Abstract
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.
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