Module overview
The module will look at the conceptual, practical and methodological issues associated with using GIS for environmental and socio-economic applications.
Linked modules
Pre-requisite: (GEOG2010 or GGES2007) or (GGES2005 or GEOG2007)
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Abstract and synthesise information from a range of different geographical sources.
- Understand the ways in which geographical data of various types can be combined, interpreted and modelled.
- The application of geographic information science for the understanding of social and economic problems and environmental management
- Analyse and critically interpret secondary geographical data.
- Produce fluent and comprehensive written reports on complex topics.
- Understand the importance of the geographical characteristics of data.
- The influence of spatial and temporal scale upon human and physical processes.
- Marshal and retrieve data from library and Internet resources
- Pursue knowledge in an in-depth, ordered and motivated way.
- Confidently use a range of relevant forms of IT software.
- Analyse critically literature in human and physical geography.
- The theory, acquisition, analysis and interpretation of geographical data across a range of applications.
- Analyse and understand data in human and physical geography using computer techniques.
- Understand the different types of spatially explicit model and their relative strengths and weaknesses.
- Use appropriate techniques, including computer software, to produce clear diagrams and maps.
- The use of concepts of space and spatial variation in geographic analysis
Syllabus
This module is comprised of two parts. Part I focuses on spatially distributed dynamic models with particular emphasis on environmental modelling. A range of spatially distributed models will be studied from application areas such as forestry, climate change, and land use planning. Subjects such as model calibration and validation, sensitivity analysis and what-if scenarios are covered, and students should be able to recognise the different types of spatially distributed model by the end of the module. In Part II of the module, the focus is on techniques and concepts in spatial data handling. This encompasses issues such as geospatial data systems, accessing and inputting data, measuring accessibility, and issues of temporal representation and uncertainty. There will be some coverage of Python coding for GIS applications, though this will not be assessed.
It should be emphasised that the methods and techniques used, and the skills developed in both halves of the course, are applicable across the breadth of quantitative geography (whether human or physical) and environmental science.
Learning and Teaching
Teaching and learning methods
Lectures provide a sound knowledge base and structure. Computing practicals provide the opportunity to put these concepts and methods into practice and to gain hands-on experience of using two major GIS software packages (the open source Quantum GIS software and ESRI’s ArcGIS). The practical sessions and associated coursework are problem-based to encourage students to develop skills in the context of the solution of real-world problems
| Type | Hours |
|---|---|
| Independent Study | 116 |
| Teaching | 34 |
| Total study time | 150 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 50% |
| Coursework | 50% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 50% |
| Coursework | 50% |
Repeat Information
Repeat type: Internal & External