REMOTE SENSING IN FORESTRY AND AGRICULTURE
Course: FRST 443 – January 2012
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Instructor:
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Nicholas Coops
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Office Hours:
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Anytime as long as door is open.
FSC 2043
Telephone: 604-822-6452
E-mail: nicholas.coops@ubc.ca
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Text Book:
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Lillesand, T. M., Kiefer, R. W. and Chipman, J (2007) Remote Sensing and Image Interpretation (6th Ed). Wiley and Sons, New York
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Other References:
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Jensen, J.R (2000) Remote Sensing of the Environment: An Earth Resource Perspective, 2nd Edition, Prentice-Hall 544p
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Lectures:
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Monday and Wednesday 12.00-1.00. ROOM FSC 1221
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Lab:
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Wednesday 8 – 10am (Room 1406).
Friday 8 – 10 am (Room 1406).
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Teaching Assistant:
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Colin Ferster (cferster@interchange.ubc.ca)
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FRST 443: Class Timetable is available online at:
http://www.forestry.ubc.ca/irss/Courses/FRST443RemoteSensingForestryAgriculture/tabid/2768/language/en-US/Default.aspx
Class overheads and notes are available from the UBC Forestry course website (FRST443) accessible only with a forestry computer login.
Course Description
This course is an introduction to the methods used to gather spatial information about the Earth’s surface by remote sensing and how this can be used to map, monitor and better manage the forestry and vegetation resources. The course begins with coverage of the fundamentals of spatial data capture, the theory of electromagnetic radiation, the spectral properties of both natural and manufactured materials and the characteristics of airborne and satellite sensor systems used in earth observations.
This is followed by consideration of the principles of photographic analysis and aerial photointerpretation. Basic digital image processing will be explained covering image rectification and classification. New advances such as LIDAR, RADAR and hyperspectral image analysis will also be covered.
Learning Objectives
It is expected that at the completion of this subject and lab program you should have learnt the following:
- The variety and capabilities of current and future airborne and spaceborne sensors.
- The nature of the information content in currently available remotely sensed imagery and how to extract this.
- The spectral properties of the earth surface and how this can be used to interpret vegetation and other aspects of the environment.
- The way in which pixel properties are a mixture of the various components within that pixel and how these can be unmixed to produce abundance maps.
- The various possible applications of the new technique of hyperspectral imagery
- The principles and techniques of Side Looking Radar and Interferometery and how these techniques can be used in the geosciences.
- How to acquire ground truth data and practical aspects of the interpretation of remotely sensed data.
- The role of image processing in the management of spatial geoscience data.
- The range of formats for spatial data that you are likely to encounter.
- The need for data preprocessing and methods of preprocessing.
- Methods of visualisation of spatial data.
- Data characteristics and statistical properties of spatial data.
- Methods of image enhancement and classification.
- The concepts of spatial filtering.
Laboratories: Attendance at all laboratories is mandatory. Laboratories will reinforce concepts learned in readings and lectures, as well as introducing students to new ideas and techniques. Laboratory assignments given out during the labs and are available on-line.
Submission dates are also available on the WWW site.
Grading
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Mid-term (in lecture)
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20%
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Presentations
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10%
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Lab Projects
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30%
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Final Exam (in exam period)
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40%
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Assignments / laboratories may be submitted to the instructor at the beginning of lecture on the deadline date, or prior to the deadline they may be placed in my mailbox, 2nd Floor, Forest Sciences Centre.
The final exam will cover all material (lectures, labs, readings) covered in the entire course. All assignments in this course will be marked for spelling, punctuation, and grammar. Late assignments will be penalized by 30% of the mark per day or partial day late. Make-up tests, exams, or laboratories will only be permitted under exceptional circumstances, with appropriate documentation.
Timetable (Updated 6th Feb 2012)
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2012
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Topic
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Labs (Due Date)
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Wednesday 4th January
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INTRODUCTION
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EXPECTATIONS with respect to REPORTS and LABS
1. Familiarisation to RS (Class: 18/01)
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Friday 7th January
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1. Familiarisation to RS (Class: 18/01)
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Monday 9th January
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ELECTROMAGNETIC SPECTRUM
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Wednesday 11th January
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ELECTROMAGNETIC SPECTRUM
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2.Spectral Signatures (Class: 25/01)
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Friday 13th January
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2. Spectral Signatures (Class: 25/01)
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Monday 16th January
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ELECTROMAGNETIC SPECTRUM
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Wednesday 18th January
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REMOTE SENSING SYSTEMS
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3. Basic Image Analysis (Class: 1/02)
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Friday 20th January
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3. Basic Image Analysis (Class: 1/02 )
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Monday 23rd January
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REMOTE SENSING SYSTEMS
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Wednesday 25th January
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REMOTE SENSING SYSTEMS
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4. Image Rectification (Class: 29/02)
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Friday 27th January
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4. Image Rectification (Class: 29/02)
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Monday 30th January
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BASIC IMAGE PROCESSING
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Wednesday 1st February
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RECTIFICATION
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4. Image Rectification (Class: 29/02)
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Friday 3rd February
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4. Image Rectification (Class: 29/02)
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Monday 6th February
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FILTERING
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Wednesday 8th February
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CLASSIFICATION
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5. Ortho-Rectification (Class: 07 / 03)
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Friday 10th February
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5. Ortho-Rectification (Class: 07 / 03)
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Monday 13th February
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CLASSIFICATION
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Wednesday 15th February
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- MID TERM ASSESSMENT -
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5. Ortho-Rectification ( Class: 07 / 03)
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Friday 17th February
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5. Ortho-Rectification ( Class: 07 / 03)
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Monday 27th February
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API
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Wednesday 29th March
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NO CLASS
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6. API
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Friday 2nd March
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6. API
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Monday 5th March
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PHOTOGRAPHIC SYSTEMS
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Wednesday 7th March
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PHOTOGRAMMETRY
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7 Image Classification (Class: 28/03)
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Friday 9th March
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7. Image Classification (Class: 28/03)
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Monday 12th March
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ACCURACY ASSESSMENT
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Wednesday 14th March
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VEGETATION ANALYSIS
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7. Image Classification (Class: 28/03)
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Friday 16th March
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7. Image Classification (Class: 28/03)
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Monday 19th March
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MICROWAVE
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Wednesday 21st March
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LIDAR
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8. Change Detection (Class 10/04)
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Friday 23rd March
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8. Change Detection (Class 10/04)
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Monday 26th March
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PRESENTATIONS
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Wednesday 28th March
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PRESENTATIONS
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8. Change Detection (Class 10/04)
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Friday 30th March
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8. Change Detection (Class 10/04)
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Monday 2nd April
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PRESENTATIONS
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Wednesday 4th April
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SUMMARY / REVIEW
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SUMMARY/ REVISION
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* Dates of lectures, topics to be covered, are approximations and are subject to change in progress of the class.