Embark on an exploration of the dynamic interplay between spatial analysis and social sciences through our hands-on course utilizing the versatile R programming language.
This 5-day course delves into the role of geospatial data in social sciences research and the valuable integration of R for in-depth analysis. The course begins with the introduction to spatial analysis and R, covering fundamental geospatial concepts, an in-depth exploration of the coordinate reference systems and map projections, and a refresher on R programming.
You will gain a solid understanding of geospatial data structures using relevant R-packages, establishing a strong foundation for subsequent modules. The vector data module focuses on concepts, plotting techniques, advanced visualization with R-packages, and map overlays. The raster data module provides a deep dive into raster concepts, data-structures with the relevant R-packages, remote sensing, and satellite data.
You will master raster reclassification, stacks, algebra, and mapping with both raster and vector data. With real-world applicability in mind, the course explores sources of vector and raster data for social sciences research, including datasets from Radboud University Global Data Lab. The culmination involves spatial analysis fundamentals, covering tools commonly used for the analysis of geospatial data separately and in combination.
This course is designed to provide you with the skills needed to navigate the complexities of geospatial data effectively, enhancing their research capabilities in the realm of social sciences.