2023/24 Taught Postgraduate Module Catalogue
GEOG5002M GIS Data Visualisation and Analysis 2
15 creditsClass Size: 40
Module manager: Helen Durham
Email: h.p.durham@leeds.ac.uk
Taught: 1 Dec to 28 Feb (adv year), 1 Dec to 31 Mar View Timetable
Year running 2023/24
Pre-requisites
| GEOG5001M | GIS Data Visualisation and Analysis 1 |
This module is not approved as an Elective
Module summary
This module develops core and intermediate spatial analysis skills required for the analysis of geographically referenced data focussing on a range of socio-economic and environmental applications. Taught through instructional notes and practical activities, students will apply their skills and knowledge of spatial analysis to analyse quantitative data. The module equips students to produce and communicate high quality outputs that can be used to inform decision making in a range of real-life applications. This module reinforces the quantitative skills and familiarity with GIS software introduced in GEOG5001: GIS DVA1 with different types of data to enable students to undertake subsequent modules and independent research.Objectives
This module seeks to:- Build on core skills introduced in GEOG5001: GIS DVA 1 and develop intermediate skills and techniques in analysis as required for quantitative analysis of spatial data
- Give students the opportunity to work with and critically evaluate a range of spatial socio-economic and environmental datasets in relation to real world applications
- Provide an opportunity for students to prepare and process data ready for analysis and independently carry out and critically evaluate spatial analyses in a range of socio-economic and environmental applications
Learning outcomes
On completion of this module, students will:
1. Have developed theoretical knowledge of core and applied spatial analysis techniques suitable for the analysis of geographically referenced data
2. Be able to apply and critique applied spatial analytical techniques using core industry standard geographical information systems
3. Critically assess insights derived from the analysis of a range of socio-economic and environmental datasets and communicate findings and insight supported by appropriate visualisation tools.
4. Design, execute and critically evaluate a ‘guided’ environmental analysis project using software, techniques and data resources introduced within this module.
Syllabus
Topics include:
1. Application of core GIS techniques: network analysis
2. Introduction to raster spatial data and sources
3. Raster analysis of environmental data
4. Interpolation of data to surfaces
5. Spatial clustering of phenomena
6. Preparing and processing raw data for analysis
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Supervision | 8 | 1.00 | 8.00 |
| Discussion forum | 8 | 2.00 | 16.00 |
| Independent online learning hours | 48.00 | ||
| Private study hours | 78.00 | ||
| Total Contact hours | 24.00 | ||
| Total hours (100hr per 10 credits) | 150.00 | ||
Private study
Private study and online learning includes directed and independent wider reading, independent practical work and researching/undertaking module assessments and related tasks.Opportunities for Formative Feedback
Formative feedback will be provided via discussion boards where students are encouraged to post questions, comments, practical outputs etc. Note that the outputs requested here will differ from those required as part of the summative portfolio.The module leader will also provide support via email and Skype/Collaborate Ultra during the software learning stages, in advance of assessment.
Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Report | Guided report on the application of skills to an environmental problem/project | 80.00 |
| Portfolio | Weekly outputs from practicals | 20.00 |
| Total percentage (Assessment Coursework) | 100.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading list
The reading list is available from the Library websiteLast updated: 28/04/2023 14:56:06
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