1 Connectivity Analysis as an Alternative Predictor of Transit Demand: The Case of Railway Network, Sri Lanka Amila Jayasinghe & Nirosha Pathiranage amilabjayasinghe@gmail.com & niroshapathiranage@gmail.com Department of Town & Country Planning, University of Moratuwa Abstract Rapidly increasing congestion of traffic in urban and suburban roads raises the urgent necessity of better and quicker railway service in Sri Lanka. In studies of rail transportation planning, though, travel demand has often taken a back seat to design and engineering features; perhaps due to the lack of adequate data available. Taking its cues, this study explores the potential of “Connectivity Analysis” to serve as an alternative methodology of travel demand forecasting. The connectivity of railway stations in terms railway and road access were computed separately by using ‘Connectivity analysis’ and analysis the relationship with travel demand of station within the railway network of Sri Lanka. Results revealed a significant correlation between transit demand and connectivity of railway stations and connectivity values have capabilities to explain over 77% of the variation in rail transit demand. Therefore the study suggests that “Connectivity Analysis” method can serve as an alternative predictor of transit demand, in the absence of good, quality data on trip-making and employment trends. Keywords: connectivity analysis, transit demand, station, railway network, road network 1. Introduction If cities are to be the sites of economic development, then transportation systems have to be, to a large extent, the foundation on which the efficiency and convenience of that development depends (Leda 2010; Singh 2005). The promotion of public transport as a backbone of mobility in urban agglomerations, or at least as an alternative to the dominance of the automobile, has become a prominent policy focusing on the largest and medium size cities around the world. Public transportation is also an essential component in the sustainability of cities (Munshi 2003; Singh 2005; Leda 2010). However, while some cities have been successful in shifting car journeys onto rail and buses, others are struggling despite considerable effort to make public transport more attractive (Scheurer, 2006). Since many cities now emphasize the desirability of increasing the mode share of public transport at least in their policy rhetoric, if not their practical priorities, it has become a commonplace for cities with weaker public transport to look closely at the success factors in cities with stronger public transport. The most important of these success factors are:  A configuration of the system in terms of network coverage and service frequencies that offer a viable alternative to the car for most, if not all, travel purposes across the urban area (Laube 1998, Nobis 1999)  A legible network structure that is efficient to operate, easy to navigate and offers a choice of routes wherever possible (Mees 2000, Vuchic 2005)