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<p>Urban land-use and land-cover dynamics in many fast-growing Indian cities often deviate from Master Plan trajectories and sustainability goals, including those set under SDG 11. Hyderabad exemplifies this challenge, where the urban landscape has undergone a profound transformation over five decades, outpacing planning blueprints. This study investigates long-term urban sprawl and densification patterns in the Hyderabad Metropolitan Region from 1975 to 2024 using multi-temporal satellite data (Landsat MSS/TM: 80 and 30&#xa0;m; IRS/ResourceSat: 5.8&#xa0;m) and object-based classification. The objectives are to map spatiotemporal changes across nine LULC classes, quantify expansion and densification using spatial metrics, and assess their implications for SDG 11.3 and urban green space equity. Results reveal a 188% increase in built-up area (from 183.05&#xa0;km² to 527.23&#xa0;km²), alongside an 84% loss of farmland and a 59% decrease in vegetation cover. Forest cover remained stable due to its protected status. Shannon’s entropy (0.90) confirms ongoing sprawl, while the compactness index (2.29) and population-weighted density (~ 19,000 persons/km²) reveal accelerating densification since 2008—processes that occur simultaneously as peripheral expansion continues alongside core vertical growth. Per capita green space averages 20.25&#xa0;m², surpassing the WHO minimums but masking inequitable distribution: the Central (12.40&#xa0;m²) and South (14.80&#xa0;m²) zones lag behind the West (31.20&#xa0;m²). The LULC classification achieved &gt; 87% overall accuracy (kappa &gt; 0.84), validated against Survey of India toposheets (1975–1989) and Google Earth imagery (1997–2024). By explicitly addressing multi-resolution data harmonization through OBIA and cross-verification, this study offers a reproducible framework suitable for data-limited contexts and provides planners with evidence-based benchmarks for SDG 11.3 monitoring and zone-specific interventions to reconcile densification with green space equity.</p>

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Spatiotemporal analysis of urban sprawl and densification in Hyderabad India across five decades

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月29日

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  • Ravali Bharadwaj,
  • Harish Gupta,
  • M. Gopal Naik,
  • Srinivasulu Ale,
  • Fouad H Jaber

摘要

Urban land-use and land-cover dynamics in many fast-growing Indian cities often deviate from Master Plan trajectories and sustainability goals, including those set under SDG 11. Hyderabad exemplifies this challenge, where the urban landscape has undergone a profound transformation over five decades, outpacing planning blueprints. This study investigates long-term urban sprawl and densification patterns in the Hyderabad Metropolitan Region from 1975 to 2024 using multi-temporal satellite data (Landsat MSS/TM: 80 and 30 m; IRS/ResourceSat: 5.8 m) and object-based classification. The objectives are to map spatiotemporal changes across nine LULC classes, quantify expansion and densification using spatial metrics, and assess their implications for SDG 11.3 and urban green space equity. Results reveal a 188% increase in built-up area (from 183.05 km² to 527.23 km²), alongside an 84% loss of farmland and a 59% decrease in vegetation cover. Forest cover remained stable due to its protected status. Shannon’s entropy (0.90) confirms ongoing sprawl, while the compactness index (2.29) and population-weighted density (~ 19,000 persons/km²) reveal accelerating densification since 2008—processes that occur simultaneously as peripheral expansion continues alongside core vertical growth. Per capita green space averages 20.25 m², surpassing the WHO minimums but masking inequitable distribution: the Central (12.40 m²) and South (14.80 m²) zones lag behind the West (31.20 m²). The LULC classification achieved > 87% overall accuracy (kappa > 0.84), validated against Survey of India toposheets (1975–1989) and Google Earth imagery (1997–2024). By explicitly addressing multi-resolution data harmonization through OBIA and cross-verification, this study offers a reproducible framework suitable for data-limited contexts and provides planners with evidence-based benchmarks for SDG 11.3 monitoring and zone-specific interventions to reconcile densification with green space equity.