Members’ Publication

Being one of the densely populated cities of the world, city dwellers of Dhaka have to face severe traffc congestion daily while commuting for diffrent purposes. According to the World Bank report, Dhaka is losing around 3.2 billion working hours daily as the current average driving speed is about seven kilometers per hour. To ease traffc congestion, urban policymakers around the world are concentrating on the geographical balance between the locations of jobs and housing. Despite the apparent acceptance of jobs-housing balance as a policy tool to guide urban development, little empirical research has been carried out on jobs-housing balance and its relation to the travel behavior of the residents. This study aims to close this research gap by: (a) quantifying neighborhoodlevel jobs-housing balance; (b) investigating whether there are any signifiant diffrences in commuting time and distance of the resident workers in correspondence with diffrent Job-Housing Ratio (JHR) values of neighbourhoods. This paper uses Traffc Analysis Zones (TAZs) demarcated on the Revised Strategic Transport Plan as a unit of measuring the Job-Housing Ratio, and then, TAZs have been categorized into three groups, named as Housing-rich, Balanced, and Employment-rich, in terms of the recommended range of Job-Housing Ratio. Residents’ home-based commuting data have been calculated from 16,000 households who participated in Household Interview Survey of Revised Strategic Transport Plan 2015. Results demonstrate that Housing-rich neighbourhoods have a signifiantly longer commuting distance and time than both Balanced and Employment-rich neighbourhoods. Above all, both commuting time and distance show exponentially declining relation, but with a decreasing rate, in correspondence with JHR. The study output suggests that the achievement of a balance between jobs and housing in a neighborhood would be benefiial for the people to economize the commuting time and distance.

The study of structure of industrial sectors of a region is important to understand the growth and development of a region's economy. The national growth of a sector is a driving factor for progressing of that sector in a region. Shift Share analysis is a standard long run regional analysis technique for assessing the performance of sectors in regional economy. It highlights the performance of a region’s mix of industries and uniqueness of a regional economy. This study seeks to quantify how much of the growth of an industry of a region is attributable to national growth and how much is proliferated by locational factors using Shift Share Components. Employment data of thirteen sectors from “Economic Census-2003 and 2013” report has been analyzed for seven districts of Barisal and Chittagong division. The comparative analysis of the selected districts reveals that Hotel and Restaurant sector is flourishing in all of the districts for both positive influence of external and internal factors while Real Estate and Renting, and Transport, Storage and Communication activities has been lagging for all the districts. All of the districts, except Bhola and Pirojpur would become economically weak in the long run, while Rangamati district is in economic malaise relative to the other districts. Thus, Shift share would be useful for the regional planners to set investment targets by identifying high-performing regional industries.

Since August 2017, more than 744,400 stateless Rohingya refugees – an ethnic Muslim minority group from the Rakhine State – have entered Bangladesh to escape serious crimes against humanity conducted by the Myanmar Army. Extensive level of deforestation and hill cutting activities took place in Cox’s Bazar District (CBD) in Bangladesh to accommodate them. The refugee camps are sitting on hills and loose soil and are highly vulnerable to rainfall-triggered landslides. Notably in June 2017, landslides in the same region killed at least 160 people. From this perspective, the study aims to develop a localised landslide early warning system (EWS) for the Rohingya refugees and their host communities in CBD. A novel method, combining landslide inventory and susceptibility maps, rainfall thresholds and dynamic web-based alert system, has been introduced to develop the landslide early warning system (EWS) by applying advanced geoinformation techniques. Results suggest that approximately 5,800 hectares of forest land cover disappeared due to the 2017 Rohingya influx. Land cover changes through hill cutting andslope modifications, and unplanned urbanisation are predominantly responsible for slope failures and consecutive 5-day periods of rainfall between 95–220 mm could initiate landslides in high susceptible areas. The EWS would support the local authorities and international organisations in reducing disaster risks and saving lives from landslides in a humanitarian context.