The Surface Urban Heat Island Intensity and Urban Expansion: A comparative analysis for the coastal areas of Pakistan

Rizvi, Shahnilla Haider; Fatima, Hira; Alam, Khan; Iqbal, Muhammad Jawed

doi:10.1007/s10668-020-00828-5

Cited by 30 publications

(6 citation statements)

References 65 publications

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“…The productivity of vegetation covers relates to evapotranspiration and precipitation, and NDVI is a valuable tool to study vegetation cover performance at the landscape scale (Gilani et al, 2015;I. Khan et al, 2019;Rizvi et al, 2020;B. J. Zoungrana et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Hussain

Karuppannan

2021

Geology, Ecology, and Landscapes

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The aim of this research was to assess the land use/land cover (LULC) changes and its impact on land surface temperature (LST) using remote-sensing (RS) technique in the district Khanewal, Punjab, Pakistan. Data were pre-processed using ERDAS imagine 15 and Arc GIS 10.4 software for layer stacking, mosaicking, and sub-setting of Landsat images. After pre-processing, the supervised classification scheme was applied for the years 1980, 2000, and 2020, which explains the maximum likelihood algorithm to identify LULC changes observed in the study area. "Built-up area" in 1980 occupied 1.75% but in 2020, the build-up area increased (5.27%) compared to 2020. Vegetation area was decreased by 4.12% from 1980 to 2020 in district Khanewal. It was observed that there has been a rapid change in vegetation area to build-up area. The LST values were increased by 0.50°C from 1980 to 2020 due to the increasing build-up area from East to West direction in district Khanewal. Maximum and minimum normalized difference vegetation index (NDVI) values were observed 0.72 and −0.2 for 1980 and 2020. The regression line produced a definitive explanation, showing a strong negative correlation with NDVI and LST. The outcomes of this study indicated that a dramatic transformation took place in district Khanewal regarding a decrease in greenness due to a rapid increase in population density, urban growth, and other infrastructural developments. Thus, these results will be used in regional and urban planning and will be used for managing agriculture in the coming years of rapid environmental changes.

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Section: Introductionmentioning

confidence: 99%

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Hussain

Karuppannan

2021

Geology, Ecology, and Landscapes

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“…The micro-climate of the Bangkok metropolitan region in Thailand was recently estimated relative to the city's future expansion [39]. The results showed that modification of the vegetated areas in the city's western region with low-rise and mid-rise buildings would increase the future surface temperature of the region by approximately 1 to 2 • C. Other studies conducted in Nigeria's cities of Abuja [21] and Potiskum [40], China's urban area of Shenzhen [41], Turkey's Sivas City [23], and five coastal cities in Pakistan [42] have demonstrated the relationship between LULC changes and LST using various satellite data and GIS techniques. However, comprehensive studies of cities in developing countries such as Nigeria are still limited.…”

Section: Introductionmentioning

confidence: 91%

Thirty Years of Land Use/Land Cover Changes and Their Impact on Urban Climate: A Study of Kano Metropolis, Nigeria

Koko

Abubakar

et al. 2021

Land

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Rapid urban expansion and the alteration of global land use/land cover (LULC) patterns have contributed substantially to the modification of urban climate, due to variations in Land Surface Temperature (LST). In this study, the LULC change dynamics of Kano metropolis, Nigeria, were analysed over the last three decades, i.e., 1990–2020, using multispectral satellite data to understand the impact of urbanization on LST in the study area. The Maximum Likelihood classification method and the Mono-window algorithm were utilised in classifying land uses and retrieving LST data. Spectral indices comprising the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) were also computed. A linear regression analysis was employed in order to examine the correlation between land surface temperature and the various spectral indices. The results indicate significant LULC changes and urban expansion of 152.55 sq. km from 1991 to 2020. During the study period, the city’s barren land and water bodies declined by approximately 172.58 sq. km and 26.55 sq. km, respectively, while vegetation increased slightly by 46.58 sq. km. Further analysis showed a negative correlation between NDVI and LST with a Pearson determination coefficient (R2) of 0.6145, 0.5644, 0.5402, and 0.5184 in 1991, 2000, 2010, and 2020 respectively. NDBI correlated positively with LST, having an R2 of 0.4132 in 1991, 0.3965 in 2000, 0.3907 in 2010, and 0.3300 in 2020. The findings of this study provide critical climatic data useful to policy- and decision-makers in optimizing land use and mitigating the impact of urban heat through sustainable urban development.

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“…NDVI values also help with the study of plants' global and regional ecological cycles. The vegetation response to environmental changes, plant life cycles and vegetation health can all be observed by NDVI (Workie and Debella, 2018;Rizvi et al, 2021;Sajan et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Monitoring Land Surface Temperature Relationship to Land Use and Land Cover in Hai Duong Province, Vietnam

Thien,

Ovsepyan,

Phuong

2024

Environ. Nat. Resour. J.

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This study utilised remote sensing data and ArcGIS 10.8 software to evaluate changes in land use and land cover (LULC) and their effects on land surface temperature (LST) in Hai Duong Province, Vietnam, from 1992 to 2022. Landsat satellite data were pre-processed and classified using supervised methods for the years 1992, 2010, and 2022. In 1992, vegetation cover accounted for 57.89% of land cover, increasing to 84.49% in 2010, but then decreasing again to 66.67% in 2022. In contrast, the built-up area consistently increased, from 2.88% in 1992 to 29.35% in 2022, as most of the barren land present in 1992 became built-up area in 2022. The LST values were calculated from the thermal bands for the years 1992, 2010, and 2022 and ranged from 16.09°C to 34.27°C, 17.04°C to 36.74°C, and 11.03°C to 28.44°C, respectively. In addition, the Normalized Difference Vegetation Index (NDVI) values were calculated using the near-infrared band and the red band, with values ranging from -0.40 to 0.70 over the study period. A linear regression analysis indicated a shift in the correlation between NDVI and LST from positive to negative. This study highlights the significant transformation that occurred in Hai Duong Province due to rapid population density increases, urban growth and infrastructure development, leading to a decline in greenery. These LULC changes can cause severe environmental damage. These research findings will assist policymakers in formulating management strategies and sustainable land-use plans to minimize potential harm and promote sustainable development in the area.

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The Surface Urban Heat Island Intensity and Urban Expansion: A comparative analysis for the coastal areas of Pakistan

Cited by 30 publications

References 65 publications

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Thirty Years of Land Use/Land Cover Changes and Their Impact on Urban Climate: A Study of Kano Metropolis, Nigeria

Monitoring Land Surface Temperature Relationship to Land Use and Land Cover in Hai Duong Province, Vietnam

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