Analysing Urban Development Patterns: A Spatio-Temporal Analysis and Predictive Scenarios around Major Railway Stations/Terminals

Rapid urbanisation trends in Southeast Asia are primarily influenced by mass transit systems, however the influence of railways on land use dynamics in India remains unique from global patterns. Unlike contemporary Light Rail Transit (LRT) or Metro systems where Transit-Oriented Development (TOD) is often a planned and post-construction intervention, Indian railway nodes typically predate the very concept of TOD, implying urban areas have integrated organically following railway infrastructure rather than being retrofitted. The study investigates this Railway-induced spatial restructuring in the Indian context, specifically the Southern West Bengal region, a rapidly densifying polycentric system, with the primary objective of determining whether railway proximity naturally fosters efficient development or induces chaotic ribbon sprawl. The methodology incorporates a multi-scalar geospatial framework by employing a 25-year temporal gradient (2000-2025) to analyse the relationship between horizontal densification and vertical building density. Data from remote sensing (Landsat 7/8) was utilised to compute fragmentation metrics using FRAGSTATS to quantify horizontal sprawl, while Google Earth Engine (Open Buildings 2.5D) was utilised to derive the average building height. These morphological outputs were further correlated with Space Syntax Integration values to assess functional connectivity. The analysis established four distinct station typologies regarding the urban form efficiency, namely saturated node, stagnant core, benchmark model and developing node. Moving beyond standard computer simulations, the study predicts future growth by analysing these distinct evolutionary categories and utilising passenger footfall data to forecast passenger and train load transfer. The research concludes that without policy intervention, rapid expansion of these urban areas will overburden infrastructure, highlighting the need for specific policy formulation to mitigate these externalities before they become irreversible.