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Overview

The UNSW course provides a theoretical understanding and practical introduction to the use of Geographical Information Systems (GIS) and remote sensing. During this course, you will analyse digital spatial data and create simple models using state of the art software.

A GIS is a tool for the analysis, storage, visualisation and management of geographic data. GIS Science is the science of how this is done. Together they allow the integration and analysis of geospatial phenomena across spatial scales, from small forest plots to global assessments of human impacts.

Remote sensing is the process of identifying and observing the physical traits of an area by measuring its reflected and emitted radiation. Cameras on satellites, planes and ships take remotely sensed images of the Earth. These images are used to map everything from the Earth’s surface to the ocean’s seafloor. They help Scientists to track large forest fires, predict weather patterns, record the growth of urban environments and much more.

Scientists who work in these fields use a variety of techniques to capture data. For example, spectrometers are used to measure the emission spectra of sunlight reflecting from objects like trees and buildings, while laser scanners bounce light from objects and measure the return times. These sensors can be hand-held or mounted on platforms ranging from drones to aircraft to satellites. An enormous amount of data is available from Earth observation satellites, including the Landsat program (the longest-running program for the acquisition of Earth imagery).

In the areas of Resource Management and Environmental Sciences, there has been an explosion of growth using digital spatial data and remote sensing data. Indeed, almost every course in Biological, Earth and Environmental Sciences deals with spatial phenomena. It is estimated that 80% of all data collection has some form of geospatial location information.

Topics covered in the course provide an overview of the use of digital geographic information and earth-resource imagery. The approaches dealt with during the Introduction to GIS and Remote Sensing course will allow you to conduct geospatial analyses in a consistent and repeatable manner.

You will explore real-world applications of GIS and remote sensing technology to a range of environments, including:

  • Geography
  • Geology
  • Ecology
  • Vegetation and forestry
  • Agriculture
  • Oceanography
  • Regional and urban analysis

Term offering: Term 2

Course attendance: In person

³¢±ð±¹±ð±ô:ÌýUndergraduate - Second year

Discipline:

  • Biology
  • Climate Science
  • Earth Science
  • Ecology
  • Geography
  • Marine Science

Course code: GEOS2821

Course breakdown

The course aims to provide you with the principles of how to manage and use GIS and remote sensing. Throughout the course, you’ll work on real-world issues, which will help you aid the management of those issues and gain a better understanding of them.

Upon completion of the course, you’ll understand how and why geographic data is stored, input and manipulated using GIS. You’ll also have the knowledge to obtain, process and analyse remotely sensed data.

The course will provide you with the following broad skills:

  • Research, inquiry and analytical thinking
  • Capability and motivation for intellectual development
  • Teamwork, collaboration and management
  • Information literacy

Career opportunities

Roles in GIS and remote sensing span the natural and built environments. Any position that requires geospatial analysis needs people with these skills.

At UNSW Science, you will learn skills in programming languages, problem-solving, processing, interpreting and presentation of data using qualitative and quantitative techniques. Through the Bachelor of Advanced Science (Honours)/Computer Science, you can further your study and specialise in a range of fields.

Relevant roles

  • Geospatial scientist
  • Analyst
  • Software engineer
  • Surveyor
  • Business systems analyst
  • Computer programmer
  • Computer scientist
  • Entrepreneur
  • Project manager
  • Data scientist

Find out more

For more information, please contact Professor Shawn Laffan.

E: shawn.laffan@unsw.edu.au

T: +61 2 9385 8093