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Forecasting Urbanisation Along NH-63 Corridor in Jagtial District Using Spatial and Socio-Economic Data by Employing Advanced GIS and Machine Learning Techniques

Publié
Serveur de preprints
Preprints.org
DOI
10.20944/preprints202609.0881.v1

India has not held a decennial census since 2011, leaving the 2015–2025 decade without a population count against which claims of small-town urbanisation can be verified. This study tests whether such growth is empirically demonstrable along a sixty-kilometre stretch of National Highway 63 in Jagtial district, Telangana, covering three corridor towns: Jagtial, Korutla and Metpally. Sentinel-2A and LISS-4 imagery for December 2015, 2020 and 2025 were segmented using Large Scale Mean Shift and classified with nine independently trained Random Forest models, achieving overall accuracies of 72.73 to 90.59 per cent. Results were cross-checked against electricity, motor-vehicle and beedi-establishment records sharing no error structure with the imagery. Built-up area grew 80.2 per cent at Jagtial, 62.6 per cent at Korutla and 31.5 per cent at Metpally between 2015 and 2025, a gradient tracking administrative rank rather than a corridor-wide wave; Korutla combines the fastest growth in service connections and load intensity with the weakest formal streetlight-network expansion, consistent with its home-based beedi cottage-industry base. An XGBoost-anchored trend model extends the built-up, electricity and vehicle series to 2040, corroborated by the Union Cabinet's June 2026 approval of highway widening for the corridor, expressly justified by congestion from this built-up growth.

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