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<p>The rapid and haphazard expansion of built-up structures, driven by demographic increase and urbanisation, has resulted in significant alterations to land use/land cover (LULC), transforming natural landscapes into concrete structures. This phenomenon is particularly pronounced in arid and semi-arid areas, which are characterized by ecologically sensitive environments. This study investigates the past and the present LULC changes in Jaipur City and forecasts future scenarios utilising the hybrid CA-ANN (cellular automata-artificial neural networks) technique. The LULC transitions from 1991 to 2022 are analysed through supervised classification employing a maximum likelihood classifier on multispectral satellite images sourced from USGS (United States Geological Survey). High-resolution Google Earth images, field surveys, and geo-tagged photographs further supplement the data. Category-wise transitions are analysed using a cross matrix. Future simulations for 2032 and 2042 are produced utilising the MOLUSCE (Modules for Land Use Change Evaluation) plugin, integrating the spatial variables including slope, aspect, elevation, rainfall, temperature, groundwater, soil type, distance from waterbodies and roads. The study indicates a notable growth in built-up land from 26.28% in 1991 to 64.67% in 2022, projected to reach 74.16% by 2042, largely at the loss of vegetation cover and agricultural/open spaces. Urban expansion in Jaipur followed a radial pattern, initially constrained by hilly terrain to the north and east but later extending into these regions as new settlements developed. The findings underscore critical environmental impacts, increased aridity, raised surface temperatures, intensified urban heat island (UHI) effect, deteriorating air quality, and biodiversity loss, stressing the importance of sustainable urban planning and heat management strategies.</p>

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Comprehensive Assessment of Land Use/Land Cover Transformations and Future Projections in a Semi-arid Metropolitan City Utilising Artificial Neural Network- Based Cellular Automation

  • 期刊论文

  • 发表日期：

    2025年12月4日

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  • Neha Khajuria,
  • S. P. Kaushik

摘要

The rapid and haphazard expansion of built-up structures, driven by demographic increase and urbanisation, has resulted in significant alterations to land use/land cover (LULC), transforming natural landscapes into concrete structures. This phenomenon is particularly pronounced in arid and semi-arid areas, which are characterized by ecologically sensitive environments. This study investigates the past and the present LULC changes in Jaipur City and forecasts future scenarios utilising the hybrid CA-ANN (cellular automata-artificial neural networks) technique. The LULC transitions from 1991 to 2022 are analysed through supervised classification employing a maximum likelihood classifier on multispectral satellite images sourced from USGS (United States Geological Survey). High-resolution Google Earth images, field surveys, and geo-tagged photographs further supplement the data. Category-wise transitions are analysed using a cross matrix. Future simulations for 2032 and 2042 are produced utilising the MOLUSCE (Modules for Land Use Change Evaluation) plugin, integrating the spatial variables including slope, aspect, elevation, rainfall, temperature, groundwater, soil type, distance from waterbodies and roads. The study indicates a notable growth in built-up land from 26.28% in 1991 to 64.67% in 2022, projected to reach 74.16% by 2042, largely at the loss of vegetation cover and agricultural/open spaces. Urban expansion in Jaipur followed a radial pattern, initially constrained by hilly terrain to the north and east but later extending into these regions as new settlements developed. The findings underscore critical environmental impacts, increased aridity, raised surface temperatures, intensified urban heat island (UHI) effect, deteriorating air quality, and biodiversity loss, stressing the importance of sustainable urban planning and heat management strategies.