147
© Springer Nature Switzerland AG 2021
Rukhsana et al. (eds.), Habitat, Ecology and Ekistics, Advances in Asian
Human-Environmental Research, https://doi.org/10.1007/978-3-030-49115-4_8
Chapter 8
Spatio-Temporal Transformation of Urban
Built-Up Areas for Sustainable
Environmental Management in Selected
Cities of West Bengal
Rajat Kumar Paul and Pradip Patra
8.1 Introduction
Urbanisation is one of the major issues in the developing countries. It is a continuous process of growth and development and transformation of demography, society
and culture. It is estimated that almost 60% of the global population (4.9 billion)
will live in urban areas than in the countryside by 2030 (UN Habitat 2003).
Urbanisation began to accelerate after independence in India, and the reason behind
it is for mixed economy and development of the private sector in the country (Datta
2006). According to Census of India, decadal percentage of urban population to
total population from 1991, 2001 and 2011 were 21.34%, 27.78% and 31.36%,
respectively. Increasing population require more built-up area. Due to unplanned
urbanisation in India, different problems have arisen like loss of water quality, environmental degradation, climate change, groundwater depletion and many more
(Uttara et al. 2012a, b; Zhang et al. 2010; Anisujjaman 2015). So it is a very much
concerning issue in terms of different government policy action.
The calculation of built-up area and its change determination has changed over
the time. To analyse the areal growth of the built-up area, remote sensing technique
has become an important technique. Using multi-temporal images, growth of a
built-up area and its spatial extent can be easily monitored. Different techniques can
be used to determine the built-up area from satellite images like utilisation of neural
networks (Seto and Liu 2003), supervised or unsupervised classifications (Masek
et al. 2000; Ward et al. 2000; Zhang et al. 2002; Xian and Crane 2005; Lu and Weng
2005; Ukwattage and Dayawansa 2012), modern techniques like object-based classifications (Guindon et al. 2004; Zhou et al. 2012), support vector machines (Huang
and Lee 2004; Melgani and Bruzzone 2004; Pal and Mather 2005) and Tasseled Cap
transformation (Deng and Wu 2012). Besides their methods, different indices have
R. K. Paul (*) · P. Patra
Department of Geography, University of Calcutta, Kolkata, West Bengal, India
© Springer Nature Switzerland AG 2021
Rukhsana et al. (eds.), Habitat, Ecology and Ekistics, Advances in Asian
Human-Environmental Research, https://doi.org/10.1007/978-3-030-49115-4_8
Chapter 8
Spatio-Temporal Transformation of Urban
Built-Up Areas for Sustainable
Environmental Management in Selected
Cities of West Bengal
Rajat Kumar Paul and Pradip Patra
8.1 Introduction
Urbanisation is one of the major issues in the developing countries. It is a continuous process of growth and development and transformation of demography, society
and culture. It is estimated that almost 60% of the global population (4.9 billion)
will live in urban areas than in the countryside by 2030 (UN Habitat 2003).
Urbanisation began to accelerate after independence in India, and the reason behind
it is for mixed economy and development of the private sector in the country (Datta
2006). According to Census of India, decadal percentage of urban population to
total population from 1991, 2001 and 2011 were 21.34%, 27.78% and 31.36%,
respectively. Increasing population require more built-up area. Due to unplanned
urbanisation in India, different problems have arisen like loss of water quality, environmental degradation, climate change, groundwater depletion and many more
(Uttara et al. 2012a, b; Zhang et al. 2010; Anisujjaman 2015). So it is a very much
concerning issue in terms of different government policy action.
The calculation of built-up area and its change determination has changed over
the time. To analyse the areal growth of the built-up area, remote sensing technique
has become an important technique. Using multi-temporal images, growth of a
built-up area and its spatial extent can be easily monitored. Different techniques can
be used to determine the built-up area from satellite images like utilisation of neural
networks (Seto and Liu 2003), supervised or unsupervised classifications (Masek
et al. 2000; Ward et al. 2000; Zhang et al. 2002; Xian and Crane 2005; Lu and Weng
2005; Ukwattage and Dayawansa 2012), modern techniques like object-based classifications (Guindon et al. 2004; Zhou et al. 2012), support vector machines (Huang
and Lee 2004; Melgani and Bruzzone 2004; Pal and Mather 2005) and Tasseled Cap
transformation (Deng and Wu 2012). Besides their methods, different indices have
R. K. Paul (*) · P. Patra
Department of Geography, University of Calcutta, Kolkata, West Bengal, India