igarss__rtc.pdf

Don Atwood & David Small IGARSS July 2011 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


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


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


Land Cover Reference


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


Problem of Topography

Span (Trace of T3 Matrix) Wishart Segmentation


Backscatter Reference Areas

Nadir

Sensor

Far

Near

Aσ & σ0

Aγ & γ0

Aβ & β0

Standard areas for Ellipsoid Normalization


Relationships between cross sections

for ellipsoidal surfaces

Backscatter Reference Areas


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).


Terrain-flattening

X

Solution: Use simulated image to Normalize β0

Example over Switzerland ASAR WS data courtesy ESA


Terrain-flattening

Convention 1 2 3 4 5

Earth Model None Ellipsoid Terrain

Reference Area

Area Derivation

Normalisation

Product GTC NORLIM RTC


Vancouver

GTC (Sept 2008) Integrated contributing area ENVISAT ASAR WSM data courtesy ESA (based on SRTM3)

Terrain Correction in Coastal BC


Terrain Correction in Coastal BC

GTC (Sept 2008) Integrated contributing area ENVISAT ASAR WSM data courtesy ESA (based on SRTM3)


ASAR WSM GTC

Coastal BC: GTC


ASAR WSM RTC

Coastal BC: RTC


ASAR WSM NORLIM

Coastal BC: NORLIM


Coherency Matrix

=

YXYX

XYXX

SSSS

S

Scattering Matrix

( )( ) ( )( )( ) ( )

( ) ( )

−+

−−+−

+−++

=2**

*2*

**2

3

422

2

2*

21

XYYYXXXYYYXXXY

XYYYXXYYXXYYXXYYXX

XYYYXXYYXXYYXXYYXX

SSSSSSS

SSSSSSSSS

SSSSSSSSS

T

22T11T 33T: “Single Bounce” : “Double Bounce” : “Volume Scattering”


Radiometric Terrain Correction of Coherency Matrix

• Radiometric Terrain Correction:

Area Normalization

terrain corrected Coherency Matrix

=

333231

232221

131211

3

TTTTTTTTT

T

Coherency Matrix

=

333231

232221

131211

3

TTTTTTTTT

T

• Scale all matrix elements by Area Normalization • Acknowledge that angular dependence of scattering

mechanisms is not addressed



GTC: No Normalization RTC: Terrain-model Normalization


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

Integration of PolSARpro and MapReady



Wishart - No Normalization Radiometric Terrain Correction



USGS Reference Radiometric Terrain Correction


Classification Results

Urban areas missed / Identified as Open Water



Inability to distinguish Mixed Forests and Shrub / Scrub



No Normalization USGS Reference RTC


Accuracy Assessment No Normalization

No Normalization Open Water

Developed Land

Barren Land

Deciduous Forest

Evergreen Forest

Mixed Forest

Shrub/ Scrub

Woody Wetlands

Herbaceous Wetlands

User 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%


Accuracy Assessment With RTC

Normalized T3 Open Water

Developed Land

Barren Land

Deciduous Forest

Evergreen Forest

Mixed Forest

Shrub/ Scrub

Woody Wetlands

Herbaceous Wetlands

User 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%


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%!


Impact of RTC on forest classification

No Normalization USGS Reference RTC


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


Discussion

Don Atwood [email protected] (907) 474-7380

Photo Credit: Don Atwood

mailto:[email protected]

igarss__rtc.pdf

Education

david small2

srtm3 terrain correction

reference data

asar wsm rtc coastal

asar wsm gtc coastal

coastal bc gtc

asar wsm norlim coastal

local contributing area