Accessibility model of BRT stop locations using Geographically Weighted regression (GWR): A case study in Banjarmasin, Indonesia

Abstract

Bus Rapid Transit (BRT) has advantages over rail-based systems as a public transportation system. The ease of implementation and low investment costs attract many cities to develop BRT systems, including Banjarmasin, Indonesia. Banjarmasin currently has eight BRT stop points that reach only two sub-districts out of five. The limited range of BRT stops within the city can affect the level of accessibility of the BRT system. The accessibility of the transit system itself can be seen from the number of daily passengers. This study aims to analyze the criteria that affect the level of accessibility of the BRT stops in the study area and then compile a model based on significant criteria. Previous literature on accessibility modeling shows varied methods and approaches. In this study, the system accessibility was measured using the composite method and modeled using Geographically Weighted Regression (GWR), which is a relatively new approach. The results show that seven criteria affect the level of accessibility of the BRT stops. The model was first built mathematically using OLS. Then, GWR analysis was accomplished on spatial variables, resulting in a higher significance model. Furthermore, the GWR produces a visual-spatial model and performs simulation and sensitivity tests to make the research purpose more informative. The spatial criteria for the accessibility of the BRT stop locations in the model include the distance of stops to the road intersection, mix-use entropy index, population density, and land value.