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Geographic Information Systems and Science (CASA0005)

Key information

Faculty
Faculty of the Built Environment
Teaching department
Centre for Advanced Spatial Analysis
Credit value
15
Restrictions
Students not registered in the Centre for Advanced Spatial Analysis (CASA) may request CASA0005 as an Elective Module but must contact the Module Leader, Dr Andrew Maclachlan, in the first instance to ensure the module will be a suitable fit with the student's proposed programme of study.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

The purpose of this module is to equip students with an understanding of the principles underlying the conception, representation/measurement and analysis of spatial phenomena. As such, it presents an overview of the core organising concepts and techniques of Geographic Information Systems, and the software and analysis systems that are integral to their effective deployment in spatial analysis. It is concerned with unearthing and understanding the importance of spatial data in a range of contexts. The module is designed to have a large practical component in order that students can use the latest software and techniques to analyse and infer from contemporary datasets. It is taught predominantly in the R data science programming language, but also covers some basic concepts in QGIS. The intention is that students will complete the course with a broad knowledge of spatial analysis which they can draw on for their dissertation and further study or employment. No prior knowledge of GIS or the R data science language is required, but the module moves quickly from basic tools to advanced GIS methodologies. The practical book for the module is available online for more detail on weekly content, however this can change annually:

Module deliveries for 2024/25 academic year

Intended teaching term: Term 1 ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
90% Fixed-time remote activity
10% Other form of assessment
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
147
Module leader
Dr Andrew Maclachlan
Who to contact for more information
casa-teaching@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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