Wednesday, 5 January 2011
ESS 421 – Introduction to Geological Remote Sensing
Prof: Alan Gillespie (JHN 343) arg3@uw.edu
Office hours: Wed - Fri 1 - 3 or by arrangement
TA: Iryna Danilina (JHN 330) danilina@uw.edu
Office hours: Wed/Fri 12:30 - 2 or by arrangement
Lectures: Wednesday/Friday 9:30-10:20 JHN-021
Labs: Wednesday/Friday 10:30-12:20 JHN-366
NO LAB TODAY – LAB 1 on FRIDAY
Midterm: Wednesday, 9 February 9:30-10:20 JHN-021
Final: Wednesday, 16 March 10:30-12:20 JHN-021
Class website:
http://gis.ess.washington.edu/keck/ess421_documents.html
What topics are covered in ESS 421?
- physical basis of remote sensing
- spectra
- radiative transfer
- image processing
- radar/lidar
- thermal infrared
- applications
Schedule
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LECTURES
Jan 05 1. Intro
Jan 07 2. Images
Jan 12 3. Photointerpretation
Jan 14 4. Color theory
Jan 19 5. Radiative transfer
Jan 21 6. Atmospheric scattering
Jan 26 7. Lambert’s Law
Jan 28 8. Volume interactions
Feb 02 9. Spectroscopy
Feb 04 10. Satellites & Review
Feb 09 11. Midterm
Feb 11 12. Image processing
Feb 16 13. Spectral mixture analysis
Feb 18 14. Classification
Feb 23 15. Radar & Lidar
Feb 25 16. Thermal infrared
Mar 02 17. Mars spectroscopy (Matt Smith)
Mar 04 18. Forest remote sensing (Van Kane)
Mar 09 19. Thermal modeling (Iryna Danilina)
Mar 11 20. Review
Mar 16
Final Exam
LABS
Class structure
1
2
3
Lectures
4
5
Reading
Labs
6
7
8
9
Ethics policy statement
UW now requires an ethics policy statement.
In ESS 421, we expect you to adhere to the following:
•Labs: collaborative work in lab exercises is encouraged,
but please write up the results yourself
•Homework: Any homework assigned should be your own
•Quizzes, Midterm, Final: All work should be your own
•All assignments must be turned in. If some problem arises,
please discuss with the TA or instructor
•Grades: grading is on a curve.
Lab Exercises
° 9 lab exercises
° one lab per week, handed out Wednesdays (except today)
° due the following Wednesday, beginning of Lab period
° lab files (e.g., “Lab_1.doc”) are available from the website
° print only the “Answers” file of the lab (e.g., “Lab_1-answers.doc”) &
turn in only this sheet to TA with your answers
Unexcused late work will be docked 10% per day
° at the beginning of the lab on Wednesdays there will be a short one-page
graded quiz on the lab just turned in, plus reading for the past week.
Bring a sheet of paper for the answers and turn in to the TA.
° the labs just handed in will be reviewed after the quiz
Reading Assignments
°Text
is Lillesand, Kiefer, and Chipman “Remote Sensing and
Image Interpretation” 6th ed. 2007, John Wiley
° Reading assignments in the text may be augmented with other
material available on class website
Examinations & Grading
°Midterm and Final will both contain questions from the
lectures, reading, and labs
° Midterm covers 1st half of class
°Final covers whole class with emphasis on 2nd half
Labs - 30%
Lab quizzes - 20%
Midterm - 20%
Final - 30%
Failure to turn in all work in each of the 4 categories above will result in an incomplete
Lecture 1: Introduction
Reading assignment: Lillesand, Kiefer & Chipman:
Ch 1.1, 1.2
Ch 1.6
Ch 1.7
Ch 1.10
Ch 2.9
radiation
reference data
GPS
GIS
Multiband imaging
For your reference
App. A
Concepts & terminology
App. B
Data and resources
1
What is remote sensing?
Measurement from a distance -
Hazardous locales -
“Denied terrain”
Nodong, N. Korea
2
X (longitude)
Y (latitude)
What is an image?
3
Images in combination with maps
add to interpretive power
Geographic Information System (GIS)
4
Images can be made at different wavelengths of light
l=11.405 mm
l=10.755 mm
l=10.275 mm
l=9.205 mm
l=8.735 mm
l
l=0.870 mm
l=0.804 mm
l=0.658 mm
l=0.542 mm
l=0.462 mm
Y
Image visualizations display
only a subset of the data
X
NASA MASTER airborne 50-band multispectral image
5
and displayed as color pictures
l=11.405 mm
l=10.755 mm
l=10.275 mm
l=9.205 mm
l=8.735 mm
l
l=0.870 mm
l=0.804 mm
l=0.658 mm
l=0.542 mm
l=0.462 mm
Y
R=0.658mm
G=0.542mm
B=0.462mm
X
NASA MASTER airborne 50-band multispectral image
6
Only 3 bands at a time can be visualized this way…
Spectrum
but there is more information,
and can be shown in a spectrum
l=11.405 mm
l=10.755 mm
l=10.275 mm
l=9.205 mm
l=8.735 mm
l
l=0.870 mm
l=0.804 mm
l=0.658 mm
l=0.542 mm
l=0.462 mm
Y
R=0.658mm
G=0.542mm
B=0.462mm
X
7
Spectra are different and convey
information about composition
R=0.658mm
G=0.542mm
B=0.462mm
8
Images can be made at
different wavelengths of light
l=11.405 mm
l=10.755 mm
l=10.275 mm
l=9.205 mm
l=8.735 mm
l
l=0.870 mm
l=0.804 mm
l=0.658
l=0.462
mm mm
l=0.542 mm
Y
X
9
They reveal different information
about scene composition
THERMAL INFRARED
VISIBLE
10
Images are not limited to light reflected or emitted from a surface.
They can be made over time, or of derived or calculated parameters.
Increasing concentration of CO
Carbon monoxide at 500 mB pressure (elevation), from NASA’s Terra/Moppitt
http://gis.ess.washington.edu/keck/lectures_ESS_421/mopit.MPE
12
How do remote sensing and GIS fit together in geospatial analysis?
Remote sensing
Engineering
Operations
& acquisition
Calibration
GIS
Image
processing
physics of
remote sensing
Analysis &
Interpretation
project goals
Scanners
& data
Validation
scene
Knowledge
13
LKC App A: radiometric terminology (p. 742)
Radiant energy (J) [Q]
Radiant flux (J s-1 = W) [Ф]
Radiant intensity (W sr-1) [I]
Irradiance (W m-2) [E]
Spectral irradiance (W m-2 µm-1) [El]
Radiance (W m-2 sr-1) [L]
Spectral radiance (W m-2 sr-1 µm-1) [Ll]
The electromagnetic spectrum
Short l
High energy
High frequency
Long l
Low energy
Low frequency
Thermal
radiation
Reflected sunlight
In the spectrum, energy is dispersed by a grating or prism according to
frequency or wavelength
Gamma rays
X rays
Ultraviolet
<10-4 µm
10-4 - 10-2 µm
0.01-0.45 µm
Visible blue B
Visible green G
Visible red R
0.47-0.48 µm
0.51-0.56 µm
0.63-0.68 µm
Near infrared
NIR
Shortwave infrared SWIR
0.67-1.4 µm
1.4-2.5 µm
Mid-wave infrared MIR
Longwave thermal infrared LWIR
3.5-5.5 µm
8-14 µm
Microwave (Radar)
Radio
0.1mm-1 m
1 m - 10 km
What was covered in today’s lecture?
•Remote sensing
•Images, maps, & pictures
•Images and spectra
•Time series images
•Geospatial analysis framework
•Useful parameters and units
•The spectrum
14
What will be covered in Friday’s lecture
imaging systems and some of their characteristics
14