TY - GEN
T1 - Assessing and Predicting Urban Growth Patterns Using ANN-MLP and CA Model in Jammu Urban Agglomeration, India
AU - Chettry, Vishal
AU - Manisha, Keerti
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1007/978-981-19-0836-1_30
DO - 10.1007/978-981-19-0836-1_30
M3 - Conference contribution
AN - SCOPUS:85134317271
SN - 9789811908354
T3 - Smart Innovation, Systems and Technologies
SP - 387
EP - 397
BT - Modeling, Simulation and Optimization - Proceedings of CoMSO 2021
A2 - Das, Biplab
A2 - Patgiri, Ripon
A2 - Bandyopadhyay, Sivaji
A2 - Balas, Valentina Emilia
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Modeling, Simulation and Optimization, CoMSO 2021
Y2 - 16 December 2021 through 18 December 2021
ER -
