In the academic year 2021-2022 this course will take place online.
March 16 (Wednesday) 2022
March 30 (Wednesday) 2022
April 28 (Thursday) 2022
May 11 (Wednesday) 2022
The conceptual framework of Geographic Information Systems, or GIS, allows to capture and analyse geographic data and spatial information easily and efficiently. Already decades ago their usefulness and popularity prompted companies as well as the open source community to develop high-level GIS software solutions, applicable to many disciplines and accessible to nearly everybody.
GIS tools include plenty of possibilities to process, analyze and visualize quantitative as well as qualitative information typically used in research in the social sciences. This course will explain frequently used GIS techniques and demonstrate their applicability across the social sciences. With examples and your own study cases, you will learn how, by combining geographic problems with GIS analytics, to create new knowledge.
During four sessions the principal GIS techniques are taught and practiced in mini-lessons, workshops and short exercises based on the participants’ study cases. Throughout the course these exercises will lead to a GIS-based conceptualization of the participants’ research questions.
To decide if this course is appropriate for you, the following indicators should be applicable for your research proposal:
- The problem of your research proposal has a spatial component (the research question includes phrases similar to near, next to, related to, in conjunction with, etc.)
- You research will make use of (secondary) quantitative data which has to be a substantial component in your data mix
- The GIS analytics can answer a relevant part of your research problem
- Visualization of results is considered as a valuable component in your research proposal
In order to assure that the course has sufficient relevancy for your research proposal you are requested to submit a summary of your research objectives and research questions in advance of the first session. The instructor can then confirm whether this course will cater to your specific needs.
- Explore and apply GIS capabilities, data models, forms of analysis, mapping concepts and data visualization based on examples and your own study cases.
- Identify and differentiate suitable analysis methods, data collection strategies, mapping concepts and visualization techniques for your research method and adopt a GIS compliant communication of your results.
- Implement the abstraction process required to adapt the existing conceptualization and the operationalization of your study to a GIS specific data and analysis framework.
Introduction to GIS, maps & data, webservices, geodata types and basic visualization methods. Getting acquainted with QGIS based on tutorials, exercises and simple study cases.
Understand the methods used to integrate theories of social sciences and research methods into a GIS-based analysis approach. Apply commonly used data analysis techniques, metadata standards and PPGIS for spatial data analysis.
Explore topological and map algebra analysis techniques and other advanced tools for qualitative and quantitative data analysis. Align the operationalization of your research objectives with the GIS data and analysis framework.
Critically review the GIS capabilities applicable to your research problem, revise the conceptualization of your analysis, optimize the operationalization and communication strategies of your results.
Dr. Alexander Los is an urban environment and climate change specialist at the Institute for Housing and Urban Development Studies (IHS) of the Erasmus University Rotterdam. He manages the MSc specialization course “urban environment, sustainability and climate change” where he teaches air quality, climate change, renewable energy and GIS/Python related subjects. Besides teaching Alexander Los contributes to the CSEOL Citizen Science research project as a scientific partner. His experience in climate change, air quality and remote-sensing is built on a continued combination of modelling and observations to study atmospheric chemistry, cloud-induced effects on solar radiation, solar resource forecasting and the Earth’s climate. Alexander Los obtained his PhD at the University of Utrecht in 2001. After a post-doc at the KNMI he worked as research associate at the TU Delft (GRS) in the Netherlands. In the private sector (at the companies Kipp & Zonen and as a director at EKO Instruments Europe) he developed scientific instruments for climate research and solar energy.