Module GEOG3261: ENVIRONMENTAL REMOTE SENSING

Department: Geography

GEOG3261: ENVIRONMENTAL REMOTE SENSING

Prerequisites

• GEOG2591 (GIS AND REMOTE SENSING)

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To develop advanced knowledge and skills in the remote sensing applications which are currently at the forefront of environmental monitoring and management
• To appreciate the power of remote sensing technology for advancing scientific understanding of the hydrosphere and biosphere

Content

• Revision of key Level 2 concepts and methods including image referencing, processing and analysis
• Topography production from imagery (using photogrammetry and Structure from Motion) and laser scanning
• Topography analysis: point-cloud elevation data versus raster format Digital Elevation Models
• Fluvial Remote Sensing I: data collection and platforms suitable to riverine environments, from UAVs and drones to satellites
• Fluvial Remote Sensing II: quantifying river properties and habitats from the air and space using panchromatic, multispectral and hyperspectral imaging
• Catchment Change: quantifying physical changes such as landslides, fluvial erosion and vegetation loss in large in large catchments using multi-temporal image datasets
• Fieldtrip on surface morphology mapping with differential GPS, UAVs and laser scanning.

Learning Outcomes

• On successful completion of the course students are expected to be able to:
• 1: Understand the role and input of earth observation into current environmental debates
• 2: Show a basic theoretical knowledge of the most important methods for computer processing and the interpretation of environmental remote sensing data
• 3: Discuss and evaluate relevant peer review papers on the subject
• 4: Evaluate the use of remote sensing for some important environmental problems in a critical way

• Access web-archived remote sensing data
• Apply the theoretical material covered in the lectures to real-world environmental remote sensing data sets
• Use advanced remote sensing software in a student led project
• Develop a quantitative appreciation for the errors in remotely sensed data

• Students are expected to:
• Present logical written arguments supported with quantitative evidence
• Be able to critically analyse remote sensing data in a given application
• Be able to work independently on a remote sensing project
• Understand remote sensing methods and critically select the most appropriate in a given application

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures introduce students to the theory and practice of remote sensing and indicate how to develop knowledge through wider reading
• Computer practicals will enable the students to gain 'hands on' experience with some of the tools and techniques in remote sensing. They will also have the chance to apply the concepts introduced in lectures to solve real-world problems. Practical exercises introduce students to analytical techniques that will be required by the group and individual based projects
• The field trip will introduce students to skills of collecting scientific data in the field and the principles of ground truthing of remotely sensed data. Students will work in small groups to interpret imagery, navigate to survey points and collect a range of scientific data. After the field class, students will learn how to analyse the data they collected in a subsequent computer-based practical class. Some lectures will build on ideas introduced in the field
• Seminars allow students to develop skills in presenting scientific data
• The student project will develop research skills
• Students will think about research design, hypothesis testing, data processing, data analysis and presentation
• Individually, students will produce a written report and try to place their results in the context of the peer review scientific literature
• The project assessment explicitly addresses Learning Outcomes 2, 3 and 4 (see above)
• The unseen examination will test students' ability to marshal and focus evidence gained from reading and practical experience of using remote sensing data
• The examination questions will cover both theory and practical elements of the module practice and case studies
• The examination assessment explicitly addresses Learning Outcomes 1, 2, 3 and 4 (see above)

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Formative feedback will be provided through an online proposal leading to the final project and verbal feedback on individual presentations during the seminars.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University