Urban Heat Island Ratio Index Research Articles

Differences in the evolution of urban and rural surface thermal environment and their responses to urban renewal in Shanghai, China.

The rapid and extensive urbanization has profound impacts on urban thermal environment. It is of great significance to comprehensively understand how urbanization affects the evolution of urban thermal environment for urban ecological safety, environmental quality, and residents' health. Based on daily land surface temperature (LST) products of MODIS Aqua satellite in the summer of 2002-2020, we investigated the evolution of urban-rural differences in surface summer thermal environment in Shanghai during 2002-2020 and its response to urban spatial renewal. We used normalized land surface temperature (NLST) and urban heat island ratio index (URI) as the surface thermal environment measurement indicators, by combining vegetation index and impervious surface cove-rage, and used M-K trend analysis and interpretation analysis. The results showed that the linear growth rate of LST in Shanghai was 0.09 ℃·a-1 (2002-2020), and that URI showed a trend of first increasing (2002-2010) and then decreasing (2010-2020). The mean summer LST was generally in the order of urban core>suburban>rural. 1.6% of the areas showed a significant cooling trend, of which 54.0% were distributed in the urban core. 39.5% of the regions showed a significant warming trend, of which 77.6% were distributed in the suburban. In general, there were concentrated significant cooling areas in the highly urbanized urban areas, while there was a significant warming trend in the suburban. The transformation from urban expansion to urban renewal was the main reason for the emergence of concentrated and significant cooling areas in the urban. Nearly 20% of the urban area showed a signi-ficant increase of vegetation coverage. Urban renewal projects such as gathering vegetation or dispersing impervious surfaces in highly urbanized areas are important ways to effectively improve the urban residential thermal environment.

Assessment of the Urban Expansion and Its Impact on the Eco-Environment—A Case Study of Hefei Municipal Area

With the advancement of urbanization, the ecological environmental changes caused by the continuous expansion of cities have become a major concern. Thus, this study is based on a remote sensing image map of Hefei city from 1984 to 2020, which is now in the process of rapid development. We constructed an index system with ecological land, ecosystem service value, ecological environment quality, urban land expansion coefficient, urban heat island rate index, total pollutant emissions, ecological pressure, and ecological deficit, and then evaluated the ecological environment of Hefei city with the help of the entropy weight comprehensive evaluation method. The results show that (1) in the positive evaluation index, the ecological land area was reduced to half of the original area, the ecological service value was reduced by 0.37 times its initial value, and the eco-environmental index was <35 and still decreasing. (2) In the negative evaluation index, the urban heat island ratio index increased by nearly 10 times its initial value, the total emission of various pollutants increased by 6.64 times its initial value, the ecological deficit increased year by year after 1999, and the ecological pressure in 2020 increased to 3 times that in 1999. (3) The overall environmental score of the Hefei urban area has decreased by 48.6 times its initial value. The values of positive evaluation indexes are decreasing, whereas the values of negative evaluation indexes are increasing, and both these items are moving backward, leading to the decrease in the comprehensive ecological environmental score. It can be noticed that the urban expansion of Hefei has had a severe impact on the ecological environment, resulting in the continuous reduction in the ecological land area, a serious urban heat island effect, and continuous weakening of regional ecological service functions. The study results can be used for reference in alleviating the impacts of urban expansion on the environment, promoting the optimization of the urban landscape and the sustainable development of the social economy and environment.

Spatial and temporal analysis of the increasing effects of large-scale infrastructure construction on the surface urban heat island

With the rapid development of China's economy and the continuous improvement of people's living standards, large-scale infrastructure constructions (LSICs) are also increasing rapidly. LSICs with impervious surfaces have increasingly resulted in replacing natural landscapes, altering surface radiation, thermal properties, and humidity in urban areas. To study the environmental thermal changes of Beijing Daxing International Airport before and after its construction and operation, four Landsat-8 images (from the year of 2014, 2017, 2019, and 2021) were used to calculate the land surface temperature (LST). Then the LST values of four images covering the study area were compared and analyzed using the urban heat island ratio index (URI). Results show that the URI value of this area increased from 0.120 of 2014 to 0.185 of 2017 after the construction of Daxing Airport, indicating that the urban surface heat island effect in this area greatly increased. Additionally, the URI value of this area increased from 0.153 of 2019 to 0.206 of 2021 after the operation of Daxing Airport, indicating that the surface urban heat island effect in this area further increased. Therefore, we infer that this effect is closely related to airport construction and operation. Afterward, the random forest classification algorithm is used to classify land types based on pixels, and then the relationship between URI and land classification types was discussed. It is found that before the construction of Daxing Airport, both dark buildings and bare land contribute significantly to the thermal environment of the airport. After the completion of Daxing Airport, the contribution model was changed to high-reflectivity buildings and bright soil. The thermal pollution generated by the airport has a greater impact on the ground objects within the range of 7.5 km, and a relatively smaller impact on the ground objects outside the range of 9.5 km. Our results can provide a valuable reference for the study of the thermal environment caused by human activities.

A New Approach to Investigate the Spatially Heterogeneous in the Cooling Effects of Landscape Pattern

Although many prior studies have found that landscape pattern significantly affects urban heat environment globally, the spatially heterogeneous in the cooling effects of landscape pattern remains poorly understood. In addition, most previous studies have only employed a single landscape metric separately, without holistic consideration of the composition and configuration of different landscapes. Taking one of the new “stove” cities in China-Fuzhou City, Fujian Province, as an example, we employed the principal component analysis (PCA) to synthesize a landscape pattern comprehensive index (LPCI) composed of the four common landscape metrics (i.e., aggregation index, AI; mean patch area, Area mn; largest patch index, LPI; and percentage of landscape, PLAND) of the three major land surfaces (i.e., water, vegetation, and impervious surface). Then, the local model (geographically weighted regression, GWR) was proposed to explore the spatially heterogeneous in the cooling effects of urban landscape. The results revealed that: (1) from 2000 to 2016, the land surface temperature (LST) increased by 4.262 °C, and the proportion of the urban heat island region showed an upward trend, while the urban-heat-island ratio index (URI) increased from 0.328 to 0.457; (2) the cooling effect of different land surfaces ranked from high to low was: water (29.69 °C), vegetation (38.56 °C), and impervious surface (41.82 °C); (3) compared with vegetation patches, water patches had a more obvious cooling effect on the surrounding environment, with the cooling distance within 60–90 m for the vegetation, while reaching 120–150 m for water body; (4) the proposed LPCI could explain more than 80% of the information for all of the landscape metrics for all of the landscape types, and presented a patchy distribution in the study area; (5) the GWR results revealed that the cooling effect of the landscape pattern varied spatially across the study area, indicating that the configuration of landscapes is more important in an urban center in alleviating urban heat environment than in an urban fringe area. The proposed approach provides a new understanding of the interaction between the landscape patterns and urban heat environments, providing a strong basis for landscape planning strategies for specific local sites.

Impact of spatiotemporal land-use and land-cover changes on surface urban heat islands in a semiarid region using Landsat data

ABSTRACT Many factors are involved in urban heat island development, such as lack of green spaces, improper choice of building materials, densification, and other human activities. The aim of this research was to quantify the effects of land-use/land-cover (LU/LC) changes on urban land surface temperature (LST) during a 25-year period (1993–2018) for the semiarid Shiraz City in southern Iran using Landsat data (TM, ETM+, and OLI/TIRS) and machine learning algorithms. Five main LU/LC classes, such as orchard, vegetation, bare surface, asphalt cover, and built-up areas, were identified using a support vector machine algorithm. Landsat images were used to retrieve normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). The results showed that the mean LST over the entire study domain increased considerably between 1993 and 2018, due to urbanization, decrease of green areas, and increasing industrial areas. Built-up areas increased considerably by 25.8% from 80 to 100.6 km2 between 1993 and 2018, while vegetation cover decreased dramatically by 69.3%. Mean LST increased from 38.4 to 40.2°C during the 25-year period with a significant increase of 3.9°C between 2013 and 2018. In addition, the Urban heat island Ratio Index (URI) displayed a substantial upward trend during the 25-year period.

Modelling the intensity of surface urban heat island and predicting the emerging patterns: Landsat multi-temporal images and Tehran as case study

ABSTRACT The increase of Land Surface Temperature (LST) and the formation of heat island in megacities have become an emerging environmental concern. The main objective of this study is to predict the intensity of Tehran’s heat island in the year 2033 based on historical changes of land cover and LST. For this purpose, Landsat satellite images were integrated with meteorological stations’ measurements from 1985 to 2017. The Cellular Automata-Markov (CA-Markov) and Artificial Neural Network (ANN) models were used to predict the land cover changes and to the modelling of the Surface Urban Heat Island Intensity (SUHII), Surface Urban Heat Island Ratio Index (SUHRI) was used. Subsequently, using statistical analysis of the effect of historical land cover changes on LST variations, SUHII for 2033 was predicted. Our findings show that within this period, the built-up lands increased significantly from 39% in 1985 to 65% in 2017. The intensity of heat island increased with an increase in the value of SUHII from 0.02 to 0.19. Our predictive analysis reveals that the intensity of the Tehran’s heat island will increase to 0.32 by 2033. Our conclusions draw attentions to the increasing LST now and in the future in Tehran so that urban planners and local authorities take adequate actions for controlling its environmental impacts.

The Impacts of the Expansion of Urban Impervious Surfaces on Urban Heat Islands in a Coastal City in China

The effect of the expansion of urban impervious surfaces on surface urban heat islands (UHIs) has attracted research attention due to its relevance for studies of local climatic change and habitat comfort. In this study, using five satellite images of Xiamen city, Southeast China (four images from the Landsat 5 Thematic Mapper (TM) and one from the Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS)) acquired in summer between 1989 and 2016, together with spatial statistical methods, the changes in impervious surface area (ISA) were investigated, the spatiotemporal variation of the intensity of urban heat islands (UHIs) was explored, and the relationships between land surface temperature (LST) and the percentage of impervious surface area (ISA%), the normalized difference vegetation index (NDVI), and fractional vegetation coverage (Fv) were investigated. The results showed the following: (1) According to the biophysical composition index (BCI) combined with an ISA post-processing method, Xiamen has witnessed a substantial increase in ISA, showing a 6.1-fold increase from 1989 to 2016. The direction of ISA expansion was consistent throughout the study period in each of the five districts of Xiamen; (2) a bay-like UHI form is observed in the study area, which is remarkably distinct from the central-radial UHI form observed in previous studies of other cities; (3) the extent of UHIs in Xiamen greatly increased between 1989 and 2016, experiencing a 4.7-fold increase in UHI areas during this time. However, during the same period, the urban heat island ratio index (URI)—that is, the ratio of UHI area to ISA—decreased slightly. The UHI area decreased in some urban parts of Xiamen due to a significant increase in vegetation coverage, urban village redevelopment, and the construction of new parks; (4) sea ports and heavy industrial zones are the greatest contributor to surface UHI, followed by urban villages; and (5) LST is strongly positively correlated with ISA%. Each 10% increase in ISA was associated with an increase in summer LST of 0.41 to 0.91 K, which compares well with the results of related studies. This study presents valuable information for the development of regional urban planning strategies to mitigate the effects of UHIs during rapid urbanization.

Modelling surface heat island intensity according to differences of biophysical characteristics: A case study of Amol city, Iran

Abstract One of the most important environmental phenomena in urban environments is urban heat island, which plays a big role in understanding anthropogenic activities. The main objective of this study is to present a novel approach based on the differences of the biophysical characteristics between built-up and non-built-up land to model Surface Heat Island Intensity (SUHII). To do so, several datasets such as Landsat images, MODIS products of MOD07L2 and MOD11A1, and data recorded at the local meteorological station for the period of 1985–2017 for Amol, Iran were used. Land Surface Temperature (LST) was calculated from single-channel algorithm and SUHII was calculated using the Surface Urban Heat Island Ratio Index (SUHIRI) as well as the surface biophysical characteristics. Finally, based on Least Squares Adjustment (LSA) model, the influence coefficient of the difference of each biophysical parameter between built-up and non-built-up land on the SUHII was calculated. The results show that the average LST of the built-up land exceeds of that for the non-built-up LST by 2.9 °C. In the study area, SUHII varies by time within 1985–2017. The standard deviation of the differences between the characteristics of brightness, greenness and surface wetness of the built-up and non-built-up land was 0.36, 0.76 and 1.17, respectively. The LSA model results show that the difference in the brightness of the built-up and non-built-up land relative to the two parameters of greenness and wetness has a greater effect on the SUHII. The coefficient of determination and root mean square error between the observed SUHII and the LSA-based calculation for the training set were 0.80 and 0.06, and for the testing set 0.75 and 0.08, respectively. The results of this study indicate the significant effect of the differences in the biophysical characteristics of land on the SUHII and the effectiveness of the model presented in the study to model the SUHII.

How Do the Multi-Temporal Centroid Trajectories of Urban Heat Island Correspond to Impervious Surface Changes: A Case Study in Wuhan, China.

Conspicuous expansion and intensification of impervious surfaces accompanied by rapid urbanization are widely recognized to have exerted evident impacts on the urban thermal environment. Investigating the spatially and temporally varying relationships between Land Surface Temperature (LST) and impervious surfaces (IS) at multiple scales is of great significance for steering IS expansion and intensification. This study proposes an analytical framework to investigate the spatiotemporal variations of LST and its responses to IS in Wuhan, China at both city scale and sub-region scale. The summer LST patterns in 2002–2017 are extracted by Multi-Task Gaussian Process (MTGP) model from raw 8-day synthesized MODerate-resolution Imaging Spectroradiometer (MODIS) LST data. At the city scale, the weighted center of LST (LSTWC) and impervious surface fraction (ISFWC), multi-temporal trajectories and coupling indicators are utilized to comprehensively examine the spatial and temporal dynamics of LST and IS within Wuhan. At the sub-region scale, urban heat island ratio index (URI), impervious surfaces contribution index (ISCI) and sprawl rate are introduced for further quantifying the relationships of LST and IS. The results reveal that IS and hot thermal landscapes expanded by 407.43 km2 and 255.82 km2 in Wuhan in 2002–2017 at city scale. The trajectories of LSTWCs and ISFWCs are visually coherent and both heading to southeast direction in general. At the sub-region scale, the specific cardinal directions with the highest ISCI variations are examined to be the exact directions of ISFWC trajectories in 2002–2017. The results reveal that the spatiotemporal variations of LST and IS are highly correlated at both city and sub-region scales within Wuhan, thus testifying the significance of steering IS expansion and renewal for controlling urban thermal environment deterioration.

Characterizing urban redevelopment process by quantifying thermal dynamic and landscape analysis

Urban redevelopment practices have received substantial attention in urban planning. Remotely sensed thermal infrared monitoring of urban heat island (UHI) is a well-documented topic, however, there is a lack of understanding of the influence on UHI change caused by urban redevelopment process. The objectives of this study was to investigate the urban redevelopment-induced efforts incorporating remote sensing of UHI and land use change. Multi-temporal ASTER thermal infrared images were employed to characterize UHI change; and high resolution Worldview images were employed to perform land use classification. UHI dynamic was quantified with urban heat island ratio index. Analysis of urban redevelopment-induced land use change with response to UHI were carried out. Landscape ecology methods were employed to quantitatively identify land use change with landscape metrics. Result demonstrated that UHI effect had a trend of mitigation during urban redevelopment process in the study area. Urban heat island intensity could be significantly eliminated or weakened by changes of land use composition and spatial configuration. These phenomena were closely related to redevelopment practices such as industrial relocation, buildings demolition, and brownfield transformation. This article presented a case study for characterizing urban redevelopment process with remote sensing monitoring, quantifying the change with urban heat island ratio index and landscape ecology analysis, research findings could be utilized as indicators for urban planning.

Statistical analysis of surface urban heat island intensity variations: A case study of Babol city, Iran

The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.

Spatial and Temporal Analysis of the Mitigating Effects of Industrial Relocation on the Surface Urban Heat Island over China

Urbanization is typically accompanied by the relocation and reconstruction of industrial areas due to limited space and environmental requirements, particularly in the case of a capital city. Shougang Group, one of the largest steel mill operators in China, was relocated from Beijing to Hebei Province. To study the thermal environmental changes at the Shougang industrial site before and after relocation, four Landsat images (from 2000, 2005, 2010 and 2016) were used to calculate the land surface temperature (LST). Using the urban heat island ratio index (URI), we compared the LST values for the four images of the investigated area. Following the relocation of Shougang Group, the URI values decreased from 0.55 in 2005 to 0.21 in 2016, indicating that the surface urban heat island effect in the area was greatly mitigated; we infer that this effect was related to steel production. This study shows that the use of Landsat images to assess industrial thermal pollution is feasible. Accurate and rapid extraction of thermal pollution data by remote sensing offers great potential for the management of industrial pollution sources and distribution, and for technical support in urban planning departments.

Influence of urban expansion on the urban heat island effect in Shanghai

ABSTRACTThe urban heat island (UHI) effect resulting from rapid urbanization is attracting increasing attention among the global scientific community. This research analyzed the relationship between urban expansion and the UHI effect utilizing an integrated approach, including urban land interpretation and retrieving land surface temperature based on remote sensing, and spatial overlay analysis for revealing the relationship for different time periods between 1984 and 2014 in Shanghai, China. The results show that (1) the spatiotemporal changes in UHI are consistent with the expansion of urban land, and rapid urban expansion leads to an expansion of the UHI, in particular along roadways. (2) The mode of urban expansion is an important factor influencing the UHI effect. Urban sprawl (urban expansion in the edge-expansion way) is a form of typical expansion that leads to the rapid increase in the UHI. When the urban compactness ratio is less than 0.15, a compact design can effectively control the expansion rate of the UHI and mitigate its range of influence and intensity. However, when the urban compactness ratio is greater than 0.15, the urban design has a marked influence on the UHI ratio index: a more compact form produces a stronger UHI effect. So, finding an equilibrium between urban compactness ratio and urban expansion rate is good for effective urban management and planning.

EVALUATION OF SPATIAL AND TEMPORAL DISTRIBUTION CHANGES OF LST USING LANDSAT IMAGES (CASE STUDY:TEHRAN)

Abstract. In traditional approach, the land surface temperature (LST) is estimated by the permanent or portable ground-based weather stations. Due to the lack of adequate distribution of weather stations, a uniform LST could not be achieved. Todays, With the development of remote sensing from space, satellite data offer the only possibility for measuring LST over the entire globe with sufficiently high temporal resolution and with complete spatially averaged rather than point values. the remote sensing imageries with relatively high spatial and temporal resolution are used as suitable tools to uniformly LST estimation. Time series, generated by remote sensed LST, provide a rich spatial-temporal infrastructure for heat island’s analysis. in this paper, a time series was generated by Landsat8 and Landsat7 satellite images to analysis the changes in the spatial and temporal distribution of the Tehran’s LST. In this process, The Normalized Difference Vegetation Index (NDVI) threshold method was applied to extract the LST; then the changes in spatial and temporal distribution of LST over the period 1999 to 2014 were evaluated by the statistical analysis. Finally, the achieved results show the very low temperature regions and the middle temperature regions were reduced by the rate of 0.54% and 5.67% respectively. On the other hand, the high temperature and the very high temperature regions were increased by 3.68% and 0.38% respectively. These results indicate an incremental procedure on the distribution of the hot regions in Tehran in this period. To quantitatively compare urban heat islands (UHI), an index called Urban Heat Island Ratio Index(URI) was calculated. It can reveal the intensity of the UHI within the urban area. The calculation of the index was based on the ratio of UHI area to urban area. The greater the index, the more intense the UHI was. Eventually, Considering URI between 1999 and 2014, an increasing about 0.03 was shown. The reasons responsible for the changes in spatio-temporal characteristics of the LST were the sharp increase in impervious surfaces, increased use of fossil fuels and greening policies.

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.

Analysis of human factors on urban heat island and simulation of urban thermal environment in Lanzhou city, China

Urban heat island (UHI) effect is a global phenomenon caused by urbanization. Because of the number and complexity of factors contributing to the urban thermal environment, traditional statistical methods are insufficient for acquiring data and analyzing the impact of human activities on the thermal environment, especially for identifying which factors are dominant. The UHI elements were extracted using thermal infrared remote sensing data to retrieve the land surface temperatures of Lanzhou city, and then adopting an object-oriented fractal net evolution approach to create an image segmentation of the land surface temperature (LST). The effects of urban expansion on the urban thermal environment were quantitatively analyzed. A comprehensive evaluation system of the urban thermal environment was constructed, the spatial pattern of the urban thermal environment in Lanzhou was assessed, and principal influencing factors were identified using spatial principal component analysis (SPCA) and multisource spatial data. We found that in the last 20 years, the UHI effect in Lanzhou city has been strengthened, as the UHI ratio index has increased from 0.385 in 1993 to 0.579 in 2001 and to 0.653 in 2011. The UHI expansion had a spatiotemporal consistency with the urban expansion. The four major factors that affect the spatial pattern of the urban thermal environment in Lanzhou can be ranked in the following order: landscape configuration, anthropogenic heat release, urban construction, and gradient from man-made to natural land cover. These four together accounted for 91.27% of the variance. A linear model was thus successfully constructed, implying that SPCA is helpful in identifying major contributors to UHI. Regression analysis indicated that the instantaneous LST and the simulated thermal environment have a good linear relationship, the correlation coefficient between the two reached 0.8011, highly significant at a confidence level of 0.001.

Influences of Urban Expansion on Urban Heat Island in Beijing during 1989–2010

Beijing has experienced rapid urbanization and associated urban heat island (UHI) effects. This study aimed at analyzing the impact of urban form on UHI in Beijing using TM/ETM images between 1989 and 2010. Spatial analysis was proposed to explore the relationships between area, compactness ratio, the gravity centers of urban land, and UHI. The UHI in Beijing spatially represented a “NE-SW” spindle. The land surface temperature (LST) was higher in south than in north. Urban Heat Island Ratio Index (URI) was well interrelated with urban land area in different zones. Under the similar urban land area condition, UHI and compactness ratio of urban land were in positive correlation. The moving direction of the UHI gravity center was basically in agreement with urban land sprawl. The encroachment of urban land on suburban land is the leading source of UHI effect. The results suggest that urban design based on urban form would be effective for regulating the thermal environment.

Temporal and Spatial Analysis of SuZhou Urban Heat Island Effect

The Suzhou urban as the research object, the surface brightness temperature was retrieved by the 1987,2005 and 2010 Landsat TM / ETM+thermal infrared band remote sensing images, then calculated the relative brightness temperature and the urban heat island ratio index, according to the relative brightness temperature, the Suzhou urban heat island effect was divided into four grades: green island, weak island, heat island and strong island, and compared the 3 periods urban heat island ratio index. The results show that: (1) with the urbanization process accelerated, the urban heat island ratio index has been rising in 1987-2010, the urban heat island effect is enhanced year by year; (2) the green island area and the strong island area in 1987-2010 are declining, are reduced by 23.82.km2and 8.75.km2, the weak island area and the heat island area are increasing, are increased by 22.69.km2and 9.83.km2; (3) the Suzhou urban expansion and the urban heat island expansion trend has the same space consistency in 1987-2010, while the urban area is sprawling, the urban heat island area is also expanding; (4) the urban vegetation and the urban heat island effect is a negative correlation in 1987-2010, appropriate to increase the urban green space for the mitigation of urban heat island effect has a positive effect.

Urban Expansion and Heat Island Dynamics in the Quanzhou Region, China

Urban spatial expansion in the Quanzhou region of southeastern China has been accelerated over the past 20 years. This has caused land cover changes and, thus, has significant impacts on the local ecosystem and climate. To study the urban expansion and heat island dynamics of the region over the past 20 years, multitemporal Landsat TM images of 1987, 1996, and 2006 were used. The estimation of the urban expansion was assisted by the index-based built-up index (IBI) through enhancing built-up land features in the images. The urban-heat-island (UHI) effect was assessed using the urban-heat-island ratio index (URI). Multitemporal analysis indicates that the great increase in urban area has resulted in the development of UHIs in the region. Regression statistics reveal that built-up land has a positive exponential relationship with land surface temperature (LST). Therefore, the increase in built-up land percentage can exponentially accelerate the rise of LST.