Transcript Lecture 6

Friday, 21 January 2010
Lecture 6: Atmospheric Scattering
http://www.youtube.com/watch?v=dOJ8Bux-SEs
(subtractive color)
http://www.mellesgriot.com/products/optics/oc_2_1.htm
(reflection: Fresnel’s Law)
Last lecture: Radiative transfer theory
DN = g·(te·r · ti·Itoa·cos(i)/p + te· r·Is↓/p + Ls↑) + o
Augustin Fresnel
What was covered in the previous lecture
•
•
LECTURES
Jan 05 1. Intro
Jan 07 2. Images
Jan 12 3. Photointerpretation
Jan 14 4. Color theory
Jan 19 5. Radiative transfer
previous
Jan 21 6. Atmospheric scattering today
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 21. Final Exam
Wednesday’s lecture:
•The atmosphere and energy budgeting
•Modeling the atmosphere
•Radiative transfer equation
•“Radiosity”
Today
•Atmospheric scattering and other effects
- where light comes from and how it gets there
- we will trace radiation from its source to camera
- the atmosphere and its effect on light
- the basic radiative transfer equation: DN = a·Ig·r + b
2
Atmospheric Effects
Mauna Loa, Hawaii
Ltoa = r te (ti I toacos(i) + Is↓ )/p + Ls↑
Ltoa = r a + b
Simulated scene viewed…
without scattering
with scattering
Why do we care about scattering?
- fundamental process in radiative transfer and
remote sensing
- must be accounted for to recover quantitative data
about surfaces
This image is entirely of scattered light
Landscapes with and without heavy
atmospheric aerosol content
Non-selective
Rayleigh scattering
scattering
(blue
(clouds)
sky) Mie scattering (haze, dust)
Gustav Mie
Image processing [x=(y-b)/a] can
partially remove atmospheric effects
Dust regionally affects images
China, SeaWifs
Dust regionally affects images
When you may not need to worry
about atmospheric effects
Atmospheric effects may not get in the way of your
analysis and therefore need not be dealt with
° photointerpretation
° classification
Atmospheric effects are all or partly removed by scenebased calibrations (such as the “empirical line” approach).
Therefore, they need not be dealt with further provided the
atmosphere over the scene is homogeneous
When you need atmospheric
compensation most
When you wish to do quantitative spectral analysis
When you need to compare image spectral data
with lab data - for composition type identification,
for example
If you need atmospheric compensation,
when do you need it the most?
•Low elevation
–Variable elevation
•Off-nadir viewing
•Image channels near
water bands (e.g.,
MASTER-40 = 7.9µm)
•Haze, dust
Again: atmospheric
compensation is not always
feasible
Transmissivity decreases with view angle
RAINIER TRANSMISSIVITY Effect of a 40 degree viewing geometry
1
nadir
0.9
0.8
Transmissivity
0.7
0.6
agu_louiselake.txt
oblique
0.5
0.4
agu_louiselake_40.txt
0.3
0.2
0.1
0
0
5
10
15
20
25
30
35
40
45
50
MASTER BAND
0.4-0.7
µm - Vis
0.7 – 2.5 µm
NIR-SWIR
3-5 µm
MIR
8-12 µm
LWIR
Transmissivity increases with ground elevation
top of mountain
base of
mountain
VNIR
0.4 µm
SWIR
MIR
TIR
12 µm
Path spectral radiance Ls↑(l) increases with view angle
Spectral radiance, W/m2/sr/µm
Mt. Rainier - TIR MASTER data
3
2
oblique
1
0
nadir
8 µm
12 µm
Wavelength
Path spectral radiance Ls↑(l) decreases with elevation
3
2.5
Base of mountain
2
W/m /sr/µm
radiance,(W/m2/sr/um)
Spectral
Path
Radiance
Mt. Rainier Path Radiance
4.3 km
2
3.8 km
3.5 km
1.5
1.4 km
1
agu_louiselake.txt
0.5
0
40
41
42
Top of mountain
8 µm
43
44
45
46
MASTER BAND
47
48
49
50
12 µm
scattering is controlled by
the wavelength and the size
of the scattering particles
scattering
l1
absorption
l2
Rayleigh Scattering
d
l>>d
l<1µm
Molecules
Amplitude proportional to l-4
Scattering in the atmosphere is dominantly
Rayleigh and Mie scattering
Rayleigh Scattering
Lord Rayleigh
(John William Stutt)
Dust
40
Mie Scattering
30
l~d
20
10
l=0.1- 10 µm
schematic
0
0.4
0.5
0.6
0.7
0.8
0.9
Wavelength, µm
Aerosols
40
30
l<<d
20
Non-selective
scattering
10
0
0.4
0.5
0.6
0.7
Wavelength, µm
Clouds
0.8
0.9
Mie Scattering
http://en.wikipedia.org/wiki/Mie_theory
Types of scattering
envelopes
Uniform scattering
Forward scattering
Back scattering
B/R
G/R
B/G
Color Ratio Images
TITAN
After learning about atmospheric
scattering, how would you interpret the
colors and intensities of this picture?
CRC:
R = B/R
G = G/R
B = B/G
To what can you attribute the
ratio differences you see?
H1) Color on Titan?
H2) Bad calibration?
B/R
RATIO = (a*BLUE+b)/(c*RED+d)
TITAN
Suppose a=c=1, d=0, b=3:
If scene is dark, RATIO = increases a lot
IF scene is light, RATIO = increases less
What do you attribute the
ratio differences to?
H1) Color on Titan?
H2) Bad calibration?
RATIO = (a*BLUE+b)/(c*RED+d)
B/R
2
1.8
1.6
HOW CAN YOU
TEST H1 & H2?
IS THERE AN H3?
Corrrectly
calibrated
1.2
Blue = poorly
calibrated
RATIO
TITAN
1.4
1
0.8
0.6
0
20
40
60
80
True surface brightness
100
What was covered in today’s lecture?
•Atmospheric scattering and other effects
- where light comes from and how it gets there
- radiation from its source to camera
- the atmosphere and its effect on light
- the basic radiative transfer equation: DN = a·Ig·r + b
20
What will be covered in next Wednesday’s lecture?
1) reflection/refraction of light from surfaces
(surface interactions)
2) volume interactions
- resonance
- electronic interactions
- vibrational interactions
3) spectroscopy
- continuum vs. resonance bands
- spectral “mining”
- continuum analysis
4) spectra of common Earth-surface materials
21
Midterm is coming up in a couple weeks….
50 minutes, questions drawn from lab, reading, & lectures
Short answers
You will not be asked to do complicated mathematics,
- but expect some simple calculations
One question will involve explaining your logic or reasoning
- this is as important as your answer