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Rapid urbanization presents significant challenges for infrastructure development and environmental sustainability. This study introduces a robust integrated geospatial framework that utilizes advanced machine learning algorithms to analyze urban growth patterns in Bhopal, India, from 1992 to 2042. By applying the Maximum Likelihood Classification (MLC) algorithm, Land Use Land Cover (LULC) maps were created for the years 1992, 2002, 2012, and 2022, categorizing the entire area into Built-Up, Vegetation, Water Body, and Barelands. The MLC mapping demonstrated high accuracy, with Kappa values of 0.890 (1992), 0.894 (2002), 0.875 (2012), and 0.886 (2022). From 1992 to 2022, Bhopal experienced notable LULC changes: built-up areas expanded from 169.98 sq.km to 224.90 sq.km (32.3% increase), vegetation decreased from 80.58 km2 to 64.81 km2 (19.6% reduction), barelands slightly decreased from 543.11 sq.km to 538.91 sq.km, and water bodies declined from 83.33 sq.km to 78.09 sq.km. Further, the Multi-Layer Perceptron-Markov Chain Analysis (MLP-MCA) model projections indicate that built-up areas will rise to 203.74 sq.km by 2032 and 224.90 sq.km by 2042, while vegetation is anticipated to continue declining, and water bodies will experience minimal changes. These results highlight the urgent need for effective urban planning policies that harmonize development with environmental conservation to mitigate the adverse effects of urbanization.

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A Spatiotemporal Urban Growth Assessment in Bhopal, India from 1992 to 2042 Using Machine Learning Algorithms

  • 章节

  • 发表日期：

    2025年

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  • Shobhit Chaturvedi,
  • Jay Amin,
  • Kratika Sharma

摘要

Rapid urbanization presents significant challenges for infrastructure development and environmental sustainability. This study introduces a robust integrated geospatial framework that utilizes advanced machine learning algorithms to analyze urban growth patterns in Bhopal, India, from 1992 to 2042. By applying the Maximum Likelihood Classification (MLC) algorithm, Land Use Land Cover (LULC) maps were created for the years 1992, 2002, 2012, and 2022, categorizing the entire area into Built-Up, Vegetation, Water Body, and Barelands. The MLC mapping demonstrated high accuracy, with Kappa values of 0.890 (1992), 0.894 (2002), 0.875 (2012), and 0.886 (2022). From 1992 to 2022, Bhopal experienced notable LULC changes: built-up areas expanded from 169.98 sq.km to 224.90 sq.km (32.3% increase), vegetation decreased from 80.58 km2 to 64.81 km2 (19.6% reduction), barelands slightly decreased from 543.11 sq.km to 538.91 sq.km, and water bodies declined from 83.33 sq.km to 78.09 sq.km. Further, the Multi-Layer Perceptron-Markov Chain Analysis (MLP-MCA) model projections indicate that built-up areas will rise to 203.74 sq.km by 2032 and 224.90 sq.km by 2042, while vegetation is anticipated to continue declining, and water bodies will experience minimal changes. These results highlight the urgent need for effective urban planning policies that harmonize development with environmental conservation to mitigate the adverse effects of urbanization.