It is estimated that 80-90% of all data contain some spatial component (Carl & Hane, 1992). Geographic Information Systems (GIS) are an essential tool to manipulate this data, draw insights and produce visualisations to inform decision-making. This Introduction course aims to familiarise students with the field of Geographic Information Science, enable them to source data from open data providers, and carry out basic spatial data analysis. Students will work on QGIS, the leading open-source software in this field.
Julien MOURA
Atelier
English
Students are expected to actively engage with the tutorial and material provided ahead of each session. Each session will start with a discussion of the tutorial. Offline discussions will be posted on an online platform (Slack) to discuss data sources, methodological choices and other general questions around GIS.
None. Familiarity with data analysis and with concepts of open-source data and software would be a plus.
Autumn 2023-2024
Coursework: working in groups of 2 or 3, students will be provided a dataset to explore and will be tasked with carrying out simple geospatial analysis and visualisation. They will produce a technical report detailing the methodology they adopted and the insights they can draw from this data.
The course will be run in 6 sessions of 2 hours. The first session will be a lecture covering GIS as a field of research, typical workflows, data sources and collection methods. Subsequent sessions will follow a more interactive format centred around tutorials and flipped classroom methods.
Longley, P.A., Goodchild, M.F., Maguire, D.J. and Rhind, D.W., 2005. Geographic information systems and science. John Wiley & Sons. (optional)
Robin Wilson's data sources listing: https://freegisdata.rtwilson.com/ (optional)
Barndt, M. (1998). Public participation GIS—Barriers to implementation. Cartography and Geographic Information Systems, 25(2), 105-112.
Elbir, T., Mangir, N., Kara, M., Simsir, S., Eren, T., & Ozdemir, S. (2010). Development of a GIS-based decision support system for urban air quality management in the city of Istanbul. Atmospheric Environment, 44(4), 441-454.
Joerin, F., Thériault, M., & Musy, A. (2001). Using GIS and outranking multicriteria analysis for land-use suitability assessment. International Journal of Geographical information science, 15(2), 153-174.
Ko, J. H., Chang, S. I., & Lee, B. C. (2011). Noise impact assessment by utilizing noise map and GIS: A case study in the city of Chungju, Republic of Korea. Applied Acoustics, 72(8), 544-550.
Vajjhala, S.P. and Walker, W.M., (2010). Roads to participatory planning: integrating cognitive mapping and GIS for transport prioritization in rural Lesotho. Journal of Maps, 6(1), pp.488-504.
Maantay, J. A., Maroko, A. R., & Herrmann, C. (2007). Mapping population distribution in the urban environment: The cadastral-based expert dasymetric system (CEDS). Cartography and Geographic Information Science, 34(2), 77-102.
- Maantay, J. A., Maroko, A. R., & Herrmann, C. (2007). Mapping population distribution in the urban environment: The cadastral-based expert dasymetric system (CEDS). Cartography and Geographic Information Science, 34(2), 77-102.
Rybarczyk, G., & Wu, C. (2010). Bicycle facility planning using GIS and multi-criteria decision analysis. Applied Geography, 30(2), 282-293.
Schuijbroek, J., Hampshire, R. C., & Van Hoeve, W. J. (2017). Inventory rebalancing and vehicle routing in bike sharing systems. European Journal of Operational Research, 257(3), 992-1004.
- Yeh, A. G. O. (1991). The development and applications of geographic information systems for urban and regional planning in the developing countries. International journal of geographical information system, 5(1), 5-27.