TY - JOUR
T1 - Understanding future urban growth, urban resilience and sustainable development of small cities using prediction-adaptation-resilience (PAR) approach
AU - Mallick, Suraj Kumar
AU - Pramanik, Malay
AU - Pradhan, Biswajeet
AU - Sahana, Mehebub
N1 - Funding Information:
The authors are greatly thankful to Suman Chakraborti for his valuable comments and suggestions at the initial stage of the article. The authors are also thankful to the editor-in-cheif Fariborz Haghighat and four anonymous reviewers for their constructive comments to improve the quality of the article.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/11/1
Y1 - 2021/11/1
N2 - Rapid urban proliferation is an indispensable and reciprocal issue in contemporary urban planning and development. This study envisages the prediction-adaptation-resilience (PAR) approach to analyze the future urban landscape resilience and sustainable development goals (SDGs). We have selected a small, unplanned growing up city, namely, Krishnanagar urban agglomeration (KUA), in India, to apply the PAR approach. Therefore, land use land cover map has been prepared for 2000, 2010, and 2020. The result shows the built-up area has been increased most in past 20 years, from 6.36 km2 to 13.23 km2. Then, the cellular automata-Markov chain model is applied to predict the future potential urban development surface for 2030 and 2040. The receiver operating characteristic (ROC) curve shows 83.6% success rate between the predicted and actual map of CA-Markov. The prediction map of 2030 and 2040 shows that the built-up area continuously expands (13.23 km2 to 16.52 km2) towards KUA's surrounding regions. Consequently, other decreasing land classes will be a threat to SDGs and urban resilience. So, people of KUA are adopting the changing hostile nature of urbanisation and urban vulnerability. Hence, this study will help the local administration to make a proper urban planning and adaptation strategies by maintaining good urban governance to achieve 8 SDGs of UN's 2030 Agenda in future.
AB - Rapid urban proliferation is an indispensable and reciprocal issue in contemporary urban planning and development. This study envisages the prediction-adaptation-resilience (PAR) approach to analyze the future urban landscape resilience and sustainable development goals (SDGs). We have selected a small, unplanned growing up city, namely, Krishnanagar urban agglomeration (KUA), in India, to apply the PAR approach. Therefore, land use land cover map has been prepared for 2000, 2010, and 2020. The result shows the built-up area has been increased most in past 20 years, from 6.36 km2 to 13.23 km2. Then, the cellular automata-Markov chain model is applied to predict the future potential urban development surface for 2030 and 2040. The receiver operating characteristic (ROC) curve shows 83.6% success rate between the predicted and actual map of CA-Markov. The prediction map of 2030 and 2040 shows that the built-up area continuously expands (13.23 km2 to 16.52 km2) towards KUA's surrounding regions. Consequently, other decreasing land classes will be a threat to SDGs and urban resilience. So, people of KUA are adopting the changing hostile nature of urbanisation and urban vulnerability. Hence, this study will help the local administration to make a proper urban planning and adaptation strategies by maintaining good urban governance to achieve 8 SDGs of UN's 2030 Agenda in future.
KW - CA-Markov chain model
KW - prediction-adaptation-resilience
KW - sustainable development goals
KW - urban governance
KW - urban resilience
UR - https://www.scopus.com/pages/publications/85111543941
U2 - 10.1016/j.scs.2021.103196
DO - 10.1016/j.scs.2021.103196
M3 - Article
SN - 2210-6707
VL - 74
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
IS - 6
M1 - 103196
ER -
