Studying urbanization pattern in Sambalpur City during 1992-2042 using CA-ANN, and Markov-Chain model

Abstract

Models of land use/land cover (LULC) are crucial for assessing changes in LULC, forecasting land use needs, and providing guidance for appropriate land use planning and management, especially in urban areas. Urban sprawl is one of the main causes of the erratic variation in LULC around the globe. In this study, we used the CA-ANN and Markov-Chain models to analyze the LULC simulation based on LULC patterns from previous decades as well as the directional changes of urban expansion in Sambalpur city. We used the random forest (RF) model and Landsat imagery to prepare LULC maps for the years 1992, 2002, 2012, and 2022 for better classification accuracy. The result showed that the overall accuracy and kappa values were 94.24%, 89%, 94%, and 90% and 0.92, 0.80, 0.90, and 0.85, respectively, for the selective years. Based on the transition matrix model (1992–2012), the LULC map of the year 2022 was obtained and validated, and subsequently, LULC maps for the years 2032 and 2042 were predicted with a Kappa value of 94.97% and 93.24%, respectively. The findings indicate that the largest proportion of bare land underwent conversion within the settlement area, with the highest degree of sprawl observed in the northwestern direction and 4-kilometer buffer zones. These findings define current and future patterns in LULC and offer vital information for planning and sustainable land use management in Sambalpur city.

Keywords

• Land use/land cover
• CA-ANN
• Markov- Chain
• Urban Sprawl
• Random Forest Model

References

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