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SURV208 Introduction to Geographic Information Systems

An introduction to the principles, methods and concepts of geographic information systems (GIS). The uses of spatial data for mapping, presenting, transforming and analysing information are emphasised.

Geographic information systems (GIS) are being applied increasingly to a variety of human and natural problems that are too numerous and too diverse to list. Since spatial factors are central to almost all issues that involve the management and use of land and human occupancy, it is important that you develop a sound grasp of the principles of GIS and the means of applying it. As surveyors (geographers, planners, geologists, etc.), it is essential to understand the end uses of survey data as they are transformed from field collection into information and eventually into new knowledge. There is barely a single area of local and national government internationally that does not use spatial data of some form or another, and through this the spatial data and information, technology industries are among the fastest-growing in the world, with a multi-billion dollar market.

In this paper, you will be introduced to the key concepts of GIS that are central to the uses of survey and other spatial data. These include technical concepts of data structures, use of ground co-ordinates and maps, and the integration of map data and tables of descriptive information linked to maps.

Paper title Introduction to Geographic Information Systems
Paper code SURV208
Subject Surveying
EFTS 0.1334
Points 18 points
Teaching period Semester 1 (On campus)
Domestic Tuition Fees (NZD) $1,173.39
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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54 points
SPIN 201, SURV 218
Schedule C
Commerce, Science
This paper supports the 200-level courses in the BAppSc GIS Degree, GIS minor and BSurv degree.
Teaching staff

Co-ordinator and Lecturer: Associate Professor Tony Moore
Aubrey Miller
Kelly Gragg

Paper Structure
Paper topics include:
  • Mapping, cartography and geovisualisation
  • Georeferencing
  • The vector and raster data structures
  • Vector and raster spatial analysis techniques
  • Error in spatial data
  • Geovisualisation
  • GIS management
  • Web and mobile GIS
  • 3D GIS
  • GIS and time
  • Volunteered GI
Teaching Arrangements
There are, in general, three lectures per week, supported by a 3-hour practical lab for eight weeks.

Geographic Information Systems and Science, 4th Edition (2015): by P. Longley, M. Goodchild, D. Maguire, and D. Rhind, John Wiley and Sons, Toronto (available as eBook or on reserve in the Central Library).

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Scholarship, Environmental literacy, Information literacy.
View more information about Otago's graduate attributes.
Learning Outcomes

Students who successfully complete the paper will:

  • Be able to distinguish between continuous and discrete geographic phenomena and field and object conceptual models of space
  • Demonstrate the capabilities of basic GIS data analysis and visualisation methods
  • Know how to apply simple analysis techniques such as database search and retrieval, overlay, buffering and filtering
  • Demonstrate knowledge and use of more advanced analytical techniques associated with networks and surfaces (DEMs)
  • Be able to use GIS to create effective maps based on cartographic symbology and composition principles
  • Know about geographic visualisation technologies
  • Be able to use fundamental GIS analytical techniques to solve a variety of problems
  • Know the correct technique to use in the correct situation and practically apply them in a structured way
  • Appreciate the massive variety of applications that GIS is used in
  • Generating derived spatial data and creating new spatial data, understanding the current context in which this occurs
  • Understand the underlying role of map projections and coordinate systems for spatial data
  • Know about the sources of spatial data and appreciate their complex nature (including data quality, data that changes through time, and three-dimensional data)
  • Appreciate that data can now be volunteered (crowdsourcing) and collected by widely-available devices (e.g. smartphones) and delivered via the web and in a mobile sense

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Semester 1

Teaching method
This paper is taught On Campus
Learning management system


Stream Days Times Weeks
A1 Monday 09:00-09:50 9-14, 16-22
Friday 10:00-11:50 9-13, 17-22


Stream Days Times Weeks
Attend one stream from
A1 Monday 10:00-12:50 9-14, 16-22
A2 Tuesday 11:00-13:50 9-14, 16, 18-22
A3 Wednesday 11:00-13:50 9-14, 16-22
A4 Thursday 11:00-13:50 9-14, 16-22