Measuring night-time urban heat island. Still a pending issue

2020 ◽  
Author(s):  
Josep Roca ◽  
Blanca Arellano
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Heat Waves ◽  
Heat Island ◽  
Night Time ◽  
Structural Problems ◽  
First Case ◽  
Urban Heat ◽  
Weather Stations ◽  
Land Covers

<p>The study of urban heat island (UHI) is of great relevance in the context of climate change (CC) and global warming. Cities accumulate heat in urban land covers as well as in built infrastructures, representing true islands of heat in relation to their rural environment, less urbanized. The literature on urban climate has highlighted the singular importance of night UHI phenomenon. It is during the night that the effects of UHI become more apparent, due to the low cooling capacity of urban construction materials and is during nighttime that temperatures can cause higher health risks, leading to the aggravation of negative impacts on people’s health and comfort in extreme events such as heat waves becoming more and more frequent and lasting longer. However, the study of nocturnal UHIs is still poorly developed, due to the structural problems regarding the availability of land surface and air temperature data for night time.</p><p>Traditional methods for obtaining nocturnal UHI have been directed either to extrapolation of data from weather stations, or obtaining air temperatures through urban transects. In the first case, the lack of weather stations in urban landscapes makes it extremely difficult to obtain data to extrapolate and propose models at a detailed resolution scale. In the second case, there is a manifest difficulty in obtaining data simultaneously and significantly representative of urban and rural zones. Another used methodology for measuring the nocturnal UHI is remote sensing from MODIS images, but the greatest limitation about this method is the low resolution, therefore it is clear the need for open source databases with better or higher resolution to quantify the night surface temperature.</p><p>This paper aims to develop a model for nocturnal UHI analysing several areas of Alta and Baja California as well as in the Mediterranean Coast, using data from the Landsat thermal bands (with an spatial resolution of 30 square meters per pixel) and contrasting Landsat's very limited nighttime images with daytime ones. The contrast allows the construction of “cooling” models of the LST based on geographical characteristics (longitude, latitude, distance to the sea, DTM, slope, orientation, etc.) and urban-spatial parameters (land uses and land covers), which are likely to be extrapolated to different time periods.</p>

Towards a new methodology to determine nighttime Urban Heat Island

2021 ◽  
Author(s):  
Blanca Arellano ◽  
Josep Roca
Keyword(s):  
Urban Heat Island ◽  
Heat Waves ◽  
Surface Radiation ◽  
Urban Landscapes ◽  
Heat Island ◽  
Structural Problems ◽  
Thermal Data ◽  
Satellite Sensors ◽  
Urban Heat ◽  
Weather Stations

<p>The study of urban heat island (UHI) is of great importance in the context of climate change (CC). The literature on urban climate has highlighted the singular importance of night UHI phenomenon. It is during the night that the effects of UHI become most evident due to the low cooling capacity of urban construction materials and it is during nighttime that the accumulated heat and high temperatures can generate greater risks to health, leading to aggravate the negative impacts on people's health and comfort, especially in extreme events such as heat waves.</p><p>Traditional methods for obtaining nocturnal UHI have been directed either to extrapolation of data from weather stations. The lack of weather stations in urban landscapes makes it extremely difficult to obtain data to extrapolate and propose models at a detailed resolution scale.</p><p>The low spatial resolution of the air temperature information contrasts with the higher resolution of the thermal data of the land covers supplied by the satellite sensors. There is a high consensus that the temperature of the earth's surface (LST) plays a fundamental role in the generation of UHI, representing a determinant of surface radiation and energy exchange, as well as the control of the heat distribution between surface and atmosphere. However, the study of the nocturnal LST is still poorly developed due to structural problems related to the availability of detailed data on the LST at night. Most of the satellite sensors (Landsat, Aster, ...) allow to obtain daytime thermal images, but in a much more limited way nighttime thermal data. Only MODIS or Sentinel 3 provide abundant thermal night images, but the low resolution of these images (1 km / pixel) does not allow the construction of detailed models of the nocturnal UHI. For these reasons, estimating the nocturnal UHI remains a pending challenge.</p><p>This paper aims to develop a new methodology to determine nighttime LST using data from Landsat thermal bands and contrasting Landsat's very limited nighttime images with daytime ones. The contrast between the daytime and nighttime LST allows the construction of “cooling” models of the LST based on geographic characteristics and urban-spatial parameters, which could be extrapolated to different periods of time (during the same season).</p><p>However, the estimation of the LST from nighttime Landsat thermal bands is not a trivial question. The most used methodology to determine daytime LST is based on estimating the emissivity of the land from its degree of vegetation (NDVI threshold). But this method shows significant limitations at night. The NDVI overvalues vegetation when considering the canopy of trees. This overestimation may be correct during the day, when the shade of the trees limits the radiation incident on the ground. But it is critical at night.</p><p>For this reason, this paper seeks to develop a new methodology to estimate the degree of vegetation and soil moisture, and, based on it, determine the emissivity and, consequently, the nocturnal LST.</p><p>The case study is the Metropolitan Area of Barcelona (636 km<sup>2</sup>, 3.3 million inhabitants).</p>

scholarly journals Climate change over UK cities: the urban influence on extreme temperatures in the UK climate projections

2021 ◽  
Author(s):  
William J. Keat ◽  
Elizabeth J. Kendon ◽  
Sylvia I. Bohnenstengel
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Climate Model ◽  
Climate Projections ◽  
Heat Island ◽  
Night Time ◽  
Urban Heat ◽  
The Uk

AbstractIncreasing summer temperatures in a warming climate will increase the exposure of the UK population to heat-stress and associated heat-related mortality. Urban inhabitants are particularly at risk, as urban areas are often significantly warmer than rural areas as a result of the urban heat island phenomenon. The latest UK Climate Projections include an ensemble of convection-permitting model (CPM) simulations which provide credible climate information at the city-scale, the first of their kind for national climate scenarios. Using a newly developed urban signal extraction technique, we quantify the urban influence on present-day (1981–2000) and future (2061–2080) temperature extremes in the CPM compared to the coarser resolution regional climate model (RCM) simulations over UK cities. We find that the urban influence in these models is markedly different, with the magnitude of night-time urban heat islands overestimated in the RCM, significantly for the warmest nights (up to $$4~^{\circ }$$ 4 ∘ C), while the CPM agrees much better with observations. This improvement is driven by the improved land-surface representation and more sophisticated urban scheme MORUSES employed by the CPM, which distinguishes street canyons and roofs. In future, there is a strong amplification of the urban influence in the RCM, whilst there is little change in the CPM. We find that future changes in soil moisture play an important role in the magnitude of the urban influence, highlighting the importance of the accurate representation of land-surface and hydrological processes for urban heat island studies. The results indicate that the CPM provides more reliable urban temperature projections, due at least in part to the improved urban scheme.

scholarly journals Analysis of Urban Heat Island and Heat Waves Using Sentinel-3 Images: a Study of Andalusian Cities in Spain

2021 ◽  
Author(s):  
David Hidalgo García
Keyword(s):  
Solar Radiation ◽  
Urban Heat Island ◽  
Heat Wave ◽  
Land Surface ◽  
Heat Waves ◽  
Economic Cost ◽  
Heat Island ◽  
Multivariate Relationships ◽  
Urban Heat ◽  
Wave Conditions

Abstract At present, understanding the synergies between the Surface Urban Heat Island (SUHI) phenomenon and extreme climatic events entailing high mortality, i.e., heat waves, is a great challenge that must be faced to improve the quality of life in urban zones. The implementation of new mitigation and resilience measures in cities would serve to lessen the effects of heat waves and the economic cost they entail. In this research, the Land Surface Temperature (LST) and the SUHI were determined through Sentinel-3A and 3B images of the eight capitals of Andalusia (southern Spain) during the months of July and August of years 2019 and 2020. The objective was to determine possible synergies or interaction between the LST and SUHI, as well as between SUHI and heat waves, in a region classified as highly vulnerable to the effects of climate change. For each Andalusian city, the atmospheric variables of ambient temperature, solar radiation, wind speed and direction were obtained from stations of the Spanish State Meteorological Agency (AEMET); the data were quantified and classified both in periods of normal environmental conditions and during heat waves. By means of Data Panel statistical analysis, the multivariate relationships were derived, determining which ones statistically influence the SUHI during heat wave periods. The results indicate that the LST and the mean SUHI obtained are statistically interacted and intensify under heat wave conditions. The greatest increases in daytime temperatures were seen for Sentinel-3A in cities by the coast (LST = 3.90 °C, SUHI = 1.44 °C) and for Sentinel-3B in cities located inland (LST = 2.85 °C, SUHI = 0.52 °C). The existence of statistically significant positive relationships above 99% (p < 0.000) between the SUHI and solar radiation, and between the SUHI and the direction of the wind, intensified in periods of heat wave, could be verified. An increase in the urban area affected by the SUHI under heat wave conditions is reported. Graphical Abstract

scholarly journals Correlation between Land Surface Temperature and Urban Heat Island with COVID-19 in New Delhi, India

2020 ◽  
Author(s):  
Semonti Mukherjee ◽  
Aniruddha Debnath
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Family Welfare ◽  
P Value ◽  
New Delhi ◽  
Heat Island ◽  
Night Time ◽  
Urban Heat

Abstract This study aims to analyses the correlation between Urban Heat Island (UHI), Land Surface Temperature (LST) with COVID-19 (Coronavirus disease) pandemic in New Delhi, India. This study engaged a secondary data analysis of surveillance data of COVID-19 from Ministry of Health and Family Welfare Government of India and temperature data from MODIS (MOD11A1 & MOD11A2). The significant relation in between COVID-19 confirmed cases and LST in day time postulate a positive significance (p value <0.05) with R2=81% and for night time this is R2= 86%.

scholarly journals Comparative Analysis of Variations and Patterns between Surface Urban Heat Island Intensity and Frequency across 305 Chinese Cities

2021 ◽  
Vol 13 (17) ◽  
pp. 3505
Author(s):  
Kangning Li ◽  
Yunhao Chen ◽  
Shengjun Gao
Keyword(s):  
Urban Heat Island ◽  
Pattern Classification ◽  
Land Surface ◽  
Heat Waves ◽  
Heat Island ◽  
Spatiotemporal Variations ◽  
Negative Effects ◽  
Chinese Cities ◽  
The North ◽  
Urban Heat

Urban heat island (UHI), referring to higher temperatures in urban extents than its surrounding rural regions, is widely reported in terms of negative effects to both the ecological environment and human health. To propose effective mitigation measurements, spatiotemporal variations and control machines of surface UHI (SUHI) have been widely investigated, in particular based on the indicator of SUHI intensity (SUHII). However, studies on SUHI frequency (SUHIF), an important temporal indicator, are challenged by a large number of missing data in daily land surface temperature (LST). Whether there is any city with strong SUHII and low SUHIF remains unclear. Thanks to the publication of daily seamless all-weather LST, this paper is proposed to investigate spatiotemporal variations of SUHIF, to compare SUHII and SUHIF, to conduct a pattern classification, and to further explore their driving factors across 305 Chinese cities. Four main findings are summarized below: (1) SUHIF is found to be higher in the south during the day, while it is higher in the north at night. Cities within the latitude from 20° N and 40° N indicate strong intensity and high frequency at day. Climate zone-based variations of SUHII and SUHIF are different, in particular at nighttime. (2) SUHIF are observed in great diurnal and seasonal variations. Summer daytime with 3.01 K of SUHII and 80 of SUHIF, possibly coupling with heat waves, increases the risk of heat-related diseases. (3) K-means clustering is employed to conduct pattern classification of the selected cities. SUHIF is found possibly to be consistent to its SUHII in the same city, while they provide quantitative and temporal characters respectively. (4) Controls for SUHIF and SUHII are found in significant variations among temporal scales and different patterns. This paper first conducts a comparison between SUHII and SUHIF, and provides pattern classification for further research and practice on mitigation measurements.

scholarly journals Urban Heat Island in Wuhan and Its Relationship With Nearby Water Bodies

2020 ◽  
Vol 185 ◽  
pp. 02008
Author(s):  
Claire Xu
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Energy Use ◽  
Heat Waves ◽  
Water Bodies ◽  
Heat Island ◽  
Island Effect ◽  
Urban Heat ◽  
The Impact

With predictions of global warming to continue into the near future, heat waves are likely to increase both in frequency and severity. Combined with the fast-developing urban areas and sky-rocketing populations in some regions, urban heat island effect becomes increasingly prominent. This trend has caused numerous problems in energy use, human health, and environmental stress. The purpose of the study in this article is to examine the effects of UHI and its impact on nearby water bodies. Through a series of data, which is collected by using Geospatial visualization tool, the study analyzes the extent to which UHI raises the water temperature in Wuhan, China, and compares lakes in different region of Wuhan to explore the impact of modified land surface and human activities. Given the exacerbation of the urban climatic crisis, the study also presents several potential solutions to a sustainable future in urban areas.

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

scholarly journals RELATIONSHIPS BETWEEN LAND USE/LAND COVER AND LAND SURFACE TEMPERATURE IN TABRIZ FROM 2000 TO 2017

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 1041-1044
Author(s):  
A. Tahooni ◽  
A. A. Kakroodi
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Impervious Surface ◽  
Bare Soil ◽  
Heat Island ◽  
Land Use Land Cover ◽  
Urban Heat

Abstract. Urban Heat Island (UHI) refers to the development of higher urban temperatures of an urban area compared to the temperatures of surrounding suburban and rural areas. Highly reflective urban materials to solar radiation present a significantly lower surface temperature and contribute to reducing the sensible heat released in the atmosphere and mitigating the urban heat island. Many studies of the UHI effect have been based on Land Surface Temperature (LST) measurements from remote sensors. The remotely sensed UHI has been termed the surface urban heat island (SUHI) effect. This study examines Tabriz city land use/land cover (LULC) and LST changes using Landsat satellite images between 2000 and 2017. Maximum likelihood classification and single channel methods were used for LULC classification and LST retrieval respectively. Results show that impervious surface has increased 13.79% and bare soil area has decreased 16.2%. The results also revealed bare soil class LST after a constant trend become increasing. It also revealed the impervious surface LST has a decreasing trend between 2000 and 2011 and has a little change. Using materials that have low absorption and high reflectance decrease the effect of heat island considerably.

scholarly journals Ecological impact evaluation of urban heat island in Dhaka city; a spatio-temporal approach

2021 ◽  
Author(s):  
Kazi Jihadur Rashid ◽  
Sumaia Islam ◽  
Mohammad Atiqur Rahman
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Ecological Impact ◽  
Urban Life ◽  
Heat Island ◽  
Dhaka City ◽  
Ecological Conditions ◽  
Urban Heat ◽  
The Impact

Abstract Urban heat island (UHI) is one of the major causes for deteriorating ecology of the rapidly expanding Dhaka city in the changing climatic conditions. Although researchers have identified, characterized and modeled UHI in the study area, the ecological evaluation of UHI effect has not yet been focused. This study uses land surface normalization techniques such as urban thermal field variance (UTFVI) to quantify the impact of UHI and also identifies vulnerable UHI areas compared to land cover types. Landsat imageries from 1990 to 2020 were used at decadal intervals. Results of the study primarily show that intensified UHI areas have increased spatially from 33.1–40.9% in response to urban growth throughout the period of 1990 to 2020. Extreme surface temperature values above 31°C have also been shown in open soils in under-construction sites for future developmental purposes. UTFVI is categorized into six categories representing UHI intensity in relation to ecological conditions. Finally, comparative analysis between land use/land cover (LULC) with UTFVI shows that the ecological conditions deteriorate as the intensity of UHI increases in the area. The developed areas facing ecological threat have increased from 9.3–19.8% throughout the period. Effective mitigating measures such as increasing green surfaces and planned urbanization practices are crucial in this regard. This study would help policymakers to concentrate on controlling thermal exposure and on preserving sustainable urban life.

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