CHAPTERS
Fusion of Satellite SAR with Passive Microwave Data for Sea Ice
Remote Sensing
S.G. BEAVEN AND S.P. GOGINENI
Contents
5.1 Introduction
91
5.2 Data Fusion Background ...................................
92
5.2.1 Data Fusion for Sea Ice Remote Sensing . . . . . . . . . . . . . . . . . . . . . . . .
92
5.2.2 Data Fusion Architectures .................................
92
5.3 Satellite Passive Microwave Algorithms .........................
94
5.4 Fusion Approach for Sea Ice Classification . . . . . . . . . . . . . . . . . . . . . . .
95
5.4.1 Determination of Multiyear Ice Concentration from ERS-1 SAR . . . . . . .
96
5.4.2 Active/Passive Image Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . .
97
5.4.3 Relationship to Freeze-Up Detected with SAR ...................
98
5.4.4 Modification of the NASA Team Algorithm for Multisensor
Ice Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 101
5.5 Active/Passive Multisensor Fusion Results ....................... 101
5.6 Discussion and Future Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 105
5.7 Conclusions ............................................ 106
References
S.l
Introduction
107
In this chapter we discuss an approach for fusing satellite synthetic aperture radar (SAR)
with passive microwave data for improved ice type concentration estimates. The algorithm is demonstrated on satellite image data obtained after the onset of freeze-up in
the central Arctic. During freeze-up new ice growth results in significant amounts of
young first-year and thin ice. These are as important as multiyear ice and open water
in modulating the heat flux between the ocean and atmosphere in the central Arctic
Ice type concentration estimates based on the NASA Team (NT) algorithm are inaccurate during the melt and freeze-up seasons because of confusion between multiyear
and first -year ice. Ambiguities between ice types are caused by dynamic changes in the
passive microwave signatures of sea ice during these seasons and are related to the use
of tie points to define pure ice type signatures.
We combined data from the European Remote Sensing Satellite (ERS-1) SAR and the
Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager
(SSM/I) to improve estimates of ice type concentration after the onset of freeze-up. We
Analysis of SAR Data of the Polar Oceans
Edited by C. Tsatsoulis and R. Kwok
© Springer-Verlag Berlin Heidelberg 1998
Fusion of Satellite SAR with Passive Microwave Data for Sea Ice
Remote Sensing
S.G. BEAVEN AND S.P. GOGINENI
Contents
5.1 Introduction
91
5.2 Data Fusion Background ...................................
92
5.2.1 Data Fusion for Sea Ice Remote Sensing . . . . . . . . . . . . . . . . . . . . . . . .
92
5.2.2 Data Fusion Architectures .................................
92
5.3 Satellite Passive Microwave Algorithms .........................
94
5.4 Fusion Approach for Sea Ice Classification . . . . . . . . . . . . . . . . . . . . . . .
95
5.4.1 Determination of Multiyear Ice Concentration from ERS-1 SAR . . . . . . .
96
5.4.2 Active/Passive Image Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . .
97
5.4.3 Relationship to Freeze-Up Detected with SAR ...................
98
5.4.4 Modification of the NASA Team Algorithm for Multisensor
Ice Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 101
5.5 Active/Passive Multisensor Fusion Results ....................... 101
5.6 Discussion and Future Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 105
5.7 Conclusions ............................................ 106
References
S.l
Introduction
107
In this chapter we discuss an approach for fusing satellite synthetic aperture radar (SAR)
with passive microwave data for improved ice type concentration estimates. The algorithm is demonstrated on satellite image data obtained after the onset of freeze-up in
the central Arctic. During freeze-up new ice growth results in significant amounts of
young first-year and thin ice. These are as important as multiyear ice and open water
in modulating the heat flux between the ocean and atmosphere in the central Arctic
Ice type concentration estimates based on the NASA Team (NT) algorithm are inaccurate during the melt and freeze-up seasons because of confusion between multiyear
and first -year ice. Ambiguities between ice types are caused by dynamic changes in the
passive microwave signatures of sea ice during these seasons and are related to the use
of tie points to define pure ice type signatures.
We combined data from the European Remote Sensing Satellite (ERS-1) SAR and the
Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager
(SSM/I) to improve estimates of ice type concentration after the onset of freeze-up. We
Analysis of SAR Data of the Polar Oceans
Edited by C. Tsatsoulis and R. Kwok
© Springer-Verlag Berlin Heidelberg 1998