Land use/land cover (LU/LC) change dynamics using indices overlay method in Gautam Buddha Nagar District-India

Kumari, Babita; Shahfahad, .; Tayyab, Mohammad; Ahmed, Ishita Afreen; Baig, Mirza Razi Imam; Ali, Mohammed Mahmood; Asıf,; Usmani, Tariq Mahmood

doi:10.1007/s10708-021-10374-w

“…In other South Asian countries including India and Pakistan, a similar trend of rapid urban growth has been observed in many less developed district towns., For instance.In India, Purulia district town has grown by 122% in terms of built-up area between 1998 and 2018 [41], while Gautam Buddha Nagar district town reported an unprecedented increase of nearly 419% between 2003 and 2015 [42]. In Pakistan, the built-up area was increased by 158% in similarly sized Sialkot [43] and 146% in Sargodha [44].…”

Section: Discussionmentioning

confidence: 99%

Rapid and unplanned urbanization in the least developed districts of Bangladesh: a case study from Jamalpur using geospatial techniques

Mamun

¹

,

Islam

²

,

Okely

³

et al. 2022

Discov Sustain

1

0

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Sustainable urban development is a key compoment in the United Nation’s Sustainable Development Goals. Monitoring urbanization is critical for planners, governments and non-governmental organizations, and scientists to design policies that maximize the use of natural resources and accommodate development while reducing environmental effects. This research aims to analyze how urbanization patterns have changed in the largely unknown least developed regions of Bangladesh. Multispectral satellite imageries over 30 years (1991 to 2021) were used to analyze the urbanization pattern of Jamapur district. Utilizing object-based image classification and on-field validation for seven Land Use and Land Cover classes, it was found that built-up area expanded by 748.92% during the past three decades while depleting bare soil (− 97.65%), deep waterbody (− 79.33%), shallow waterbody (− 8.46%), light vegetation (− 14.28%) and agricultural land (− 26.33%).. Because of increased in built-ups, the land surface temperatures (LST) were also increased over the study period (the minimun recorded LST were 12.84 °C, 15.89 °C, 15.8 °C and 17 °C while the maximun LST were 17.93 °C, 23.7 °C, 23.79 °C and 26.73 °C for the year of 1991, 2001, 2013 and 2021 respectively). This study will act as a baseline for future studies It be insightful to urban planners and policymakers in developing countries regarding urban sustainability and minimizing urban risks and hazards in the least developed districts.

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“…This process involves altering the natural and functional components of the environment and accelerates the transition from natural landscapes to urban structures (Castle and Crooks 2006;Dahal et al 2016;Ahmad 2020, Jamal et al 2022;Shahfahad et al 2023;Kumari et al 2021;Naikoo et al 2022). In developing countries, urbanization often occurs without adequate infrastructure and services, resulting in haphazard changes in land use patterns (Rahaman et al 2019;Ajmal et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Determining Urban Growth in Response to Land Use Dynamics using Multi-Layer Perceptron and Markov Chain Models in a Metropolitan city: Past and Future

Jamal

¹

,

Ali

²

2023

Preprint

0

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Monitoring changes in land use and land cover over a specific timeframe, as well as predicting future trends, is of paramount importance due to its increasing influence on local, regional, and global environments. This study focuses on analyzing the dynamics of land use and land cover patterns, rapid urban expansion, and the underlying driving forces in the past three decades in KMC, West Bengal. To establish the relationship between land use/land cover dynamics and built-up expansion from 1990 to 2020, this study utilizes multi-temporal satellite data (Landsat-5 TM, Landsat-8 OLI) and census data. The analysis reveals that the highest transformation occurred in green spaces, followed by fallow lands and water bodies, as they were converted into built-up areas. Kolkata, being the third-ranking megacity in India and the capital of West Bengal, faces immense pressure for land transformation due to its Kolkata Municipal Corporation's floating population of 6 million, surpassing the total residential population of 4.5 million. This rapid urbanization is driven by the need for residential facilities, administrative services, business and commercial services, and employment opportunities. Statistical analysis demonstrates a strong correlation (coefficient of determination = 0.93) between built-up expansion and population growth. The substantial floating and residential population exert significant pressure for fast built-up expansion, resulting in the transformation of land use and land covers, with adverse environmental impacts such as loss of biodiversity, air and noise pollution, soil and water pollution, creation of microclimates, and the urban heat island effect.

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“…This process involves altering the natural and functional components of the environment and accelerates the transition from natural landscapes to urban structures (Castle and Crooks 2006;Dahal et al 2016;Ahmad 2020, Jamal et al 2022;Shahfahad et al 2023;Kumari et al 2021;Naikoo et al 2022). In developing countries, urbanization often occurs without adequate infrastructure and services, resulting in haphazard changes in land use patterns (Rahaman et al 2019;Ajmal et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Determining urban growth in response to land use dynamics using multilayer perceptron and Markov chain models in a metropolitan city: past and future

Jamal,

Ali

2023

Environ Dev Sustain

1

0

View full text Add to dashboard Cite

Monitoring changes in land use and land cover over a specific timeframe, as well as predicting future trends, is of paramount importance due to its increasing influence on local, regional, and global environments. This study focuses on analyzing the dynamics of land use and land cover patterns, rapid urban expansion, and the underlying driving forces in the past three decades in KMC, West Bengal. To establish the relationship between land use/land cover dynamics and built-up expansion from 1990 to 2020, this study utilizes multi-temporal satellite data (Landsat-5 TM, Landsat-8 OLI) and census data. The analysis reveals that the highest transformation occurred in green spaces, followed by fallow lands and water bodies, as they were converted into built-up areas. Kolkata, being the third-ranking megacity in India and the capital of West Bengal, faces immense pressure for land transformation due to its Kolkata Municipal Corporation's floating population of 6 million, surpassing the total residential population of 4.5 million. This rapid urbanization is driven by the need for residential facilities, administrative services, business and commercial services, and employment opportunities. Statistical analysis demonstrates a strong correlation (coefficient of determination = 0.93) between built-up expansion and population growth. The substantial floating and residential population exert significant pressure for fast built-up expansion, resulting in the transformation of land use and land covers, with adverse environmental impacts such as loss of biodiversity, air and noise pollution, soil and water pollution, creation of microclimates, and the urban heat island effect. Keywords Land use/land cover • Land transformation • Urban expansion • Regression analysis • Kolkata Municipal

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Land use/land cover (LU/LC) change dynamics using indices overlay method in Gautam Buddha Nagar District-India

Cited by 14 publications

References 79 publications

Rapid and unplanned urbanization in the least developed districts of Bangladesh: a case study from Jamalpur using geospatial techniques

Rapid and unplanned urbanization in the least developed districts of Bangladesh: a case study from Jamalpur using geospatial techniques

Determining Urban Growth in Response to Land Use Dynamics using Multi-Layer Perceptron and Markov Chain Models in a Metropolitan city: Past and Future

Determining urban growth in response to land use dynamics using multilayer perceptron and Markov chain models in a metropolitan city: past and future

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