Investigation of the Microwave Signatures of the Baltic Sea Ice

OF DOCTORAL DISSERTATION HELSINKI UNIVERSITY OF TECHNOLOGY P.O. BOX 1000, FI-02015 TKK http://www.tkk. fi Author Marko Mäkynen Name of the dissertation Investigation of the Microwave Signatures of the Baltic Sea Ice Manuscript submitted 16.10. 2006 Manuscript revised 2.3. 2007 Date of the defence 4.5. 2007 Monograph Article dissertation (summary + original articles) Department Electrical and Communications Engineering Laboratory Laboratory of Space Technology Field of research Microwave remote sensing Opponent Dr. Wolfgang Dierking, Alfred Wegener Institute, Germany Supervisor Prof. Martti Hallikainen Instructor Prof. Martti Hallikainen Abstract It is essential for winter shipping in the Baltic Sea to get reliable and up-to-date information of its rapidly changing ice conditions. Spaceborne synthetic aperture radar (SAR) images are the only way to produce this information operationally in fine scale independent of daylight and nearly independent of weather conditions. Currently, classification algorithms for the RADARSAT-1 and ENVISAT SAR images utilize mainly the image structure and only limited information on sea ice geophysics and empirical statistics of backscattering signatures of various ice types are utilized. Therefore, interpretation of the classification results is often difficult. Both classification results and their interpretation should very likely improve with the addition of this information. Spaceborne microwave radiometer data are not suitable for the operational Baltic Sea ice monitoring aiding ship navigation due to their coarse spatial resolution, but they can provide an independent data source on the sea ice conditions for validation of the SAR classification algorithms. In order to support development of operational classification algorithms for the Baltic Sea ice SAR and radiometer data, following studies have been conducted: (1) statistics of Cand X-band backscattering coefficient ( ) signatures of various ice types, (2) statistics of Land C-band polarimetric discriminants of various ice types, (3) radar incidence angle dependence of in RADARSAT-1 SAR images, (4) dependence between standard deviation and measurement length for signatures and its usability in sea ice classification, (5) comparison between SAR ° σIt is essential for winter shipping in the Baltic Sea to get reliable and up-to-date information of its rapidly changing ice conditions. Spaceborne synthetic aperture radar (SAR) images are the only way to produce this information operationally in fine scale independent of daylight and nearly independent of weather conditions. Currently, classification algorithms for the RADARSAT-1 and ENVISAT SAR images utilize mainly the image structure and only limited information on sea ice geophysics and empirical statistics of backscattering signatures of various ice types are utilized. Therefore, interpretation of the classification results is often difficult. Both classification results and their interpretation should very likely improve with the addition of this information. Spaceborne microwave radiometer data are not suitable for the operational Baltic Sea ice monitoring aiding ship navigation due to their coarse spatial resolution, but they can provide an independent data source on the sea ice conditions for validation of the SAR classification algorithms. In order to support development of operational classification algorithms for the Baltic Sea ice SAR and radiometer data, following studies have been conducted: (1) statistics of Cand X-band backscattering coefficient ( ) signatures of various ice types, (2) statistics of Land C-band polarimetric discriminants of various ice types, (3) radar incidence angle dependence of in RADARSAT-1 SAR images, (4) dependence between standard deviation and measurement length for signatures and its usability in sea ice classification, (5) comparison between SAR ° σ ° σ ° σ ° σ time series and results from a thermodynamic snow/ice model, and (6) statistics of passive microwave signatures of various ice types. The main results of this work include the following. It is not possible to discriminate open water and various ice types using the level of , coor cross-polarization ratio, or standard deviation of ° σ ° σ . C-band VH-polarized ° σ at high incidence angle provides slightly better ice type discrimination accuracy than any other combination of radar parameters. VH-polarization is more suitable for estimating the degree of ice deformation than co-polarizations. Snow wetness has a large effect on the statistics, e.g. when snow cover is wet then the ° σ ° σ contrasts between various ice types are smaller than in the dry snow case. Incidence angle dependence of the C-band HH-polarized ° σ was derived for level ice and deformed ice. The method for deriving this is applicable for any SAR sensor. There is a large variation of level ice ° σ with changing weather conditions. A 1-D high-resolution thermodynamic snow/ice model generally helps to interpret changes in the time series. The modeled snow and ice parameters are related to the changes in . It was found out that the standard deviation of for various ice types depends on the length of measurement. This may be utilized in the SAR image classification. It is not possible to resolve concentrations of thin new ice and all other ice types combined in the Baltic Sea using radiometer data as has been done for the Arctic seasonal ice zones. ° σ ° σ ° σ