Department of Urban and Regional Planning
Bangladesh University of Engineering and Technology (BUET)

Md Waliullah


Urban and Regional Planning

Academic Biography

Md Waliullah currently works at the Department of Urban and Regional Planning, BUET. He completed his Bachelor of Urban and Regional Planning(BURP) from the Department of Urban and Regional Planning, BUET and is doing his Master of Urban and Regional Planning(MURP) in the same department. His research interests are in the areas of land suitability analysis, AI and Machine Learning application for urban management, regional economics, and applications of GIS in urban planning.

Educational Information
  • Master of Urban and Regional Planning (MURP), Bangladesh University of Engineering and Technology (BUET), Continuing
  • Bachelor of Urban and Regional Planning (BURP), Bangladesh University of Engineering and Technology (BUET), 2021

Research Accounts

  • Worked as research assistant in the Project “Needs assessment of Local level Institutions on SDG Localization initiatives to implement Agenda 2030 in the context of adaptation project planning”, Funded by GIZ

Research Interests
  • Land Suitability Analysis
  • AI and Machine Learning Application for Urban Management
  • Applications of GIS in Urban Planning
  • Regional Economics

All Publications
Md. Hamidur Rahman, Niaz Mahmud Zafri, Fajle Rabbi Ashik, Md Waliullah, Asif Khan
Identification of risk factors contributing to COVID-19 incidence rates in Bangladesh: A GIS-based spatial modeling approach
Elsevier, Heliyon, 2021
Publication Type: Journal Article
, Publication Link
Background: COVID-19 pandemic outbreak is an unprecedented shock throughout the world, which has generated a massive social, human, and economic crisis. Identification of risk factors is crucial to prevent the COVID-19 spread by taking appropriate countermeasures effectively. Therefore, this study aimed to identify the potential risk factors contributing to the COVID-19 incidence rates at the district-level in Bangladesh. Method: Spatial regression methods were applied in this study to fulfill the aim. Data related to 28 demographic, economic, built environment, health, and facilities related factors were collected from secondary sources and analyzed to explain the spatial variability of this disease incidence. Three global (ordinary least squares (OLS), spatial lag model (SLM), and spatial error model (SEM)) and one local (geographically weighted regression (GWR)) regression models were developed in this study. Results: The results of the models identified four factors: percentage of the urban population, monthly consumption, number of health workers, and distance from the capital city, as significant risk factors affecting the COVID-19 incidence rates in Bangladesh. Among the four developed models, the GWR model performed the best in explaining the variation of COVID-19 incidence rates across Bangladesh, with an R2 value of 78.6%. Conclusion: Findings and discussions from this research offer a better insight into the COVID-19 situation, which helped discuss policy implications to negotiate the future epidemic crisis. The primary policy response would be to decentralize the urban population and economic activities from and around the capital city, Dhaka, to create self-sufficient regions throughout the country, especially in the north-western region.
Niaz Mahmud Zafri, Md Nurullah, Meher Nigar Neema, Md Waliullah
Spatial accessibility to healthcare facilities in coastal region of Bangladesh
John Wiley & Sons, Inc., The International Journal of Health Planning and Management, 2021
Publication Type: Journal Article
, Publication Link
Though equal and easy accessibility to healthcare facilities are a fundamental right, people of the coastal region often get poor accessibility to healthcare facilities. This research aimed to assess the spatial accessibility to healthcare facilities in the coastal region of Bangladesh. Patuakhali district was selected as the study area. Accessibility to three levels of healthcare facilities: Community Clinic (CC), Upazila Health Complex (UHC) and District Hospital (DH) was measured individually using Geographic Information System (GIS) adopting the simple distance measures. Finally, overall accessibility to healthcare facilities was measured by overlaying accessibility to all three levels of healthcare facilities according to their relative importance. The findings of this study showed that a significant portion (70%) of Patuakhali district had high accessibility to CC; whereas, almost 60% and 40% of the area had poor accessibility to UHC and DH, respectively. Furthermore, 40% and 28% of the area of Patuakhali district had low and high accessibility to overall healthcare facilities, respectively. Furthermore, accessibility to healthcare facilities was found very poor in rural areas, char areas, and seashore. Thereafter, it is recommended to provide an UHC in every upazila and a DH in the southern part of Galachipa upazila to ensure high spatial accessibility of healthcare facilities.