GIS for Global Studies
In this second part of Geo Spatial Data Science with QGIS and R, we shift our focus to applying geospatial data science techniques within the context of global studies. While the first part laid the groundwork by introducing essential concepts and tools, this section explores how these techniques can be utilized to address complex global issues, ranging from international trade and migration to environmental sustainability and political risks.
Part II is dedicated to understanding how geospatial data science can provide critical insights into global phenomena by integrating spatial data with global studies methodologies. Through detailed examples and case studies, you will learn how to use QGIS and R to analyze and visualize global patterns, trends, and networks. This includes mapping financial networks, understanding migration flows, assessing political risks, and examining the impacts of globalization on food systems and the environment.
Each chapter in this section builds upon the knowledge gained in the previous one, gradually guiding you from basic spatial analyses to more sophisticated, multi-layered geospatial models. The examples provided are drawn from real-world global studies, demonstrating the practical applications of geospatial data science in understanding and addressing global challenges.
By the end of Part II, you will have a deeper understanding of how to leverage the power of QGIS and R to analyze global issues through a spatial lens. This knowledge will equip you to contribute meaningfully to the study of global phenomena, using geospatial data science as a tool for both academic research and practical problem-solving.