Dr Rajkumar Kamaljit Singh

Dr Rajkumar Kamaljit Singh

Dr Rajkumar Kamaljit Singh

Assistant Professor

Qualification:

1. Bachelor’s Degree: Gold medallist, Manipur University 2004 2. Master’s Degree: 1 st Division, Manipur University 2006 3. Ph.D.: Gujarat University, 2013 4. Other: (Post-Doctoral) Research Associateship, Space Applications Centre-ISRO, Ahmedabad 2012-2015

Areas of Specialization:

Satellite remote sensing of the Polar Regions of the Earth

  1. Development of INSAR based techniques for high resolution surface topography and ice velocity. Collaborators: ISRO-MTU. Funding agency: Space Applications Centre-ISRO, Ahmedabad (Ongoing).
  2. Spatio-temporal investigation of Arctic and Antarctic sea ice area and thickness. Collaborators: ISRO-MTU. Funding agency: Space Applications Centre-ISRO, Ahmedabad (Ongoing).
  3. Signature analysis, monitoring Ice calving events and marginal changes using SCATSAT-1 data over the Antarctica. Collaborators: ISRO-NIT Manipur. Funding Agency: Space Applications Centre-ISRO, Ahmedabad (Completed)
  1. Detection of Two Recent Calving Events in Antarctica from SCATSAT-1, (2021), Singh et al., 10.1109/IGARSS47720.2021.9553306, IEEE Xplore, IEEE- International Geoscience and Remote Sensing Symposium (IGARSS) 2021, Belgium and the Netherlands.
  2. Application of Principal Component Analysis and Unsupervised Classification (ISODATA) to Estimate Arctic Sea Ice Extent Using ISRO’s SCATSAT-1 Data, (2021), Singh et al., 5th International Young Earth Scientists (YES) Congress “Rocking Earth’s Future”, Berlin, Germany, http://dx.doi.org/10.2312/yes19.21
  3. Long-Term Observation of the Arctic Sea Ice Melt Onset from Microwave Radiometry, (2020), Singh et al., Journal of the Indian Society of Remote Sensing 49(1), http://dx.doi.org/10.1007/s12524-020-01220-6
  4. Discrimination of Arctic multi-year ice from first-year ice using SCATSAT-1 data, (2020), Singh et al., Indian Journal of Radio and Space Physics 49:98-104.
  5. Application of maximum-likelihood classification for segregation between Arctic multi-year ice and first-year ice using SCATSAT-1 data, (2020), Singh et al., Remote Sensing Applications Society and Environment 18:100310, http://dx.doi.org/10.1016/j.rsase.2020.100310
  6. Observing Larsen C ice-shelf using ISRO’s SCATSAT-1 data, (2019), Singh et al., https://doi.org/10.1016/j.polar.2018.12.007
  7. Antarctic Sea Ice Extent from ISRO’s SCATSAT-1 Using PCA and An Unsupervised Classification, (2018), Singh et al., Proceedings 2(7):340, https://doi.org/10.3390/ecrs-2-05153
  8. Sea ice occurrence probability data and its applications over the Antarctic, (2015), Rajak et al., Journal of Geomatics vol 9(No 2):Pages 193-197.
  9. Comparing Modelled Arctic Sea Ice Trend with Remotely Sensed Estimates, (2015), Rajak et al., Journal of Geomatics Journal of Geomatics(9):1
  10. Estimation of Sea Ice Freeboard from SARAL-AltiKa Data, (2015), Maheshwari et al., Marine Geodesy 38(sup1), http://dx.doi.org/10.1080/01490419.2015.1005782
  11. Concurrent Use of OSCAT and AltiKa to Characterize Antarctic Ice Surface Features, (2015), Singh et al., Marine Geodesy 38(sup1), http://dx.doi.org/10.1080/01490419.2014.1001047
  12. Ice calving and deformation from Antarctic Ice margins using RISAT-1 circular polarization SAR data, (2014), Jayaprasad et al., Int. Arch. Photogramm. Remote Spatial Inf. Sci., XL-8, 525–529, https://doi.org/10.5194/isprsarchives-XL-8- 525-2014
  13. Long-term variability in Arctic sea surface temperatures, (2013), Singh et al., Polar Science 7(3-4):233-240, http://dx.doi.org/10.1016/j.polar.2013.10.003
  14. An Investigation of the Southern Ocean Surface Temperature Variability Using Long- Term Optimum Interpolation SST Data, (2013), Maheshwari et al., ISRN Oceanography 2013(1), http://dx.doi.org/10.5402/2013/392632
  15. Inter-annual variations observed in spring and summer Antarctic sea ice extent in recent decade, (2011), Oza et al., Mausam 62(4):633-640, http://dx.doi.org/10.54302/mausam.v62i4.381
  16. Estimation of Thin Ice Thickness From the Advanced Microwave Scanning Radiometer-EOS for Coastal Polynyas in the Chukchi and Beaufort Seas, (2011), Singh et al., IEEE Transactions on Geoscience and Remote Sensing 49(8):2993 – 2998, https://doi.org/10.1109/TGRS.2011.2123101
  17. Spatio-temporal analysis of melting onset dates of sea-ice in the Arctic, (2011), Oza et al., Indian Journal of Geo-Marine Sciences 40(4):497-501.
  18. Spatio-Temporal Coherence Based Technique for Near-Real Time Sea-Ice Identification from Scatterometer Data, (2011), Oza et al., Journal of the Indian Society of Remote Sensing 39(2):147-152, http://dx.doi.org/10.1007/s12524-011- 0070-x
  19. Study of inter-annual variations in surface melting over Amery Ice Shelf, East Antarctica, using space-borne scatterometer data, (2011), Oza et al., Journal of Earth System Science 120(2):329-336, http://dx.doi.org/10.1007/s12040-011-0055-8
  20. Recent Trends of Arctic and Antarctic Summer Sea-Ice Cover Observed from SpaceBorne Scatterometer, (2010), Oza et al., Journal of the Indian Society of Remote Sensing 38(4):611-616, http://dx.doi.org/10.1007/s12524-011-0071-9
  21. Spatio-temporal monitoring of the iceberg D28 using SCATSAT-1 data, Singh et al., Polar Record , Volume 59 , 2023 , e15, https://doi.org/10.1017/S0032247423000062
  22.  Antarctic sea ice concentration estimation using bi-frequency SARAL/AltiKa data, (2022), Thombson et al., 10th SCAR Open Science Conference, Abstract #721, p. 171, https://scar.org/library/conferences/scar-open-science-conferences/abstracts/5876-scar-open-science-conference-2022-abstracts/file/
  23. Spatio-temporal monitoring of the iceberg D28 using SCATSAT-1 data, (2023), Singh et al., Polar Record 59(E15), https://doi.org/10.1017/S0032247423000062.
  24. Surface roughness from in-situ measurements around Indian Antarctic stations, (2023), Maheswhari et al., Polar Science 100971, https://doi.org/10.1016/j.polar.2023.100971.
  25. Rathong glacier’s Line-Of-Sight (LOS) Velocity Measured Using the Modified Four-Pass DInSAR Technique, Kangjam et al., (2023), Lecture notes in Civil Engineering (431), https://doi.org/10.1007/978-981-99-4665-5_21.
  26. Estimation of sea ice concentration in the Arctic using SARAL/AltiKa data, Thombson et al., IEEE Transactions on Geoscience and Remote Sensing 61, https://doi.org/10.1109/TGRS.2023.3328786.
  1. Investigations of the Recent Polar Ice Variations Observed from the Space-borne Optical and Microwave Sensors, Oza et al., Ramesh, R., Sudhakar, M., Chattopadhyay, S., (eds.), Scientific and Geopolitical Interests in Arctic and Antarctic, Proceedings of International Conference on Science and Geopolitics of Arctic and Antarctic, (iSaGAA), March 2013, LIGHTS, Research Foundations, 296, ISBN(13): 978-9350679081.
  1. A method to analyze the variability in the Arctic Snowmelt Onset Dates (SMOD). Innovation Patent (Australia) (http://pericles.ipaustralia.gov.au/ols/auspat/applicationDetails.do?applicationNo=202 1101298)
  2. "A system for estimating sea ice concentration of an area" (South African Patent) https://patents.google.com/patent/ZA202305319B/"
  1. Head of the Department of Physics from 2018 to 2021
  2. Member Exam sub-committee
  3. Member Student Academic Support Committee
  4. Coordinator- Research & Development