A framework to measure transit-oriented development around transit nodes: Case study of a mass rapid transit system in Dhaka, Bangladesh

Abstract

Transit-oriented development (TOD) is a tool that aids in achieving sustainable urban development. It promotes economic, environmental, and social sustainability by integrating land use and transportation planning. Many researchers have investigated mass rapid transit (MRT) station regions for TOD in developed cities. However, in a developing city such as Dhaka, measuring node-based TOD (TOD index) during MRT construction has been disregarded in planning future land use. Furthermore, no prior research on quantitative TOD measurement in Dhaka exists. As a result, we developed a framework for both quantitative and spatial node-based TOD measurement based on the four Ds (density, diversity, destination accessibility, and design) of the TOD concept. With 17 stations under construction, MRT 6 was selected as our study area. The TOD index was measured by nine indicators based on the four criteria (4Ds), spatially in the geographic information system (GIS). After calculating the indicators, the TOD index for each station’s 800m buffer was estimated using the spatial multi-criteria analysis (SMCA). A sensitivity analysis of four TOD scenarios was performed to check the model’s robustness. Additionally, a heatmap of the TOD index for MRT 6 was created for informed planning and policymaking. Furthermore, statistically significant hotspots (both Getis Org Gi* and Anselen Local Moran Statistics) and hotspot clusters were identified. Finally, we illustrate the station-based ranking based on the maximum TOD score. In addition, a detailed spider-web of nine indicators for 17 stations depicts sustainable TOD planning. However, regarding density and diversity, sustainable development and (re)development policies should be implemented not only for MRT 6 but for all Dhaka’s TOD regions.

Revolutionizing TOD Planning in a Developing Country: An Objective-Weighted Framework for Measuring Nodal TOD Index

“…To conclude, analyzing MRT 6 stations' TOD scores in Dhaka provides signifcant insights into the factors contributing to TOD. One of the signifcant contributions is incorporating objective weightage to enhance better outcomes than the study conducted by Uddin et al [22] utilizing subjective weightage. Te study reveals that stations with higher TOD scores serve multiple transportation modes and are located in the city's urban core, where commercial facilities are more feasible.…”

“…Once the indicators were calculated, they were aggregated by Aeronautical Reconnaissance Coverage Map (ArcMap) and Quantum GIS (QGIS) to create the TOD index for these 224 grid cells using TerrSet 2020's IDRISI GIS Analysis. However, an in-depth calculation of these TOD indicators can be found in the paper by Uddin et al [22]. So, the authors referred this paper to the readers who wanted to fnd the detailed calculation of these indicators and index values.…”

“…However, the weightage for diferent TOD indicators has been taken subjectively in most cases. For example, a study by Uddin et al [22] also used subjective weightage for nodal TOD measurement, which can be considered the frst study of TOD index calculation for Dhaka, Bangladesh. However, the primary disadvantage of subjective weightage is human biasedness.…”

Measuring Effectiveness of Non-Motorized Vehicles on Spatial Extent for TOD Development: A Case Study for MRT 6 in Dhaka

“…Further studies show that well-planned and designed communities and neighborhoods benefit from making public transit accessible and bicycling and walking more convenient (Samimi et al, 2009). However, the fundamental concept of TOD supports sustainable development (Li & Lai, 2009) by promoting economic, environmental, and social sustainability (Uddin et al, 2023).…”

Land use change in Dhaka City Corporation Area and its impact on transportation: A way forward towards integration into national policies

“…United Nations projections show that by 2040, Bangladesh's urban population will likely have increased by 50% from the present 28% (Jones et al, 2016). Rapid GDP growth and urbanisation have resulted in considerable loss of arable lands and exerted tremendous pressure on limited resources, predominantly cultivated areas and forest cover (Dewan et al, 2012;Uddin et al, 2023). With a higher population density, the forest coverage of the country has been progressively depleted by agricultural expansion (Chandra and Shrestha, 1996).…”