MSc International Disaster Management / Course details

Year of entry: 2023

Course unit details:
GIS and Disasters: A Critical Introduction

Course unit fact file
Unit code HCRI60072
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Offered by
Available as a free choice unit? No

Overview

Geographic information systems (GIS) are computer systems for capturing, storing, analysing, displaying and sharing data related to positions on Earth's surface. GIS and the analysis of spatial data has application to many fields, such as environmental management, urban planning, business, government, as well as disaster management. Today more than ever we need innovative approaches to understanding and managing hazards, risk, and vulnerabilities to reduce negative disaster impacts.

 

In this course students will be exposed to a range of transferrable GIS techniques and analysis tools and will learn how to apply these to various disaster management tasks, such as mapping vulnerability using census data, or modelling risk using meteorological and other physical geography data. Students will learn important cartographic principles and develop their own GIS maps. In addition to the practical components, the course will develop theoretical understandings and critically consider the appropriateness and implications of GIS approaches and map making.

Aims

The course aims to:

• Develop an understanding of spatial data and its analysis

• Develop spatial problem-solving abilities and practical skills in GIS analysis and cartography

• Explore a broad set of applications of spatial data and GIS for crisis management and disaster risk reduction

• Critically reflect on the power, usefulness, and limitations of GIS and spatial data broadly and in disaster management

Syllabus

All topics are indicative examples:

  1. Understanding geographic data, spatial analysis and geographic information systems (GIS)
  2. Disaster vulnerability and risk reduction
  3. Coordinate systems / map projections
  4. Data models: Vector data / Raster data
  5. Data collection
  6. Spatial analysis (e.g. buffer, overlay, reclassification)
  7. Surface modelling (e.g. interpolation, digital elevation models)
  8. Cartography / map making
  9. Remote sensing and drones
  10. Digital Humanitarianism / Career in GIS risk

Teaching and learning methods

2 hr practical (composed of 30-40 min lecture and 80 mins of lab work

Independent learning/reading

Blackboard (E.g. discussions)

Knowledge and understanding

Demonstrate knowledge and understanding of:

• Different types of spatial data and how they are developed and analysed

• Current and potential applications of spatial data and GIS in disaster management

• Spatial analysis as a mechanism for assessing hazard risk and vulnerability

• The implications of GIS, including the power of maps to persuade, digital divides and unequal access to spatial information, contemporary trends and changing practices

Intellectual skills

• Identify and evaluate patterns and trends in spatial data

• Investigate dynamic phenomena through interrogation of spatial and temporal data

• Consider the influence of geography on different approaches to analysing and managing disasters

• Critically analyse the role of GIS and mapping in disaster management, and the underpinning theories

Practical skills

• Conduct a range of analyses on both vector and raster datasets

• Combine multiple data to address real world problems

• Cartography skills and the design and production of GIS maps

• Research skills, including planning, prioritisation of tasks, identification and location of sources, critical evaluation of findings

• Communicating analysis results in the form of map analysis

• Participation in online and in-class discussions

Transferable skills and personal qualities

  • Spatial data analysis and interpretation skills.
  • Experience in preparing GIS maps of the same kind that may be used in academia, policy development, or the professional sector.
  • Critical thinking, research and project management skills
  • Skills to help them interpret current and future disaster risk and vulnerability
  • Ethical awareness

Employability skills

Innovation/creativity
Professional knowledge and skills: GIS and spatial data analysis (ESRI ArcGIS in particular)
Project management
Time management
Oral communication
Communication skills
Problem solving
Problem solving skills
Written communication
Reporting of scientific data/analyses
Other
Ability to work independently

Assessment methods

Method Weight
Other 60%
Written assignment (inc essay) 40%

Feedback methods

Informal oral feedback during class/labs

Formative

Written feedback on  on disaster map scenario returned to students according to SALC guidelines and time limits, using a bespoke rubric

Formative / summative

Additional one-to-one feedback (during the consultation hour or by making an appointment)

Formative

Blackboard discussion forum

Formative

Recommended reading

Brewer, C.A. (2006). Basic mapping principles for visualizing cancer data using geographic information systems (GIS). American Journal of Preventative Medicine, 30(2S): S25-S36.

Canevari-Luzardo, L., Bastide, J.,  Choutet, I., and Liverman, D. (2017) Using partial participatory GIS in vulnerability and disaster risk reduction in Grenada, Climate and Development, 9:2, 95-109, DOI: 10.1080/17565529.2015.1067593

Cutter, S. (2003). GIScience, disasters, and emergency management. Transactions in GIS, 7(4): 439–445.

Dempsey, C. (2018) GIS Lounge at https://www.gislounge.com/free-gis-books/ (Accessed September 2022)

Esri (2022) Disaster Response Programme Webpage.  Accessed September 2022 at https://www.esri.com/en-us/disaster-response/overview.

Esri (2022) Emergency and disaster management webpage.  Accessed September 2022 at https://www.esri.com/en-us/industries/emergency-management/overview

Gaillard, J.C., and Pangilinan, M.L.C.J.D. (2010). Participatory mapping for raising disaster risk awareness among the youth. Journal of Contingencies and Crisis Management, 18(3): 175-179.

Goodchild, M.F., & Glennon, J.A. (2010). Crowdsourcing geographic information for disaster response: A research frontier. International Journal of Digital Earth, 3(3): 231-241.

Scheduled activity hours Seminars 20

Independent study hours
Independent study 130

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