Spatial Analysis (10230.2)
|Level:||Level 3 - Undergraduate Advanced Unit|
|HECS Bands:||2, 4|
|Faculty:||Faculty of Science and Technology|
|Discipline:||Academic Program Area - Science|
UC - Canberra, Bruce
Year Teaching Period Convener Mode of Delivery 2020 Semester 1 DR Bernd GRUBER (Ph: +61 2 62063804 ) ON-CAMPUS 2021 Semester 1 DR Bernd GRUBER (Ph: +61 2 62063804 ) ON-CAMPUS
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- Semester 1, 2020, ON-CAMPUS, BRUCE (193705) - View
- Semester 1, 2019, ON-CAMPUS, BRUCE (185280) - View
- Semester 1, 2018, ON-CAMPUS, BRUCE (182005) - View
- Semester 1, 2017, ON-CAMPUS, BRUCE (169944) - View
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This units aims to develop a broader and more comprehensive understanding of spatial scientific methods and how to analyse scientific data using a diversity of existing methods employed in the various scientific sub-disciplines. The unit will include current research projects from within the faculty. Research projects and accompanied data will be presented via a short introduction and then the required methodology to analyse the type of data will be studied and applied.
On successful completion of this unit, students will be able to:
1. Apply prior knowledge from a range of scientific methods in the analysis and interpretation of spatial data sets;
2. Demonstrate knowledge of spatial extensions such as spatial sampling and interpolation methods, cartographic modelling skills and point-pattern analysis along with associated new technologies;
3. Develop an understanding of the key concepts underpinning each method and the associated assumptions and limitations. Acquiring problem solving skills to enable the resolution of new problems and data types;
4. Communicate effectively using well-developed scientific thinking which leads to the formulation of a justified recommendation or advice;
5. Develop ability to recognise scientific problems and being able to apply independent critical scientific thinking that is globally relevant; and
6. Work effectively as an individual and cooperatively within a team setting.
UC - Canberra, Bruce
- Semester 1, 2020
- Semester 1, 2019
- Semester 1, 2018
The mode of delivery is Standard face-to-face teaching and online. This will consist of lectures accompanied with computer labs., with 2x2 hrs of contact for 11 weeks.
Statistical skills, particularly linear regression.
Geographic Information Systems, 6919.