MyAV·¶

This module provides an applied introduction to the use of GIS in the environmental sciences. The course covers the underlying concepts of spatial data and their analyses and offers extensive hands-on experience of GIS in its application to practical problems and research questions in the environmental sciences.

The Environmental GIS module commences with an introduction to the concept of GIS and explores the range of software and programming options available. The course provides a foundation in cartography, coordinate systems, and data types. The module then progresses through a range of data integration, data management, and analytical procedures to provide a hands-on experience of the application of GIS to real environmental problems. The course is specifically focused on place- or site-based questions, problems, solutions, and analysis. This ensures that you encounter many of the day to day issues that arise when working with data from multiple sources and multiple scales, and we also work with data generated from fieldwork to experience the process of generating and using original spatial data.

The main sessions cover the following core GIS principles and approaches:

- Cartography, geovisualisation, and geospatial data

- Coordinate systems and projections, and georeferencing

- Types (raster/vector) and sources of spatial data

- Integration, organisation and management of spatial data

- Spatial analyses

- Spatial statistics

The course is delivered through a series of extended computer-based practicals supported by lecture material, videos, and directed reading. The assessment comprises a group presentation covering the role of GIS in the environmental sciences, and an independent written analytical report delivering an original application of GIS and geospatial analysis to a specific environmental question.

The module delivers a range of core and transferable skills:

- Critical thinking: ability to assess and evaluate data and ideas

- Problem-solving: working with real environmental data can be complicated, and requires thinking through the problem to find the best analytical solution

- GIS: core GIS skills focused on the open-source package QGIS

- Statistical analysis: geospatial statistical analyses

- Coding: some aligned analytical and data-processing using Google Earth Engine and Python

- Teamwork: assessed presentations are undertaken as small groups