Rhodes, Greece, 3-7 November, 2008

Evaluating the use of ALOS data (microwave and optical) for mapping geomorphological

features of selected areas in Livingston Island, South Shetland Islands, West Antarctica

Magaly Koch1, Jerónimo López-Martínez2, Thomas Schmid3, Enrique Serrano4, José Gumuzzio2

1Center for Remote Sensing, Boston University - mkoch@bu.edu2Universidad Autónoma de Madrid, Spain

3CIEMAT, Madrid, Spain4Universidad de Valladolid, Spain

Introduction

About 97 % of Antarctica is covered by ice; however 10 % of the South Shetland Islands is ice free in summer ⇒ good conditions for the observation of permafrost related landforms

The study of periglacial landforms is important as permafrost is sensitive to climatic fluctuations, and surface exposure is expected to increase with global warming

The effects of repeated freezing and thawing of water give rise to a range of periglacial processes, including permafrost (permanently frozen ground), active layer, patterned ground

Byers Peninsula in Livingston Island is the largest ice-free area of the South Shetland Islands in maritime Antarctica

Extensive ground truth information exists for Byers Peninsula from various field expeditions carried out by our group

Objectives

Study/map periglacial & glacial features by remote sensing

Perform supervised classifications using ALOS PALSAR and Landsat ETM+

Compare PALSAR and ETM+ results with field based maps

Evaluate application potential of PALSAR in ice-free polar regions

Location of Study Areas

0 25 50 75 100 km

South Shetland Islands: Livingston Island

Field Work & Mapping

Livingston Island: Byers & Hurd Peninsula

Differential GPS

Lineation

Byers PeninsulaGeomorphologic & Geological Map

Byers Peninsula

Hydrography

Topography

Byers Peninsula: PALSAR Dual-Pol Image

HH

HV

15 October 2006

PALSAR-HH Synthetic Color Image

Selection of Training Sites

Geomorphologic Map PALSAR Image

Lee-filtered color composite (R= HH, G= HH-VH, B= VH)Scale = 1:25,000

PALSAR Supervised Wishart Classification

Confusion Matrix of PALSAR Classification

ClassesGeo-morphic units

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 Total %

Open sea water 45.52 0 0 0 0 0 14.75 6.74 0 0 32.99 0 100

Sea water w/ brass 0 88.01 2.46 0 0.11 7.32 0 0 0 1.25 0 0.85 100

Raised beaches 0 0.09 72.08 14.96 7.77 4.72 0.13 0 0 0.25 0 0 100

Stone field (platform) 0 0.33 18.05 37.17 18.34 11.63 12.17 2.32 0 0 0 0 100

Patterned ground 0 0 14.43 12.27 56.87 9.88 2.47 0 0 4.09 0 0 100

Volcanic plugs 0 1.22 2.08 7.7 4.4 51.83 0.49 0.12 11.25 0.12 0 20.78 100

Lakes / Pools 11.11 0 0 3.17 0 0 65.61 17.99 0 0 2.12 0 100

Moraine ridge 0 0 0 0 0 0 3.82 96.18 0 0 0 0 100

Glacier (center) 0 0 0 0 0 6.51 0 0 93.49 0 0 0 100

Glacier w/ crevasses 0 0 1.71 0 9.39 0 0 1.56 0 85.92 0 1.42 100

Scarp shadows 12.99 0 0 0 0 0 12.55 0 0 0 74.46 0 100

Slope debris (sunlit) 0 5.52 0 0 0 14.11 0 0 0 0 0 80.37 100

Trai

ning

Are

as

Classified Training Areas

Landsat ETM+ Image Processing

1 March 2004 (Bands 4, 3, 2)

• Unsupervised Classification (IsoData)

• Principal Component Analysis

• Normalized Difference Vegetation Index

• Tasseled Cap

• Geomorphologic Map

Data Exploration & Extraction of Reference Spectra

Landsat ETM+ SAM Classification

Classification Comparison

PALSAR Dual Pol Landsat ETM+

Geomorphologic Map Geologic Map

Future Work: Hurd Peninsula

liv ingston_prsm.jpg

PRISM: 9 October 2006 Mapped Areas

Hurd Peninsula: PALSAR Dual-Pol

HH

HV

15 October 2006

PALSAR Dual Pol & PRISM & Maps

HH HVPRISM

Conclusion

The Spectral Angle Mapper classification of the Landsat ETM+data discriminates well the different surface materials according to their spectral properties (snow/glacier ice, beach sand, stone covered surfaces, vegetation, water); some surface materials arerelated to the underlying lithology (stone covered platforms andpatterned grounds) ⇒ good discrimination of lithologic units.

The Wishart Classification of the partially polarized PALSAR data highlights landforms and distinguishes well high frequency (moraine ridge, scarps, volcanic plugs) from low frequency features (raised beaches, stone covered platforms, lakes, glacial ice surface).

Geomorphic features with low frequency characteristics achieved lower classification accuracies than those associated with high frequency features.

Furthermore, very smooth (beach, lakes, shadows) and very roughsurfaces (escarpments, ridges) were more accurately classified due to their slope-dominated scattering properties, than those with diffused scattering properties (stone fields and patterned grounds on raised platforms).

Acknowledgements

Funding was obtained from the Spanish Polar Program with the aim of contributing to the Antarctic Permafrost and Soils (ANTPAS) project within the framework of IPY 2007-2008

PALSAR data were obtained from the Japan Aerospace Exploration Agency (JAXA) as part of the ALOS user agreement (ALOS-RA-81)