SOIL&WAT 7008 - Remote Sensing

North Terrace Campus - Semester 2 - 2016

The course deals with use of satellite and airborne imagery for environmental and agricultural applications such as land mapping, site evaluation and monitoring degradation and change. Topics include the interaction of electromagnetic radiation with the earth's surface, spectral characteristics of earth surface materials, the nature of imagery collected by a variety of current earth-observation sensors, the use of this imagery for detecting, mapping and monitoring environmental features, collection of field data to interpret imagery, integration of remote sensing and geographic information systems (GIS) for environmental monitoring and modelling, and specialised forms of imagery such as radar, thermal, airborne video and digital photography. Practicals use computer-based image analysis software to enhance and interpret digital images, produce thematic maps, analyse change over time and combine images and map data. Field-based practicals include the use of spectroradiometers for collecting reflectance data about land cover.

  • General Course Information
    Course Details
    Course Code SOIL&WAT 7008
    Course Remote Sensing
    Coordinating Unit School of Biological Sciences
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 5 hours per week
    Available for Study Abroad and Exchange Y
    Incompatible GEOLOGY 3010
    Course Description The course deals with use of satellite and airborne imagery for environmental and agricultural applications such as land mapping, site evaluation and monitoring degradation and change. Topics include the interaction of electromagnetic radiation with the earth's surface, spectral characteristics of earth surface materials, the nature of imagery collected by a variety of current earth-observation sensors, the use of this imagery for detecting, mapping and monitoring environmental features, collection of field data to interpret imagery, integration of remote sensing and geographic information systems (GIS) for environmental monitoring and modelling, and specialised forms of imagery such as radar, thermal, airborne video and digital photography. Practicals use computer-based image analysis software to enhance and interpret digital images, produce thematic maps, analyse change over time and combine images and map data. Field-based practicals include the use of spectroradiometers for collecting reflectance data about land cover.
    Course Staff

    Course Coordinator: Professor Megan Lewis

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    A successful student in this course should be able to:

    1 Explain the physical principles and concepts underlying common forms of remote sensing;
    2 Describe the sources, nature and characteristics of common forms of remote sensing data;
    3 Be able to locate sources of technical information about satellites, sensors and applications;
    4 Be aware of new developments and trends in earth observation;
    5 Perform a range of key digital image analyses using specialist software;
    6 Interpret the information provided by digital imagery for a range of applications and prepare reports that incorporate outputs from digital image analysis software;
    7 Describe how remote sensing is being used for a range of disciplines and applications;
    8 Choose appropriate forms of remote sensing and recommend analyses for particular applications.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    1,2,3,4,7,8
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    5,6,7,8
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    3,4,5,6,7,8
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    1,2,3,4,5,6,7,8
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • Able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    7,8
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
    6,7,8
  • Learning Resources
    Required Resources
    The course lecture notes and practical manual are the key resources for this course. Materials will provided on the MyUni website (http://myuni.adelaide.edu.au). Other teaching materials including lecture recordings, additional exercises and practical notes, course documentation and past examination papers will also be posted on this site.
    Recommended Resources
    Text and reference books
    * Campbell, J.B. (2006). Introduction to Remote Sensing. 4th edn. Guilford Press.
    Cracknell, A. (2007). Introduction to Remote Sensing 2nd. edn. Taylor and Francis.
    Drury, S.A. (2001). Image Interpretation in Geology 3rd edn. Blackwell Science.
    * Gibson, P.J. and Power, C. H. (2000). Introductory Remote Sensing Principles and Concepts. London, Routledge.
    * Jensen, J.R. (1986). Introductory Digital Image Processing 2nd edn. Prentice Hall.
    Jensen, J.R. (2007). Remote Sensing of the Environment: An Earth Resource Perspective 2nd edn. Prentice Hall.
    * Lillesand, T.M. and Kiefer, R.W. (2000). Remote Sensing and Image Interpretation. 4th edn. John Wiley & Sons, New York.
    McCloy, K. (2006). Resource Management Information Systems: Remote Sensing, GIS and Modelling. 2nd edn. Taylor and Francis.
    Richards, J.A. and Xiuping, J. (1999). Remote Sensing Digital Image Analysis: An Introduction 3rd edn. Springer.

    *Text is available in the reserve collection or short-term loan from the Barr Smith Library.

    Reference journals
    Numerous remote sensing journals are available online through the library. Key journals include
    Canadian Journal of Remote Sensing
    Geocarto International
    IEEE Transactions on Geoscience and Remote Sensing
    International Journal of Remote Sensing
    Journal of Spatial Science
    Photogrammetric Engineering
    Remote Sensing Remote Sensing of Environment

    On-line resources
    A wealth of on-line remote sensing resources and learning materials are available. Details of some are provided via MyUni for the course.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The course consists of:
    • 2 X 1-hour lectures per week
    • 1 X 3 -hour practical session per week
    The program is organised so that lectures provide background concepts, theory and applications of remote sensing, and are closely followed by practical sessions that implement these methods using image analysis software. Some scheduled lecture sessions will be used for interactive student exercises.

    It is important to attend the lectures or listen to the recorded lecture materials prior to the corresponding practical session. The practical exercises will be difficult to understand without this background.

    The assignments draw on knowledge and skills covered in several lectures and practicals, with additional interpretation, synthesis and presentation. If you attend and complete the exercises during practical sessions, you will have achieved much of the work required for the assignments.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    A student enrolled in a 3 unit course, such as this, should expect to spend, on average 12 hours per week on the studies required. This includes both the formal contact time required to the course (e.g., lectures and practicals), as well as non-contact time (e.g., reading and revision).
    Learning Activities Summary
    Schedule
    Lecture  Practical 
    Week 1 Introduction to Remote sensing Introduction to ERDAS Imagine image analysis software
    Week 2 Sources and characteristics of remotely sensed data Internet resources for remote sensing. Image interpretation, comparison of remote sensing data sources
    Week 3 Image display, enhancement and interpretation Image enhancement: image enhancement, multispectral transformations
    Week 4 Digital analysis of images Image analysis: principal components analysis
    Week  5         Geometric distortion of airborne and satellite imagery Geometric correction and geo-registration of images
    Digital image classification
    Week 6 Classification of multispectral digital imagery Digital image classification
    Week 7 Field data for remote sensing Advanced image classification; accuracy assessment
    Week 8 Hyperspectral remote sensing Hyperspectral analysis
    Week 9 Monitoring environmental change with remote sensing  Monitoring change with multitemporal imagery
    Week 10 Gamma radiometric sensing Gamma radiometric data interpretation
    Week 11 Integrating remote sensing and GIS Integrating remote sensing and GIS for display, analysis and intrpretation
    Week 12 Answering the big science questions with remote sensing Completion of practical assignments
    Small Group Discovery Experience
    One major assignment conmprises group collaboration on a research
    project involving application of remote sensing information and analyses
    to an environmental or geoscience problem. Tasks involve review of
    relevant background research, selection and sourcing of appropriate
    data, choice and conduct of analyses, interpretation of results and
    presentation in the form of a journal article.Students will be
    asked to provide peer-assessment of individual contributions to the
    final report, which may be used to moderate marks awarded.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Task Type Weighting Hurdle Learning Outcome Due
    Up to 4 assignments based on practical exercises  Summative

    40%

    No 1,2,3,4,5,6,7,8 Advised in course handbook
    Research project based on small group discovery  Summative 20% No 1,2,3,4,5,6,7,8 Advised in course handbook
    Final Exam  Summative 40% No 1,2,4,7,8 Exam period
    Assessment Detail
    Assessments 1, 2, 3 and 4 are based on individual student submission of assignments. While students may work together during practicals, assignments must be individual and original work.
    Assignment 5 is based on work conducted in small groups; one assignment is submitted for the group, with individual contributions clearly identified.

    Assignment 1: Image Sources and Characteristics. (5% of total)Written assignment of short answers, based on lectures and practicals in weeks 1 and 2.

    Assignment 2: Image enhancement and interpretation (10% of total)Illustrated written report based on practical exercises and lectures in weeks 3-5.

    Assignment 3: Image classification (15% of total)Illustrated written report based on practical exercises and lectures in weeks 6 and 7.

    Assignment 4: Hyperspectral analysis (10% of total)Illustrated written report of short answers based on practical exercises and lectures in week 8.

    Assignment 5: Applied remote sensing assignment (20% of total)Illustrated written report based on practical exercises and lectures in weeks 10 and 11 and reading of journal articles.

    Exam (40% of total)A 2 hour written exam drawing on lecture material, exercises and practicals. Comprises short answers, questions requiring calculations and diagrams and longer written explanations. Examples of previous exam papers are provided in MyUni.
    Submission
    Assignments must be submitted electronically via MyUni. Ensure that you are familiar with procedures for doing this: if in doubt seek assistance in practical classes.

    Do NOT email assignments to the lecturing or demonstrating staff – assignments are not accepted this way.

    Extensions for Assessments
    Extensions of deadlines for assessment tasks may be allowed for reasonable causes. Such situations
    include compassionate and medical grounds of the severity that would justify the awarding of a replacement examination. Evidence for the grounds must be provided when an extension is requested.
    Students are required to apply for an extension to the course co-ordinator before the assessment task is due. Extensions will not be provided on the grounds of poor prioritising of time.

    Penalties for Late Submission
    If an extension is not applied for, or not granted then a penalty for late submission will apply. A penalty of 10% of the value of the assignment for each calendar day that is late (i.e. weekends count as 2 days), up to a maximum of 50% of the available marks will be applied. This means that an assignment that is 5 days or more late without an approved extension can only receive a maximum of 50% of the mark
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
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