Title : Spatial Analysis of Road Transportation Network in Thanlyin Town
Keywords : Alpha Index, Beta Index, Eta Index, Gamma Index, GIS, Network Indices, Road density, Transportation Network Analysis
Authors : Win Thet Myint
Publication Date : 2018-12-01
Description : Developed and efficient transportation network in urban areas is just like blood flowing through veins in blood. It is a basic infrastructural requirement to meet the need of the increasing population and growing economy. The study was taken up to provide road and railway network information to city dwellers which help them to choose appropriate route for increasing the transport network system efficiency. The study area of Thanlyin Town is located in Thanlyin Township, southern part of Yangon Region. It is located in the southern part of Yangon Region. Thanlyin Town lies between 16º 45' north and 16º 47' north Latitude, and also between 96º 13' east and 96º 16' east longitude. The town has an area of (7.93) square miles. It is composed of (17) wards. Among them, Myoma (South) and Myo Houng (East) are densely populated area. In the town area, main transportation routes is Kyaik Khauk Pagoda Road (Bago-Thanatpin-Khayan- Thonegwa- Kyauktan), and Bogyoke Nay Win Road is secondary road. In this project, I present the spatial analysis of transportation network in Thanlyin Town. The Arc GIS 10 is used to perform the extraction of region of interest from primary data and for Road Generalization, like selection, merging, elimination,
symbolization etc. Total Road length and total area is calculated using the Arc Map software, using these data and population data, a Population Density and Road Density is calculated. Network dataset is created in Arc Catalog 10 which provides the number of Transport Lines and number of Junctions. It is used to calculate the Network Connectivity Indices. An Alpha Index, Beta Index, Gamma Index are calculated for Transportation Analysis. This provides the spatial relationship between the transportation and Town planning of Thanlyin. We present the land cover classification of study area by Remote Sensing, Population Density, Road Density, Buffer analysis and Network analysis by Geographic Information System