture the diurnal cycle of land surface temperature (LST) through thermal infrared channel (10.5–12.5 μm) observations of the Very High Resolution Radiometer (VHRR) sensor. A study was carried out to retrieve LST by adapting a generalized single-channel (SC) algorithm (Jiménez-Muñoz and Sobrino, 2003) for the VHRR sensor over India. The basis of SC algorithm depends on the concept of Atmospheric Functions (AFs) that are dependent on transmissivity, upwelling and downwelling radiances of the atmosphere. In the present study AFs were computed for the VHRR sensor through the MODTRAN simulations based upon varying atmospheric and surface inputs. The AFs were fitted with the atmospheric columnar water vapour content and a set of coefficients was derived for LST retrieval. The K1-LST derived with the SC algorithm was validated with (a) in situ measurements at two sites located in western parts of India and (b) the MODIS LST products. Comparison of K1-LST with the in situ measurements demonstrated that SC algorithm was successful in capturing the prominent diurnal variations of 283–332 K in the LST at desert and agriculture experimental sites with a rmse of 1.6 K and 2.7 K, respectively. Inter comparison of K1-LST and MODIS LST showed a reasonable agreement between these two retrievals up to LST of 300 K, however a cold bias up to 7.9 K was observed in MODIS LST for higher LST values (310–330 K) over the hot desert region.  相似文献   

17.
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.  相似文献   

18.
Spatio‐temporal prediction and forecasting of land surface temperature (LST) are relevant. However, several factors limit their usage, such as missing pixels, line drops, and cloud cover in satellite images. Being measured close to the Earth's surface, LST is mainly influenced by the land use/land cover (LULC) distribution of the terrain. This article presents a spatio‐temporal interpolation method which semantically models LULC information for the analysis of LST. The proposed spatio‐temporal semantic kriging (ST‐SemK) approach is presented in two variants: non‐separable ST‐SemK (ST‐SemKNSep) and separable ST‐SemK (ST‐SemKSep). Empirical studies have been carried out with derived Landsat 7 ETM+ satellite images of LST for two spatial regions: Kolkata, India and Dallas, Texas, U.S. It has been observed that semantically enhanced spatio‐temporal modeling by ST‐SemK yields more accurate prediction results than spatio‐temporal ordinary kriging and other existing methods.  相似文献   

19.
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 …  相似文献   

20.
Alteration in climatic pattern has resulted to a steady decline in quality of life and the environment, especially in and around urbanized areas. These areas are faced with increasing surface temperature arising mostly from human activities and other natural sources; hence land surface temperature has become an important variable in global climate change studies. In this paper, Landsat TM/ETM imagery acquired between 1997 and 2013 were used to extract ground brightness temperature and land use/land cover change in Kuala Lumpur metropolis. The main objective of this paper is to examine the effectiveness of quantifying UHI effects, in space and time, using remote sensing data and, also, to find the relationship between UHI and land use change. Four land use types (forest, farmland, built-up area and water) were classified from the Landsat images using maximum likelihood classification technique. The result reveals that Greater KL experienced an increase in average temperature from 312.641°K to 321.112°K which was quite eminent with an average gain in surface temperature of 8.4717°K. During the period of investigation (1997–2013), generally high temperature is been experienced mostly in concentrated built-up areas, the less concentrated have a moderate to intermediate temperature. Again, the study also shows that low and intermediate temperature classes loss more spatial extent from 2,246.89 Km2 to 1,164.53 Km2 and 6,102.42 Km2 to 3,013.63 Km2 and a gain of 4,165.963 Km2 and 307.098 Km2 in moderate and high temperature respectively from 1997 to 2013. The results of this study may assist planners, scientists, engineers, demographers and other social scientists concerned about urban heat island to make decisions that will enhance sustainable environmental practices.  相似文献   

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