Current Research- Funded by NASA

The Urban Transition in Ghana and Its Relation to Land Cover and Land Use Change Through Analysis of Multi-scale and Multi-temporal Satellite Image Data

Dr. Ryan Engstrom has been funded by the NASA Interdisciplinary Science program to study drivers of land cover change within the southern portion of Ghana including the city of Accra over a 25 year period (1986-2010). The project is collaborative project with San Diego State University (Doug Stow PI) and University of California, Santa Barbara and is funded for three years (2012-2015). Dr. Engstrom’s portion of the project will focus on using regression and decision trees to map changes in both urban and rural areas using high and medium resolution satellite imagery. His work will link the changes in urban extant to different drivers of change throughout the region.

Previous Research – Funded by National Institute of Health

Health, Poverty and Place: Modeling Inequalities in Accra, Ghana using Remote Sensing and GIS

Dr. Ryan Engstrom and Dr. David Rain were funded by the National Institute of Health (NIH) to study inter-urban variability of health conditions in Accra, Ghana. The project was a five year (2007-2012) collaborative project with San Diego State University Geography (PI, John Weeks) and Harvard University to combine numerous health datasets with remotely sensed data to create a model for the interpretation of urban health inequalities in the city of Accra, Ghana. The ultimate goal was to develop methodologies in the data rich city Accra that can used as templates for comparative for analysis in other major developing world cities. The George Washington University portion of the work focused on gathering information on neighborhoods on the ground in Accra, running focus groups, and integrating remotely sensed and GIS data. The team traveled to Ghana multiple times and spent numerous hours walking the streets of Accra. This has resulted in a new vernacular neighborhood map that covers the entire Accra Metropolitan Assembly (AMA) study area. The remote sensing work focused on using decision trees to map variations in vegetation, bare soil, and built up area within the city using Quickbird and Ikonos imagery from 2002, 2007 and 2010.