Abstract:
Colombo city hosts almost eight hundred thousand people from various parts of the world and it is one of the
fastest growing cities in the Asian continent. The city subjects to heavy migration because of urbanization. Due
to this reason, the living conditions also vary from place to place in the city. The immigrants are often concerned
about their mobility and accessibility to different civic services. Hence, selection of a living area becomes an
important factor for an inhabitant physically, mentally and financially. However, systematic methodology has
not been implemented to evaluate these living conditions. This study explicates utilizing of hotspot analysis
and Network Analysis extension of ArcGIS to extrapolate crime and the accessibility to six fundamental civic
services including education, healthcare, public parks, shopping centres and emergency response (fire fighting
and ambulance) from different neighbourhoods of the city. Weighted overlay approach is utilized to aggregate
above the criteria and find the most inhabitable neighbourhoods in the city. The study indicates the best area as
“neighbourhoods with least crime and easiest accessibility to all mentioned fundamental services”. Accessibility to
each civic service is calculated by the service area and converted to a raster data which further aggregates them
into a single raster using the above mentioned weighted overlay approach. After exporting the graphical model as
a python script, the system is further developed to handle and return the dynamic influence rate based on the
user inputs and ultimately the user obtains results for the best area. Then, the generated map automatically gets
uploaded into the geo-server and the users can view the final liveability map on a dedicated web platform. Based
on the approaches such as network analysis, multi criteria evaluation and decision support system, this study
assists in selecting a neighbourhood on the basis of selected criteria by a particular user and also helps urban
planners to identify design gaps in urban areas related to each criteria.
