Landsat Calibration: Interpolation, Extrapolation, and Reflection - - PowerPoint PPT Presentation

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Landsat Calibration: Interpolation, Extrapolation, and Reflection - - PowerPoint PPT Presentation

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Landsat Calibration: Interpolation, Extrapolation, and Reflection L DCM Sc ie nc e T e a m Me e ting USGS E ROS Aug ust 16-18, 2011 De nnis He lde r, Da ve Aa ro n And the I P L a b c re w Outline I nte rpo la tio n: Wha t ha

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SLIDE 1

Landsat Calibration: Interpolation, Extrapolation, and Reflection

L DCM Sc ie nc e T e a m Me e ting USGS E ROS Aug ust 16-18, 2011 De nnis He lde r, Da ve Aa ro n And the I P L a b c re w

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SLIDE 2

Outline

  • I

nte rpo la tio n: Wha t ha s b e e n do ne to c a lib ra te the L a ndsa t a rc hive ?

  • E

xtra po la tio n: Ho w is c a lib ra tio n g o ing to e xte nd to the L DCM e ra ?

  • Re fle c tio n: Ca lib ra tio n, the Sc ie nc e

T e a m a nd…

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SLIDE 3

Interpolation

  • Whe re we re we whe n we sta rte d this da nc e in Ja nua ry

2007?

– L

a ndsa t 7 E T M+ wa s sta b le with c a lib ra tio n to 5% unc e rta inty

– L

a ndsa t 5 T M wa s unsta b le b ut c ha ra c te rize d, c ro ss-c a l’ d to E T M+ with 3-5% pre c isio n. No w 27 ye a rs o ld!

  • Wha t didn’ t we kno w in Ja nua ry 2007?

– L

a ndsa t 4 T M c a lib ra tio n (a ltho ug h ne a rly do ne )

– L

a ndsa t MSS c a lib ra tio n

  • 5 se nso rs x 4 b a nds x 6 de te c to rs = 120 c ha nne ls
  • Co nsiste nt with e a c h o the r? Ab so lute ? ?

– Use o f Pse udo I

nva ria nt Ca l Site s (PI CS)

  • E

xte nd b a c k to 1972?

  • Da ta a va ila b le ?
  • E

no ug h pre c isio n?

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SLIDE 4

Interpolation (2)

  • Whe re a re we to da y in Aug ust 2011?

– L

a ndsa t 4 T M c a lib ra tio n do ne

– L

a ndsa t 1-5 MSS se nso rs do ne

  • Co nsiste nt with e a c h o the r
  • Pla c e d o n a n a b so lute sc a le

– Co nfide nt tha t the PI

CS a ppro a c h c a n pro vide 3% pre c isio n

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SLIDE 5

Interpolation (3)

  • F

ro m F

  • rty-Ye a r Ca lib ra te d Re c o rd o f E

a rth Re fle c te d Ra dia nc e fro m L a ndsa t: A Re vie w

– By Bria n Ma rkha m a nd De nnis He lde r, Re mo te

Se nsing o f the E nviro nme nt, Vo l. So me time so o n…

Table 11. Landsat Sensor Absolute Radiometric Calibration Uncertainties (%)

Landsat-7 ETM+ Landsat-5 TM Landsat-4 TM Landsat-5 MSS Landsat-4 MSS Landsat-3 MSS Landsat-2 MSS Landsat-1 MSS Band 1 5 7 9 8 9 9 10 11 Band 2 5 7 9 8 9 9 10 11 Band 3 5 7 9 9 10 10 11 12 Band 4 5 7 9 14 18 18 22 25 Band 5 5 7 9 Band 7 5 7 9 Band 8 5

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SLIDE 6

Interpolation (4)

  • Do e s a ll this c a lib ra tio n e ffo rt, mo stly in

the de se rt, a c tua lly impro ve thing s?

– A q uic k study in the fo re sts o f Wa shing to n

sta te …

– L

a ndsa t 5: 20 MSS a nd 16 T M sc e ne s fro m 1984 – 1992. 7 sa me da y sc e ne s.

– Nine Hype rio n sc e ne s fo r ta rg e t spe c tra

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SLIDE 7

Site Selection

  • Se le c tio n o f ve g e ta te d site

fo r c ro ss c a l is de pe nde nt

  • n

– Na ture o f ve g e ta tio n: no t

c ha ng ing fre q ue ntly

– Ho mo g e ne ity o f

Ve g e ta tio n

– Ava ila b ility o f

hype rspe c tra l sig na ture o f ta rg e t a re a

– Ava ila b le c lo ud-fre e T

M a nd MSS sc e ne s

  • Co nife ro us fo re st site

– lo c a te d a t WRS Pa th/ Ro w-

46/ 28

– I

n Wa shing to n Sta te

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SLIDE 8

ROI Selection

ROI 2: 0.414 km2 22 X 21 Pixe ls ROI 1: 0.550 km2 34 X 18 Pixe ls ROI 3: 2.527 km2 52 X 54 Pixe ls ROI 4: 0.678 km2 26X 29 Pixe ls

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SLIDE 9

Spectral Signature of Target

  • verlapped with TM and MSS RSR

400 500 600 700 800 900 1000 1100 1200 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Wavelength(nm)

Normalized Response

L5 MSS and TM RSR Profile (Band 1-4) with Target Spectral Signature

TM MSS Average Minimum Maximum

Minimum - 5/ 31/ 2007 Ma ximum – 9/ 7/ 2005

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SLIDE 10

MSS to TM Consistency: Forests

No Ca lib ra tio n No SBAF Co rre c tio n With Ca lib ra tio n No SBAF With Ca lib ra tio n With SBAF

Δ=23% Δ=7% Δ=3% Δ=16% Δ=8% Δ=3%

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SLIDE 11

MSS to TM Consistency: Forests

With Ca lib ra tio n No SBAF With Ca lib ra tio n With SBAF No Ca lib ra tio n No SBAF Co rre c tio n

Δ=34% Δ=41% Δ=8% Δ=3% Δ=6% Δ=3%

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SLIDE 12

EO12005070130654_SGS_01

  • 1. Post-Image Bias removal
  • 2. SCA based RG

correction

  • 1. Relative SCA-to-SCA

Correction based on the ten detector

  • verlap

Interpolation  Extrapolation

  • Se c o nd a re a o f inte re st/ c o nc e rn wa s de te c to r

re la tive g a ins, unifo rmity, b a nding , e tc .

– No te AL

I sc e ne in the b a c kg ro und

  • T

his pro vide s the pe rfe c t se g ue into …

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SLIDE 13

Extrapolation (1)

  • Wha t a re we g e tting with the OL

I se nso r?

– Co mme nts a lso g e ne ra lly a pply to T

I RS

– Be tte r dyna mic ra ng e – Be tte r sig na l-to -no ise ra tio – Be tte r ra dio me tric re so lutio n – Be tte r a b so lute c a lib ra tio n – Be tte r sta b ility(? )

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SLIDE 14

SPIE Earth Observing Systems XVI NASA GSFC / USGS EROS

OLI Radiometric Performance

  • SNR

– SNR significantly exceeds requirements and heritage

  • Calibration

– Absolute uncertainty ~4%

  • Extensive round robin for

validation

  • Transfer-to-Orbit

uncertainties included – Stability over 60 seconds (2 standard scenes)

  • <0.02% 2σ

– Stability over 16 days (time between Solar Diffuser Cals)

  • <0.54% 2σ for all but Cirrus

Band which is <1.19%

16 Day Stability

Change in Response, Green band, w/ hot cycle in middle Median SNR

(Slide courtesy Brian Markham)

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SLIDE 15

Extrapolation

ETM+ High Gain OLI ETM+/OLI Band Min Sat Level Rad./DN Min Sat Level Rad./DN Res. Ratio Blue 190 0.742 581 0.142

5.2

Green 194 0.758 544 0.133

5.7

Red 150 0.586 462 0.113

5.2

NIR 150 0.586 281 0.069

8.5

SWIR 1 31.5 0.123 71 0.017

7.1

SWIR 2 11.1 0.043 24 0.006

7.4

PAN 156 0.609 515 0.126

4.8

  • Co mpa riso n o f

ra dio me tric re so lutio n o f E T M+ a nd OL I

– E

T M+ = 8 b its

– OL

I = 12 b its

  • Ba se d o n pub lishe d

do c ume nts

– L

a ndsa t 7 Sc ie nc e Da ta Use rs Ha ndb o o k

– L

DCM OL I Re q uire me nts Do c ume nt

  • 5—8 time s impro ve d

ra dio me tric re so lutio n with the SNR to suppo rt it!

15

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SLIDE 16

Excerpts from OLI Requirements

5.6.2.3 Pixe l- to- Pixe l Unifor

mity

  • 5.6.2.3.1 F

ull F ie ld o f Vie w

–

T he sta nda rd de via tio n o f a ll pixe l c o lumn a ve ra g e ra dia nc e s a c ro ss the F OV within a b a nd sha ll no t e xc e e d 0.5% o f the a ve ra g e ra dia nc e .

  • 5.6.2.3.2 Banding

–

T he ro o t me a n sq ua re o f the de via tio n fro m the a ve ra g e ra dia nc e a c ro ss the full F OV fo r a ny 100 c o ntig uo us pixe l c o lumn a ve ra g e s o f ra dio me tric a lly c o rre c te d OL I ima g e da ta within a b a nd sha ll no t e xc e e d 1.0% o f tha t a ve ra g e ra dia nc e .

  • 5.6.2.3.3 Str

e aking

–

T he ma ximum va lue o f the stre a king pa ra me te r within a line o f ra dio me tric a lly c o rre c te d OL I ima g e da ta sha ll no t e xc e e d 0.005 fo r b a nds 1-7 a nd 9, a nd 0.01 fo r the pa nc hro ma tic b a nd.

T he se r e quir e me nts allow the pr e se nc e of str iping and banding…

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SLIDE 17

OLI Scene Simulation

  • L

a ke T a ho e simula te d OL I ima g e b e fo re g a in/ b ia s c o rre c tio n

  • Co ur

te sy Jo hn Sc ho tt/ RIT via DIRSIG

–

F ully synthe tic sc e ne

  • OL

I Simula tio n

–

14 a rra ys

–

60 de te c to rs e a c h; a c tua l va lue s

–

12 b it q ua ntiza tio n

–

Ac tua l OL I no ise le ve ls

–

Ac tua l spe c tra l re spo nse

–

Ac tua l de te c to r g a ins/ b ia se s

–

Sa mple d o b se rve d no n-line a rity func tio n

–

No ra dio me tric c o rre c tio ns a pplie d—ra w da ta

–

Pe rfe c t g e o me try

17

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SLIDE 18

OLI Scene Simulation (2)

  • L

a ke T a ho e I ma g e a fte r g a in a nd b ia s c o rre c tio n

– No no n-line a rity

c o rre c tio n a pplie d

  • Be a utiful!

18

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SLIDE 19

OLI Scene Simulation (3)

  • Ga in/ b ia s

c o rre c te d ima g e with la nd stre tc h

– Sq ua re ro o t stre tc h

  • Be a utiful!

19

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SLIDE 20

OLI Scene Simulation (4)

  • Wa te r stre tc h o n L

a ke T a ho e Simula te d I ma g e

– L

ine a r 2%

  • Striping
  • Ba nding
  • No ise
  • OL

I (and T IRS) will be be tte r than anything you’ve se e n, b ut the y

will ha ve ‘ a dditio na l fe a ture s’

20

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SLIDE 21

Extrapolation

  • OL

I a nd T I RS will b e sub sta ntia lly b e tte r tha n a ny pre vio us L a ndsa t se nso r with re spe c t to ra dio me tric pe rfo rma nc e

  • Sub sta ntia l inc re a se in ra dio me tric re so lutio n

a nd SNR will a llo w use rs to de te c t the sig na ture o f the instrume nt in ho mo g e ne o us re g io ns with se ve re stre tc he s

  • Stro ng ly sug g e st use rs a c c e pt this a s a n

a dditio na l b e ne fit o f using hig h pe rfo rma nc e se nso rs ra the r tha n vie wing it a s a dra wb a c k

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SLIDE 22

Reflections

  • Wha t a g re a t jo b !

– Nic e to wo rk with so me re a lly sma rt pe o ple

fo r a c ha ng e !

  • Push the c a lib ra tio n in yo ur a pplic a tio ns

– Wha t a re the limits? – Whe re do e s it e xc e e d yo ur ne e ds? – Whe re do e s the c a l fa ll sho rt?

  • Wha t’ s the va lue pro po sitio n?
  • Ho w do yo u se ll a 40 ye a r pro g ra m to a 2

ye a r g o ve rnme nt?