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<p>Urban expansion driven by increasing population and rapid industrial growth is crucial in developing nations’ Land Use and Land Cover (LULC) transformations. This study aims to assess the spatial characteristics of industrial cities using LULC metrics. Spatiotemporal LULC data were used to analyse and compare urban growth patterns and planning approaches for Surat, an industrial city in India. Remote Sensing (RS) data and Geographic Information Systems (GIS) software were utilised to examine LULC dynamics over the past 15 years (2005–2020). Landsat images and the Maximum Likelihood Classification method are used, and LULC is broadly classified into four categories: Water Bodies, Vegetation, Built-up and Range or Barren land. Statistical analyses and spatial mapping reveal rapid socioeconomic and industrial growth in Surat, complex urban development patterns, and multiple development nodes along major transportation routes. This research provides insights into the quantitative aspects of urban expansion through LULC transformation in industrial cities of developing countries like India. The study’s findings indicate a decline in barren land and vegetation, substantial growth in urban built-up areas, and high built-up densities in and around industrial zones as Surat experienced dynamic built-up growth, increasing from 13.43% in 2005 to 31.13% in 2020.</p>

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Spatial Analysis of Land Use and Land Cover Transformations in Industrial Cities of India Using Remote Sensing Data: A Case Study of Surat

  • 期刊论文

  • 发表日期：

    2025年8月19日

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  • Purba Biswas,
  • Priyanka Dey

摘要

Urban expansion driven by increasing population and rapid industrial growth is crucial in developing nations’ Land Use and Land Cover (LULC) transformations. This study aims to assess the spatial characteristics of industrial cities using LULC metrics. Spatiotemporal LULC data were used to analyse and compare urban growth patterns and planning approaches for Surat, an industrial city in India. Remote Sensing (RS) data and Geographic Information Systems (GIS) software were utilised to examine LULC dynamics over the past 15 years (2005–2020). Landsat images and the Maximum Likelihood Classification method are used, and LULC is broadly classified into four categories: Water Bodies, Vegetation, Built-up and Range or Barren land. Statistical analyses and spatial mapping reveal rapid socioeconomic and industrial growth in Surat, complex urban development patterns, and multiple development nodes along major transportation routes. This research provides insights into the quantitative aspects of urban expansion through LULC transformation in industrial cities of developing countries like India. The study’s findings indicate a decline in barren land and vegetation, substantial growth in urban built-up areas, and high built-up densities in and around industrial zones as Surat experienced dynamic built-up growth, increasing from 13.43% in 2005 to 31.13% in 2020.