GGR 337 Environmental Remote Sensing:

½ courseMonday 10:00 am-12:00 noon

Jing M. ChenDepartment of Geography

University of Toronto Office: Room 305, 45 St. George St.

Physical Geography BuildingConsultation Time: Wednesday 3:15 to 5:15 PM

T.A.: Weimin Ju, Room 306, 45 St. George St.

This space is for references

Course Outline

1. Introduction2. Electromagnetic Radiation (Lab. #1, 5%)3. Spectral characteristics4. Satellite orbits and sensors5. Digital data handling and geometric corrections (Lab. #2, 10%)6. Image enhancement and filtering (Lab. #3, 10%)7. Color display techniques (Lab. #4, 10%)8. Multispectral transformations and vegetation indices9. Radiometric correcitons10. Clustering and unsupervised classification11. Supervised classification techniques (Lab, #5, 15%)12. Remote sensing applications I13. Advanced remote sensing tools. Review

Definition of Remote Sensing

Remote Sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation

Key words:1. “science and art”2. “not in contact”

Lillesand et al., Chapter 1

Other Definitions of Remote Sensing

Remote sensing is the practice of deriving information about the earth’s land and water surfaces using images acquired from an overhead perspective, using electromagnetic radiation in one or more regions of the electromagnetic spectrum, reflected or emitted from the earth’s surface.

Campbell (1996), Chapter 1.2

The art of dividing up the world into little multi-coloured squares and then playing computer games with them to release unbelievable potential that's always just out of reach. - Jon Huntington, CSIRO Exploration, Geoscience, Australia

Definitions

Remote Sensing is the most expensive way to make a picture.- Andrew Bashfield, Intergraph Corporation

Seeing what can't be seen, then convincing someone that you're right. - David Pairman, Landcare Research, New Zealand

Being as far away from your object of study as possible and getting the computer to handle the numbers.- Clare Power, N.R.S.C., England

The acquisition of information about an object, without being in physical contact with that object.- Christine Hutton, CCRS

Staying as far away from the problem as possible. - G. Archer, World Bank

Having fun without touching.- Peter Hausknecht, DLR, Germany

Canada Centre for Remote Sensing Web Site: www.ccrs.nrcan.gc.ca

Schedule and Topics

January 5

OverviewCourse Description

Resources, References, BooksComputer Accounts, Unix Systems

Introduction to PCI

Definition and Principles of Remote SensingHistory of Remote Sensing

January 12

Electromagnetic Radiation

Electromagnetic Spectrum

Radiation Laws

Atmospheric Absorption

Radiation Terminology

Lab 1: Radiation Questions

January 19

Spectral Signatures of Ground Targets

Spectral Signatures: Passive SensorsVegetation

SoilWater

Thermal

Spectral Signatures: Active Sensors

January 26

Satellite Orbits and Sensors

Geostationary and Polar-Orbiting Active and Passive Sensors

CharacteristicsComponents

February 2

Interpretation of Digital Data

Bit and ByteASCIIBinary

Image Recording Media and Formats

Geometric correctionsImage registration

Projections

Lab. #2, 10%

February 9

Image Enhancement and Filtering

Single-Band Image ProcessingHistogram

Image contrast enhancement(Linear stretch, histogram equalization)

Spatial feature enhancementEdge enhancement

Filters

Lab. #3, 10%

February 23

Colour Display Techniques

Colour DisplayAdditive and Subtractive Colours

Colour TriangleColour Cube

HexconeHue, Intensity and Satruation

Class 8: Radiometric Corrections

Sensor CorrectionsAtmospheric Corrections

Conversion from DN to reflectanceBRDF Corrections

March 01

Lab. #4, 10%

March 08

Multispectral transformation and Vegetation Indices

Two-band vegetation indices

Three-band vegetation indices

Leaf area index

March 15

Clustering and Unsupervised Classification

Histogram-basedSequential Clustering

Spectral Similarity

Lab. #5, 15%

March 22

Supervised Classification

Training FieldsParallel Piped Classifier

Maximum Likelihood Classifier

Assessment of Classification Accuracy

March 29

Remote Sensing Applications

Forestry

Agriculture

Climate Change

Environment, etc.

April 05

Advanced Remote Sensing Tools

Geometric-optical model

Atmospheric correction model

Review of major concepts

Marking Scheme

Grading PolicyWork which is handed in late will be downgraded by 10% for each day overdue (give the assignment to the TA and he will note the date on it), i.e., the grade is multiplied by 0.90 if handed one day late; multiplied by 0.80 for 2 days, etc.

Lab Work 50% Throughout the term (5 labs)35% For graduate students (4 labs)

Mid-term Exam 10% Also for graduate students

Final Exam 40% Date to be determined30% for graduate students

Term Paper 25% for graduate students only

Text Book

Remote Sensing and Image InterpretationT.M. Lillesand, R. W. Kiefer, and J. W. Chipman, Wiley, 2004 (5th Ed.)

References

Remote Sensing : Principles and InterpretationFloyd F. Sabins , 1996 (3rd Ed.)

Satellite Remote Sensing of Natural Resources David L. Verbyla, CRC Lewis Publishers, 1995

Introduction to Remote Sensing

James B. Campbell, Guilford Press, 1996 (2nd Ed.)

History of Remote SensingHistory of Remote Sensing

Milestones

Principles

Campbell Chapter 1

Milestones

1826-27 Beginning of photography

1847 Properties of infrared showed to be like visible

1856 F. Tournachon: Aerial photographs of Bièvre from a balloon

Campbell 1.3

1909 Photography from airplanes

1873 Maxwell’s electromagnetic energy theory

Milestones

Campbell 1.3

1910-1920 WW I: aerial reconnaissance

1920-1930 Development & Application of aerial photography and photogrammetry

1930-1940 Development of radar

1940-1950 WW II: Applications of nonvisible electromagnetic spectrum training for interpretation and acquisition of airphotos

1950-1960 Military research and development

Milestones

Campbell 1.3

1971 Canada Centre for Remote Sensing

Milestones1956 Colwell’s research on crop disease detection with infrared photography

1960-1970 TIROS weather satellite; First use of term “remote sensing”

1972 Launch of LANDSAT 1 (Multi-Spectral Scanner)

1970-1980 Rapid advance in digital image processing

1980 USSR METEOR Satellite

1986 Système Pour l’Observation de la Terre (SPOT)

1995 RADARSAT

1979 Advanced Very High Resolution Radiometer (AVHRR)

1999 TERRA (launched December 18, 1999)2002 AQUA (launched May 4, 2002)

1978 SEASAT

1957 First satellite: Sputnik

1982 LANDSAT Thematic Mapper

Campbell 1.3

Principles

Spectral Differentiation

Radiometric Differentiation

Spatial Differentiation

Geometric Transformation

Multi to Hyperspectral remote sensing

The science of observing at different wavelengths to derive information

Detection of differences in brightness of objects and features

Picture elements or “pixels”Sensor limitation in respect to the size of the smallest area thatcan be separately recorded on an image

The 2-D representation of the 3-D real world requires corrections basedon the sensor optics, motion of scanning optics, terrain relief, and earthcurvature

Temporal DifferentiationImaging revisit interval (satellite)

Campbell 1.6

Interchangeability of Pictorial and Digital Formats

Remote Sensing Instrumentation Acts as a System

Role of the Target in Remote Sensing

Role of the Atmosphere

Digital array of numbers = photograph-like image

The image interpreter must have good knowledge about the system-instruments used in the acquisition of remote sensing data: optical, mechanical, electronics, and chemical processes.

Size, shape, patterns, physical properties

Sensors have to “see” through the atmosphere. The sun radiation reaching the target is also altered by the atmosphere.

Principles

Campbell 1.6