Share This Article:

A Review on Applications of Imaging Synthetic Aperture Radar with a Special Focus on Cryospheric Studies

Abstract Full-Text HTML XML Download Download as PDF (Size:527KB) PP. 163-175
DOI: 10.4236/ars.2015.42014    4,902 Downloads   6,142 Views   Citations


The cryosphere is the frozen part of the Earth’s system. Snow and ice are the main constituents of the cryosphere and may be found in different states, such as snow, freshwater ice, sea ice, perma-frost, and continental ice masses in the form of glaciers and ice sheets. The present review mainly deals with state-of-the-art applications of synthetic aperture radar (SAR) with a special emphasize on cryospheric information extraction. SAR is the most important active microwave remote sensing (RS) instrument for ice monitoring, which provides high-resolution images of the Earth’s surface. SAR is an ideal sensor in RS technology, which works in all-weather and day and night conditions to provide useful unprecedented information, especially in the cryospheric regions which are almost inaccessible areas on Earth. This paper addresses the technological evolution of SAR and its applications in studying the various components of the cryosphere. The arrival of SAR radically changed the capabilities of information extraction related to ice type, new ice formation, and ice thickness. SAR applications can be divided into two broad classes-polarimetric applications and interferometric applications. Polarimetric SAR has been effectively used for mapping calving fronts, crevasses, surface structures, sea ice, detection of icebergs, etc. The paper also summarizes both the operational and climate change research by using SAR for sea ice parameter detection. Digital elevation model (DEM) generation and glacier velocity mapping are the two most important applications used in cryosphere using SAR interferometry or interferometric SAR (InSAR). Space-borne InSAR techniques for measuring ice flow velocity and topography have developed rapidly over the last decade. InSAR is capable of measuring ice motion that has radically changed the science of glaciers and ice sheets. Measurement of temperate glacier velocities and surface characteristics by using airborne and space-borne interferometric satellite images have been the significant application in glaciology and cryospheric studies. Space-borne InSAR has contributed to major evolution in many research areas of glaciological study by measuring ice-stream flow velocity, improving understanding of ice-shelf processes, yielding velocity for flux-gate based mass-balance assessment, and mapping flow of mountain glaciers. The present review summarizes the salient development of SAR applications in cryosphere and glaciology.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Jawak, S. , Bidawe, T. and Luis, A. (2015) A Review on Applications of Imaging Synthetic Aperture Radar with a Special Focus on Cryospheric Studies. Advances in Remote Sensing, 4, 163-175. doi: 10.4236/ars.2015.42014.


[1] SAR.
[2] Aher, S.P., Khemnar, S.B. and Shinde, S.D. (2014) Synthetic Aperture Radar in Indian Remote Sensing. International Journal of Applied Information Systems (IJAIS), 7, 41-44.
[3] Chakraborty, M., Panigrahy, S., Rajawat, A.S., Kumar, R., Murthy, T.V.R., Haldar, D., Chakraborty, A., Kumar, T., Rode, S., Kumar, H., Mahapatra, M. and Kundu, S. (2013) Initial Results Using RISAT-1 C-Band SAR Data. Current Science, 104, 490-501.
[4] Ersahin, K., Cumming, I. and Yedlin, M. (2006) Classification of Polarimetric SAR Data Using Spectral Graph Partitioning. IEEE International Symposium on Geosciences and Remote Sensing, Denver, 31 July-4 August 2006, 1756-1759.
[5] Sandven, S., Johannessen, M. and Kloster, K. (2006) Sea Ice Monitoring by Remote Sensing.
[6] Wesche, C., Jansen, D. and Dierking, W. (2013) Calving Fronts of Antarctica: Mapping and Classification. Remote Sensing, 5, 6305-6322.
[7] Jezek, K., Sohn, H. and Noltimier, K. (1998) The Radarsat Antarctic Mapping Project. Proceedings of 1998 IEEE Geoscience and Remote Sensing Symposium Proceedings, 5, 2462-2464.
[8] Septhon, A., Brown, L., Macklin, J.T., Partington, K.C., Veck, N. and Rees, W. (1994) Segmentation of Synthetic-Aperture Radar Imagery of Sea Ice. International Journal of Remote Sensing, 15, 803-825.
[9] Young, N.W., Turner, D., Hyland, G. and Williams, R.N. (1998) Near-Coastal Iceberg Distribution in East Antarctica. Annals of Glaciology, 27, 68-74.
[10] Wesche, C. and Dierking, W. (2012) Iceberg Signatures and Detection in SAR Images in Two Test Regions of the Weddell Sea, Antarctica. J. Glaciol., 58, 325-339.
[11] Willis, C.J., Macklin, J.T., Partington, K.C., Teleki, K.A., Rees, W.G. and Williams, R.G. (1996) Iceberg Detection Using ERS-1 Synthetic Aperture Radar. International Journal of Remote Sensing, 17, 1777-1795.
[12] Mouginot, J., Scheuchl, B. and Rignot, E. (2012) Mapping of Ice Motion in Antarctica Using Synthetic Aperture Radar Data. Remote Sensing, 4, 2753-2767.
[13] Rignot, E., Mouginot, J. and Scheuchl, B. (2011) Measures InSAR-Based Antarctica Ice Velocity Map. National Snow and Ice Data Center, Boulder.
[14] Fricker, H.A., Young, N.W., Allison, I. and Coleman, R. (2002) Iceberg Calving from the Amery Ice Shelf, East An- tarctica. Annals of Glaciology, 34, 241-246.
[15] Jawak, S.D. and Luis, A.J. (2014) Prospective Application of NASA-ISRO SAR (NISAR) in Cryospheric Studies: A Practical Approach. NISAR Science Workshop, Space Applications Centre (SAC), Ahmadabad, 17-18 November 2014.
[16] Maitra, S. (2013) Analysis of Polarimetric Synthetic Aperture Radar and Passive Visible Light Polarimetric Imaging Data Fusion for Remote Sensing Applications. PhD Thesis, Rochester Institute of Technology, New York.
[17] Sandholt, I. (2001) Combination of Polarimetric SAR with Satellite SAR and Optical Data for Classification of Agricultural Land. Geografisk Tidsskrift-Danish Journal of Geography, 101, 21-32.
[18] Pottier, E. and Cloude, S.R. (1995) Unsupervised Classification of Full Polarimetric SAR Data and Feature Vectors Identificat1on Using Radar Target Decomposition Theorems and Entropy Analysis. Conference Paper Published for International Geosciences and Remote Sensing Symposium, Vol. 3, Firenze, 2247-2249.
[19] Ianninia, L., Molijna, R.A. and Hanssena, R.F. (2014) Integration of Multispectral and C-Band SAR Data for Crop Classification. Proceedings of SPIE, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 8887, Article ID: 88871D.
[20] Betbeder, J., Rapinel, S., Corpetti, T., Pottier, E., Corgne, S. and Hubert-Moy, L. (2014) Multitemporal Classification of TerraSAR-X Data for Wetland Vegetation Mapping. Remote Sensing, 8, Article ID: 083648.
[21] Ma, X.S., Yang, H.S.G., Zhang, L. and Li, P. (2014) Polarimetric-Spatial Classifcation of SAR Images Based on the Fusion of Multiple Classifiers. Remote Sensing, 7, 961-971.
[22] Haldar, D., Das, A., Mohan, S., Pal, O., Hooda, R.S. and Chakraborty, M. (2012) Assessment of L-Band SAR Data at Different Polarization Combinations for Crop and Other Land Use Classification. Electromagnetics Research B, 36, 303-321.
[23] Dargahi, A., Maghsoudi, Y. and Abkar, A.A. (2013) Supervised Classification of Polarimetric SAR Imagery Using Temporal and Contextual Information. Remote Sensing and Spatial Information Sciences, XL-1/W3, 107-110.
[24] Kiranyaz, S., Uhlmann, S. and Gabbouj, M. (2011) Polarimetric SAR Images Classification using Collective Network of Binary Classifiers. Conference Paper published in Urban Remote Sensing Event, Munich, 11-13 April 2011, 245- 248.
[25] Zhang, Y.D., Wu, L.N. and Wei, G. (2009) A New Classifier for Polarimetric SAR Images. Electromagnetics Research, 94, 83-104.
[26] Vanitha, A., Subashini, P. and Krishnaveni, M. (2013) SAR Ice Image Classification Using Parallelepiped Classifier Based On Gram-Schmidt Spectral Technique. Conference Paper Published in Computer Science & Information Technology (CS & IT), Coimbatore, 385-392.
[27] Rogan, J., Zhu, Z., Woodcock, C.E. and Kellndorfer, J. (2012) Assessment of Spectral, Polarimetric, Temporal, and Spatial Dimensions for Urban and Peri-Urban Land Cover Classification Using Landsat and SAR Data. Remote Sensing, 117, 72-82.
[28] Frison, P.L., Lardeux, C., Rudant, J.P., Souyris, J.C., Tison, C. and Stoll, B. (2006) Use of the SVM Classification with Polarimetric SAR Data for Land Use Cartography. Conference Paper Published in Geoscience and Remote Sensing Symposium, Denver, 31 July-4 August 2006, 493-496.
[29] Mishra, P., Singh, D. and Yamaguchi, Y. (2011) Land Cover Classification of Palsar Images by Knowledge Based Decision Tree Classifier and Supervised Classifiers Based On SAR Observables. Electromagnetic Research B, 30, 47-70.
[30] Yang, W., Dai, D., Triggs, B. and Xia, G. (2012) SAR-Based Terrain Classifcation Using Weakly Supervised Hierarchical Markov Aspect Models. IEEE Transactions on Image Processing, 21, 4232-4243.
[31] Hong, S., Jang, H., Kim, N. and Sohn, H. (2015) Water Area Extraction Using RADARSAT SAR Imagery Combined with Landsat Imagery and Terrain Information. Sensors, 15, 6652-6667.
[32] NSIDC.
[33] Ambinakudige, S. and Joshi, K. (2012) Remote Sensing of Cryosphere. In: Boris Escalante-Ramirez, Ed., Earth and Planetary Sciences, Geology and Geophysics, InTech.
[34] Scheuchl, B., Flett, D.G., Caves, R. and Cumming, I. (2004) Potential of RADARSAT-2 Data for Operational Sea Ice Monitoring. Canadian Journal of Remote Sensing, 30, 448-461.
[35] Kasturirangan, K., Navalgund, R.R. and Ajai (2013) Observed Changes in the Himalayan-Tibetan Glaciers. Fate of Mountain Glaciers in the Anthropocene Pontifical Academy of Sciences, Scripta Varia, 118.
[36] Pichel, W.G., Thompson, D.R. and Clemente-Colon, P. (2004) A Systematic Comparison of QuikSCAT and SAR Ocean Surface Wind Speeds. Remote Sensing, 42, 283-291.
[37] Sandven, S., Kloster, K., Tangen, H., Andreassen, T., Goodwin, H. and Partington, K. (2004) Sea Ice Mapping Using Envisat Asar Wideswath Images.
[38] Wackerman, C. and Johannessen, J. (2003) Operational Monitoring of Coastal and Marine Environment with Space- borne Sar Systems: Where Are We Now and Where Are We Going.
[39] Karvonen, J. (2012) Operational SAR-Based Sea Ice Drift Monitoring over the Baltic Sea. Ocean Science Discussions, 9, 359-384.
[40] Karvonen, J., Cheng, B., Vihma, T., Arkett, M. and Carrieres, T. (2012) A Method for Sea Ice Thickness and Concen- tration Analysis Based on SAR Data and a Thermodynamic Model. The Cryosphere, 6, 1507-1526.
[41] Scharien, R.K., Landy, J. and Barber, D.G. (2014) Sea Ice Melt Pond Fraction Estimation from Dual-Polarisation C-Band SAR—Part 1: In Situ Observation. The Cryosphere, 8, 805-844.
[42] Bouillon, S. and Rampal, P. (2015) On Producing Sea Ice Deformation Data Sets from SAR-Derived Sea Ice Motion. The Cryosphere, 6, 663-673.
[43] Dongchen, E., Zhou, C. and Liao, M. (2004) Application of SAR Interferometry on DEM Generation of the Grove Mountains. Photogrammetric Engineering & Remote Sensing, 70, 1145-1149.
[44] Rignot, E., Bamber, J.L., van den Broeke, M.R., Davis, C., Li, Y., van de Berg, W.J. and van Meijgaard, E. (2008) Recent Antarctic Ice Mass Loss from Radar Interferometry and Regional Climate Modelling. Nature Geoscience, 1, 106-110.
[45] Rignot, E., Velicogna, I., van den Broeke, M.R., Monaghan, A. and Lenaerts, J. (2011) Acceleration of the Contribution of the Greenland and Antarctic Ice Sheets to Sea Level Rise. Geophysical Research Letters, 38.
[46] Cryosphere Theme Report.
[47] Jawak, S.D. and Luis, A.J. (2012) Synergistic Use of Multitemporal RAMP, ICESat and GPS to Construct an Accurate DEM of the Larsemann Hills Region, Antarctica. Journal of Advances in Space Research, 50, 457-470.
[48] Jawak, S.D., Sambhus, P.G, Paranjape, R.A. and Luis, A.J. (2012) Assessment of Spatial Interpolation Techniques for Generating Accurate Digital Elevation Surface Using Combined Radar & LiDAR Elevation Data. Proceedings of 8th International Conference on Microwaves, Antenna Propagation and Remote Sensing (ICMARS), Jodhpur, 11-15 December 2012, 288-291.
[49] Jawak, S.D. and Luis, A.J. (2011) Synergetic Use of GLAS/ICESat and RAMP to Construct 3D DEM of Schirmacher Oasis, East Antarctica. 11th International Symposium on Antarctic Earth Sciences (ISAES), Edinburgh, 10-16 July 2011.
[50] Jawak, S.D. and Luis, A.J. (2010) Synergistic Use of SAR, GLAS/ICESat & Ground Survey (GPS) Data to Construct an Accurate DEM of the Larsemann Hills Region. 4th SCAR-OSC-2010, Buenos Aires, 3-6 August 2010.
[51] Jawak, S.D. and Luis, A.J. (2014) Synergetic Merging of Cartosat-1 and RAMP to Generate Improved Digital Elevation Model of Schirmacher Oasis, East Antarctica. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-8, 517-524.
[52] Joughin, I., Smith, B.E. and Abdalati, W. (2010) Glaciological Advances Made with Interferometric Synthetic Aperture Radar. Journal of Glaciology, 56, 1026-1042.
[53] Rignot, E. (1998) Radar Interferometry Detection of Hinge-Line Migration on Rutford Ice Stream and Carlson Inlet, Antarctica. Annals of Glaciology, 27, 25-32.
[54] Jezek, K.C. (1999) Glaciological Properties of the Antarctic Ice Sheet from Radarsat-1 Synthetic Aperture Radar Imagery. Annals of Glaciology, 29, 286-290.
[55] Jezek, K.C., Farness, K., Carande, R., Wu, X. and Labelle-Hamer, N. (2003) Radarsat-1 Synthetic Aperture Radar Observations of Antarctica: Modified Antarctic Mapping Mission. Radio Science, 38.
[56] Michel, R. and Rignot, E. (1999) Flow of Glaciar Moreno, Argentina, from Repeat-Pass Shuttle Imaging Radar Images: Comparison of the Phase Correlation Method with Radar Interferometry. Journal of Glaciology, 45, 93-100.
[57] Bamber, J.L., Gomez-Dans, J.L. and Griggs, J.A. (2008) A New 1 km Digital Elevation Model of the Antarctic Derived from Combined Satellite Radar and Laser Data—Part 1: Data and Methods. The Cryosphere, 3, 101-111.
[58] Hoen, W.E. and Zebker, H. (2000) Penetration Depths Inferred from Interferometric Volume Decorrelation Observed over the Greenland Ice Sheet. IEEE Transactions on Geoscience and Remote Sensing, 38, 2571-2583.
[59] Rignot, E., Echelmeyer, K. and Krabill, W. (2001) Penetration Depth of Interferometric Synthetic-Aperture Radar Signals in Snow and Ice. Geophysical Research Letters, 28, 3501-3504.
[60] Rignot, E., Mouginot, J. and Scheuchl, B. (2011) Ice Flow of the Antarctic Ice Sheet. Science, 333, 1427-1430.
[61] Joughin, I.R., Kwok, R. and Fahnestock, M.A. (1998) Interferometric Estimation of Three-Dimensional Ice-Flow Using Ascending and Descending Passes. IEEE Transactions on Geoscience and Remote Sensing, 36, 25-37.
[62] Joughin, I. (2002) Ice-Sheet Velocity Mapping: A Combined Interferometric and Speckle-Tracking Approach. Annals of Glaciology, 34, 195-201.
[63] Griggs, J.A. and Bamber, J.L. (2009) A New 1 km Digital Elevation Model of Antarctica Derived from Combined Radar and Laser Data—Part 2: Validation and Error Estimates. The Cryosphere, 3, 113-123.
[64] Helm, V., Humbert, A. and Miller, H. (2014) Elevation and Elevation Change of Greenland and Antarctica Derived from CryoSat-2. The Cryosphere, 8, 1539-1559.
[65] Beck, I., Ludwig, R., Bernier, M., Strozzi, T. and Boike, J. (2015) Vertical Movements of Frost Mounds in Sub-Arctic Permafrost Regions Analyzed Using Geodetic Survey and Satellite Interferometry. Earth Surface Dynamics Discussions, 3, 251-283.
[66] Stenseng, L. (2009) Development of SAR Altimetry Mode Studies and Applications over Ocean, Coastal Zones and Inland Water. DTU-Space, National Space Institute, Denmark.
[67] Rao, Y.S., Venkataraman, G. and Rao, K.S. (2005) Application of SAR Interferometry for Himalayan Glaciers. Pro- ceedings of Fringe 2005 Workshop, Frascati, 28 November-2 December 2005.
[68] Dunse, T., Schellenberger, T., Hagen, J.O., Kaab, A., Schuler, T.V. and Reijmer, C.H. (2015) Glacier-Surge Mechanisms Promoted by a Hydro-Thermodynamic Feedback to Summer Melt. The Cryosphere, 9, 197-215.
[69] Zhou, C., Deng, F., Wan, L., Wang, Z., Dongchen, E. and Zhou, Y. (2014) Application of Synthetic Aperture Radar Remote Sensing in Antarctica. Proceedings of SPIE, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 9158, Article ID: 91580L.

comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.