Postgraduate taught 

Quantitative Methods in Biodiversity, Conservation & Epidemiology MSc

Geographic Information Systems for Ecologists BIOL5250

  • Academic Session: 2024-25
  • School: School of Biodiversity One Health Vet Med
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No

Short Description

This course will provide students with core training in the collection and analysis of ecological data using geographic information systems (GIS).

Timetable

The taught component of the course will be an intensive 3-day course, held at SCENE, with approximately eight hours teaching per day which will consist of a mixture of lectures, practical sessions and fieldwork.

Co-requisites

None

Assessment

Proposed new assessment

Scientific report (2000 words approx).

Course Aims

The aim of the course is to provide students with training in the collection and analysis of ecological data using a geographic information system (GIS). The objective is to develop key skills in creating a GIS using existing data and collecting suitable field data for an ecological project.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Critically evaluate the specific data requirements of an ecological research project for implementation into a geographical information system (GIS)

■ Design a specialised GIS project to answer a biological question using appropriate advanced software

■ Verify GIS compatible field data using a global positioning system (GPS) receiver with previously collected data to produce a high quality map of publication standard

■ Extract relevant spatial data from GIS project for use in statistical analyses and examine relationship between variables using appropriate statistical methods.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.