Impact of urbanization and land surface temperature changes in a coastal town in Kerala, India

Arulbalaji, P.; Padmalal, D.; Maya, K.

doi:10.1007/s12665-020-09120-1

Cited by 29 publications

(8 citation statements)

References 53 publications

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“…The dominant typology of urban sprawl in the peri-urban areas was scatter development, indicating the prevalence of discontinuous low-density urban growth. The major cause of such development is due to dispersed pattern of settlement and industrial growth in the peri-urban areas (Arulbalaji et al 2020 ). There is an absence of coordinating agencies for the census towns located in the periphery of Thiruvananthapuram UA.…”

Section: Discussionmentioning

confidence: 99%

Peri-urban area delineation and urban sprawl quantification in Thiruvananthapuram Urban Agglomeration, India, from 2001 to 2021 using geoinformatics

Chettry

2022

Appl Geomat

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In Southeast Asia, rising population, economic growth, and lack of land supply in the city core have led to the widespread irreversible land cover transformation in peri-urban areas. Such extensive and haphazard urban growth in peri-urban areas raises concern about analyzing and promoting planned urban growth. Therefore, this paper attempts to assess land cover changes from 2001 to 2021 and delineate peri-urban areas of a midsized Indian city, i.e., Thiruvananthapuram Urban Agglomeration (UA) using geoinformatics. The maximum likelihood supervised classification tool in ArcGIS 10.3 was used to prepare land cover maps for 2001, 2007, 2014, and 2021. Further, the presence of urban sprawl in the peri-urban areas was detected through Shannon’s entropy index. The urban sprawl typologies in the peri-urban areas were quantified using the adjacent neighborhood relationships concept. The results revealed rapid growth in built-up land cover and decline in non-built-up land cover within Thiruvananthapuram UA during the study period. Peri-urban areas were delineated based on nine indicators, such as total population, population growth, population density, literacy rate, percentage of the male workforce, percentage of the female workforce, agricultural land cover, distance from urban core, and percentage of cultivators to agricultural workers. A rise in Shannon’s entropy index from 1.59 in 2001 to 2.05 in 2021 exhibited the occurrence of rapid urban sprawl in the peri-urban areas. Dominance of discontinuous low-density development, i.e., scatter development typology of urban sprawl, was observed in peri-urban areas of Thiruvananthapuram UA. Such studies using geoinformatics would assist local governments in scientifically formulating sustainable urban policies and plans.

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Section: Discussionmentioning

confidence: 99%

Peri-urban area delineation and urban sprawl quantification in Thiruvananthapuram Urban Agglomeration, India, from 2001 to 2021 using geoinformatics

Chettry

2022

Appl Geomat

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“…In developing countries a linear relationship has been observed between road expansion and increasing land surface temperature (Aboelnour & Engel, 2018;Arulbalaji et al, 2020). Small isolated urban areas and roads represent micro UHI within cities or sub rural areas, and the intensity of UHI is dependent on land cover changes in the relative composition of vegetated land, water bodies, and built-up (Chen et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

Past and Future Impacts of Urbanisation on Land Surface Temperature in Greater Cairo Over a 45 Year Period

et al. 2022

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“…The farmers can monitor the overall image of their plantations, extracted through different classification tools. These satellite images give the farmers essential information to plan better for their fields [12,13]. The function of remote sensing is to provide data that helps analyze the variabilities of temporal and spatial parameters of the environment on a large scale.…”

Section: Remote Sensingmentioning

confidence: 99%

Land-Cover Classification and its Impact on Peshawar’s Land Surface Temperature Using Remote Sensing

Islam¹,

Jan²,

Waheed³

et al. 2022

Computers, Materials &Amp; Continua

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Spatial and temporal information on urban infrastructure is essential and requires various land-cover/land-use planning and management applications. Besides, a change in infrastructure has a direct impact on other land-cover and climatic conditions. This study assessed changes in the rate and spatial distribution of Peshawar district's infrastructure and its effects on Land Surface Temperature (LST) during the years 1996 and 2019. For this purpose, firstly, satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper) plus and OLI (Operational Land Imager) of 30 m resolution were taken. Secondly, for classification and image processing, remote sensing (RS) applications ENVI (Environment for Visualising Images) and GIS (Geographic Information System) were used. Thirdly, for better visualization and more in-depth analysis of land sat images, pre-processing techniques were employed. For Land use and Land cover (LU/LC) four types of land cover areas were identified -vegetation area, water cover, urbanized area, and infertile land for the years under research. The composition of red, green, and near infra-red bands was used for supervised classification. Classified images were extracted for analyzing the relative infrastructure change. A comparative analysis for the classification of images is performed for SVM (Support Vector Machine) and ANN (Artificial Neural Network). Based on analyzing these images, the result shows the rise in the average temperature from 30.04 • C to 45.25 • C. This only possible reason is the increase in the built-up area from 78.73 to 332.78 Area km 2 from 1996 to 2019. It has also been witnessed that

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Impact of urbanization and land surface temperature changes in a coastal town in Kerala, India

Cited by 29 publications

References 53 publications

Peri-urban area delineation and urban sprawl quantification in Thiruvananthapuram Urban Agglomeration, India, from 2001 to 2021 using geoinformatics

Peri-urban area delineation and urban sprawl quantification in Thiruvananthapuram Urban Agglomeration, India, from 2001 to 2021 using geoinformatics

Past and Future Impacts of Urbanisation on Land Surface Temperature in Greater Cairo Over a 45 Year Period

Land-Cover Classification and its Impact on Peshawar’s Land Surface Temperature Using Remote Sensing

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