Overview
An introduction to the mathematical methods used in spatial positioning and analysis. Includes concepts of measurement, least squares analysis using observation equations, transformations, spherical trigonometry and map projections.
About this paper
| Paper title | Surveying Mathematics |
|---|---|
| Subject | Surveying |
| EFTS | 0.1334 |
| Points | 18 points |
| Teaching period | Semester 2 (On campus) |
| Domestic Tuition Fees ( NZD ) | $1,355.21 |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- SURV 201 or SURV 211
- Pre or Corequisite
- MATH 130
- Restriction
- SURV 212
- Schedule C
- Science
- Eligibility
Suitable for students with a good understanding of fundamental surveying methods and techniques.
Requires an understanding of mathematical and statistical concepts.- Contact
- paul.denys@otago.ac.nz
- Teaching staff
- Lecturer: Dr Paul Denys
- Paper Structure
The paper covers the following topics:
- Survey measurement and spatial analysis
- Statistical testing
- Least squares analysis using linear observation equations
- Least squares analysis using non-linear observation equations
- Spherical trigonometry
- Teaching Arrangements
Lectures: Four 1-hour lectures
Tutorials: Two 1-hour tutorials
- Textbooks
Required:
- Denys, P. H. (2024), Computational Models for Surveying Applications
Recommended:
- Cooper, M.A.R. Fundamentals of Survey Measurement and Analysis (Granada Publishing)
- Anderson and Mikhail, (1998). Surveying Theory and Practice (7th Edition)
- Graduate Attributes Emphasised
- Scholarship, Critical thinking, Information literacy.
View more information about Otago's graduate attributes. - Learning Outcomes
The goals of the paper are
- To apply basic mathematical and statistical procedures to spatial measurement and analysis problems
- To understand measurement errors, their sources and error propagation of a set of linear or non-linear functions
- To establish an appropriate statistical hypothesis for a surveying-related problem and test it using the appropriate statistical distribution
- To formulate simple observation equations, as might be needed to solve surveying applications
- To apply non-linear least squares analysis techniques to problems in surveying practice
- To use spherical trigonometry to be able to solve practical navigation problems
Overview
An introduction to the mathematical methods used in spatial positioning and analysis. Includes concepts of measurement, least squares analysis using observation equations, transformations, spherical trigonometry and map projections.
About this paper
| Paper title | Surveying Mathematics |
|---|---|
| Subject | Surveying |
| EFTS | 0.1334 |
| Points | 18 points |
| Teaching period | Semester 2 (On campus) |
| Domestic Tuition Fees | Tuition Fees for 2027 have not yet been set |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- SURV 201 or SURV 211
- Pre or Corequisite
- MATH 130
- Restriction
- SURV 212
- Schedule C
- Science
- Eligibility
Suitable for students with a good understanding of fundamental surveying methods and techniques. Requires an understanding of mathematical and statistical concepts.
- Contact
- paul.denys@otago.ac.nz
- Teaching staff
- Lecturer: Dr Paul Denys
- Paper Structure
The paper covers the following topics:
- Survey measurement and spatial analysis
- Statistical testing
- Least squares analysis using linear observation equations
- Least squares analysis using non-linear observation equations
- Spherical trigonometry
- Teaching Arrangements
This paper comprises:
- Lectures: Four 1-hour lectures
- Tutorials: Two 1-hour tutorials
- Textbooks
Required:
- Denys, P. H. (2024), Computational Models for Surveying Applications.
Recommended:
- Cooper, M.A.R. Fundamentals of Survey Measurement and Analysis (Granada Publishing).
- Anderson and Mikhail, (1998). Surveying Theory and Practice (7th Edition).
- Graduate Attributes Emphasised
- Scholarship, Critical thinking, Information literacy.
View more information about Otago's graduate attributes. - Learning Outcomes
The goals of the paper are
- To apply basic mathematical and statistical procedures to spatial measurement and analysis problems
- To understand measurement errors, their sources and error propagation of a set of linear or non-linear functions
- To establish an appropriate statistical hypothesis for a surveying-related problem and test it using the appropriate statistical distribution
- To formulate simple observation equations, as might be needed to solve surveying applications
- To apply non-linear least squares analysis techniques to problems in surveying practice
- To use spherical trigonometry to be able to solve practical navigation problems