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dc.contributor.authorKhan, Maruf
dc.contributor.authorRouf, Abdur
dc.contributor.authorMeem, Mst. Aysa Siddika
dc.date.accessioned2026-05-13T08:29:43Z
dc.date.available2026-05-13T08:29:43Z
dc.date.issued2026-04
dc.identifier.urihttps://ar.iub.edu.bd/handle/11348/1202
dc.description.abstractThis study investigates the exposure of schools in Bangladesh to air pollution caused by nearby brick kilns, a major contributor to PM2.5 pollution. Using satellite imagery, deep learning, and GIS-based spatial analysis, the researchers identified around 7,000 brick kilns and analyzed their proximity to approximately 33,850 schools nationwide. The findings reveal that 4.8% of schools are located within 500 meters, 13.3% within 1 kilometer, and 37.3% within 2 kilometers of a brick kiln, with peri-urban and industrial regions facing the highest risks. The study highlights exposure hotspots in areas such as Gazipur, Narayanganj, Chattogram, and Khulna. In addition, machine learning frameworks were explored to predict school-level PM2.5 concentrations based on kiln distance and kiln type. The proposed satellite-based and reproducible framework provides a scalable method for environmental exposure assessment and supports policy interventions such as air quality monitoring, stricter kiln regulations, and protective measures for schools.en_US
dc.language.isoenen_US
dc.publisherIUBen_US
dc.subjectClimate and Healthen_US
dc.subjectBrick Kilnsen_US
dc.subjectPM2.5 Pollutionen_US
dc.subjectEnvironmental Exposure Assessmenten_US
dc.subjectGeographic Information Systems (GIS)en_US
dc.subjectRemote Sensingen_US
dc.subjectSatellite Imageryen_US
dc.subjectSemantic Segmentationen_US
dc.subjectMachine Learningen_US
dc.subjectEnvironmental Healthen_US
dc.subjectAir Pollution Monitoringen_US
dc.subjectPublic Healthen_US
dc.subjectClimate and Healthen_US
dc.subjectDeep Learningen_US
dc.subjectIndustrial Emissionsen_US
dc.subjectExposure Mappingen_US
dc.titleMapping School Vulnerability to Brick Kiln Exposure in Bangladesh Using Remote Sensing and Geospatial Analysisen_US
dc.typeThesisen_US


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