Department of Geography & Resource Management
The Chinese University of Hong Kong
2nd Term, 2010-2011
GRMD3104 Satellite Image Analysis
Professor:
Graduate Assistant:
Fung Tung
Liu Xiang
Website:
https://webct.cuhk.edu.hk/
Lecture
Time
T3-T4
(10:30 am – 12:15 pm)
F9-F10
(4:30 pm – 6:15 pm)
Laboratory demonstration
Laboratory
Rm 238A
Rm 216
tungfung@cuhk.edu.hk
liuxiang@cuhk.edu.hk
Venue
SB UG05 (Jan 11 and 18)
FYB 233 (Jan 28 – Apr 15)
Room 222
Any time
Room 222
Learning Objectives
This course discusses the concept and application of digital image processing techniques in
analysing digital satellite data for geographical and environmental studies. Topics include:
image preprocessing, image enhancement, image classification, accuracy verification and
change detection. Upon completion of the course, students are expected to grasp basic
understanding of the principle of digital remote sensing image analysis and how different
processing techniques are applied in generating thematic information.
Content and Lecture Schedule
Week
Date
Content
1
Jan 11
Overview
(Tue)
 Principle of remote sensing
 Electromagnetic Radiation
 Electromagnetic Spectrum
 Spectral properties of terrestrial features
2
Jan 18
Satellite Remote Sensing
(Tue)
 Types of satellites
 Landsat ETM+
 SPOT
 IKONOS, Quickbird, Worldview
3
Jan 28
Image Structure and Formats
(Fri)
Image Resolution
 Spatial resolution
 Spectral resolution
 Radiometric resolution
 Temporal resolution
Effect of resolutions on image analysis
4
Feb 4
Holiday
5
Feb 11
Image processing systems
(Fri)
 Hardware and software
 PCI Geomatica system
Image Display Methods
6
Feb 18
7
Feb 25
8
Mar 4
9
Mar 11
10
Mar 18
11
Mar 25
12
Apr 1
13
Apr 8
14
Apr 15
15
Apr 22
 Black and white display
 Pseudocolor display
 Color composite
Image Enhancement
 Image histogram
 Linear Stretching
Image Enhancement
 Piecewise stretching
 Histogram equalization
 Image Matching
Image preprocessing
 Radiometric adjustment
 Geometric correction
Multispectral Transformation

Image Ratioing

Vegetation Indices
Multispectral Transformation
 Principal components analysis
 Tasseled cap transformation
Hue-saturation-intensity transform
Data Fusion
Spatial filtering
 Low pass filters
 High pass filters
Textures
Logic of Image Classification
Supervised classification I
 Procedures in classification
 Training set selection
Supervised classification II
 Feature Selection
 Classification Algorithms
 Parallelepiped classifier
 Euclidean distance classifier
 Maximum likelihood classifier
 Fuzzy classifier
 Neural Network classifiers
Unsupervised classification
 Spectral classes
 Clustering criteria
 Clustering algorithms
Accuracy verification
 Spatial sampling
 Error matrix and interpretation
Change Detection
 Nature of changes
 Techniques for change detection
Easter Holiday
Laboratory
Week
3
6
7
9
Laboratory
1 Search for satellite data
2 Image display and enhancement
3 Geometric correction
4 Multispectral image transformation
11
12
14
5 Spatial filtering
6 Supervised classification
7 Unsupervised classification
Assessment
Laboratory:
Final examination:
50%
50%
Feedback for Evaluation
Early course evaluation, classroom discussion, discussion and mail with webCT, course
evaluation
Honesty in Academic Work
Attention is drawn to University policy and regulations on honesty in academic work,
and to the disciplinary guidelines and procedures applicable to breaches of such policy
and regulations. Details may be found at
http://www.cuhk.edu.hk/policy/academichonesty/ .
With each assignment, students will be required to submit a signed declaration that they
are aware of these policies, regulations, guidelines and procedures.
For assignments in the form of a computer-generated document that is principally textbased and submitted via the plagiarism detection engine CUPIDE, the statement, in the
form of a receipt, will be issued by the system upon students’ uploading of the soft copy
of the assignment. Assignments without the receipt will not be graded by teachers.
Required Readings
Jensen, J.R., 2005, Introductory Digital Image Processing: A Remote Sensing Perspective, 3rd
edition, Prentice-Hall, Englewood Cliffs, New Jersey.
Topic
Overview
Satellites
Digital Images
Image Resolution
Image Display
Image Enhancement
Image Preprocessing
Multispectral Transforms
Spatial Filtering
Supervised Classification
Unsupervised Classification
Accuracy assessment
Change Detection
Reading
Jensen2005: Chapter 1
Jensen2005: Chapter 2
Jensen2005: Chapter 2 (p.101-103)
Jensen2005: Chapter 1 (p.14-19)
Jensen2005: Chapter 5 (p.151-164)
Jensen2005: Chapter 8 (p.255-274)
Jensen2005: Chapter 7 (p.194-222; 227-252)
Jensen2005: Chapter 8 (p.274-276; 296-322)
Jensen2005: Chapter 8 (p.276-296; 322-329)
Jensen2005: Chapter 9 (p.337-370)
Jensen2005: Chapter 9 (p.370-385)
Jensen2005: Chapter 13
Jensen2005: Chapter 12
Recommended Readings
1.
Campbell, J.B., 2002, Introduction to Remote Sensing, 3rd edition, Guilford, New York.
2.
Canty, M.J., 2010, Image Analysis, Classification, and Change Detection in Remote
Sensing, with Algorithms for ENVI/IDL, CRC Press, Taylor & Francis, Boca Raton.
3.
Chuvieco, E. and A. Huete, 2010, Fundamentals of Satellite Remote Sensing, CRC Press,
Boca Raton.
4.
Fenstermaker, L.K., 1994 (ed.), Remote Sensing Thematic Accuracy Assessment: A
Compendium, American Society for Photogrammetry and Remote Sensing, Nethesda.
5. Jensen, J.R., 2005, Introductory Digital Image Processing: A Remote Sensing
Perspective, 3rd edition, Prentice-Hall, Englewood Cliffs, New Jersey.
6. Jensen, J.R., 2000, Remote Sensing of the Environment, an Earth Resource
Perspective, Prentice Hall, New York.
7.
Lillesand, T.M., R.W. Kiefer and J.W. Chipman, 2008, Remote Sensing and Image
Interpretation, 6th edition, John Wiley and Son, New York.
8.
Mather, P.M., 2004, Computer Processing of Remotely Sensed Images, 3rd edition, John
Wiley & Sons, New York.
9.
Richards, J.A. and X. Jia, 2006, Remote Sensing Digital Image Analysis, 4th edition,
Springer & Verlag, Berlin.
10. Schott, J.R., 1997, Remote Sensing: the Image Chain Approach, Oxford University Press,
New York.
11. Schowengert, R.A., 1997, Remote Sensing: Models and Methods for Image Processing, 2nd
Edition, Academic Press, New York.
T. Fung
January, 2011
Remote Sensing materials on internet
Tutorials
Canada Centre for Remote Sensing:
Fundatmentals of Remote Sensing
American Society for Photogrammetry &
Remote Sensing
http://www.ccrs.nrcan.gc.ca/ccrs/eduref/tu
torial/tutore.html
http://research.umbc.edu/~tbenja1/
General
Earth Observatory, NASA, USA
Earth Today
Virtual Library
http://earthobservatory.nasa.gov/
http://www.nasm.si.edu/earthtoday/
http://www.vtt.fi/aut/rs/virtual/
Remote Sensing Data
SPOT
Landsat, IKONOS
ASTER
Radarsat
Orbview
Quickbird
Earth Observing System
NOAA Satellite Active Archive
http://www.spot.com
http://www.spaceimaging.com
http://asterweb.jpl.nasa.gov/
http://radarsat.space.gc.ca
http://www.orbimage.com
http://www.digitalglobe.com
http://eospso.gsfc.nasa.gov/
http://www.saa.noaa.gov/
Governmental / professional organizations
Earth Observing System, NASA
JPL Imaging Radar
NASA (Landsat 7)
American Society for Photogrammetry &
Remote Sensing
CCRS, Natural Resources Canada
Australian Centre for Remote Sensing
European Space Agency
Swedish Space Corporation
Centre for Remote Imaging, Sensing and
Processing, The National University of
Singapore
Chinese Society of Photogrammetry and
Remote Sensing (Taiwan)
Earth Observation Center, National Space
Development Agency of Japan
http://eospso.gsfc.nasa.gov/
http://southport.jpl.nasa.gov/
http://landsat.gsfc.nasa.gov/
http://www.asprs.org/
http://www.ccrs.nrcan.gc.ca/ccrs/
http://www.auslig.gov.au/acres/index.htm
http://www.esa.int/
http://www.ssc.se
http://www.crisp.nus.edu.sg/
http://www.csprs.org.tw/chinataipei.html
http://hdsn.eoc.nasda.go.jp/homepage.html
Remote Sensing Software
ERMAPPER
PCI Geomatics
ENVI
ERDAS
TNT
IDRISI, Clark Labs, Clark University
http://www.ermapper.com/
http://www.pci.on.ca
http://www.envi-sw.com/
http://www.erdas.com/
http://www.microimages.com/
http://www.clarklabs.org/