My name is Prince Obosu, and I am a Ph.D. student in Remote Sensing of Forest Resources and Biology at the University of Maine. I am a multidisciplinary researcher with a strong interest in applying geospatial technologies across various domains. Currently, I am working on developing a spatial community resilience framework for the state of Maine. Prior to this, my research focused on using satellite data and machine learning techniques to predict malaria prevalence in the Ashanti Region of Ghana. See more
Miam University
Collaborated with a team of GIS students at Miami University under Robbyn Abbitt to develop a website preserving the history of the Randolph Freed people. The site highlights their journey from Virginia to Ohio, land acquisitions made on their behalf, and the challenges they faced settling in Mercer County.
View ProjectCapstone project for the GIS Certificate at Miami University. Conducted a multi-criteria analysis in ArcGIS to identify optimal locations for a new health facility in Butler County, Ohio, based on ranked factors influencing site suitability.
View ProjectDeveloped as a final project in a graduate-level Geospatial Programming course. Created an ArcPy script to identify parcels within 500 feet of fire hydrants, generating maps and mailing lists to help municipalities assess fire coverage and improve emergency response planning.
View ProjectThis was a volunteer project in which I assisted in coordinating geographic information system (GIS) activities at both the state and local government levels. I worked with the Ohio Geographically Referenced Information Program (OGRIP), which supports the OGRIP Council, the coordinating body for GIS initiatives across Ohio’s state and local governments. Additionally, OGRIP operates the GIS Support Center, which provides technical assistance and GIS support services to various state agencies
View ProjectThis project utilized Sentinel-2 imagery, combined with elevation and slope data derived from a DEM, to perform a supervised land cover classification of Mount Kasigau, Kenya.
View ProjectPredicting Malaria Prevalence at the Local and Regional Level: A Case Study in the Ashanti Region, Ghana.
– OhioLinkPredicting malaria prevalence in the Ashanti Region of Ghana: A Machine Learning Approach.
– Under ReviewMalaria Prevalence Factors Among Households in the Central Districts of Ashanti Region, Ghana.
– Under ReviewPerformance Comparison of Machine Learning Algorithms for Land Use Land Cover Classification.
– Under ReviewSpatial Accessibility to Health Care in the Awutu Senya East, Central region, Ghana.
– Under ReviewTen finalists competed in the Miami University Graduate School Three Minute Thesis (3MT) competition
Read MoreI was part of a team of Miami University students who mapped the land in Ohio that was originally purchased for, but ultimately denied to, the Randolph Freedpeople.
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