The Impact of landscape composition for urban heat island intensity in Addis Ababa City using Landsat data (1986–2016)

Abstract. Exploring changes in land use and land cover (LULC) in the city area and its surrounding is important to understand the variation of surface urban heat island (SUHI) and surface urban heat island intensity (SUHII). The SUHII can be calculated based on the local climate zone by using land use and land cover compossition of the city and based on the urban rural zone . The objective of this research is to examine the spatiotemporal changes of LULC and the impact of its composition for the formation of SUHI in Addis Ababa City, Ethiopia based on the urban rural zones. The mean center of the central business district of the Addis Ababa City was considered as the central point of the study area. We represented the 30&thinsp;km&thinsp;&times;&thinsp;30&thinsp;km geographical area as a study area with a 15km radius from the central point. As data sources, multi-temporal satellite data provided by the United States Geological Survey (USGS) were used in respect to the years of 1986, 2001, and 2016. In the methodology, we first completed the classification of LULC by using pixel-oriented method for the three years and the validation of the classification has been made. For the classification five LULC classes were identified such as forest, impervious surface, grass land, bare land and crop land. Afterward, land surface temperature (LST) has been computed for three years respectively. Finally, urban rural gradient zones (URGZs) have been generated as a set of polygons with 210m distance in each zone from the central point of the study area. In order to evaluate the SUHII along the URGZs in respect to the LULC, the following analyses were accomplished: (i) the relationship between mean LST and composition of the LULC was computed, (ii) the SUHII was calculated based on the LST variation of main LULC categories and the temperature difference between URGZs, (iii) multi-temporal and multi-directional SUHII was computed, and (iv) linear regression analyses were used to assess the correlations of the mean LST with composition of LULC. The results of the analyses show that (i) distribution pattern of SUHII has changed over the study period as results of changes in LULC, and (ii) mean LST gradually declines from city centre to outside of the city , then it can be seen increasing trends due to the effect of bare lands in rural area. This pattern can be seen over the three years as the result of multi-directional approach. The methodology presented will be able to apply other cities which are showing similar growth pattern by making necessary calibration, and our finding can be used as a proxy indicator to introduce appropriate landscape and town planning in a sustainable viewpoint in Addis Ababa City.

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The impact of COVID-19 lockdowns on surface urban heat island changes and air-quality improvements across 21 major cities in the Middle East

Environmental Pollution ◽

10.1016/j.envpol.2021.117802 ◽

2021 ◽

pp. 117802

Author(s):

Ahmed M. El Kenawy ◽

Juan I. Lopez-Moreno ◽

Matthew F. McCabe ◽

Fernando Domínguez-Castro ◽

Dhais Peña-Angulo ◽

...

Keyword(s):

Air Quality ◽

Middle East ◽

Urban Heat Island ◽

Heat Island ◽

Quality Improvements ◽

Urban Heat ◽

Surface Urban Heat Island ◽

The Impact

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Effects of Dubai coastline extreme urbanization in land and sea on local near-surface climate variables patterns

10.5194/egusphere-egu21-6348 ◽

2021 ◽

Author(s):

Emily Elhacham ◽

Pinhas Alpert

Keyword(s):

Urban Heat Island ◽

Heat Island ◽

Rapid Urbanization ◽

Near Surface ◽

Modis Data ◽

The World ◽

Urban Heat ◽

Surface Urban Heat Island ◽

Coastal Urbanization ◽

The Impact

Over a billion people currently live in coastal areas, and coastal urbanization is rapidly growing worldwide. Here, we explore the impact of an extreme and rapid coastal urbanization on near-surface climatic variables, based on MODIS data, Landsat and some in-situ observations. We study Dubai, one of the fastest growing cities in the world over the last two decades. Dubai's urbanization centers along its coastline &#8211; in land, massive skyscrapers and infrastructure have been built, while in sea, just nearby, unique artificial islands have been constructed.Studying the coastline during the years of intense urbanization (2001-2014), we show that the coastline exhibits surface urban heat island characteristics, where the urban center experiences higher temperatures, by as much as 2.0&#176;C and more, compared to the adjacent less urbanized zones. During development, the coastal surface urban heat island has nearly doubled its size, expanding towards the newly developed areas. This newly developed zone also exhibited the largest temperature trend along the coast, exceeding 0.1&#176;C/year on average.Overall, we found that over land, temperature increases go along with albedo decreases, while in sea, surface temperature decreases and albedo increases were observed particularly over the artificial islands. These trends in land and sea temperatures affect the land-sea temperature gradient which influences the breeze intensity. The above findings, along with the increasing relative humidity shown, directly affect the local population and ecosystem and add additional burden to this area, which is already considered as one of the warmest in the world and a climate change 'hot spot'.&#160;References:E. Elhacham and P. Alpert, "Impact of coastline-intensive anthropogenic activities on the atmosphere from moderate resolution imaging spectroradiometer (MODIS) data in Dubai (2001&#8211;2014)", Earth&#8217;s Future, 4, 2016. https://doi.org/10.1002/2015EF000325E. Elhacham and P. Alpert, "Temperature patterns along an arid coastline experiencing extreme and rapid urbanization, case study: Dubai", submitted.

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Assessment of Changes in Land Use/Land Cover and Land Surface Temperatures and Their Impact on Surface Urban Heat Island Phenomena in the Kathmandu Valley (1988–2018)

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9120726 ◽

2020 ◽

Vol 9 (12) ◽

pp. 726

Author(s):

Md. Omar Sarif ◽

Bhagawat Rimal ◽

Nigel E. Stork

Keyword(s):

Urban Heat Island ◽

Land Surface ◽

Agricultural Land ◽

Kathmandu Valley ◽

Heat Island ◽

City Center ◽

Urban Heat ◽

Surface Urban Heat Island ◽

The City ◽

Normal Difference

More than half of the world’s populations now live in rapidly expanding urban and its surrounding areas. The consequences for Land Use/Land Cover (LULC) dynamics and Surface Urban Heat Island (SUHI) phenomena are poorly understood for many new cities. We explore this issue and their inter-relationship in the Kathmandu Valley, an area of roughly 694 km2, at decadal intervals using April (summer) Landsat images of 1988, 1998, 2008, and 2018. LULC assessment was made using the Support Vector Machine algorithm. In the Kathmandu Valley, most land is either natural vegetation or agricultural land but in the study period there was a rapid expansion of impervious surfaces in urban areas. Impervious surfaces (IL) grew by 113.44 km2 (16.34% of total area), natural vegetation (VL) by 6.07 km2 (0.87% of total area), resulting in the loss of 118.29 km2 area from agricultural land (17.03% of total area) during 1988–2018. At the same time, the average land surface temperature (LST) increased by nearly 5–7 °C in the city and nearly 3–5 °C at the city boundary. For different LULC classes, the highest mean LST increase during 1988–2018 was 7.11 °C for IL with the lowest being 3.18 °C for VL although there were some fluctuations during this time period. While open land only occupies a small proportion of the landscape, it usually had higher mean LST than all other LULC classes. There was a negative relationship both between LST and Normal Difference Vegetation Index (NDVI) and LST and Normal Difference Moisture Index (NDMI), respectively, and a positive relationship between LST and Normal Difference Built-up Index (NDBI). The result of an urban–rural gradient analysis showed there was sharp decrease of mean LST from the city center outwards to about 15 kms because the NDVI also sharply increased, especially in 2008 and 2018, which clearly shows a surface urban heat island effect. Further from the city center, around 20–25 kms, mean LST increased due to increased agriculture activity. The population of Kathmandu Valley was 2.88 million in 2016 and if the growth trend continues then it is predicted to reach 3.85 million by 2035. Consequently, to avoid the critical effects of increasing SUHI in Kathmandu it is essential to improve urban planning including the implementation of green city technologies.

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Evaluation of the surface urban heat island effect in the city of Madrid by thermal remote sensing

International Journal of Remote Sensing ◽

10.1080/01431161.2012.716548 ◽

2012 ◽

Vol 34 (9-10) ◽

pp. 3177-3192 ◽

Cited By ~ 47

Author(s):

José A. Sobrino ◽

Rosa Oltra-Carrió ◽

Guillem Sòria ◽

Juan Carlos Jiménez-Muñoz ◽

Belén Franch ◽

...

Keyword(s):

Remote Sensing ◽

Urban Heat Island ◽

Urban Heat Island Effect ◽

Heat Island ◽

Thermal Remote Sensing ◽

Island Effect ◽

Urban Heat ◽

Surface Urban Heat Island ◽

The City

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Urban Informal Housing and Surface Urban Heat Island Intensity

Environment and Urbanization Asia ◽

10.1177/0975425318783548 ◽

2018 ◽

Vol 9 (2) ◽

pp. 158-177 ◽

Cited By ~ 13

Author(s):

Surabhi Mehrotra ◽

Ronita Bardhan ◽

Krithi Ramamritham

Keyword(s):

Heat Stress ◽

Spatial Analysis ◽

Urban Heat Island ◽

Urban Form ◽

Spatial Association ◽

Heat Island ◽

Urban Heat ◽

Surface Urban Heat Island ◽

The Impact ◽

Slum Housing

Urbanization leads to the densification of built-up areas, and thereby increases surface heat island intensity which is one of the growing concerns in the rapidly urbanizing cities. Another notable aspect of cities like Mumbai is the uncontrolled growth of informal slum housing clusters, which have emerged as a significant urban built form in the landscape of cities. This study presents a case of Mumbai that aims to explore the linkages between slum housing—here referred as ‘slum urban form’ (SUF)—and surface urban heat island (SUHI) supported by spatial-statistical analysis. The magnitude of the impact of urban form on SUHI, measured by land surface temperature (LST), is examined using Cohen’s d index, which measures the effect size for two groups—SUF and ‘formal’ housing—on LST. The results confirm a ‘large’ effect indicating a significant difference in mean LST between the two groups. The spatial analysis reveals a statistically significant spatial clustering of LST and SUF ( p-value < 0.05), and bivariate local indicator of spatial association (LISA) confirms that the spatial association of SUF is surrounded by ‘high’ LST (Moran I: 0.49). The exploratory spatial analysis indicates that the contribution of SUF in elevating SUHI intensity is more than the formal housing areas and has increased vulnerability to heat stress. The results were validated on the ground using environmental sensors, which confirms the susceptibility of SUF to heat stress.

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Analysis of the Impact of Land Use on Spatiotemporal Patterns of Surface Urban Heat Island in Rapid Urbanization, a Case Study of Shanghai, China

Sustainability ◽

10.3390/su12031171 ◽

2020 ◽

Vol 12 (3) ◽

pp. 1171 ◽

Cited By ~ 1

Author(s):

Hongyu Du ◽

Fengqi Zhou ◽

Chunlan Li ◽

Wenbo Cai ◽

Hong Jiang ◽

...

Keyword(s):

Land Use ◽

Urban Heat Island ◽

Land Surface ◽

Agricultural Land ◽

Heat Island ◽

Rapid Urbanization ◽

Urban Heat ◽

Surface Urban Heat Island ◽

The Impact

In the trend of global warming and urbanization, frequent extreme weather influences the life of citizens seriously. Shanghai, as a typical mega-city in China that has been successful in urbanization, suffers seriously from the urban heat island (UHI) effect. The research concentrates on the spatial and temporal pattern of surface UHI and land use. Then, the relation between them are further discussed. The results show that for the last 15 years, the UHI effect of Shanghai has been increasing continuously in both intensity and area. The UHI extends from the city center toward the suburban area. Along with the year, the ratio in area of Agricultural Land (AL), Wetland (WL), and Bare Land (BL) has decreased. On the contrary, Construction Land (CL) and Green Land (GL) have increased. The average land surface temperature (LST) rankings for each research year from high to low were all CL, BL, GL, AL, and WL. CL contributed the most to the UHI effect, while WL and GL contributed the most to mitigate the UHI. The conclusion provides practical advice aimed to mitigate the UHI effect for urban planning authorities.

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