Spatial Data Science
Module title | Spatial Data Science |
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Module code | GEOM183 |
Academic year | 2023/4 |
Credits | 15 |
Module staff | Professor Rolf Aalto (Convenor) |
Duration: Term | 1 | 2 | 3 |
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Duration: Weeks | 10 |
Number students taking module (anticipated) | 15 |
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Module description
Spatial data science adds multidimensional geographical data including evolving timescales and place-based context to the growing field of data science. Incorporate spatial data with cutting edge tools, and methods to enhance analytics and problem solving.
Building on coding and remote sensing skills learned in Term 1, discover advanced spatial approaches that incorporate geography into GIS-based computation. This module will provide deeper understanding how to incorporate spatial characteristics with specialist techniques to turn the data into useful information that links to the science, with examples drawn from Exeter research. Approaches you will use include analysing multidimensional data to solve problems delineating land-use types and quantifying change. As part of the module you will undertake local fieldwork to understand land classification techniques and integration of real-time sensor networks.
Module aims - intentions of the module
This module explores the science in “data science” including research design, statistical significance, and work flow development in order to truly achieve insight rather than just information. This will empower students with the knowledge and skills to conduct sophisticated analyses needed for understanding dynamic environmental changes across space and time, supporting both their Applied Projects (GEOM185/186) and future careers.
The module consists of mix of lectures, computer practicals, group work exercises, seminars, field work, and wider reading. The weekly pattern will vary throughout the term, with term split into two teaching blocks that revolve around research-enriched teaching: the first half will be focused on computer lab analysis of data sourced from international research projects conducted by Exeter staff, and the second half will involve research data collected more locally, including during fieldwork by the class.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Evaluation and analysis of multidimensional data collected by various techniques across space and time
- 2. Apply data science approaches to achieve spatial insight into dynamic environments
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. Critical understanding of how different field datasets represent environmental conditions
- 4. Extract quantitative information from large datasets with an appreciation of uncertainty and limitations
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 5. Critically interpret and present results from quantitative analysis, both for the specific research and also presented with respect to previous studies.
- 6. Clearly present results both graphically and as written text, with attention to structure, narrative clarity, and with justification of how the information is presented.
Syllabus plan
Topics covered in the module are expected to include:
- Fieldwork using emerging techniques to collect various spatial data
- Spatial data science for research data from Earth's greatest rivers
- Multidimensional geographical data registration & analysis across space and time
- Production of Digital Elevation Models to investigate environmental dynamics
- Visualisation for 3D data such as lidar, sonar, structure from motion, and/or radar
- Advanced spatial & scientific approaches including differencing and machine learning
- Wireless Sensor Networks and Internet of Things technologies for environmental monitoring
- Spatial and temporal analysis of dynamic environmental changes.
Learning activities and teaching methods (given in hours of study time)
Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
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30 | 120 | 0 |
Details of learning activities and teaching methods
Category | Hours of study time | Description |
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Scheduled Learning and Teaching | 6 | Lectures |
Scheduled Learning and Teaching | 14 | Practical computing tasks |
Scheduled Learning and Teaching | 6 | Half day field course |
Scheduled Learning and Teaching | 4 | Discussion seminars |
Guided Independent Study | 70 | Computer-based tasks to support learning and assessments |
Guided Independent Study | 50 | Reading relevant literature and posted material on ELE, online research to support learning and assessments |
Formative assessment
Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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Short seminar presentations | 2 x 5-min oral presentations | 2-5 | Peer-to-peer and in-class feedback from staff |
Discussion during practical sessions and field excursion | Throughout the module | 1-4 | Peer-to-peer and in-class feedback from staff, responses on ELE |
Summative assessment (% of credit)
Coursework | Written exams | Practical exams |
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100 | 0 | 0 |
Details of summative assessment
Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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Technical Report 1 | 50 | 2000 word equivalent | 1-6 | Individual written feedback |
Technical Report 2 | 50 | 2000 word equivalent | 1-6 | Individual written feedback |
Details of re-assessment (where required by referral or deferral)
Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
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Technical Report 1 | Technical Report 1 | 1-6 | Referral/deferral period |
Technical Report 2 | Technical Report 2 | 1-6 | Referral/deferral period |
Re-assessment notes
Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.
Referral – if you have failed the module overall (i.e., a final overall module mark of less than 50%) you will be required to submit a further assessment. The mark given for a re-assessment taken as a result of referral will count for 100% of the final mark and will be capped at 50%.
Indicative learning resources - Basic reading
- Publications and online resources to be provided
Indicative learning resources - Web based and electronic resources
- ELE
Indicative learning resources - Other resources
- Relevant journal articles will be provided in advance of the discussion seminars
Credit value | 15 |
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Module ECTS | 7.5 |
Module pre-requisites | GEOM180, GEOM181 |
Module co-requisites | None |
NQF level (module) | 7 |
Available as distance learning? | Yes |
Origin date | 27/02/2023 |
Last revision date | 20/06/2023 |