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ESS 421 – Introduction to Geological Remote Sensing Prof: Alan Gillespie (JHN 343) [email protected]
Office hours: Wed - Fri 1 - 3 or by arrangement
TA: Iryna Danilina (JHN 330) [email protected] hours: Wed/Fri 12:30 - 2 or by arrangement
Lectures: Wednesday/Friday 9:30-10:20 JHN-021Labs: Wednesday/Friday 10:30-12:20 JHN-366
NO LAB TODAY – LAB 1 on FRIDAY
Midterm: Wednesday, 9 February 9:30-10:20 JHN-021Final: Wednesday, 16 March 10:30-12:20 JHN-021
Class website: http://gis.ess.washington.edu/keck/ess421_documents.html
Wednesday, 5 January 2011
What topics are covered in ESS 421?
- physical basis of remote sensing- spectra- radiative transfer- image processing- radar/lidar- thermal infrared- applications
Schedule• LECTURES LABS• Jan 05 1. Intro• Jan 07 2. Images 1• Jan 12 3. Photointerpretation 2• Jan 14 4. Color theory• Jan 19 5. Radiative transfer 3• Jan 21 6. Atmospheric scattering• Jan 26 7. Lambert’s Law 4• Jan 28 8. Volume interactions• Feb 02 9. Spectroscopy 5• Feb 04 10. Satellites & Review• Feb 09 11. Midterm 6• Feb 11 12. Image processing• Feb 16 13. Spectral mixture analysis 7• Feb 18 14. Classification• Feb 23 15. Radar & Lidar 8• Feb 25 16. Thermal infrared• Mar 02 17. Mars spectroscopy (Matt Smith) 9• Mar 04 18. Forest remote sensing (Van Kane)• Mar 09 19. Thermal modeling (Iryna Danilina)• Mar 11 20. Review• Mar 16 Final Exam
Lectures
Reading Labs
Class structure
Ethics policy statementUW 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 radiationCh 1.6 reference dataCh 1.7 GPSCh 1.10 GISCh 2.9 Multiband imaging
For your referenceApp. A Concepts & terminology App. B Data and resources
1
What is remote sensing?
2
“Denied terrain”
Measurement from a distance -
Hazardous locales -
Nodong, N. Korea
What is an image?
3
Y (
lati
tude
)X (longitude)
4
Images in combination with mapsadd to interpretive power
Geographic Information System (GIS)
Images can be made at different wavelengths of light
5
NASA MASTER airborne 50-band multispectral image
X
Y
λ
λ=8.735 µmλ=9.205 µm
λ=10.275 µmλ=10.755 µm
λ=11.405 µm
λ=0.462 µmλ=0.542 µm
λ=0.658 µmλ=0.804 µm
λ=0.870 µm
Image visualizations display only a subset of the data
6
NASA MASTER airborne 50-band multispectral image
R=0.658µmG=0.542µmB=0.462µm
and displayed as color pictures
NASA MASTER airborne 50-band multispectral image
X
Y
λ
λ=8.735 µmλ=9.205 µm
λ=10.275 µmλ=10.755 µm
λ=11.405 µm
λ=0.462 µmλ=0.542 µm
λ=0.658 µmλ=0.804 µm
λ=0.870 µm
7
X
Y
λ
λ=8.735 µm
λ=9.205 µmλ=10.275 µm
λ=10.755 µmλ=11.405 µm
λ=0.462 µmλ=0.542 µm
λ=0.658 µmλ=0.804 µm
λ=0.870 µm
R=0.658µmG=0.542µmB=0.462µm
Only 3 bands at a time can be visualized this way…
but there is more information,
and can be shown in a spectrum
Spectrum
8
R=0.658µmG=0.542µmB=0.462µm
Spectra are different and convey
information about composition
Note the scale change!
9
Images can be made at different wavelengths of light
X
Y
λ
λ=8.735 µm
λ=9.205 µmλ=10.275 µm
λ=10.755 µmλ=11.405 µm
λ=0.462 µmλ=0.542 µm
λ=0.658 µmλ=0.804 µm
λ=0.870 µm
10
They reveal different information about scene composition
VISIBLE
THERMAL INFRARED
Images are not limited to light reflected or emitted from a surface. They can be made over time, or of derived or calculated parameters.
12
Carbon monoxide at 500 mB pressure (elevation), from NASA’s Terra/Moppitt
Increasing concentration of CO
http://gis.ess.washington.edu/keck/lectures_ESS_421/mopit.MPE
How do remote sensing and GIS fit together in geospatial analysis?
13
Remote sensing GIS
EngineeringAnalysis &
InterpretationOperations
& acquisition
Image processing
Calibration Validation
sceneproject goalsphysics of
remote sensing
Knowledge
Scanners & data
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] Radiance (W m-2 sr-1) [L]
Spectral irradiance (W m-2 µm-1) [Eλ] Spectral radiance (W m-2 sr-1 µm-1) [Lλ]
In the spectrum, energy is dispersed by a grating or prism according to frequency or wavelength
Gamma rays <10-4 µmX rays 10-4 - 10-2 µm
Ultraviolet 0.01-0.45 µm
Visible blue B 0.47-0.48 µmVisible green G 0.51-0.56 µmVisible red R 0.63-0.68 µm
Near infrared NIR 0.67-1.4 µmShortwave infrared SWIR 1.4-2.5 µm
Mid-wave infrared MIR 3.5-5.5 µmLongwave thermal infrared LWIR 8-14 µm
Microwave (Radar) 0.1mm-1 mRadio 1 m - 10 km
Ref
lect
ed s
unlig
ht
The
rmal
radi
atio
n
The electromagnetic spectrum
Short λHigh energyHigh frequency
Long λLow energyLow frequency
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
14
imaging systems and some of their characteristics