Abstract
Connected street networks significantly encourage higher levels of people walking and biking and less trip by motorized vehicles leading to significant reduction in carbon emissions which can greatly contribute to develop a green and sustainable city with community and environment friendly transportation system in order to achieve Sustainable Development Goal (SDG) 11 as well as to combat climate change . This study aims to explore street connectivity of Dhaka city, Bangladesh which is the ninth largest megacity of the world. The study will explore connectivity of road network of Dhaka city for all 93 communities (wards), two City Corporations under Dhaka City and Dhaka City as a whole . The study will employ Intersection Density, Link to Node Ratio and Street Network Density (miles per square mile) to evaluate network connectivity of Dhaka city. GIS shape file prepared for Dhaka city under Regional Development will be used as key data source for the study. Data Analysis will be conducted using ArcGIS software and python programming. Shape file of road network of Dhaka city will be converted to Network database which will contain information of links and nodes of Dhaka city. Road network of each community will be separated by using Clip tool in ArcGIS. Number of nodes and links in a community will be determined by using statistics tools of ArcGIS. Length of road network of each community will be determined using Calculate Geometry tool. To calculate intersection density, number of nodes in each community will be divided by respective area. Link to Node ratio will be calculated by divining number of links in a community by number of nodes in a community. Street network density will be determined by diving total length of road network in a community by it’s area. To avoid manually repeating same procedure for each community, python code will be developed to determine connectivity using ArcPy and GIS Programming techniques. Findings of the study will help to identify the communities which are in good and bad situation in terms of network connectivity and help concerned authority to take policy measures to improve network connectivity to enhance walking and bicycle ridership which will contribute to better livability and sustainability for communities and green city development. Besides, the GIS programming method and computer program developed for this study can be used to determine connectivity of road network of communities of any cities of the world and contribute to develop sustainable transportation system for other cities of the world.
