Researchers, developmental practitioners, special government agencies and other professionals value geospatial data for the potential insights it offers. Updated maps not only offer directions, they improve planning for development assistance, they allow for better impact reporting, enable institutions make informed decisions about land use, infrastructure development, community needs, and environmental impacts. This would be very difficult without geospatial analysis. The current course gives learners practical skills to use Python and ArcGIS for geospatial data analysis and visualization. Key concepts underpinning the course include:
Fundamentals of GIS
Students define core geospatial concepts, practice with subset data using selections and feature attributes, create map books using advanced mapping techniques and afterwards create layer and map packages.
GIS Data Formats, Design and Quality
Learners will be involved in designing data tables and use separating and joining data in a relational database before writing query strings to subset data. Students will be led to creating and working with raster data and creating web maps.
Geospatial Analysis with ArcGIS
Learners will apply their GIS knowledge in this module on geospatial analysis, centering on analysis tools, 3D data, rasters, projections, and environment variables. Practical exercises and support by tutors will focus on data retrieval, initial data management and processing, and finally to the analysis products.
Visualizing geospatial data with Python
Learners are introduced to Folium, a python module for geospatial data manipulation. Simple exercises involving folium mapping are presented complemented by other tools such as choropleth maps.