Urban heat islands related to Land-use and land-cover (LULC) changes and its impact on health risks in Brunei using machine learning | |
| Author | Jaya, Nur Fatin Nazihah |
| Call Number | AIT Thesis no.RS-25-03 |
| Subject(s) | Urban heat island--Brunei Land use--Health aspects--Brunei Machine learning |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | Extreme heat waves, intensified by climate change, pose a significant health risk globally. In Southeast Asia, countries like Brunei are experiencing rising temperatures, leading to concerns about heat-related illnesses. The urban heat island (UHI) effect. where urban areas are much warmer than rural areas, further intensifies heat stress. This study aims to investigate the UHI that are caused by land use land cover (LULC) and its impact to the health risks in Brunei. This study maps the spatial distribution of UHI using remote sensing data, and exploring which land use has contributed most to the UHI. Random forest algorithm is utilized for the LULC classification via Google Earth Engine (GEE).. A survey is made to obtain any patterns of heat-related illnesses and is analyzed temporally with extreme heat events to provide more insight on period with high health risk. The climate data such as humidity and temperature are calculated into heat stress index to show health risks A trained model using Random Forest based on the heat stress index is applied to global data to predict health risk. Results shows that built-up areas have the highest maximum UHI value, and the minimum UHI values of all classes are increasing, suggesting a lower cooling effect. Overall, areas with higher UHI value on LULC class type of built-up, and combined with the high-level predicted risk results to a high health risk. This study has contributed to a better understanding of the health risks associated with UHI and LULC which may help to inform strategies for mitigating heat-related illnesses in Brunei. By understanding the UHI's contribution to LULC, and towards health risks, policymakers can develop effective mitigation strategies to promote better public health. |
| Year | 2025 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing and Geographic Information Systems (RS) |
| Chairperson(s) | Tripathi, Nitin Kumar; |
| Examination Committee(s) | Sarawut Ninsawat;Sanit Arunpold; |
| Scholarship Donor(s) | AIT Scholarship; |
| Degree | Thesis (M.Sc.) - Asian Institute of Technology, 2025 |