Remote Sensing 2 Course Code: Geog424 Dr. M. M. Yagoub E-mailE-mail: myagoub@uaeu.ac.aemyagoub@uaeu.ac.ae E-mail: myagoub@hotmail.com URL : myagoub.

Remote Sensing 2Course Code: Geog424

Dr. M. M. Yagoub 

E-mail :myagoub@uaeu.ac.ae

E-mail: myagoub@hotmail.com

URL : http://faculty.uaeu.ac.ae/~myagoub

URL : http://www.angelfire.com/mo/yagoub

Overview• Course description

• Course outcomes

• Topics

• Assessment

• Software used for the course

• Textbook and References

• Examples remote sensing web sites

• Remote Sensing Organizations

• Remote sensing basic processes

• Advantages of remote sensing

• Remote sensing applications

Course description

 This course covers various advanced techniques of image processing and analysis of remotely sensed digital data. Topics include radiometric correction, geometric correction, atmospheric and ground effects, image enhancement, spectral analysis, color processing, image filtering, image classification, post-classification, change detection, and practical exercises based on satellite datasets.

Course outcomes

Participants who successfully complete this course will be able to perform the followings:

-  Understand and apply image processing techniques for information extraction.

-   Implement and analyze image enhancement techniques.

-  Implement, evaluate, and analyze image classification methods.

-  Understand current representations and methods in image processing.

Topics

Topics covered in the course include the followings:

• Introduction to digital image processing and visual interpretation

• Remote sensing data acquisition alternatives

• Image processing system considerations

• Image processing statistics and visualization

• Radiometric and geometric correction

• Image Enhancement

• Digital Image classification (Supervised, Unsupervised, Fuzzy)

• Digital change detection

• New trend in remote sensing (Digital cameras, Hyper-spectral scanners, high resolution satellite imagery-IKONOS)

Assessment

• Final Exam 40%

• Mid Term Exam 25%

• Quiz 10%

• Course work 20%

• Computer presentation 5%

Total 100%

Software used for the course

• Software used for the course: ERDAS Imagine and ArcGIS.

•  ERDAS: ERDAS is a raster image processing software that can be used to display, enhance, geo-reference, classify, and produce a layout map of an images. ERDAS will be used as the main software for this course.

•  ArcGIS: ArcGIS is a vector GIS software that can be used to geo-reference satellite image and produce a map from the image through on screen digitization.

Textbook and References

Textbook• Jensen, J. R., 1996. Introductory Digital Image Processing : A Remote Sensing Perspective, 2nd ed. New Jersey: Prentice Hall.

References• Avery T. E. and Berlin G. L., 2004. Fundamentals of Remote Sensing and Air photo Interpretation. Prentice Hall: New Jersey.•Campbell, J. B., 1996. Introduction to Remote Sensing. 2nd ed., Taylor and Francis: London.•Castleman, K. R. 1996. Digital Image Processing. Prentice-Hall: London. •Lillesand, T. M. and R. W. Kiefer, 2000. Remote Sensing and Image Interpretation. 4thed., John Wiley and Sons, Inc.: New York.

Remote sensing web sites

• http:// www.esrin.esa.it - Eurpopean Space Agency• http://geo.arc.nasa.gov - NASA program • http://www.spot.com - French satellite SPOT• http://www.nasda.go.jp/ - Japan space agency• http://www.rka.ru./ - Russian Space Agency (RSA)• http://www.coresw.com - Russian imagery source• http://www.space.gc.ca/ - Canadian Space Agency (CSA)• http://www.ccrs.nrcan.gc.ca/ccrs/ -Canada Center for Remote Sensing• http://www.inpe.br/ - National Institute for Space Research (Brazil)• http://www.asprs.org - American Society of Photo. And RS.• http://www.man.ac.uk - Manshester Univ.• http://www.idrisi.clarku.edu - Idrisi site• http://www.amazon.com - Bookstore• http://www.brevard.cc.fl.us/BTR_Labs/bober/martin/rs/overview.htm Dr. Martin McClinton, (*.ppt) format (V. Good)

Remote Sensing Organizations

• ISPRS- International Society for Photogrammetry and Remote Sensing

• IGARSS- International Geosciences And Remote Sensing Symposium

• NASA -National Aeronautic and Space Administration (USA)

• ESA- European Space Agency (Europe)

• NASDA- National Space Development Agency (Japan)

• CNES- Centre National d'Etudes Spatiales (France )

• DARA- German Space Agency

• CSA - Canadian Space Agency

• NRSA- National Remote Sensing Agency of India

Remote sensing basic processes

• Statement of the problem (appropriate logic: inductive, deductive, technological, formulate hypothesis).

• Data collection (In situ, field, lab, passive and active remote sensing, energy propagation, platforms, conversion of energy pattern to images).

• Data Analysis (Visual image interpretation, digital image processing, hypothesis testing –accept or reject, quantitative and qualitative analysis).

• Information presentation (images, image maps, thematic, spatial database, graphs, accuracy/error assessment, (radiometric and geometric correction).

• Information distribution to users (hard copy, CCT, CD-ROM, X-BYTE, Flash Disk, Internet).

Electromagnetic spectrum

• Ultraviolet (UV) angstrom(Å) 10-10 m

• Visible to human eye (0.4-0.7 ) RGB

• Infrared (0.7-1000 ) - emitted thermal radiation (temperature of objects)

• Microwave (0.1 mm - 100 cm)- Active system (RADAR-back scattering, SLAR)

Image recording• Radiation reflected or emitted from earth surface is

converted to signal (Digital Numbers- DN)• The reflectance from a feature depends on the

atmospheric conditions, seasons, time of a day, and physical and chemical characteristics of the feature

• Specular reflectance from smooth surfaces e.g. water, paved roads is lower than that from rough surfaces e.g. forest. In specular reflectance most energy scatter away from the sensor, therefore, objects like water and roads appeared as black in the image

Receiving stationprocessing Archiving

Distribution

Remote sensing basic processes

Selection of a remote sensing system

• Selection of a remote sensing system is a compromise between:– primary sources of EM energy– atmospheric windows– spectral characteristics of surface being sensed– spectral sensitivity of sensors available

Advantages of remote sensing

• Provides a regional view (large areas) • Provides repetitive looks at the same area • Remote sensors "see" over a broader portion of the

spectrum than the human eye • Sensors can focus in on a very specific bandwidth in

an image or a number of bandwidths simultaneously

• Provides geo-referenced, digital, data • Some remote sensors operate in all seasons, at night,

and in bad weather

Remote sensing applications

• Land-use mapping• Forest and agriculture applications• Telecommunication planning• Environmental applications• Hydrology and coastal mapping • Urban planning• Emergencies and Hazards• Global change and Meteorology

World vegetation 1999

World vegetation 2000-2001

Source: http://www.spotimaging.fr