Overview
Geographic Information Science (GIS) through raster analysis, geographic visualisation and big spatial data. Surface and hydrology analysis, visual communication in three dimensions and time, and GIS algorithms and customisation emphasised.
This is an intermediate level Geographic Information Science (GIScience) paper, reflecting the increasingly prominent role of Geographic Information System (GIS) technologies in the world at large. Evidence for this comes from the ubiquity of GIS apps such as Google Earth and Google Maps, associated crowdsourcing resources for various themes (e.g. OpenStreetMap) and the elevated profile of GIS within professions and disciplines (e.g. nationally, the recent change from ‘Surveying’ to ‘Surveying and Spatial’).
The paper will explore large volume and complex spatial datasets (Digital Elevation Models, including 3D point cloud data), whilst extending spatial analysis into raster analysis. The surface modelling aspect of that combines with 3D space and time visualisation content to form a body of content that builds on the foundations of GIS analysis and visualisation through a strong focus on continuous natural phenomena.
Other topics include surface analysis methods, hydrological techniques and visibility modelling. The geographic visualisation module will extend from mapmaking into more complex, flexible and realistic communication technologies such as 3D GIS, Virtual Reality (VR) and tangible Augmented Reality (AR). These are underpinned by spatial data handling topics such as point to surface conversion and uncertainty management. The paper ends with a short capstone project that applies and integrates the major topics covered.
This paper and the introductory GIS paper together form a comprehensive package, covering the essential GIS aspects of data, analysis and visualisation for surveyors, geographers, geologists, life scientists and health scientists, amongst others, who will need GIS knowledge and skills going forward.
About this paper
| Paper title | Spatial Analysis and Visualisation |
|---|---|
| Subject | Surveying |
| EFTS | 0.1334 |
| Points | 18 points |
| Teaching period | Semester 2 (On campus) |
| Domestic Tuition Fees ( NZD ) | $1,278.51 |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- 216 points including SURV 220 or SURV 208
- Restriction
- SURV 520
- Schedule C
- Science
- Eligibility
This paper assumes introductory-level GIS and is suitable for surveyors, geographers, geologists, life scientists and health scientists, amongst others, who need GIS knowledge and skills going forward.
- Contact
- More information link
- Teaching staff
Coordinator and lecturer: Aubrey Miller
Lecturers: Tony Moore, Pascal Sirguey, Kelly Gragg- Paper Structure
The paper covers the following topics:
- Spatial data for analysis
- Introduction to geostatistics and interpolation
- Introductory raster analysis
- Surface and Hydrological analysis (slope, hillshade, water flow modelling)
- Visibility analysis (viewshed, cost path),
- GIS evaluation, error modelling and visualisation
- 3D modelling and visualisation using GIS
- Visualisation of spatial data using Virtual Reality and Augmented Reality
- Spatial and temporal data structures
- Spatiotemporal visualisation
- Teaching Arrangements
In general there are two lectures per week supported by a weekly two-hour practical.
- Textbooks
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, Communication, Critical thinking, Environmental literacy, Information literacy.
View more information about Otago's graduate attributes. - Learning Outcomes
Through successful completion of this paper, students will be able to:
- Extend spatial analysis knowledge and skills by applying simple raster analysis techniques such as reclass, map algebra and filtering.
- Explain the basic theory of and apply surface, hydrological and visibility analysis methods using Digital Elevation Models (DEMs).
- Apply conversion methods from vector to raster, including interpolation.
- Describe 3D and space-time data structures.
- Explain the basic theory of and apply 3D modelling in various contexts using GIS, extending into more complex, flexible and realistic 3D tools, Virtual Reality (VR) and tangible Augmented Reality (AR).
- Translate basic visualisation techniques to other contexts such as data of dynamic phenomena, uncertain data and analysis planning.
- Apply this knowledge practically through a capstone project that unifies data handling and uncertainty, analysis and visualisation skills and knowledge.