Training Course on Radar & Optical RS, IES, Cēsis, Latvia, 5-9 September SAR Marine Applications. Practicals
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1 SAR Marine Applications Practicals Martin Gade Uni Hamburg, Institut für Meereskunde
2 SAR Marine Applications Friday, 9 Sep, Morning: 1 - History & Basics Introduction Radar/SAR History Basics Scatterometer 2 - Wind and Waves SAR Wind Fields Storms, Tropical Cyclones Ocean Surface Waves Oceanic Internal Waves Marine Surface Films Rain Friday, 9 Sep, Afternoon: 3 - Currents and Objects Surface Currents Sea Bottom Topography Ship Detection Oil Pollution Monitoring Sea Ice 4 - Practicals SNAP Toolbox: Georeferencing, Mosaics Image Interpretation: Wind Fields, Oil Pollution, Sea Ice, Objects 2
3 Feature Scale Ocean Features on SAR Imagery Derived Measurement Imaging Mechanism Wind Speed Range [m s -1 ] Characteristics and Considerations Surface Waves m wavelength Wavelength Tilt Hydrodynamic Velocity Propagation direction Bunching Wave height 3 40 Azimuth-traveling waves may be nonlinear without correction. Other limiting factors include wavelength, wave height and fetch. Internal Waves km wavelength Wavelength Direction Amplitude Mixed layer depth Convergence/Divergence Surfactants 2 10 Curvilinear packets with multiple waves, decreasing wavelength from front to back. Sensitive to wind conditions, wave crest orientation to platform. Internal Tides km Wavelength Direction Interaction of centimeter Waves/Currents/Surfactants 3 7 Currents and Fronts km Location Shear Strain Velocity Shear/Convergence Convergence Wind stress Surfactants Sensitive to wind conditions. Often multiple mechanisms present simultaneously. Eddies km diameter Location and source Diameter Velocity Shear Strain Shear/Convergence Wind Stress Surfactants Sensitive to wind conditions. Often multiple mechanisms present simultaneously. Shallow Water Bathymetry 5-50 m depth Location/change detection Current velocity Depth Convergence 3-12 Sensitive to wind, current properties, depth. [Jackson & Apel, 2004] 3
4 Air-Sea Interactions on SAR Imagery Feature Scale Derived Measurement Imaging Mechanism Wind Speed Range [m s -1 ] Characteristics and Considerations Surface Winds > 1km grid Wind speed Wind direction Wind stress Indirectly via windrows, models, or sensors 3 25 For mesoscale, coastal variability. Requires good calibration. Roll Vortices 1-5 km wavelength Boundary Layer: Stratification Wind stress 3 15 Long axis/crests parallel to wind direction. Gravity Waves 2-10 km wavelength Height Turbulence spectrum Drag coefficient Wind stress 3 15 Long axis/crests perpendicular to wind direction, often associated with topography Rain Cells 2-40 km diameter Rain rate Wind stress Rain damping 3-15 Appearance sensitive to frequency, rain rate, wind speed. [Jackson & Apel, 2004] 4
5 Surface Films on SAR Imagery Feature Scale Derived Measurement Imaging Mechanism Wind Speed Range [m s -1 ] Characteristics and Considerations Biogenic Surfactants > 100m² area Areal extent Convergence 2 8 Both forms have signatures similar to low wind, cold thermal water masses, etc. Mineral Oils > 100m² area Areal extent Seeps Ship discharge Run-off 3 15 Wind speed, combination of L- and C-/Xbands may enable discrimination of each form. [Jackson & Apel, 2004] 5
6 Seasat SAR Image What is shown here? Seasat SAR Image (L-HH, 80 km 75 km) Nantucket Island (27 August 1978, 12:34 UTC) 6
7 Practicals! 7
8 Two Sentinel 1A SAR Images Sentinel 1A SAR Images (C-VV, 259 km 167 km) Baltic Proper (19 August 2016, 16:36 UTC) 8
9 Two Sentinel 1A SAR Images Georeferencing SNAP: - Radar - Geometric - Terrain Correction - Range-Doppler TC Sentinel 1A SAR Images (C-VV, 259 km 167 km) Baltic Proper (19 August 2016, 16:36 UTC) 9
10 Two Sentinel 1A SAR Images 10
11 Two Sentinel 1A SAR Images Georeferencing SNAP: - Radar - Geometric - Terrain Correction - Range-Doppler TC Sentinel 1A SAR Images (C-VV, 259 km 167 km) Baltic Proper (19 August 2016, 16:36 UTC) 11
12 Two Sentinel 1A SAR Images SAR Mosaicking SNAP: - Radar - Geometric - SAR-Mosaic Sentinel 1A SAR Images (C-VV, 259 km 167 km) Baltic Proper (19 August 2016, 16:36 UTC) 12
13 Two Sentinel 1A SAR Images 13
14 One Sentinel 1A SAR Mosaic Sentinel 1A SAR Images (C-VV, 259 km 167 km) Baltic Proper (19 August 2016, 16:36 UTC) 14
15 One Sentinel 1A SAR Mosaic Landmask SNAP: - Raster - Masks - Land/Sea Mask Sentinel 1A SAR Images (C-VV, 259 km 167 km) Baltic Proper (19 August 2016, 16:36 UTC) 15
16 Two Sentinel 1A SAR Images Landmask SNAP: - Raster - Masks - Land/Sea Mask Different projection! Sentinel 1A SAR Images (C-VV, 259 km 167 km) Baltic Proper (19 August 2016, 16:36 UTC) 16
17 Books: Basics & Theory 17
18 Books: Examples and Applications 18
19 Some Articles on Basics and Theory Donelan, M.A., and W.J. Pierson, 1987: Radar scattering and equilibrium ranges in wind-generated waves with application to scatterometry, J. Geophys. Res., 92, Jones, W.L., and L.C. Schroeder, 1978: Radar backscatter from the ocean: dependence on friction velocity, Boundary Layer Meteor., 13, Kwoh, D.S., and B.M. Lake, 1985: The nature of microwave backscattering from water waves, in The Ocean Surface, Y. Toba & H. Mitsuyasu (Eds), D. Reidel Publishing Company, Liu, W.T., 2002: Progress in scatterometer application, J. Oceanogr., 58, Liu, W.T., X. Xie, and W. Tang, 2010: Scatterometer s Unique Capability in Measuring Ocean Surface Stress, in Oceanography from Space, V. Barale, J.F.R. Gower, and L. Alberotanza (Eds), Springer, Heidelberg, Phillips. O.M., 1988: Radar returns from the sea surface Bragg scattering and breaking waves, J. Phys. Ocean., 18, Valenzuela, G.R., 1978: Theories for the interaction of electromagnetic and oceanic waves A review, Boundary Layer Meteor., 13, Wright, J.W., 1969: A new model for sea clutter, IEEE Trans. Antennas Propagat., AP-16,
20 Some Articles on Examples and Applications Alpers, W., D.B. Ross, and C.L. Rufenach, 1981: On the detectability of ocean surface waves by real and synthetic aperture radar, J. Geophys. Res., 86, Alpers, W., and E. Salusti, 1983: Scylla and Charybdis observed from space, J. Geophys. Res., 88, Alpers, W., and I. Hennings, 1984: A theory of the imaging mechanism of underwater bottom topography by real and synthetic aperture radar, J. Geophys. Res., 89, Brekke, C., and H.A.S. Solberg, 2005: Oil spill detection by satellite remote sensing, Remote Sens. Environ., 95, Gade, M., W. Alpers, H. Huehnerfuss, H. Masuko, and T. Kobayashi, 1998: The imaging of biogenic and anthropogenic ocean surface films by the multi-frequency/multi-polarization SIR-C/X-SAR, J. Geophys. Res., 103, Gade, M., W. Alpers, C. Melsheimer, and G. Tanck, 2008: Classification of sediments on exposed tidal flats in the German Bight using multi-frequency radar data, Remote Sens. Environ., 112, Melsheimer, C., W. Alpers, and M. Gade, 1998: Investigation of multifrequency/ multipolarization radar signatures of rain cells derived from SIR-C/X-SAR data, J. Geophys. Res., 103, Romeiser, R., S. Suchandt, H. Runge, U. Steinbrecher, and S. Grünler, 2010: First analysis of TerraSAR-X along-track InSAR-derived current fields, IEEE Trans. Geosci. and Remote Sensing, 48,
21 Liels paldies! 21
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