GEOGRAPHICAL INFORMATION SCIENCE AND REMOTE SENSING - 2018/9

Module code: ENGM285

Module Overview

Spatial data ­— data tied to a specific geographical location or area — is ubiquitously available and provides rich insight into our natural and built environment, social and economic activities and much more. Geographical Information Science (GIS) provides the concepts, methods and tools to analyse such data, using the spatial component of the data as an integral part of the analysis. Remote Sensing (RS) systems image the entire Earth on daily basis. RS methods allow the derivation of a wide range of spatial information from the imagery, providing a major source of spatial data.

GIS and RS are used in a wide range of disciplines including hydrology, natural resource management, climate change and infrastructure planning. This module introduces the theoretical foundations and trains the student in using these techniques to solve problems and support decision making, with an emphasis on Civil and Environmental Engineering practice.

Module provider

Civil and Environmental Engineering

Module Leader

HAGEN-ZANKER AH Dr (Civl Env Eng)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

JACs code: F755

Module cap (Maximum number of students): 50

Module Availability

Semester 2

Prerequisites / Co-requisites

Capability in basic data analysis using Excel or other spreadsheet software.

Module content

Geographical information science:


The role of GIS in Civil and Environmental Engineering practice
Measurement and representation of geographical information
Methods of spatial analysis
Geosimulation and agent based modelling
Cartography and data visualisation


Remote Sensing:


Applications of RS in Civil and Environmental Engineering practice
Fundamentals of RS
Digital images
Passive and active sensors. Data sources
Image analysis. Image enhancement, band operations and classification

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Portfolio 50
Examination Exam 50

Alternative Assessment

N/A

Assessment Strategy


Over the course of the module, the students will develop a portfolio of work based on the practical GIS and RS exercises they complete in computer laboratory sessions and independently outside of scheduled hours. The portfolio will allow the assessment of students in a more critical sense regarding their capacity to apply, analyze and evaluate GIS and RS methods and tools. The lecturers will provide individual feedback on the portfolio in progress during computer laboratory sessions.
The summative assessment consists of two parts:


End of term exam (50%) (LO1, LO2, LO3)
Individual portfolio (50%) (LO2, LO3, LO4, LO5)


Module aims

  • Introduce the background, theory and methods of Geographical Information Science and Remote Sensing
  • Develop awareness of the spatial component of engineering and environmental problems, the available data sources and analytical methods
  • Gain practical experience using GIS software and spatial data to solve problems and support decision making
  • Train students to identify remote sensing data useful for their engineering and environmental problems, and to access, acquire and analyse such data

Learning outcomes

Attributes Developed
001 Comprehend key concepts of GIS and remote sensing K
002 Be aware of engineering and environmental applications of GIS and RS KP
003 Be capable of applying GIS and RS tools to engineering/environmental problems CP
004 Be able to critically evaluate data, analysis techniques and results KCPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Overall student workload

Independent Study Hours: 114

Lecture Hours: 18

Laboratory Hours: 18

Methods of Teaching / Learning

The learning and teaching strategy is designed to:


describe the fundamental concepts and analytical techniques of GIS and RS in lectures, and demonstrate these with examples;
provide students with hands-on experience of the introduced techniques using practical problems in guided computer laboratory sessions;
laboratory sessions will be used to foster interactions and engagement with students. This will also allow students to work in groups through problem-based learning and offer an opportunity for academics to provide individual feedback


The learning and teaching methods include:


Lectures (18 hours)
Computer laboratory sessions (18 hours)
Independent learning (114 hours)

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

Reading list for GEOGRAPHICAL INFORMATION SCIENCE AND REMOTE SENSING : http://aspire.surrey.ac.uk/modules/engm285

Other information

 

 

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Structural Engineering MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module
Civil Engineering MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module
Advanced Geotechnical Engineering MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module
Bridge Engineering MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module
Infrastructure Engineering and Management MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module
Water and Environmental Engineering MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2018/9 academic year.