Search our site
Search our site

Cartography, Remote Sensing and Spatial Analysis

  • Module code: GG5155
  • Year: 2018/9
  • Level: 5
  • Credits: 30
  • Pre-requisites: None
  • Co-requisites: None

Summary

Maps are tools for visualising geospatial data to communicate spatial patterns and processes and the results of geographical analysis. This module explores the principles of map design and production in a GIS environment. It introduces ground, aerial and space based surveying, exploring the underlying physical principles and geographical/technological concepts. It covers remotely sensed data capture, image processing and data modelling. The third element develops skills in spatial data analysis and modelling and to explore the application of techniques with respect to point patterns, spatially continuous data and area based data. Cartography, Remote Sensing and Spatial Analysis skills (broadly under the heading 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. These employability skills will be introduced and developed in the Level 4 module GG4010 Digital Earth and Spatial Analysis and are developed in greater depth (enhancing knowledge and the skills portfolio). This module provides a baseline for students taking GG6140 GIS: Transforming Geography and Environment at Level 6.

Aims

  • Examine the importance of good cartographic design for effective communication and provide students with the skills to produce effective maps using GIS
  • Provide an understanding of the principles of remotely sensed surveying and technology (platforms, sensors and data products) and to provide an overview of interpretation techniques used to monitor environmental features through the use of remotely sensed data sets
  • Introduce students to state-of-the-art image processing software and techniques.
  • Develop skills in spatial data analysis and modelling and explore the application of spatial statistical techniques using Geographical Information Systems and their employability-relevance.

Learning outcomes

  • Explain fundamental cartographic principles for effective data communication.
  • Produce thematic and topographic maps in accord with good design criteria, symbolisation, colour and other features.
  • Outline the principles of remote sensing, the electromagnetic spectrum and its relevance to remote sensing techniques and surveying by means of laser scanning.
  • Use modern software packages to manipulate remotely sensed data.
  • Explain the purpose of spatial analysis, including spatial statistics, and their application to geographical data and formulate and execute the solution to a spatial problem taking account of differences between data types using appropriate spatial analytical methods.
  • Describe and interpret the uneven spatial distribution of geographic events such as crime, disease, deprivation, land cover and pollution and highlight the employability advantages these skills bring to solving real world problems.

Curriculum content

  • Cartography and the Earth: introduction to cartography, the framework of the Earth and map projections.
  • Principles of cartography: geographical data in cartography, cartographic abstraction and symbolisation.
  • Cartographic design principles: colour, symbols, typography and layout.
  • Introduction to the principles of remote sensing: the electromagnetic spectrum, radiation interaction at the Earth's surface
  • Introduction to platforms and sensing systems; TM, ETM+, SPOT, AVHRR, MODIS
  • Principles of surveying: relationship between surveying and laser scanning
  • Introduction to image processing: data integration and feature recognition techniques
  • Spatial and non-spatial analytical techniques: Principles of spatial and non-spatial techniques and concepts in spatial data analysis
  • Analysis of spatial entities: use and application of techniques relating to points, lines areas and continuous geospatial data.

Teaching and learning strategy

This module is delivered through a series of lectures and ICT-based practical sessions together with directed reading: the lectures identify and introduce key topics, which will be developed through guided reading and independent study. The ICT-based practical sessions allow students to learn and apply a range of analytical techniques at their own pace. The practical sessions will cover the design and production of maps, the methodologies used to interpret remotely sensed images and datasets that are available in digital format and application of spatial statistical techniques using GIS software and data sets. Students will be introduced to techniques used to enhance and interpret digital images through computer assisted image processing. Students will apply their skills to develop solutions to practical problems outside of class contact time. The module will develop a series of employability skills from Level 4 (eg. GG4010 Digital Earth and Spatial Analysis) including, digital literacies, teamwork, time management, and oral and written communication skills. 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 Lecture Practical Seminar 42 40 4
Guided independent study 214
Total (number of credits x 10) 300

Assessment strategy

Summative assessment consists of:

(A) Map collection ('mini atlas') comprising a mixture of large and small scale maps (50%)

(B) Unified project report based on practical work (50%). Students review anonymised maps produced by previous student cohorts and discuss these during teaching sessions to identify students' strengths and weaknesses as formative assessment.

Formative assessment includes:

A series of short duration multiple choice tests 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.

Tutors will emphasise employability skills linkages between the assessments and their application to real world problems through the articulation of the formative and summative assessment briefs and associated feedback.

Mapping of Learning Outcomes to Assessment Strategy (Indicative)

Learning Outcome Assessment Strategy
1) Explain fundamental cartographic principles for effective data communication In-class formative assessment informing (A) Map collection
2) Produce thematic and topographic maps in accord with good design criteria, symbolisation, colour and other features (A) Map collection
3) Outline the principles of remote sensing, the electromagnetic spectrum and its relevance to remote sensing techniques and surveying by means of laser scanning In-class formative assessment informing (B) Project report
4) Use modern software packages to manipulate remotely sensed data (B) Project report
5) Explain the purpose of spatial analysis, including spatial statistics, and their application to geographical data and formulate and execute the solution to a spatial problem taking account of differences between data types using appropriate spatial analytical methods In-class formative assessment informing (A) Map collection and (B) Project report
6) Describe and interpret the uneven spatial distribution of geographic events such as crime, disease, deprivation, land cover and pollution and highlight the employability advantages these skills bring to solving real world problems (A) Map collection

Elements of Assessment

Description of Assessment Definitive UNISTATS Categories Percentage
Map collection (‘mini atlas') Coursework 50
Project report Coursework 50
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.

Peterson, GN (2014) GIS Cartography: a Guide to effective Map Design. Boca Raton: CRC Press

Bibliography recommended reading

Brewer CA (2008) Designed Maps: a Sourcebook for GIS Users, Redlands, ESRI Press.

Campbell JB (2006) Introduction to Remote Sensing, Fourth Edition, New York: Guildford Press.

Jensen JR (2006) Remote Sensing of Environment: An Earth Resource Perspective. (2nd ed). New Jersey: Prentice Hall.

Lillesand TM, Kiefer RW and Chipman J (2015). Remote Sensing and Image Interpretation. (7th edition). Chichester: John Wiley & Sons.

Mather PM (1999) Computer Processing of Remotely Sensed Images. (2nd ed). Chichester: John Wiley & Sons.

Schen J and Toth C (2008) Topographic Laser Scanning: Principles and Processing. CRC Press.

Smith de MJ, Goodchild MF and Longley PA (2008) Geospatial Analysis: a Comprehensive Guide to Principles, Techniques and Software Tools. (3rd ed). Winchelsea Press. Online link.

Warner TA Nellis MD and Foody GM (2009) SAGE Handbook of Remote Sensing. SAGE Publications.

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

Find a course

Course finder

>
Undergraduate study
Site menu