During the last two decades, determining the urban boundaries of cities has become one of the major concerns in the urban and regional planning subject domains. Many scholars have tried to model the change of urban boundaries as it helps with sustainable development, population projections and social policy making, but such efforts have been futile, owing to the complex nature of urbanization and the theoretical and technical limitations of the proposed applications. Hence, many countries continue to rely on the administrative boundary demarcation, which rarely represent the actual urbanizing pattern. In such context, this study utilized the “Intersection-Based Clustered Network Model—(iCN Model)” to determine the urban boundaries of cities and selected Sri Lanka as the study area and considered few cities to test the model empirically, with satellite imagery classified urban boundaries. The findings of the study depict that the iCN Model is capable of capturing the complex and dynamic socioeconomic interdependencies of cities via the transportation network configurations. Therefore, the proposed approach is an excellent proxy to derive the urban boundaries of cities, which correspond with the same, derived by the satellite imageries. The proposed model is entirely based on open-source GIS applications and is free to implement and modify using the methods described in this paper.

As a critical infrastructure, the transportation network impacts health, safety, comfort, and the economy, making it highly vulnerable to disruptions that significantly affect social and economic well-being. To maintain optimal service during such disruptions, the critical links that are vulnerable to disruptions must be identified and their impact on network performance must be understood. This study proposes a method for identifying network vulnerabilities by targeting critical links based on topological parameters, assessing worst-case scenarios under severe conditions. These parameters serve as proxies for performance and are utilized to generate critical-link attacks to assess the network vulnerability. In addition, this study proposes a straightforward and simplistic modeling framework using topological parameters to assess the impact of such attacks on traffic flow changes. To characterize network performance and traffic volume changes under critical-link attacks, this study utilizes the complementary cumulative distribution function (CCDF), which highlights the upper tail of the distribution where extreme or rare events occur. The proposed method was applied to a real network in the Colombo Municipal Council (CMC) area in Sri Lanka. The findings of this study will help us understand the impact of critical-link attacks on transportation network performance and traffic flow and develop proactive policies to address vulnerabilities and improve overall network performance.

Simulation of flood inundation in urban areas longer important, given the magnitude of potential loss and disruption associated with non-river based, urban flooding. The complexity of the urban environment and lack of high-resolution topographic and hydrologic data compromise the development and implementation of models. Low impact development (LID) is technical know-how on a collection of sustainable practices that mimic natural hydrological functions including infiltration, evapotranspiration or use of surface runoff. Several studies have been carried out to discuss the impact of urbanization scenarios in reducing the urban flood risk in watershed scale in Sri Lanka. Yet, there is a gap remains in simulating the effectiveness of LID-based planning practices to reduce flood risk with the complex built form scenarios. In such a situation, this study attempts to make a significant contribution to simulate the variations of flood regulation functions under different high-intensive urban development scenarios, particularly focusing on the urban metropolitan regions. The analyses were carried out utilizing SWMM (Storm Water Management Model) which is open-source flood inundation simulation approach with the help of GIS in a more qualitative manner. The simulation results indicate that expanding built form scenarios increase the flood venerability for city functions, increasing inundation duration and LID scenarios able to reduce the surface runoff to reduce flood vulnerability at a significant level. The simulation results had been verified with the real ground situation (mean percentage change < 15.5%) which able to capture the thresholds of built form variation, as well as dynamic land uses and infrastructure supply which can be used as a tool for future planning practices and decision-making.

As a critical infrastructure, the transportation network impacts health, safety, comfort, and the economy, making it highly vulnerable to disruptions that significantly affect social and economic well-being. To maintain optimal service during such disruptions, the critical components that are vulnerable to disruptions must be identified and their impact on network performance must be understood. This study proposes a method for identifying network vulnerabilities in worst-case scenarios by targeting critical components derived from network topological parameters. These parameters serve as proxies for performance and are utilised to generate critical-link attacks to assess the network vulnerability. In addition, this study proposes a straightforward and simplistic modelling framework using topological parameters to assess the impact of critical link attacks on traffic flow changes. To characterise network performance and traffic volume changes under critical-link attacks, this study utilises the complementary cumulative distribution function (CCDF), which has rarely been utilised in previous studies. The proposed method was applied to a real network in the Colombo Municipal Council (CMC) area in Sri Lanka. The findings of this study will help us understand the impact of critical-link attacks on transportation network performance and traffic flow and develop proactive policies to address vulnerabilities and improve overall network performance.