The increasing trend of the urban heat island intensity

Levermore, Geoff; Parkinson, John; Lee, Kwan-Ho; Laycock, P. J.; Lindley, Sarah

doi:10.1016/j.uclim.2017.02.004

Cited by 126 publications

(56 citation statements)

References 2 publications

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“…The difference can be seen in the figure. 2 beside cloud and shadow gave impact for LST result in both images such as increase or decrease the surface temperature around [42,43]. Landsat 7 ETM+ and MODIS Terra have difference patterns especially in the wet season (2008 -2009), where Landsat has a high temperature in March but MODIS Terra in October (2009).…”

Section: Land Surface Temperature Validationmentioning

confidence: 99%

Downscaling land surface temperature on multi-scale image for drought monitoring

Nugraha

Gunawan

Kamal

2019

Sixth Geoinformation Science Symposium

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Land Surface Temperature (LST) is an important indicator of environmental changes, especially related drought monitoring. It is necessary to accurately detect drought events using advanced technology proved information regarding the drought areas. Remote sensing images have proven to be efficient in detecting drought events. MODIS Terra and Landsat 7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat 8 OLI/TIRS (The Operational Land Imager and the Thermal Infrared Scanner) represent remote imaging images with different spatial resolutions that enable us to provide drought information. However, proper methods are needed to optimize these images for monitoring drought events. The purpose of this study is to find out the ability of multi-scale images provide information about drought monitoring using LST methods. The method used in LST is a Temperature Condition Index (TCI), the Crop Water Stress Index (CWSI), and Principal Component Analysis (PCA). All three equations are selected because they represent a modification of the method for LST input. The results suggest that the three equations used in multi-level imagery have a critical alignment of information regarding the drought. The results show that the drought pattern identified by MODIS Terra image was similar to the one detected by Landsat ETM+ and OLI/TIRS images. However, we found a temperature difference in the dry season (especially in October) between Landsat ETM+ and OLI/TIRS. The degree of LST estimation accuracy between MODIS Terra and Landsat (ETM+ and OLI/TIRS) is indicated by the average difference between the results of those images, which was 1 degree Celsius (1°C). The use of these three equations for drought monitoring with multi-level imagery suggests that there is a positive relationship. This relationship manifests the same pattern, shape, and association that are produced, thus using a common equation for drought monitoring is more focused.

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Section: Land Surface Temperature Validationmentioning

confidence: 99%

Downscaling land surface temperature on multi-scale image for drought monitoring

Nugraha

Gunawan

Kamal

2019

Sixth Geoinformation Science Symposium

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“…We then calculated the SUHII at the pixel level for each pixel in the UA, which was the difference between the LST of each pixel in the UA and the averaged LST in the NoUA. After we obtained the data of SUHII, LST, EVI, and NDBI from 2000 to 2015, we investigated the temporal trends of such variables (e.g., SUHII) at every pixel using ordinary least squares (OLS) linear regression models [36,43,72]. Here we use Trend LST as an example to illustrate the calculation of Trend LST, Trend SUHII , Trend EVI , and Trend NDBI .…”

Section: The Calculation Of Temporal Trends For Suhii Lst Evi and mentioning

confidence: 99%

Time-Series Analysis Reveals Intensified Urban Heat Island Effects but without Significant Urban Warming

2019

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Numerous studies have shown an increased surface urban heat island intensity (SUHII) in many cities with urban expansion. Few studies, however, have investigated whether such intensification is mainly caused by urban warming, the cooling of surrounding nonurban regions, or the different rates of warming/cooling between urban and nonurban areas. This study aims to fill that gap using Beijing, China, as a case study. We first examined the temporal trends of SUHII in Beijing and then compared the magnitude of the land surface temperature (LST) trend in urban and nonurban areas. We further detected the temporal trend of LST (TrendLST) at the pixel level and explored its linkage to the temporal trends of EVI (TrendEVI) and NDBI (TrendNDBI). We used MODIS data from 2000 to 2015. We found that (1) SUHII significantly increased from 4.35 °C to 6.02 °C, showing an intensified surface urban heat island (SUHI) effect, with an annual increase rate of 0.13 °C in summer during the daytime and 0.04 °C in summer at night. In addition, the intensification of SUHII was more prominent in new urban areas (NUA). (2) The intensified SUHII, however, was largely caused by substantial cooling effects in nonurban areas (NoUA), not substantial warming in urban areas. (3) Spatially, there were large spatial variations in significant warming and cooling spots over the entire study area, which were related to TrendNDBI and TrendEVI. TrendNDBI significantly affected TrendLST in a positive way, while the TrendEVI had a significant positive effect (p = 0.023) on TrendLST only when EVI had an increasing trend. Our study underscores the importance of quantifying and comparing the changes in LST in both urban and nonurban areas when investigating changes in SUHII using time-series trend analysis. Such analysis can provide insights into promoting city-based urban heat mitigation strategies which focused on both urban and nonurban areas.

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“…In fact, model simulations, performed in the ClimateCost project, have estimated that residential cooling energy demand will increase of 16 Mtoe/year by 2050 and 53 Mtoe/year by 2100 in Europe [11]. Nevertheless, the intensification of air conditioning systems use produces a lot of heat and greenhouse gases that, in addition to climate change and other anthropogenic emissions, contribute to intensify Urban Heat Island (UHI) effect [12]. It consists of a more significant increase in air temperature in urban areas than in surrounding rural ones.…”

Section: Pcms and Cool Materials In Building Retrofittingmentioning

confidence: 99%

Energy efficiency and resilience against increasing temperatures in summer: the use of PCM and cool materials in buildings

Lassandro¹,

Turi²

2017

IJHT

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Nowadays, it is important to understand how to combine energy efficiency and the point of view of resilience. Regarding buildings, resilience represents the ability to recover from or adapt to an unfavorable condition or event, maintaining their own functionality and performances. This issue has been ignored for several years, especially in building sector, but the impacts of natural hazards and climate change are becoming more and more influential and frequent. Moreover, urban areas are responsible of a great part of global energy consumption and CO2 emissions, in addition to the intensification of greenhouse effect. For this reason, the use of new technologies (PCM and cool materials) for buildings can affect not only indoor microclimate, but also urban environment. Starting from the dynamic simulations of common buildings in South of Italy and then in other hotter Mediterranean climate (Athens, Tunis), the research analyses various typologies of these materials and possible combined applications. The aim of the study is to understand, through a set of proper indicators, how they can contribute to enhance energy performance of buildings and climate resilience in order to face rising temperatures also at neighbourhood level.

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The increasing trend of the urban heat island intensity

Cited by 126 publications

References 2 publications

Downscaling land surface temperature on multi-scale image for drought monitoring

Downscaling land surface temperature on multi-scale image for drought monitoring

Time-Series Analysis Reveals Intensified Urban Heat Island Effects but without Significant Urban Warming

Energy efficiency and resilience against increasing temperatures in summer: the use of PCM and cool materials in buildings

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