Accessibility Skip to Global Navigation Skip to Local Navigation Skip to Content Skip to Search Skip to Site Map Menu

SURV102 Geospatial Science

Due to COVID-19 restrictions, a selection of on-campus papers will be made available via distance and online learning for eligible students.
Find out which papers are available and how to apply on our COVID-19 website

A study of techniques as applied in surveying to built and natural environments, including statistics, trigonometry, mechanics, engineering, introductory programming, Geographic Information Systems (GIS) and remote sensing.

This introductory paper covers foundational material important to future surveying papers and is recommended for progress into SURV 208 Introduction to GIS. GIS is an extremely useful tool for many disciplines in both undergraduate and postgraduate study. It encompasses:

  • Geometry and trigonometry
  • Problem-solving approaches and computational thinking
  • Geospatial data and methods
  • Essential statistics for measurement analysis
  • Essential principles from the physics of motion

Paper title Geospatial Science
Paper code SURV102
Subject Surveying
EFTS 0.15
Points 18 points
Teaching period Semester 2 (On campus)
Domestic Tuition Fees (NZD) $1,262.70
International Tuition Fees (NZD) $5,109.00

^ Top of page

Schedule C
Science
Eligibility
This introductory paper covers foundational material for surveying and GIS papers. It is recommended for progress into SURV 208 Introduction to GIS. GIS and spatial analysis are extremely useful tools in many disciplines, at both undergraduate and postgraduate levels.
Contact
christina.hulbe@otago.ac.nz
Teaching staff

Convenor: Professor Christina Hulbe
Lecturers: Professor Christina Hulbe, Associate Professor Tony Moore, Aubrey Miller and Dr Pascal Sirguey

Paper Structure

This paper reviews and introduces foundational topics in geospatial and measurement science, including:

  • Problem-solving appoaches and computational thinking
  • Essential statistics for measurement analysis
  • Geospatial data and methods

Using the following software:

  • ArcGIS (and/or QGIS)
  • Matlab
Teaching Arrangements

Three or four 1-hour lectures, plus one 3-hour practical per week

A 3-hour final exam (all students must gain a minimum of 40% in the final exam in order to pass the paper)

Internal assessment will count for 50% of the final mark and all work must be completed to meet terms.

  • Practical labs 45%
  • Blackboard quizzes 50%
  • Seminar reports 5%

Communication:

  • Information regarding all aspects of the paper will be provided via the Blackboard site and during the lecture. The Blackboard site will be updated regularly. Your instructors are also available during scheduled lab practicals and at other times by arrangement. If you have a question, ask.

Student responsibilities and participation:

  • It is your responsibility as a student to be aware of the requirements for this paper. How you participate in the paper is both your responsibility and your choice. It is important that you attend lectures. Content is developed over sequences of days, so when you skip days, you miss information, linkages between key ideas and worked examples. You should be aware that you will not earn the best marks possible if you routinely arrive late or choose not to attend lectures and practical sessions.
Textbooks
Textbooks are not required for this paper.

All materials are available online.
Graduate Attributes Emphasised
Critical thinking, Information literacy, Self-motivation.
View more information about Otago's graduate attributes.
Learning Outcomes

Students who successfully complete the paper will be able to

  • Apply problem-solving skills and strategies, including computer implementation of simple mathematical algorithms
  • Understand the importance of measurement errors, use descriptive statistics to quantify errors, and choose and apply appropriate hypothesis tests to gain deeper understanding of the data used in geospatial analysis
  • Use GIS to visualise data and conduct simple spatial analysis and understand the fundamentals of remotely sensed data and its application in geospatial science

^ Top of page

Timetable

Semester 2

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard

Lecture

Stream Days Times Weeks
Attend
A1 Monday 11:00-11:50 28-34, 36-41
Wednesday 11:00-11:50 28-34, 36-41
Thursday 11:00-11:50 28-34, 36-41
Friday 11:00-11:50 28-34, 36-41

Tutorial

Stream Days Times Weeks
Attend one stream from
A1 Monday 08:00-10:50 28-34, 36-41
A2 Wednesday 08:00-10:50 28-34, 36-41
A3 Wednesday 16:00-18:50 28-34, 36-41
A4 Thursday 08:00-10:50 28-34, 36-41

A study of techniques as applied in surveying to built and natural environments, including statistics, trigonometry, mechanics, engineering, introductory programming, Geographic Information Systems (GIS) and remote sensing.

This introductory paper covers foundational material important to future surveying papers and is recommended for progress into SURV 208 Introduction to GIS. GIS is an extremely useful tool for many disciplines in both undergraduate and postgraduate study. It encompasses:

  • Geometry and trigonometry
  • Problem-solving approaches and computational thinking
  • Geospatial data and methods
  • Essential statistics for measurement analysis
  • Essential principles from the physics of motion

Paper title Geospatial Science
Paper code SURV102
Subject Surveying
EFTS 0.15
Points 18 points
Teaching period Semester 2 (On campus)
Domestic Tuition Fees Tuition Fees for 2022 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

Schedule C
Science
Contact
christina.hulbe@otago.ac.nz
Teaching staff

Convenor: Professor Christina Hulbe
Lecturers: Professor Christina Hulbe
Associate Professor Tony Moore
Aubrey Miller
Dr Pascal Sirguey

Paper Structure

This paper reviews and introduces foundational topics in geospatial and measurement science, including:

  • Problem-solving appoaches and computational thinking
  • Essential statistics for measurement analysis
  • Geospatial data and methods

Using the following software:

  • ArcGIS (and/or QGIS)
  • Matlab
Teaching Arrangements

Three or four 1-hour lectures, plus one 3-hour practical per week

A 3-hour final exam (all students must gain a minimum of 40% in the final exam in order to pass the paper)

Internal assessment will count for 50% of the final mark and all work must be completed to meet terms.

  • Practical labs 45%
  • Blackboard quizzes 50%
  • Seminar reports 5%

Communication:

  • Information regarding all aspects of the paper will be provided via the Blackboard site and during the lecture. The Blackboard site will be updated regularly. Your instructors are also available during scheduled lab practicals and at other times by arrangement. If you have a question, ask.

Student responsibilities and participation:

  • It is your responsibility as a student to be aware of the requirements for this paper. How you participate in the paper is both your responsibility and your choice. It is important that you attend lectures. Content is developed over sequences of days, so when you skip days, you miss information, linkages between key ideas and worked examples. You should be aware that you will not earn the best marks possible if you routinely arrive late or choose not to attend lectures and practical sessions.
Textbooks
Textbooks are not required for this paper.

All materials are available online.
Graduate Attributes Emphasised
Critical thinking, Information literacy, Self-motivation.
View more information about Otago's graduate attributes.
Learning Outcomes

Students who successfully complete the paper will be able to

  • Apply problem-solving skills and strategies, including computer implementation of simple mathematical algorithms
  • Understand the importance of measurement errors, use descriptive statistics to quantify errors, and choose and apply appropriate hypothesis tests to gain deeper understanding of the data used in geospatial analysis
  • Use GIS to visualise data and conduct simple spatial analysis and understand the fundamentals of remotely sensed data and its application in geospatial science

^ Top of page

Timetable

Semester 2

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard

Lecture

Stream Days Times Weeks
Attend
A1 Monday 11:00-11:50 28-34, 36-41
Wednesday 11:00-11:50 28-34, 36-41
Thursday 11:00-11:50 28-34, 36-41
Friday 11:00-11:50 28-34, 36-41

Tutorial

Stream Days Times Weeks
Attend one stream from
A1 Monday 08:00-10:50 28-34, 36-41
A2 Wednesday 08:00-10:50 28-34, 36-41
A3 Wednesday 16:00-18:50 28-34, 36-41
A4 Thursday 08:00-10:50 28-34, 36-41