Abstract
Globally, rapid and haphazard urban growth has induced land use land cover (LULC) transformations in cities and their surroundings. The cities located in the Himalayan foothills have experienced tremendous urban growth in recent years. In this context, urban growth modeling integrated with remote sensing and geoinformatics assists to predict the future urban growth pattern. Therefore, the urban growth pattern of Jammu Urban Agglomeration (UA) from 1991 to 2021 is assessed in this paper. Shannon’s entropy index assesses the trend of built-up expansion in Jammu UA. Further, the upcoming urban growth for the year 2031 was predicted by integrating artificial neural network-multi-layer perceptron (ANN-MLP) and cellular automata (CA) model. The results revealed a substantial rise in built-up land cover while fallow land, vegetation, agriculture, and water body land cover decreased during 1991–2021. The occurrence of dispersed growth in Jammu UA was specified by the entropy index. The predicted urban growth pattern for the year 2031 showcased a further escalation in the built-up land cover while other land cover categories continued declining trend. Overall, such an urban growth pattern is unsustainable for Jammu UA, and there is an urgent requirement of urban containment measures.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
United Nations: World Urbanization Prospects: The 2014 Revision. New York (2015). https://doi.org/10.18356/527e5125-en
Government of India: India HABITAT III National Report. New Delhi (2016)
Behera, M.D., Tripathi, P., Das, P., Srivastava, S.K., Roy, P.S., Joshi, C., Behera, P.R., Deka, J., Kumar, P., Khan, M.L., Tripathi, O.P., Dash, T., Krishnamurthy, Y.V.N.: Remote sensing based deforestation analysis in Mahanadi and Brahmaputra river basin in India since 1985. J. Environ. Manage. 206, 1192–1203 (2018). https://doi.org/10.1016/j.jenvman.2017.10.015
Nkeki, F.N.: Spatio-temporal analysis of land use transition and urban growth characterization in Benin metropolitan region, Nigeria. Remote Sens. Appl. Soc. Environ. 4, 119–137 (2016). https://doi.org/10.1016/j.rsase.2016.08.002
Chettry, V., Surawar, M.: Assessment of urban sprawl characteristics in Indian cities using remote sensing: case studies of Patna, Ranchi, and Srinagar. Environ. Dev. Sustain. 23, 11913–11935 (2021). https://doi.org/10.1007/s10668-020-01149-3
Chettry, V., Surawar, M.: Urban sprawl assessment in Raipur and Bhubaneswar urban agglomerations from 1991 to 2018 using geoinformatics. Arab. J. Geosci. 13, 667 (2020). https://doi.org/10.1007/s12517-020-05693-0
Mansour, S., Al-Belushi, M., Al-Awadhi, T.: Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques. Land Use Policy 91 (2020). https://doi.org/10.1016/j.landusepol.2019.104414
Yang, Y., Zhang, L., Ye, Y., Wang, Z.: Curbing sprawl with development-limiting boundaries in urban China: A review of literature. J. Plan. Lit. 35, 25–40 (2020). https://doi.org/10.1177/0885412219874145
Yang, J., Gong, J., Tang, W., Shen, Y., Liu, C., Gao, J.: Delineation of urban growth boundaries using a patch-based cellular automata model under multiple spatial and socio-economic scenarios. Sustainability 11, 6159 (2019). https://doi.org/10.3390/su11216159
Bharath, H.A., Chandan, M.C., Vinay, S., Ramachandra, T.V: Modelling urban dynamics in rapidly urbanising Indian cities. Egypt. J. Remote Sens. Sp. Sci. 1–10 (2017). https://doi.org/10.1016/j.ejrs.2017.08.002
Wang, W., Zhang, X., Wu, Y., Zhou, L., Skitmore, M.: Development priority zoning in China and its impact on urban growth management strategy. Cities 62, 1–9 (2017). https://doi.org/10.1016/j.cities.2016.11.009
Zhuang, Z., Li, K., Liu, J., Cheng, Q., Gao, Y., Shan, J., Cai, L., Huang, Q., Chen, Y., Chen, D.: China’s new urban space regulation policies: a study of urban development boundary delineations. Sustainability 9, 45 (2017). https://doi.org/10.3390/su9010045
Zheng, X.Q., Lv, L.N.: A WOE method for urban growth boundary delineation and its applications to land use planning. Int. J. Geogr. Inf. Sci. 30, 691–707 (2016). https://doi.org/10.1080/13658816.2015.1091461
Bharath, A.H., Vinay, S., Ramachandra, T.V: Agent based modelling urban dynamics of Bhopal, India. J. Settlements Spat. Plan. 7, 1–14 (2016). https://doi.org/10.19188/01JSSP012016
Mondal, B., Chakraborti, S., Das, D.N., Joshi, P.K., Maity, S., Pramanik, M.K., Chatterjee, S.: Comparison of spatial modelling approaches to simulate urban growth: a case study on Udaipur city, India. Geocarto Int. 35, 411–433 (2020). https://doi.org/10.1080/10106049.2018.1520922
Padmanaban, R., Bhowmik, A.K., Cabral, P., Zamyatin, A., Almegdadi, O., Wang, S.: Modelling urban sprawl using remotely sensed data: a case study of Chennai city, Tamilnadu. Entropy 19, 1–14 (2017). https://doi.org/10.3390/e19040163
Pandey, B., Joshi, P.K.: Numerical modelling spatial patterns of urban growth in Chandigarh and surrounding region (India) using multi-agent systems. Model. Earth Syst. Environ. 1, 1–14 (2015). https://doi.org/10.1007/s40808-015-0005-6
Dame, J., Schmidt, S., Müller, J., Nüsser, M.: Urbanisation and socio-ecological challenges in high mountain towns : insights from Leh (Ladakh), India. Landsc. Urban Plan. 189, 189–199 (2019). https://doi.org/10.1016/j.landurbplan.2019.04.017
Nengroo, Z.A., Bhat, M.S., Kuchay, N.A.: Measuring urban sprawl of Srinagar city, Jammu and Kashmir. India. J. Urban Manag. 6, 45–55 (2017). https://doi.org/10.1016/j.jum.2017.08.001
Kumar, A.D.: Analysing urban sprawl and land consumption patterns in major capital cities in the Himalayan region using geoinformatics. Appl. Geogr. 89, 112–123 (2017). https://doi.org/10.1016/j.apgeog.2017.10.010
Singh, L., Singh, H.: Managing natural resources and environmental challenges in the face of urban sprawl in Indian Himalayan City of Jammu. J. Indian Soc. Remote Sens. (2020). https://doi.org/10.1007/s12524-020-01133-4
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Chettry, V., Manisha, K. (2022). Assessing and Predicting Urban Growth Patterns Using ANN-MLP and CA Model in Jammu Urban Agglomeration, India. In: Das, B., Patgiri, R., Bandyopadhyay, S., Balas, V.E. (eds) Modeling, Simulation and Optimization. Smart Innovation, Systems and Technologies, vol 292. Springer, Singapore. https://doi.org/10.1007/978-981-19-0836-1_30
Download citation
DOI: https://doi.org/10.1007/978-981-19-0836-1_30
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-0835-4
Online ISBN: 978-981-19-0836-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)