Abstract
Medium-sized industrial cities account for a growing share of Indian urbanisation, yet their land transformation remains poorly documented. This study assesses urban expansion and land use/land cover (LULC) change in Jamshedpur, Jharkhand, over a fixed 250 km² extent between 2000 and 2024. Landsat TM, ETM+, OLI and OLI-2 imagery for 2000, 2010, 2020 and 2024 was classified into five classes using the maximum likelihood classifier, and the results were evaluated through error matrices and the Kappa coefficient. Post-classification comparison, land consumption indicators, Shannon’s entropy, proximity analysis, the Normalised Difference Vegetation Index (NDVI), land surface temperature (LST) and a CA-Markov model were used to examine the extent, pattern, consequences and future trajectory of growth. Overall accuracy rose from 86.80% to 92.40%, with Kappa values between 0.825 and 0.896. Built-up land expanded from 38.75 km² to 100.50 km² (159.35%), while agricultural land, vegetation and water bodies declined by 39.88%, 33.31% and 26.40%, respectively. About three-quarters of new built-up land was drawn directly from agricultural and vegetated land. Relative entropy increased from 0.9843 to 0.9918, the land consumption rate rose from 35.17 to 57.35 m² per person, and growth beyond 8 km from the centre exceeded 500%, indicating dispersed peripheral expansion. Mean NDVI fell by 34.95%, and urban heat island intensity rose from 5.10 °C to 7.40 °C. Under a business-as-usual scenario, built-up land would occupy 55.02% of the area by 2040. The findings call for density-oriented planning, protection of agricultural land and small water bodies, and deliberate sequencing of infrastructure.
Introduction
1.1 Urban Growth in the Indian Context
India is in the middle of a long urban transition. Cities are absorbing an increasing share of the national population and economic activity, and their physical footprint is growing even faster than their populations. Much of the research on this transition has concentrated on metropolitan regions such as Delhi, Bengaluru and Chennai, where satellite-based studies have documented rapid paving of land and the loss of lakes, farmland and green spaces (Aithal & Ramachandra, 2016; Ramachandra et al., 2015; Tripathy & Kumar, 2019). Medium-sized cities have received less attention, although they are now among the fastest-growing urban places in the country and are expanding in a manner that is frequently dispersed and weakly regulated (Chettry & Surawar, 2021).
1.2 Industrial Cities and Land Transformation
Industrial cities occupy a distinct position within this transition. Their growth is driven by a clearly identifiable economic engine, and industrial expansion generates employment, migration, housing demand and supporting infrastructure that together reshape the surrounding countryside. In eastern India, mineral-based industrial regions such as Asansol–Durgapur show how industry, mining and settlement combine to alter land cover and raise surface temperatures (Choudhury et al., 2019). Similar processes are visible in the state capital of Jharkhand, Ranchi, where built-up land has expanded rapidly into agricultural and open land (Ahmad & Goparaju, 2016). Understanding how such cities grow is essential if the economic benefits of industrialisation are to be reconciled with the protection of land, water and ecological resources.
1.3 Jamshedpur: Setting and Urban Character
Jamshedpur, in the East Singhbhum district of Jharkhand, was established in the early twentieth century as a planned company town around an integrated steel works and is widely known as the Steel City of India. It lies on the north-eastern margin of the Chota Nagpur plateau near the confluence of the Subarnarekha and Kharkai rivers, with the forested Dalma hills to the north. The urban agglomeration is administratively divided among the Jamshedpur and Mango Notified Area Committees, Jugsalai Municipality and the Adityapur Municipal Corporation, and its settlement geography is polycentric rather than concentric. The planned township with its green belts contrasts sharply with the informal growth of its fringes, and research on the adjoining Dalma Wildlife Sanctuary has already recorded steady losses of dense forest to settlement and bare land (Ranjan et al., 2016). A city-wide, multi-decadal assessment of land change, however, has been lacking.
1.4 Geospatial Technology for Land Change Monitoring
Remote sensing and geographic information systems (GIS) offer the most practical means of reconstructing land change over several decades. The free Landsat archive provides consistent 30 m multispectral observations from the 1980s onwards, and GIS supports overlay analysis, spatial metrics and modelling (Phiri & Morgenroth, 2017). Advances in classification algorithms, cloud processing platforms and artificial intelligence continue to expand these capabilities (Gorelick et al., 2017; Gu & Zeng, 2024; Talukdar et al., 2020). Together, these tools allow analysts to measure not only how much land has changed, but also where, in what form and with what environmental consequences.
1.5 Environmental Significance of Land Use Change
The replacement of vegetation, cropland and water with impervious surfaces alters runoff, groundwater recharge, habitat connectivity and local climate. Impervious surfaces absorb and re-emit more heat than vegetated or wet surfaces, which intensifies the surface urban heat island (Mathew et al., 2016; Pal & Ziaul, 2017). For an industrial city where heavy industry, dense settlement, forested hills and rivers sit in close proximity, these effects carry direct implications for public health, flood exposure and long-term sustainability. This paper therefore presents an integrated geospatial assessment of urban expansion and LULC change in Jamshedpur from 2000 to 2024, combining classification, change detection, growth metrics, environmental indicators and predictive modelling.
Conclusion
This study used multi-temporal Landsat imagery, GIS analysis and predictive modelling to assess urban expansion and LULC change in Jamshedpur from 2000 to 2024. The classifications were reliable, with overall accuracies of 86.80–92.40% and Kappa values of 0.825–0.896. Built-up land expanded by 159.35% and became the dominant land cover, while agricultural land, vegetation and water bodies declined substantially. Three-quarters of new urban land came directly from farmland and vegetation, and the transformation is effectively irreversible. Growth was dispersed and peripheral rather than compact. Rising entropy, an increasing land consumption rate, falling built-up density and outer-zone growth more than eighteen times faster than in the core all point to sprawl. The environmental costs are substantial: dense vegetation fell by nearly four-fifths, mean NDVI declined by about 35%, small water bodies largely disappeared and UHI intensity increased by 45%. If current trends continue, more than half of the study area will be built up by 2035. Several planning implications follow. Density policy offers greater leverage over land consumption than any other instrument, since the 2024 population could have been housed on about 39 km² less land at year-2000 densities. Statutory protection has demonstrably curbed conversion and should be extended to productive agricultural land and to small water bodies. Road investment should be sequenced deliberately because development follows access, and clearance of land should be phased with construction to avoid thermal and hydrological costs. Future research should apply machine learning and higher-resolution imagery, incorporate socio-economic survey data and test alternative policy scenarios to support sustainable, climate-resilient growth in Jamshedpur and similar industrial cities.
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