Journal of the Indian Society of Remote Sensing

, Volume 45, Issue 5, pp 847–858 | Cite as

Multi-sensor Space-Borne Earth Observation Data for Characterizing Fluvial-Geomorphic Provinces: A Case Study from Kosi River, India

  • Priyom RoyEmail author
  • Arindam Guha
  • K. Vinod Kumar
Research Article


The dynamism of geomorphic provinces in fluvial systems present considerable ambiguities in mapping by remote sensing. This necessitates use of multiple satellite data to characterize such depositional provinces. We use, an integrated dataset to characterize the geomorphic provinces (e.g. active flood plain, older food plain, fan etc.) of the Kosi River (Bihar), India. This is done using contrast in spectral signatures derived from multispectral bands (of IRS-P6 LISS III), radiant temperature (from ETM+) and radar-roughness (from radar brightness image RISAT-1). ASTER DEM has been used in deriving topographic profiles. The optical imagery, enables regional characterization through direct tonal changes (e.g. active flood plain is brighter than older flood plain). The radiant temperatures show variations across provinces. Geomorphic transitions are represented by topographic breaks. Radar backscatter imagery, show differences in radar-return from different sub-provinces. Observations made using specific sensor characterize each provinces and is supplementary/complimentary to the parameter(s) from other sensors.


Spectral contrast Radiant temperature Radar backscattering Fluvial geomorphology Kosi River 



This study is a part of a “Technology Development Project” of NRSC/ISRO. The authors thank Director, NRSC and Deputy Director, Remote Sensing Applications Area, NRSC, for their continuous support and encouragement.


  1. Agarwal, R. P., & Bhoj, R. (1992). Evolution of Kosi river fan, India: structural implications and geomorphic significance. International Journal of Remote Sensing, 13(10), 1891–1901.CrossRefGoogle Scholar
  2. Aslam, M. M., & Balasubramanian, A. (2001). Identification of palaeochannels around Cauvery river near Talakad, Karnataka using remote sensing data. Journal of the Indian Society of Remote Sensing, 29(4), 237–242.CrossRefGoogle Scholar
  3. Chakraborty, T., Kar, R., Ghosh, P., & Basu, S. (2010). Kosi megafan: Historical records, geomorphology and the recent avulsion of the Kosi River. Quaternary International, 227(2), 143–160.CrossRefGoogle Scholar
  4. 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. (2013). Initial results using RISAT-1 C-band SAR data. Current Science (Bangalore), 104(4), 490–501.Google Scholar
  5. Gillespie, A. R., Kahle, A. B., & Walker, R. E. (1986). Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches. Remote Sensing of Environment, 20(3), 209–235.CrossRefGoogle Scholar
  6. Gohain, K., & Prakash, B. (1990). Morphology of the Kosi Megafan. In A. Rachoki & M. Church (Eds.), Alluvial fans: A field approach (pp. 151–178). Chichester: Wiley.Google Scholar
  7. Guha, A., Kumar, K. V., Kamaraju, M. V. V., & Govindharaj, K. B. (2009). Potentials of alternate polarization of Envisat ASAR data in geological mapping—A case study in Kurnool Group of rocks, Andhra Pradesh. Journal of the Geological Society of India, 73(2), 268–272.CrossRefGoogle Scholar
  8. Guha, A., Vinod Kumar, K., & Kamaraju, M. V. V. (2008). Influences of look angle and look direction of space-borne SAR sensor in geological feature delineation in Metasedimentary terrain of Kurnool Group of rocks, Andhra Pradesh. Current science, 95(1), 99–104.Google Scholar
  9. Gupta, R. P. (2013). Remote sensing geology. New York: Springer.Google Scholar
  10. Gustavsson, M., Kolstrup, E., & Seijmonsbergen, A. C. (2006). A new symbol-and-GIS based detailed geomorphological mapping system: Renewal of a scientific discipline for understanding landscape development. Geomorphology, 77(1), 90–111.CrossRefGoogle Scholar
  11. Jensen, J. R. (2005). Introductory digital image processing: A remote sensing perspective. London: Pearson College Division.Google Scholar
  12. Lee, J. B., & Berman, M. (1990). Enhancement of high spectral resolution remote-sensing data by a noise-adjusted principal components transform. IEEE Transactions on Geoscience and Remote Sensing, 28(3), 295–304.CrossRefGoogle Scholar
  13. Markham, B. L., & Barker, J. L. (1986). Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Landsat Technical Notes, 1(1), 3–8.Google Scholar
  14. Mitra, D., Tangri, A. K., & Singh, I. B. (2005). Channel avulsions of the Sarda River system, Ganga Plain. International Journal of Remote Sensing, 26(5), 929–936.CrossRefGoogle Scholar
  15. Munteanu, C., & Lazarescu, V. (1999). Evolutionary contrast stretching and detail enhancement of satellite images. In Proceedings of MENDEL’99, pp.94–99.Google Scholar
  16. Narayana, A. C., Priju, C. P., & Chakrabarti, A. (2001). Identification of a palaeodelta near the mouth of Periyar River in Central Kerala. Geological Society of India, 57(6), 545–547.Google Scholar
  17. NRSC. (2010). Manual for national geomorphological and lineament mapping on 1:50000 scale (a project under National Resources Census (NRC), technical report no: NRSC-RS&GISAA- ERG-G&GD-FEB’ 10-TR149 (Unpublished), 146 p.Google Scholar
  18. Philip, G., Gupta, R. P., & Bhattacharya, A. (1989). Channel migration studies in the middle Ganga basin, India, using remote sensing data. International Journal of Remote Sensing, 10(6), 1141–1149.CrossRefGoogle Scholar
  19. Seker, D. Z., Kaya, S., Musaoglu, N., Kabdasli, S., Yuasa, A., & Duran, Z. (2005). Investigation of meandering in Filyos River by means of satellite sensor data. Hydrological Processes, 19(7), 1497–1508.CrossRefGoogle Scholar
  20. Singh, S., Guha, A., Kumar, K. V., Bardhan, S., Lesslie, A., Ravi Kumar, M. V., & Chatterjee, A. (2015). Satellite based mapping and morphogenetic analysis of the landforms in the tertiary fold belts of parts of Tripura, India. Geocarto International, 30(9), 1016–1032.Google Scholar
  21. Singh, A. K., Parkash, B., & Choudhury, P. R. (2007). Integrated use of SRM, Landsat ETM+ data and 3D perspective views to identify the tectonic geomorphology of Dehradun valley, India. International Journal of Remote Sensing, 28(11), 2403–2414.CrossRefGoogle Scholar
  22. Singh, H., Parkash, B., & Gohain, K. (1993). Facies analysis of the Kosi megafan deposits. Sedimentary Geology, 85(1), 87–113.CrossRefGoogle Scholar
  23. Sinha, R. (2009). The great avulsion of Kosi on 18 August 2008. Current Science, 97(3), 429–433.Google Scholar
  24. Wilford, J., & Creasey, J. (2002). Landsat thematic mapper. In E. Papp (Ed.), Geophysical and remote sensing methods for regolith exploration (pp. 6–12). CRCLEME open file report 144.Google Scholar
  25. Woodhouse, I. H. (2006). Introduction to microwave remote sensing. Boca Raton: Taylor and Francis.Google Scholar
  26. Zyl, J. J., Zebker, H. A., & Elachi, C. (1987). Imaging radar polarization signatures: Theory and observation. Radio Science, 22(4), 529–543.CrossRefGoogle Scholar

Copyright information

© Indian Society of Remote Sensing 2016

Authors and Affiliations

  1. 1.Geosciences Group, National Remote Sensing CentreIndian Space Research OrganisationHyderabadIndia

Personalised recommendations