Evaluation of ALOS PALSAR for Operational Ice Monitoring
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Evaluation of ALOS PALSAR for Operational Ice Monitoring Preliminary Observations. Roger De Abreu, Matt Arkett, Dean Flett Canadian Ice Service Pablo Clemente-Colón, Sean Helfrich, Brian Melchior U.S. National Ice Center. Outline. Overview of PALSAR L-Band Expectations

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Presentation Transcript

Roger De Abreu, Matt Arkett, Dean Flett

Canadian Ice Service

Pablo Clemente-Colón, Sean Helfrich, Brian Melchior

U.S. National Ice Center


Outline
Outline

  • Overview of PALSAR

  • L-Band Expectations

  • Motivation, Obectives

  • Data Collection

  • Preliminary Observations

  • Final Words


PALSAR Overview

ScanSAR Modes Only

  • Launched October 2006

  • L-Band SAR PALSAR

  • Primary difference is wavelength

  • Strong basis for comparison of ScanSAR modes


Expectations for L-Band

  • Dierking and Busche (TGARS, 2006) -- Sea Ice Monitoring by L-Band SAR: An Assessment Based on Literature and Comparisons of JERS-1 and ERS-1 Imagery

  • L-Band and C-Band SAR Scattering Signature of Sea Ice for Operational Applications -- Son Nghiem, JPL, 2007.

  • Very good at mapping ice deformation, e.g. ridges, rubble fields

  • Better penetration into sea ice could yield unique and complementary information to C-band information

  • L-band signatures are significantly less sensitive to wet snow than C-band

  • However, less capable of identifying thin ice and separating FYI and MYI, especially at high incidence angles.


Study objectives
Study Objectives

  • Identify what unique and complementary sea ice information PALSAR can provide compared to C-band SARs (focus on RADARSAT-1)

  • Identify the role(s) PALSAR data could play in NAIS operational programs

    • Complementary role to RADARSAT?

    • Contingency role to C-band SARs?

  • Better understand the potential for future multi-frequency SAR platforms/missions


Data collection
Data Collection

  • Collect concurrent RADARSAT-1/2 and PALSAR ScanSAR image pairs

  • Collect seasonally over major operational ice regimes

  • Collect under range of wind conditions

  • Collect over various incidence angles and polarizations

  • Where possible, collect in situ data to support analysis


Case study locations
Case Study Locations

  • 4 case studies from two PALSAR and R-1 pairs

  • All HH polarization

  • Collected June 10 (spring) and July 15/16 (smmer)

  • ASF Convert tool used to ingest and geoproject data




June 10th 2007 Spring Thick FYI Regime

(9+ Thick FYI w/

traces of old ice;

Vast floes)

ALOS-PALSAR

RADARSAT-1

  • Rough interfloe areas more apparent in wet conditions in L-band

  • Thick FYI floes more easily identifiable in L-Band


R-1 Beaufort Sea 20070610 15:00:21 SWB HH

R-1 Baffin Bay 20070715 22:14:27 SWA HH



July 15/16 2007 Summer FYI - MYI

ALOS-PALSAR 2:13:57 UTC

RADARSAT-1 22:14:27 UTC

  • Floes appear much more homogeneous in R-1

  • PALSAR appears to provide considerable more contrast within and between floes

  • Aids in identifying FYI and MYI concentrations




June 10th 2007 – Mackenzie Delta

RADARSAT-1: 15:00:21 UTC

ALOS-PALSAR: 20:41:12 UTC

  • Wet ice lost in clutter at C- band – Better at L-band

  • Need to understand the ocean clutter better


R-1 July 15, 2007 22:14:27 SWA HH

R-1 Feb. 25, 2007 21:56 SWB


PALSAR July 16, 2007 2:13:57 WB1 HH

R-1 July 15, 2007 22:14:27 SWA HH


PALSAR July 16, 2007 2:13:57 WB1 HH

R-1 July 15, 2007 22:14:27 SWA HH

  • L-band has better penetration in melt conditions

  • Improved separation of second year ice from FYI


Summary
Summary

  • Preliminary examination of summer scenes indicates that PALSAR does appear to be “seeing” more of the ice surface under wet snow

  • In melt conditions, when C-band monitoring is challenged, PALSAR appears to do a better job typing and characterizing ice.

  • Better floe definition in FYI and MYI regimes

  • Better separation of FYI and MYI floes


Next steps
Next Steps

  • Quantitatively characterize these differences

  • Involve ice analysts to further/validate visual assessment

  • Extend to PALSAR VV data

  • Incorporate R-2 data (HH/HV) and possibly TerraSAR X.

  • Collect field-validated datasets – e.g. Southern Beaufort Sea – IPY CFL.

  • Focus on winter freeze-up and PALSAR’s ability to type thin ice types

  • Collect and analyze Great Lakes dataset

  • Icebergs in ice


Acknowledgements
Acknowledgements

  • CIS JAXA AO --- Evaluation of L-Band ScanSAR Data for Regional Ice Monitoring in Support of Navigation

  • NESDIS/NIC AO

  • Alaska SAR Facility – ALOS North American Node



Analysis objectives
Analysis Objectives

Separately and combined with C-band, assess PALSAR’s ability to:

  • Separate sea ice from open water

  • Type (classify) sea ice over a broad range of thicknesses

  • Provide other information

    • floe size, floe shape

    • surface deformation

    • surface melt conditions

      Focus on situations where C-band does not work well

  • Spring and summer ice typing

  • Ice and water separation under windy conditions


Analysis methodology
Analysis Methodology

  • Pre-launch assessment of L-band SAR based on airborne data sets and backscatter modelling

    Completed -- L-Band and C-Band SAR Scattering Signature of Sea Ice for Operational Applications -- Son Nghiem, JPL, 2007.


Nghiem, JPL, 2007

L-band modelled and observed backscatter


Nghiem, JPL, 2007

C-band modelled and observed backscatter


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