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Digital Earth and Spatial Analysis

  • Module code: GG4020
  • Year: 2018/9
  • Level: 4
  • Credits: 30
  • Pre-requisites: None
  • Co-requisites: None

Summary

Digital Earth: Spatial Analysis introduces and develops the fundamental geographical skills of data collection, analysis and presentation and the solving of spatial problems using GIS. It concerns data types, representations of reality and key spatial analysis techniques. GIS-based skills are important employability skills for geography and environment students with many course-relevant employers requiring a working knowledge of GIS and the application of GIS to solve real world geographical and environmental challenges. Digital literacy employability skills will be introduced and developed in this module and the module will provide a baseline for students taking GG5155 Cartography, Remote Sensing and Spatial Analysis at Level 5 and GG6140 GIS: Transforming Geography and Environment at Level 6.

Aims

  • To focus on the concepts and value of GIS in geosciences and their real world applications.
  • To introduce the underlying geographical and environmental skills of data collection, manipulation, analysis and presentation using Geographical Information Systems (GIS).
  • To explore fundamental GIS analysis techniques: polygon overlay; buffering and neighbourhood operations; network analysis and surface modelling and associated sources of error in spatial data sets, error assessment and metadata.
  • To develop geographical problem solving approaches and highlight the employability value of developing a range of GIS knowledge and skills.

Learning outcomes

On successful completion of the module, students will be able to:

  • Understand basic techniques of data acquisition, analysis, interpretation and presentation.
  • Explain the different data structures used to represent geographical information in digital data sets.
  • Identify the appropriateness of digital datasets and GIS techniques for particular tasks.
  • Apply a range of GIS (spatial) analytical techniques and understand their use and their employability application
  • Apply the technology of GIS to solve geospatial problems and communicate the results of analysis.
  • Understand the errors and limitations inherent in analyses.

Curriculum content

  • Techniques of data collection, analysis, representation, storage and interpretation
  • Essential map skills (understanding of scale, representation, orientation and navigation using maps)
  • An overview of the historical development of digital spatial data handling and GIS
  • Data models for representing digital data - vector and raster, graphic elements and attribute data
  • GIS as a tool for geographical enquiry in cognate disciplines
  • Basic query analysis and querying spatial databases
  • Introductory spatial statistics
  • Geocoding and address matching
  • Spatial data processing
  • Geoanalysis techniques
  • Surface modelling, network analysis and spatial modelling

Teaching and learning strategy

The module will comprise lectures and practical sessions together with directed reading. Lectures will be used to identify and introduce key topics, which will be developed through use of guided reading to prepare students for the practical sessions.

The practical sessions will cover the methods used to transform and query spatial data in order to solve real-world problems. The practicals will increase in sophistication throughout the year and incorporate skills learned in lectures and prior practicals.

Employability skills will be embedded within the teaching and learning strategy of this module and will include specific skills such as digital literacy and developmental skills such as teamwork and problem-solving (eg. through discussion and debate) and oral, written and graphical communication skills (including cartography).

Canvas VLE will be used to support all aspects of learning and teaching, providing a platform for articulating the module syllabus, assessment and feedback, archiving module-related resources (eg. specific reading materials) and a digital discussion platform.

Breakdown of Teaching and Learning Hours

Definitive UNISTATS Category Indicative Description Hours
Scheduled learning and teaching Lectures Lab Practicals 23 66
Guided independent study 211
Total (number of credits x 10) 300

Assessment strategy

Summative assessment consists of:

(A) Portfolio of Arc-GIS maps (30%). The portfolio consists of three equally weighted maps (10% each) that incrementally develop students' learning of map production using Arc-GIS.

(B) Web mapping project (35%).

(C) Analytical assignment (35%).

Formative assessment will include short in-class tests that will assess the students' ability to recall key information concerning the theoretical underpinnings of geographical information systems, and short duration interactive in-class activities that explore theoretical and practical topics covering the topics presented in lectures and practicals. Rapid, automatic, feedback will highlight areas of strength and weakness, directing the student to areas where greater emphasis is needed. Tutors will provide regular guidance how to develop student's strengths and to improve performance to overcome weaknesses. Assessments will reflect real world applications of GIS and students will reflect on their acquired employability skills through their feedback received.

Mapping of Learning Outcomes to Assessment Strategy (Indicative)

Learning Outcome Assessment Strategy
1) Understand basic techniques of data acquisition, analysis, interpretation and presentation. In class formative assessment informing (A) Portfolio of ArcGIS maps and (C) Web Mapping Assignment.
2) Explain the different data structures used to represent geographical information in digital data sets. In-class formative assessments.
3) Identify the appropriateness of digital datasets and GIS techniques for particular tasks. (A) Portfolio of ArcGIS maps, (B) Web Mapping Assignment and (C) Analytical Assignment informed by in-class formative assignments.
4) Apply a range of GIS (spatial) analytical techniques and understand their use and their employability application. In-class formative assessment supporting the (A) Portfolio of ArcGIS maps and (C) Analytical Assignment.
5) Apply the technology of GIS to solve geospatial problems and communicate the results of analysis. (A) Portfolio of ArcGIS maps and (C) Analytical Assignment informed by in-class formative assignments.
6) Understand the errors and limitations inherent in analyses. In class formative assessment supporting the (A) Portfolio of ArcGIS maps, (B) Web Mapping Assignment and (C) Analytical Assignment.

Elements of Assessment

Description of Assessment Definitive UNISTATS Categories Percentage
Portfolio of ArcGIS maps Coursework 30%
Web mapping project Coursework 35%
Analytical assignment Coursework 35%
Total (to equal 100%) 100%

Achieving a pass

It IS NOT a requirement that any major element of assessment is passed separately in order to achieve an overall pass for the module.

Bibliography core texts

Longley PA, Goodchild MF, Maguire DJ, and Rhind DW (2015) Geographic Information Science and Systems. Hoboken, New Jersey: John Wiley & Sons.

Walford, NS (2011) Practical Statistics for Geographers and Earth Scientists. Chichester: Wiley-Blackwell.

Bibliography recommended reading

Chrisman, N. (1997) Exploring Geographic Information Systems. New York: John Wiley & Sons.

DeMers MN (2008) Fundamentals of Geographic Information Systems.(4th ed). Chichester: John Wiley and Sons.

Heywood I, Cornelius S, and Carver S (2006) An introduction to Geographical Information Systems. (3rd edition), Prentice Hall, New York.

Lo, C P and Yeung, A (2007) Concepts and Techniques of Geographic Information Systems (2nd edition). Prentice Hall, New Jersey.

Rogerson P (2001) Statistical Methods for Geography. Sage, London.

Walford N (2002) Geographical Data: Characteristics and Sources. Wiley, Chichester.

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