GEOGRAPHICAL INFORMATION SCIENCE AND REMOTE SENSING - 2019/0

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 Alex (Civl Env Eng)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

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

This modules sits within the core subject of surveying, and through its integration of engineering and environmental analysis contributes to the program thread of sustainability. 

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

• 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

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 portfolio consists of reports for five separate assignments. The submission of these is spread over the course of semester to allow feedback from earlier assignments to be incorporated in later assignments. 

The summative assessment consists of two parts:

1. End of term exam (50%) (Learning outcomes 001, 002, and 004)


2. Individual portfolio consisting of five separate assignments (50%) (Learning outcomes 003 and 004)

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

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

• 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

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ENGM285

Other information

Programmes this module appears in

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 2019/0 academic year.