Course overview
Research teams increasingly need defensible spatial evidence rather than maps that only illustrate a report. Questions about service access, disease exposure, land-use change, disaster impacts, market reach, infrastructure gaps and environmental risk require analysts to combine location data with survey, administrative, satellite and field observations. The central challenge is producing findings that are geographically valid, statistically sound, reproducible and understandable to decision-makers.
This course develops the GIS research workflow from research question to analytical output. Participants prepare spatial and tabular data, define coordinate reference systems, assess data quality, design geodatabases, conduct spatial joins and overlays, measure proximity and accessibility, analyse point patterns, interpolate continuous surfaces, and test spatial relationships. They also apply remote-sensing imagery for classification and change detection, select suitable map projections, communicate uncertainty, and document methods for reproducible research.
Teaching combines concise technical briefings with guided analysis of realistic cases drawn from public health, humanitarian response, banking, urban services, agriculture and environmental monitoring. Participants work with GIS software, structured datasets, satellite imagery and research scenarios from the first week. They leave with a documented GIS research analysis package: a research design, data dictionary, analysis workflow, maps, statistical outputs, quality checks and a decision-focused presentation.
The course suits analysts who already work with data and need to add location-based methods to research, monitoring, planning or policy work. It is particularly relevant where findings must withstand internal review, donor scrutiny, regulatory questions or public-sector decision processes.
