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Pedestrians are the most vulnerable road users and their risky behaviours make the situation worse. This study aimed to assess the crash risk associated with various pedestrian groups and their road crossing behaviours at intersections in Dhaka, Bangladesh. A two-stage, multi-criteria decision-making approach—analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS)—was used for risk assessment. In the first stage, five risk assessment criteria: nearest vehicle speed, nearest vehicle type, vehicle flow, interrupted by vehicle, and minimum gap were identified from the literature, and these criteria were weighted by the AHP. In the second stage, risk associated with various pedestrian groups and their road-crossing behaviours were quantified and ranked by the TOPSIS. The results indicate that male and young pedestrians had higher risk among pedestrian groups. Furthermore, an oblique crossing type, a running crossing pattern, mobile phone usage while crossing, carrying medium-weight baggage, a rolling gap crossing type, high crossing speed, and cross by using conflict zone were found as the riskiest behaviours. Besides, using crosswalk while crossing, single-stage and two-stage crossing types, perpendicular crossing type, and group crossing were found to be the safest behaviours.

Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Although GIS has substantial potential in planning to slow down the spread, surveillance, contact tracing, and identify the trends and hotspots of breakdowns, it was not employed as much as it could have been. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that this geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our systematic review also provides how both scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the future. Conclusions: Despite the limited applications of GIS in identifying the nature and spatio-temporal pattern of this raging pandemic, there are opportunities to utilize these techniques in handling the pandemic. The use of spatial analysis and GIS could significantly improve how we understand the pandemic as well as address the underserviced demographic groups and communities.

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.