Geographic Information Systems (GIS) Workshop: Spatial Analysis and Mapping

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Geographic Information Systems (GIS) play a crucial role in understanding spatial data and making informed decisions across various fields such as urban planning, environmental management, epidemiology, and business analysis. This 4-week module provides a comprehensive introduction to GIS, covering fundamental concepts, tools, and practical applications.

• Postgraduate students and staff
• Further details regarding eligibility criteria are available here

Number of sessions: 8

Throughout the workshop, students will learn how to:

• Understand the fundamental concepts and applications of GIS.
• Acquire, manage, and organise geospatial data from various sources.
• Perform basic and advanced spatial analysis techniques to solve real-world problems.
• Develop spatial models and decision support systems using GIS tools.
• Design and create high-quality maps and data visualisations.

The module will comprise 4 sessions. Each session will be held once a week. During these sessions, participants will engage in a 2-hour class. Within these 2 hours, the class will be divided into half an hour of recorded video lecture and 1.5 hours of In-Person practical sessions.

Session 1: Introduction to GIS fundamentals, data types and sources, and software overview.

Session 2: Working with GIS data: formats, management, basic analysis, and hands-on exercises.

Session 3: Mapping and visualisation techniques, cartography basics, thematic maps, web mapping.

Session 4: Spatial analysis introduction, spatial queries, geoprocessing tools, spatial statistics, and final project.

You will need your own personal computer or laptop, along with internet access. Ensure that GIS software is pre-loaded and ready for use. Two software options are available: QGIS, a free option that will be utilise, and ArcGIS, a paid alternative. Access QGIS software from the provided link:https://qgis.org/en/site/forusers/download.html

By the end of this workshop, participants will understand:

• How to work with raster data, including satellite imagery, land cover maps, and digital elevation models, and how to visualise and analyse these data types.
• Techniques for spatial query and spatial joins to combine and analyse different geospatial datasets, such as linking health data with air quality data.
• Methods for density mapping and hotspot analysis using kernel density estimation on point data, such as crime incident locations.
• The process of conducting a site suitability analysis by combining various spatial analysis tools and techniques, including raster analysis, buffer, overlay, and intersect operations.
• How to automate and streamline spatial analysis workflows using QGIS Model Builder.

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