Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
IGARSS__RTC.pdf
1. USE OF RADIOMETRIC TERRAIN
CORRECTION TO IMPROVE
POLSAR LAND COVER CLASSIFICATION
Don Atwood1 and David Small2
1) University of Alaska Fairbanks
2) University of Zurich, Switzerland
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2. Presentation Overview
• Introduce Boreal Land Cover Classification project
• Focus on species differentiation in boreal environment
• Introduce reference data for land cover classification
• Introduce method of Radiometric Terrain Correction (RTC)
• Terrain-flattened Gamma Naught Backscatter
• Perform RTC on polarimetric parameters to address topography
• Demonstrate synergy of PolSARpro and MapReady Tools
• Compare results for RTC-corrected and non-corrected classification
• Characterize optimal classification approach for Interior Alaska
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3. Study Region
Boreal environment of Interior Alaska
Characterized by:
• rivers
• wetlands
• herbaceous tundra
• black spruce forests (north facing)
• birch forests (south facing)
• low intensity urban areas
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5. Study Data
Quad-Pol data selected:
• ALOS L-band PALSAR
• 21.5 degree look angle
• Of April, May, July, and Nov dates,
July 12 2009 selected
• Post-thaw
• Leaf-on
• Coverage includes Fairbanks and
regional roads
Pauli Image
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6. Problem of Topography
Span (Trace of T3 Matrix) Wishart Segmentation
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7. Backscatter Reference Areas
Sensor
Aβ & β0
Aγ & γ0 Nadir
Near
Aσ & σ0
Standard areas for Ellipsoid Normalization Far
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9. Terrain-flattening
The concept of a single Local Incident Angle determining the terrain’s
local normalization area is flawed:
• adapted from ellipsoidal incident angle for ocean, sea-ice, &
flatlands
• fails to account for foreshortening and the radiometric impact of
topography.
To improve sensor model:
➡use local contributing area, not angle!
Ref.: Small, D., Flattening Gamma: Radiometric Terrain Correction for SAR Imagery,
IEEE Transactions on Geoscience and Remote Sensing, 13p (in press).
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10. Terrain-flattening
Solution: Use simulated image to Normalize β0
X
Example over Switzerland
ASAR WS data courtesy ESA
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11. Terrain-flattening
Convention 1 2 3 4 5
Earth Model None Ellipsoid Terrain
Reference Area
Area Derivation
Normalisation
Product GTC NORLIM RTC
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12. Terrain Correction
in Coastal BC
Vancouver
GTC (Sept 2008) Integrated contributing area
ENVISAT ASAR WSM data courtesy ESA (based on SRTM3)
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13. Terrain Correction
in Coastal BC
GTC (Sept 2008) Integrated contributing area
ENVISAT ASAR WSM data courtesy ESA (based on SRTM3)
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17. Coherency Matrix
Scattering Matrix
S XX S XY
S =
S
YX SYX
S XX + SYY
2
(S XX + SYY )(S XX − SYY )* * 2 (S XX + SYY )S * XY
T3 =
1 (S − S )(S + S )* S XX − SYY
2
2 (S XX − SYY )S * XY
2 XX YY XX YY
2 S (S + S )* 2 S XY (S XX − SYY )
*
4 S XY
2
XY XX YY
T11: “Single Bounce” T22 : “Double Bounce” T33 : “Volume Scattering”
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18. Radiometric Terrain Correction
of Coherency Matrix
• Radiometric Terrain Correction:
Coherency Matrix
terrain corrected
T11 T12 T13 Coherency Matrix
T3 = T21 T22 T23
T11 T12 T13
T3 = T21 T22 T23
Area Normalization
T31 T32 T33
T31 T32 T33
• Scale all matrix elements by Area Normalization
• Acknowledge that angular dependence of scattering
mechanisms is not addressed
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19. Radiometric Terrain Correction
of Coherency Matrix
GTC: No Normalization RTC: Terrain-model Normalization
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20. Radiometric Terrain Correction
of Coherency Matrix
GTC: No Normalization RTC: Terrain-model Normalization
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21. Integration of PolSARpro
and MapReady
Ingest PALSAR data Terrain-correct Perform Wishart Export to GIS
Generate T3 decomposition Cluster-busting
RTC using area image provided by UZH
Lee Sigma Speckle Filter
POC
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22. Radiometric Terrain Correction
of Coherency Matrix
Wishart - No Normalization Radiometric Terrain Correction
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23. Radiometric Terrain Correction
of Coherency Matrix
USGS Reference Radiometric Terrain Correction
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27. Accuracy Assessment
No Normalization
Open Developed Barren Deciduous Evergreen Mixed Shrub/ Woody Herbaceous User
No Normalization Water Land Land Forest Forest Forest Scrub Wetlands Wetlands Accuracy
Open Water 42402 22539 15229 2168 1512 99 1024 6299 498 46%
Developed Land 836 27431 1304 3130 903 458 123 2663 64 74%
Barren Land 0 0 0 0 0 0 0 0 0 NA
Deciduous Forest 11217 50614 1795 390417 228454 112888 12687 52712 528 45%
Evergreen Forest 13734 69849 6849 162366 323079 49803 12643 94157 617 44%
Mixed Forest 0 0 0 0 0 0 0 0 0 NA
Shrub/ Scrub 0 0 0 0 0 0 0 0 0 NA
Woody Wetlands 7062 15611 4924 56052 135667 12103 30585 480635 11594 65%
Herbaceous Wetlands 0 0 0 0 0 0 0 0 0 NA
Producer Accuracy 56% 15% 0% 64% 47% 0% 0% 76% 0% 51%
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28. Accuracy Assessment
With RTC
Open Developed Barren Deciduous Evergreen Mixed Shrub/ Woody Herbaceous User
Normalized T3 Water Land Land Forest Forest Forest Scrub Wetlands Wetlands Accuracy
Open Water 45570 33695 17297 3595 2188 165 1616 9905 739 40%
Developed Land 942 27464 1320 4717 1547 608 148 1878 27 71%
Barren Land 0 0 0 0 0 0 0 0 0 NA
Deciduous Forest 10161 59438 1461 482548 234568 128097 10344 30375 147 50%
Evergreen Forest 10614 50149 4409 53025 335583 30621 13520 138224 527 53%
Mixed Forest 0 0 0 0 0 0 0 0 0 NA
Shrub/ Scrub 0 0 0 0 0 0 0 0 0 NA
Woody Wetlands 7964 15298 5614 70248 115729 15860 31434 456084 11861 64%
Herbaceous Wetlands 0 0 0 0 0 0 0 0 0 NA
Producer Accuracy 61% 15% 0% 79% 49% 0% 0% 72% 0% 54%
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29. Accuracy Assessment
Comparison
Producer Class RTC No RTC Improvement
Open Water 61% 56% 5%
Developed Land 15% 15% 0%
Deciduous Forest 79% 64% 15%
Evergreen Forest 49% 47% 2%
Woody Wetlands 72% 76% -4%
• RTC yields improved accuracy (particularly for Deciduous Forest)
• But statistics may not tell the whole story: the USGS reference has
a stated accuracy of approximately 75%!
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30. Impact of RTC
on forest classification
No Normalization USGS Reference RTC
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31. Conclusions
• In general, PolSAR classification is difficult!
• Data fusion provides greatest hope for accurate classification results
• Radiometric variability caused by topography dominates PolSAR classification
• Area-based RTC offers effective way to “flatten” SAR radiometry
• RTC of Coherency Matrix shown to improve classification accuracy:
• Impact most pronounced for Deciduous Forests
• Although not complete, RTC approach is simple and effective
• Different scattering mechanisms (SB, DB, Volume) have different
sensitivities to topography. RTC does not address this
• However, RTC is very effective first order correction for segmenting
polarimetric data by phenology rather than topography
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32. Discussion
Don Atwood
dkatwood@alaska.edu
(907) 474-7380 32
IGARSS July 2011 Don Atwood & David Small
Photo Credit: Don Atwood
