Skip to main content

Remote Sensing for National Development: The Legacy of Dr. Vikram Sarabhai

Abstract

Dr. Vikram Sarabhai was a great visionary, and we are celebrating his Centenary birth anniversary, this year. It was amazing to see, 50 years back, he had planned meticulously various possible remote sensing applications that materialised in the fields of weather and oceans, coastal zone management, geoscience, hydrology, forestry, land use and agriculture and contributed significantly towards national development. Not only that, he had thought about the kinds of sensors, processing and communicating technologies that would be required. He had stressed need for the domain expertise in different disciplines and collaboration with various stakeholders for developing various remote sensing-based products and services and their utilisation. The concept of the National Natural Resources Management System had born out this vision. Such approach has really paid rich dividends. Today, because of such approach, India is in forefront of operational utilisation of remote sensing data and provides weather services for farmers, potential fishery zone advisories to fishermen, accurate and reliable forecast on cyclones and droughts, groundwater targeting for drinking water, condition and status of forest and glaciers, annual forecast of production of major food grains, to name a few. The time is now appropriate to transform this world-class technology into a national system of remote sensing in collaboration with industries to provide operational services to not only users in India, but also all developing countries. Such approach will pave way in translating technology development into innovation for the benefit of all stakeholders. These benefits will help in improving particularly social and economic conditions of developing societies, and is the best way to pay tribute to him. In this article, the vision of Dr. Sarabhai vis-à-vis the status of utilisation of remote sensing in the country has been discussed.

This is a preview of subscription content, access via your institution.

References

  1. Ajai, A. S., Dhinwa, P. S., Pathan, S. K., & Ganesh Raj, K. (2009). Desertification/land degradation status mapping of India. Current Science, 97(10), 1478–1483.

    Google Scholar 

  2. Bahuguna, I. M., Kulkarni, A. V., Nayak, S., Negi, H. S., & Mathur, P. (2007). Himalayan glacier retreat using IRS 1C PAN stereo data. International Journal of Remote Sensing, 28(2), 437–442.

    Google Scholar 

  3. Bahuguna, A., & Nayak, S. (1998). Coral Reefs of the Indian Coast. Scientific Note, Space Applications Centre, Ahmedabad. SAC/RSA/RSAG/DOD-COS/SN/16/97. 56 p

  4. Bahuguna, A., Nayak, S., & Roy, D. (2008). Impact of the Tsunami and Earthquake of 26th December 2004 on the Vital coastal Ecosystems of the Andaman and Nicobar Islands Assessed using RESOURCESAT AWiFS Data. International Journal of Applied Earth Observation and Geoinformation, 10(2), 229–237.

    Google Scholar 

  5. Balaji, S. (2010). A paleo-stress analysis of Precambrian granulite terrain of northern Tamil Nadu, Peninsular India—A remote sensing study. Asian Journal of Geoinformatics, 10(4), 12–16.

    Google Scholar 

  6. Basnett, S., Kulkarni, A. V., & Bloch, T. (2013). The influence of debris cover and glacial lakes on the recession of glaciers in Sikkim Himalaya, India. Journal of Glaciology, 59(218), 1035–1046.

    Google Scholar 

  7. Bharati, R., & Ramakrishnan, D. (2014). Uriniferous calcrete mapping using hyperspectral remote sensing. In IEEE international geoscience and remote sensing symposium (pp. 2902–2905).

  8. Bhowmick, S. A. (2019). An assessment of the performance of ISRO’s SCATSAT-1scatterometer. Current Science Special Section: SCATSAT-1, 117(6), 959–972.

    Google Scholar 

  9. Biancamaria, S., Hossain, F., & Lettenmajor, D. (2011). Forecasting trans boundary flood with satellites. Geophysical Letters, 38, L11401.

    Google Scholar 

  10. Chakraborty, M., Manjunath, K. R., Panigrahy, S., Kundu, N., & Parihar, J. S. (2005). Rice crop parameter retrieval using multi-temporal, multi-incidence angle Radarsat SAR data. ISPRS Journal Photogrammetry and Remote Sensing, 59(5), 310–322.

    Google Scholar 

  11. Chaturvedi, R. K., Kulkarni, A., Karyakarte, Y., Joshi, J., & Bala, G. (2014). Glacial mass balance changes in the Karakoram and Himalaya based on CMIP5 multi-model climate projections. Climate Change. https://doi.org/10.1007/s10584-013-1052-5.

    Article  Google Scholar 

  12. Chauhan, P., & Nayak, S. (1996). Shoreline-change mapping from space: a case study on the Indian coast. In The Proceedings of the International Workshop on International Mapping from Space, ISPRS (pp. 130–141).

  13. Chauhan, P., & Raman, M. (2017). Satellite remote Sensing for ocean biology: an Indian perspective. Proceedings of the National Academy of Science India Section Physics Science, 87(4), 629–640. https://doi.org/10.1007/s40010-017-0439-5.

    Article  Google Scholar 

  14. Chitale, V. S., Behera, M. D., & Roy, P. S. (2019). Deciphering plant richness using satellite remote Sensing: A study from three biological hotspots. Biodiversity and Conservation. https://doi.org/10.1007/s10521-019-01761-4.

    Article  Google Scholar 

  15. Dadhwal, V. K. (2012). Assessment of Indian carbon cycle components using Earth Observation systems and ground inventory. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXIX-B8, 2012. XXII ISPRS Congress, Melbourne, Australia. 25 Aug–01 Sep 2012.

  16. Dadhwal, V. K., Parihar, J. S., Ruhal, D. S., Jarwal, S. D., Medhavy, T. T., Khera, A. P., et al. (1989). Journal of Indian Society of Remote Sensing, 17(4), 1727–1734.

    Google Scholar 

  17. Dadhwal, V. K., Ruhal, D. S., Medhavy, T. T., Jarwal, S. D., Khera, A. P., Singh, J., et al. (1991). Wheat acreage estimation for Haryana using satellite digital data. Journal of Indian Society of Remote Sensing, 19(1), 1–15.

    Google Scholar 

  18. Dadhwal, V. K., Singh, R. P., Dutta, S., & Parihar, J. S. (2002). Remote sensing based crop inventory: A review of Indian experience. Tropical Ecology, 43(1), 107–122.

    Google Scholar 

  19. Dakshinamurti, C., Krishnamurthy, B., Summanwar, A. S., Sharma, P., & Pisharoty, P. R. (1971). Remote sensing for coconut wilt. In Proceedings of the 6th international symposium remote sensing and environment (pp. 25–29), Ann Arbor, Michigan.

  20. Das, S., & Pardeshi, S. D. (2018). Comparative analysis of lineaments extracted from Cartosat, SRTM and ASTER DEM: a study based on four watersheds in Konkan region, India. Spatial Information Research, 26, 47–57.

    Google Scholar 

  21. Das, K., & Paul, P. K. (2015). Present status of soil moisture estimation by microwave remote sensing. Cogent Geoscience, 1, 1–21.

    Google Scholar 

  22. Dasgupta, S., Das, I. C., Subramanian, S. K., & Dadhwal, Y. K. (2014). Space-based gravity data analysis for ground water storage estimation in the Gangetic plain, India. Current Science, 107(5), 832–844.

    Google Scholar 

  23. Dasgupta, S., & Mukerjee, S. (2019). Remote sensing in lineament identification: Examples from western India. Developments in Structural geology and Tectonics, 5, 205–211. https://doi.org/10.1016/B978-0-12-814048-2.00016-8.

    Article  Google Scholar 

  24. Deb, S. K., Kishtawal, C. M., Kumar, P., Kiran Kumar, A. S., Pal, P. K., Kaushik, N., et al. (2016). Atmospheric motion vectors from INSAT 3D: Initial Quality assessment and its impact on track forecast of cyclonic storm NANAUK. Atmospheric Research, 169, 1–16.

    Google Scholar 

  25. Desai, P. S., Narain, A., Nayak, S. R., Manikiam, B., Adiga, S., & Nath, A. N. (1991). IRS-1A applications for coastal and marine resources. Current Science, 61(3&4), 204–208.

    Google Scholar 

  26. Dwivedi, R. M., Solanki, H. U., Nayak, S. R., Gulati, D., & Somvanshi, V. S. (2005). Exploration of fishery resources through integration of Ocean colour data with sea surface temperature: Indian experience. Indian Journal of Marine Science, 34, 430–440.

    Google Scholar 

  27. Fransis, P. A., Jithin, A. K., John, E. B., Chatterjee, A., Chakraborty, K., Paul, A., et al. (2020). High-resolution operational ocean forecast and reanalysis system for the Indian ocean. Bull: American Meteorological Society. https://doi.org/10.1175/BAMS-D-19-0083.1.

    Book  Google Scholar 

  28. FSI. (1989). The State of Forest Report—1989 (p. 50). New Delhi: Forest Survey of India, Ministry of Environment and Forests, Govt. of India.

    Google Scholar 

  29. Gantayat, P., Kulkarni, A. V., & Srinivasan, J. (2014). Estimation of ice thickness using surface velocities and slope: Case study at Gangotri glacier. Indian Journal of Glaciology, 60(220), 227–282. https://doi.org/10.3189/2014jog13j078.

    Article  Google Scholar 

  30. Garg, J. K., Singh, T. S., & Murthy, T. V. R. (1998). Wetlands of India. In Project Report: RSAM/SAC/RESA/PR/01/98. Space Applications Centre, Ahmedabad.

  31. Ghosh, S., Karmakar, S., Saha, A., Mohanty, M. P., Ali, S., Raju, S. K., et al. (2019). Development of India’s first integrated expert urban food forecasting system for Chennai. Current Science, 117(5), 741–745.

    Google Scholar 

  32. Gohil, B. S., Mathur, A. K., & Varma, A. K. (2000). Geophysical parameters retrieval over Global oceans from IRS P4/MSMR (pp. 207–211). NIO, India: PORSEC.

    Google Scholar 

  33. Goswami, B. B., Mukhopadhyay, P., Mahanta, R., & Goswami, B. N. (2010). Multiscale interaction with topography and extreme rainfall events in the northeast Indian region. Journal of Geophysical Research: Atmospheres, 115(D12), D12114.

    Google Scholar 

  34. Goyal, S., Mohapatra, M., & Sharma, A. K. (2013). Comparison of best track parameters of RSMC, New Delhi, with satellite estimates over North Indian Ocean. Mausam, 64(1), 25–34.

    Google Scholar 

  35. GSI. (2014). National geomorphological and lineament mapping at 1:50,000 scale using satellite data. Code No.: PRS/CHQ/OP-MPP/2009/025. Geological survey of India and National Remote Sensing Centre, ISRO.

  36. Gupta, P. K., Chauhan, S., & Oza, M. P. (2016). Modelling surface runoff and trend analysis over India. Journal of Earth System Science, 125, 1089–1102.

    Google Scholar 

  37. Gupta, E., Das, S., & Rajani, M. B. (2017). Archeological explorationin Srirangapatna and its environ through remote sensing analysis. Journal of Indian Society of Remote Sensing, 45, 1057–1063.

    Google Scholar 

  38. Gupta, P. K., Dutta, S., & Panigrahi, S. (2009). Mapping of conjunctive use productivity pattern in an irrigation command using temporal IRS WiFs data. Journal of Water Resources Management, 24, 157–171.

    Google Scholar 

  39. Hegde, V. S., Nayak, S. R., Krishnaprasad, P. A., Rajawat, A. S., Shalini, R. S., & Jayakumar, S. (2015). Evolution of diverging spits across the tropical river mouths, Central West Coast of India. Journal of Coastal Zone Management. https://doi.org/10.4172/2473-3350.1000402.

    Article  Google Scholar 

  40. Hegde, V. S., Nayak, S. R., Shalini, G., Krishnaprasad, P. A., Rajawat, A. S., Girish, K. H., et al. (2012). Spit dynamics along the Central West Coast of India: implications for coastal zone management. J. Coastal Research, 28(2), 505–510.

    Google Scholar 

  41. Hithin, N. K., Remya, P. G., Balakrishna Nair, T. M., Harikumar, R., Kumar, Raj, & Nayak, S. (2015). Validation and intercomparison of SARAL/ALTIKA and PISTACH-derived coastal wave heights using in situ measurements. IEEE Journal Selected Topics in Applied Earth Science Observations and Remote Sensing. https://doi.org/10.1109/jstars.2015.2418251.

    Article  Google Scholar 

  42. IMD. (2014). INSAT 3D Products Catalougue. New Delhi: India Meteorological Department.

    Google Scholar 

  43. Indira Rani, S., & Das Gupta, M. (2013). Oceansat-2 and RAMAbuoy winds: A comparison. Journal of Earth System Science, 122(6), 1571–1582.

    Google Scholar 

  44. Indira Rani, S., Das Gupta, M., Sharma, P., & Prasad, V. S. (2014). Inter-comparison of Oceansat-2 and ASCAT winds with in situ buoy observations and short-term numerical forecasts. Atmosphere-Ocean, 52(1), 92–102. https://doi.org/10.1080/07055900.2013.869191.

    Article  Google Scholar 

  45. Indira Rani, S., Taylor, R., Sharma, P., & Bushair, M. T. (2019). Assimilation of INSAT 3D Imager water vapour clear sky brightness temperature in the NCMRWF’s assimilation and forecast system. Journal of Earth System Science, 128, 197. https://doi.org/10.1007/s12040-019-1230-6.

    Article  Google Scholar 

  46. Jain, V., & Sinha, R. (2008). Geomorphological manifestations of the flood hazard: A remote sensing-based approach. J. Geocarto International, 18(4), 51–60. https://doi.org/10.1080/10106040308542289.

    Article  Google Scholar 

  47. Jaiswal, R. K., Mukerjee, S., Krishnamurthy, J., & Saxena, R. (2003). Role of Remote Sensing and GIS techniques for generation of ground water prospect zones towards rural development—An approach. International Journal of Remote Sensing, 24, 993–1008.

    Google Scholar 

  48. Jha, C. S., Thumaty, K. C., Rodda, S. R., Sonakia, A., & Dadhwa, V. K. (2013). Analysis of carbon dioxide, water vapour and energy fluxes over an Indian teak mixed deciduous forest for winter and summer months using eddy covariant technique. Journal of Earth System Science, 122(5), 1259–1268.

    Google Scholar 

  49. Johny, C. J., & Prasad, V. S. (2014). Impact of assimilation of Meghatropique ROSA radio occultation refractivity by observing system simulation experiment. Current Science, 106(9), 1297–1305.

    Google Scholar 

  50. Johny, C. J., Singh, S. S., & Prasad, V. S. (2019). Validation and impact of SCATSAT-1 scatterometer winds. Pure and Applied Geophysics. https://doi.org/10.1007/s00024-019-02096-5.

    Article  Google Scholar 

  51. Joseph, G. (2016). India’s journey towards excellence in building earth observation cameras (p. 173p). Chennai: Notion Press.

    Google Scholar 

  52. Kelkar, R. R. (2019). Satellite meteorology in India: Its beginning, growth and future. Mausam, 70(1), 1–14.

    Google Scholar 

  53. Kelkar, R. R., & Rao, A. V. R. K. (1990). Interannual variability of monsoon rainfall as estimated from INSAT 1B Data. Mausam, 41, 183–188.

    Google Scholar 

  54. Khan, S. D., & Mahmood, K. (2008). The application of remote sensing techniques to study ophiolites. Earth Science Reviews, 89(3–4), 135–143. https://doi.org/10.1016/j.earscirev.2008.04.004.

    Article  Google Scholar 

  55. Kishtawal, C. M. (2019). Use of satellite observations for weather prediction. Mausam, 70(4), 709–724.

    Google Scholar 

  56. Kishtawal, C. M., Deb, S. K., Pal, P. K., & Joshi, P. C. (2009). Estimation of atmospheric motion vectors from Kalpana-1 imagers. Journal of Applied Meteorology and Climatology, 48(11), 2410–2421.

    Google Scholar 

  57. Krishnanunni, K. (1983). Geological applications of remote sensing and prospects. Journal of the Indian Society of Photo-interpretation and Remote Sensing, 11, 7–14.

    Google Scholar 

  58. Kulkarni, A. V. (1991). Glacier inventory in Himachal Pradesh using satellite images. Journal of the Indian Society of Remote Sensing, 19(3), 195–203.

    Google Scholar 

  59. Kulkarni, A. V. (1992). Mass balance of Himalayan glaciers using AAR and ELA Methods. Journal of Glaciology, 38(128), 101–104.

    Google Scholar 

  60. Kulkarni, A. V., Bahuguna, I. M., Rathore, B. P., Singh, S. K., Randhuwa, S. S., Sood, R. K., et al. (2007). Glacial retreat in Himalaya using Indian Remote Sensing Satellite Data. Current Science, 9(1), 69–74.

    Google Scholar 

  61. Kulkarni, A. V., & Karyakarte, Y. (2014). Observed changes in Himalayan glaciers. Current Science, 106(2), 237–244.

    Google Scholar 

  62. Kulkarni, A. V., Nayak, S., & Pratibha, S. (2017). Variability of glaciers and snow cover in observed climate variability and change over the Indian Region, In M. Rajeevan, & S. Nayak, (Eds.), Springer geology (pp. 193–217). https://doi.org/10.1007/978-981-10-2531-0-12.

  63. Kulkarni, A. V., Randhava, S. S., Rathore, B. P., Bahuguna, I. M., & Sood, R. K. (2002). Snow and glacier melt runoff model to estimate hydropower potential. Journal of Indian Society of Remote Sensing, 30(4), 220–228.

    Google Scholar 

  64. Kulkarni, A. V., & Rathore, B. P. (2003). Snow cover monitoring in Baspa basin using IRS WiFS data. Mausam, 54(1), 335–340.

    Google Scholar 

  65. Kulkarni, A. V., Rathore, B. P., & Alex, S. (2004). Monitoring of glacial mass balance in the Basra basin using accumulation area method. Current Science, 86(1), 185–190.

    Google Scholar 

  66. Kulkarni, A. V., Rathore, B. P., Singh, S. K., & Bahuguna, I. M. (2011). Understanding changes in cryosphere using remote Sensing techniques. International Journal of Remote Sensing, 32(3), 601–615. https://doi.org/10.1080/01431161.2010.517802.

    Article  Google Scholar 

  67. Kulkarni, A. V., Singh, S. K., Mathur, P., & Mishraji, V. D. (2006). Algorithm to monitor tor snow cover using AWiFs data of Resourcesat -1 for the Himalayan region. International Journal of Remote Sensing, 27(12), 2449–2457.

    Google Scholar 

  68. Kumar, P., & Kishtawal, C. M. (2017). Importance of satellite-derived retrieved rain/no rain information on short range weather predictions. International Journal of Remote Sensing, 38(13), 3851–3864. https://doi.org/10.1080/01431161.2017.1306140.

    Article  Google Scholar 

  69. Kumar, P., Kishtawal, C. M., & Pal, P. K. (2014). Impact of satellite rainfall assimilation on weather research and forecasting model predictions over Indian region. Journal of Geophysics Researcher, 119(5), 2017–2031.

    Google Scholar 

  70. Kumar, P., Kumar, K. H., & Pal, P. K. (2012). Impact of Oceansat-2 scattometer winds and TMI observations on Phet cyclone simulation. IEEE Transactions on Geoscience and Remote Sensing, 51(6), 3774–3779.

    Google Scholar 

  71. Kumar, T. S., Mahendra, R. S., Nayak, S., Radhakrishna, K., & Sahu, K. C. (2010). Coastal vulnerability assessment for Orissa State, East Coast of India. Journal of Coastal Research, 26(3), 523–534.

    Google Scholar 

  72. Kumar, K. V., Martha, T. S., & Roy, P. S. (2006). Detection of volcanic eruption in Barren Island using IRS P6 AWiFs data. Current Science, 91(6), 752.

    Google Scholar 

  73. Kumar, P., & Varma, A. K. (2016). Assimilation of INSAT 3D Hydroestimator method retrieved rainfall for short range weather prediction. Quarterly Journal of the Royal Meteorological Society, 143(702), 384–394. https://doi.org/10.1002/qj.2929.

    Article  Google Scholar 

  74. Kumari, Beena, & Raman, M. (2010). Whale shark habitat assessment in northeastern Arabian Sea using satellite remote Sensing. International Journal of Remote Sensing, 31, 379–389.

    Google Scholar 

  75. Kumari, Beena, Raman, M., & Mali, K. (2009). Locating tuna forage ground through satellite remote Sensing. International Journal of Remote Sensing, 30, 5977–5988.

    Google Scholar 

  76. Kusuma, K. N., Ramakrishnan, D., & Pandalai, H. S. (2012). Spectral pathways for effective delineation of high-grade bauxites: A case study of from the Savitri River basin, Maharashtra, India using EO-1 Hyperion data. International Journal of Remote Sensing, 33(22), 7273–7290.

    Google Scholar 

  77. Lodh, A., George, G., Singh, H., George, J. P., & Rajagopal, E. N. (2019). Assimilation of INSAT 3D Land Surface Temperature in EKF based Land Data Assimilation System. Technical Report. NMRF/TR/07/2019. National Centre for Medium Range Weather Forecasting. Noida, India.

  78. Maanya, U. S., Kulkarni, A. V., Tiwari, A., Dasgupta Bhar, E., & Srinivasan, J. (2016). Identification of potential lake sites and mapping maximum extent of existing glacier lakes in Drang Drung and Samudra Tapu glaciers, Indian Himalaya. Current Science, 111(3), 553–560. https://doi.org/10.18520/CS/v111/i3/553-560.

    Article  Google Scholar 

  79. Mankad, B. M., Sharma, R., Basu, S., & Pal, P. K. (2012). Altimeter data assimilation in the tropical Indian Ocean using water property conserving scheme. Journal of Earth System Science, 121(1), 251–262.

    Google Scholar 

  80. Martha, T. R., Govindharaj, K. B., & Vinod Kumar, K. (2015). Damage and geological assessment of the 18th September 2011 Mw 6.9 earthquake in Sikkim, India using very high-resolution satellite data. Geoscience Frontiers, 6(6), 793–805. https://doi.org/10.1016/j.gsf.2013.12.011.

    Article  Google Scholar 

  81. Martha, T. R., Guha, A., Vinod Kumar, K., Kamaraju, M. V. V., & Raju, E. V. R. (2010a). Recent coal fire and land use status of Jharia coal field, India from satellite data. International Journal of Remote Sensing, 31(12), 3243–3262. https://doi.org/10.1080/01431160903159340.

    Article  Google Scholar 

  82. Martha, T. S., Kerle, N., van Jetten, Y., Westen, C. J., & Kumar, K. V. (2010b). Characteristic spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods. Geomorphology, 116(1), 24–36.

    Google Scholar 

  83. Mohapatra, M., Nayak, D. P., Sharma, M., Sharma, R. P., & Bandopadhyay, B. K. (2013). Evaluation of official tropical cyclone track forecast over North Indian Ocean issued by India Meteorological Department. Journal of Earth System Science, 122(3), 589–601.

    Google Scholar 

  84. Mohapatra, M., Nayak, D. P., Sharma, M., Sharma, R. P., & Bandopadhyay, B. K. (2015). Evaluation of official cyclone landfall forecast issued by India Meteorological Department. Journal of Earth System Science, 124(4), 861–874.

    Google Scholar 

  85. Murthy, C. S., Sesha Sai, M. V. R., Bhanu Murthy, Y., & Krishna Murthy, Y. V. (2016). Satellite remote sensing and geo-spatial technologies for crop insurance. 9th NIAS-FAIR Inter. Seminar on Agricultural Insurance, Risk Mitigation for Livelihood Security and Sustainable Development, Pune.

  86. Narain, A., Dwivedi, R. M., Solanki, H. U., Kumari, B., Chaturvedi, N., James, P. S. B. R., et al. (1990). The use of NOAA-AVHRR data in fisheries exploration in the Indian EEZ. In The Proceeding of the Seminar on Remote Sensing for Marine Fisheries Studies in Indian EEZ, Beijing, China. ESCAP/UNDP (pp. 226–232).

  87. Nayak, S. (2009). Application of remote sensing and GIS for coastal zone management. In M. Madden (Ed.), The manual of geographic information systems (pp. 1075–1093). Bethesda: The American Society for Photogrammetry and Remote Sensing.

    Google Scholar 

  88. Nayak, S. (2017). Coastal zone management in India—Present status and future needs. Geo-spatial Information Science. https://doi.org/10.1080/10095020.2017.1333715.

    Article  Google Scholar 

  89. Nayak, S., & Bahuguna, A. (2008). Application of remote sensing for damage assessment of coastal ecosystems in India Due to December 2004 Tsunami. In S. Nayak & S. Zlatanova (Eds.), Remote sensing and GIS technologies for monitoring and prediction of disasters (pp. 37–56). Berlin: Springer.

    Google Scholar 

  90. Nayak, S., Bahuguna, A., Deshmukh, B., Shah, D. G., Rao, R. S., Dhargalkar, V. K., et al. (2003b). Eco-morphological zonation of Selected Coral Reefs of India using Remotely Sensed Data. Scientific Note. Space Applications Centre, Ahmedabad. SAC/RESIPA/MWRG/MSCED/SN/16/2003.

  91. Nayak, S., Bahuguna, A., Shah, D. G., Dhargalkar, V. K., Jagtap, T.G., Komarpant, D. S., et al. (2003a). Community zonation of Selected Mangrove Habitats of India using Satellite Data. Scientific Note, Space Applications Centre, Ahmedabad. SAC/RESA/MWRG/MSCED/SN/17/2003.

  92. Nayak, S., Bahuguna, A., Shaikh, M., Chauhan, H. B., Rao, R. S., Arya, A., Aggarwal, J. P., et al. (1992). Coastal Environment. Scientific Note. Space Applications Centre, Ahmedabad. RSAM/SAC/COM/SN/11/92.

  93. Nayak, S., Bahuguna, A., Shaikh, M., Rao, R. S., Trivedi, C. R., Prasad, K. N., Kadri, S. A., et al. (1991). Manual for Mapping of Coastal Wetlands/landforms and Shoreline Changes Using Satellite Data. Technical Note. IRS-UP/SAC/MCE//SN/32/91. Space Applications Centre, Ahmedabad, India

  94. Nayak, S., Chauhan, P., Bahuguna, A., & Nath, A. N. (1996). IRS-1C applications for coastal zone management. Current Science, 70(7), 614–618.

    Google Scholar 

  95. Nayak, S. R., Hegde, V. S., Shalini, R., Rajawat, A. S., Ali, M., Venkateshwrlu, B., et al. (2012). Application of satellite remote sensing for investigation of sediment dispersion pattern in the Near Shore Region: A Case Study from the Central West Coast of India. Journal of Coastal Research, 28(2), 399–406.

    Google Scholar 

  96. Nayak, S. R., Hegde, V. S., Shalini, G., Rajawat, A. S., Girish, K. H., Jayakumar, S., et al. (2010). Geomorphic processes in the vicinity of the Venkatapur River Mouth, Central West Coast of India: Implications for Estuarine Sedimentation. Journal of Coastal Research, 26(5), 925–934.

    Google Scholar 

  97. Nayak, S., & Kumar, T. S. (2011). Tsunami watch and warning centres. In H. K. Gupta (Ed.), Encyclopedia of solid earth geophysics (Vol. 2, pp. 1498–1505). Dordrecht: Springer.

    Google Scholar 

  98. Nayak, S., Kumar, T. S., & Rama Rao, E. P. (2020). Tsunami watch and warning centers. In H. K. Gupta (Ed.), Encyclopedia of solid earth geophysics. Encyclopedia of Earth Science Series. https://doi.org/10.1007/978-3-030-10475-7_230-1.

  99. Nayak, S., Raman, M., & Bahuguna, A. (2007). Remote Sensing for marine algae. In A. Tiwari (Ed.), Monograph on Recent Advances on Applied Aspects of Indian Marine Algae with reference to Global scenario (Vol. 2, pp. 1–20). New Delhi: CSIR Press.

    Google Scholar 

  100. Nayak, S. R., & Sahai, B. (1985). Coastal morphology: A case study in the Gulf of Khambhat (Cambay). International Journal of Remote Sensing, 6(3&4), 559–567.

    Google Scholar 

  101. Nayak, S., Sarangi, R. K., & Rajawat, A. S. (2001). Application of IRS-P4 OCM data to study the impact of cyclone on coastal environment of Orissa. Current Science, 80(9), 1208–1213.

    Google Scholar 

  102. NCAER. (2010). Impact assessment and economic benefits of weather and marine services. New Delhi: National Council of Applied Economic Research.

    Google Scholar 

  103. NCAER. (2015). Economic Benefits of Dynamic Weather and Ocean Information and Advisory Services in India and Coast and Pricing of Customized Products of ESSO-NCMRWF and ESSO-INCOIS. New Delhi: National Council of Applied Economic Research.

    Google Scholar 

  104. Oza, S. R., Singh, R. P., Dadhwal, V. K., & Desai, P. S. (2006). Large area soil moisture estimation using space borne multifrequency passive microwave data. Journal of Indian Society of Remote Sensing, 34, 343–350.

    Google Scholar 

  105. Pal, P. K., Varma, A. K., & Gairola, R. M. (2013). Rainfall estimation using satellite data. NNRMS Bulletin, 38, 11–12.

    Google Scholar 

  106. Panigrahy, S., Chakroborty, M., Sharma, S. A., Kundu, N., Ghose, S. C., & Pal, M. (1997). Early estimation of rice area using temporal ERS-1 synthetic aperture radar data a case study for the Howrah and Hughly districts of West Bengal, India. International Journal Remote Sensing, 18(8), 1827–1833. https://doi.org/10.1080/014311697218133.

    Article  Google Scholar 

  107. Panigrahy, S., Manjunath, K. R., Chakraborty, M., Kundu, N., & Parihar, J. S. (1999). Evaluation of RADARSAT standard beam data for identification of potato and rice crops in India. ISPRS Journal of Phtogrammetry and Remote Sensing, 54, 254–262.

    Google Scholar 

  108. Papa, F., Bala, S. K., Pandey, R. K., Durand, V. V., Gopalkrishna, V. V., et al. (2012). Ganga-Brahmaputra river discharge from Jason-2 radar altimeter: an update to long term satellite derived information of continental fresh water forcing flux into Bay of Bengal. Journal Geophysical Research, 117, C11021.

    Google Scholar 

  109. Parihar, S., Mitra, A. K., Mohapatra, M., & Bhatla, R. (2018). Potential of INSAT 3D sounder-derived total precipitable water product for weather forecast. Atmospheric Measurement Techniques, 11, 6003–6012. https://doi.org/10.5194/amt-11-6003-2018.

    Article  Google Scholar 

  110. Parihar, J. S., & Oza, M. P. (2006). FASAL: An integrated approach for crop assessment and production forecasting. In Proceedings of the Asia-Pacific remote sensing symposium, International Society for Optics and Photonics (pp. 641101–641113).

  111. Pathan, S. K., Dhinwa, P. S., Sastry, S. V. G., & Rao, M. (1993). Urban growth trend analysis using GIS techniques—A case study of the Bombay Metropolitan Region. International Journal of Remote Sensing, 14(17), 3169–3179.

    Google Scholar 

  112. Pathan, S. K., Shukla, V. K., Patel, R. G., & Mehta, K. (1991). Urban land use mapping—A case study of Ahmedabad city and its environs. Journal of Indian Society of Remote Sensing, 19(2), 95–112.

    Google Scholar 

  113. Pattabhi Rama Rao, E., Udaya Bhaskar, T. V. S., Venkat Seshu, R., Srinivas Rao, N., Suprit, K., & Geetha, G. (2018). Marine data services at National Oceanographic Data Centre-India. Data Science J., 17(17), 1–7. https://doi.org/10.5334/dsj-2018-011.

    Article  Google Scholar 

  114. Prakash, S., Mahesh, C., Gairola, R. M., & Pal, P. K. (2010). Estimation of Indian summer rainfall using Kalpana-1 VHRR data and its validation using rain gauge and COCP data. Meteorology and Atmospheric Physics, 110, 45–57.

    Google Scholar 

  115. Prakash, S., Mitra, A. K., Pai, D. S., & Kouchak, A. A. (2016). From TRMM to GPM: How well can heavy rainfall be detected from space? Advances in Water Resources, 88, 1–7.

    Google Scholar 

  116. Prasad, V. S., Gupta, A., Rajagopal, E. N., & Basu, S. (2013). Impact of Oscat surface wind data on T574l64 assimilation and forecasting system—A study involving tropical cyclone Thane. Current Science, 104(5), 627–631.

    Google Scholar 

  117. Prasad, V., Kulkarni, A. V., Srinivasulu, P., & Pratibha, S. (2019). Large losses in glacier area and water availability by the end of twenty-first century under high emission scenario, Satluj basin, Himalaya. Current Science, 116(10), 1721–1730.

    Google Scholar 

  118. Prasad, J. S., Rajawat, A. S., Pradhan, Y., Chauhan, O. S., & Nayak, S. (2002). Retrieval of sea surface velocities using sequential ocean colour monitor (OCM) Data. Journal of Earth System Science, 111(3), 189–195.

    Google Scholar 

  119. Raghu Nandan, K. R. (1995). Project Vasundhara. Notes. Journal of the Geological Society of India, 45, 111–114.

    Google Scholar 

  120. Rajani, M. B. (2016). The expanse of archeological remains at Nalanda: A study using remote sensing and GIS. Archives of Asian Art, 66, 1–23.

    Google Scholar 

  121. Rajani, M. B., & Das, S. (2018). Archeological remains at Nalanda: A spatial comparison of 19th century observations and protected world heritage site. In A. Sharma (Ed.), Records, recoveries, remnants and Inter-Asian interconnections: Decoding cultural heritage (pp. 239–256). Singapore: ISEAS.

    Google Scholar 

  122. Rajani, M. B., & Kasturirangan, K. (2011). Sea level changes and its impact on coastal archaeological monuments: Seven pagodas of Mahabalipuram. Journal of Indian Society of Remote Sensing.. https://doi.org/10.1007/s12524-013-0346-4.

    Article  Google Scholar 

  123. Rajani, M. B., & Kasturirangan, K. (2014). Multispectral remote sensing data analysis and application for detecting moats around medieval settlements in South India. Journal of Indian Society of Remote Sensing.. https://doi.org/10.1007/s12524-013-0346-4.

    Article  Google Scholar 

  124. Ramamoorthi, A. S. (1986). Forecasting snowmelt runoff of Himalayan rivers using NOAA AVHRR imageries since 1980. International Association of Hydrological Sciences Publication, 160, 341–348.

    Google Scholar 

  125. Ramesh Kumar, K., Misra, A., Pande, D., & Nanda, L. K. (2009). Uranium in lake sediments—A report on Didwana Salt Lake, Nagaur district, Rajasthan. Current Science, 97(11), 1545–1546.

    Google Scholar 

  126. Ranganath, B. K., Roy, P. S., Dutt, C. B. S., & Diwakar, P. G. (2000). Use of modern technologies and information systems for sustainable Forest management: Status Report. Bengaluru: ISRO.

    Google Scholar 

  127. Rao, D. P., et al. (1997). Integrated mission for sustainable development (IMSD), a synergistic approach towards management of land and water resources. http://www.ncap.res.in/uploadfiles/workshop/ws5_chapter9.pdf.

  128. Rao, D. P., Gautam, N. C., Nagaraja, R., & Mohan, P. R. (1996). IRS 1C applications in land use mapping and planning. Current Science, 70(7), 575–581.

    Google Scholar 

  129. Rao, A. V. R. K., Kelkar, R. R., & Armin, P. A. (1989). Estimation of precipitation and outgoing Longwave radiation from INSAT 1B radiance Data. Mausam, 40, 123–130.

    Google Scholar 

  130. Rathore, B. P., Kulkarni, A. V., & Sherasia, N. K. (2009). Understanding future changes in snow and glacier melt runoff due to global warming in Wangar Gad basin, India. Current Science, 97(7), 1077–1081.

    Google Scholar 

  131. Ravishankar, T., Sreevas, K., Ravishankar, G., Fyzee, M. A., Sujatha, G., Rajivkumar, M. R. S., et al. (2013). Land resources management and monitoring. NNRMS Bulletin, 37, 76–85.

    Google Scholar 

  132. Ray, S. S., Jain, N., Das, G., Singh, J. P., Rachna, Nair, S., et al. (2008). Use of remote sensing for precision farming. Scientific Note. SAC/RESA/AFEG/PF/SR/01/2008. Space Applications Centre, Ahmedabad, p. 60.

  133. Ray, S. S., & Neetu, S. (2017). Crop area estimation with remote sensing. In J. Delince (Ed.), Handbook on remote sensing for agricultural statistics. Quebec City: Food and Agriculture Organisation.

    Google Scholar 

  134. Ray, S. S., Sesha Sai, V. V. R., & Chattopadhyay, N. (2014). Agricultural drought assessment: Operational approaches in India with special emphasis on 2012. In K. Ray, M. Mohapatra, B. K. Bandpopadhyay, & L. S. Rathore (Eds.), High impact weather events over SAARC Region (pp. 349–364). New York: Spring.

    Google Scholar 

  135. Reddy, C. S., Jha, C. S., Diwakar, P. G., & Dadhwal, V. K. (2015). Nation-wide classification of forest types of India using remote sensing and GIS. Environment Monitor Assessment. https://doi.org/10.1007/s10661-015-4990-8.

    Article  Google Scholar 

  136. Roy, P. S., Behera, M. D., Murthy, M. S. R., Roy, A., Singh, S., Kushwaha, S. P. S., et al. (2015a). New vegetation type map of India prepared using satellite remote Sensing: Comparison with global vegetation maps and utilities. International Journal of Applied Earth Observation and Geoinformation, 39, 142–159.

    Google Scholar 

  137. Roy, P. S., Kushwaha, S. P. S., Roy, A., Karnataka, H., & Saran, S. (2012). Biodiversity characterisation at landscape level: National assessment. Dehradun: Indian Institute Remote Sensing.

    Google Scholar 

  138. Roy, P. S., Rangnath, B. K., Diwakar, P. G., Vohra, T. P. S., Bhan, S. K., Singh, I. J., et al. (1991). Tropical forest type mapping and monitoring using remote sensing. International Journal of Remote Sensing, 12(11), 2205–2225.

    Google Scholar 

  139. Roy, P. S., Roy, A., Joshi, P. K., & Kale, M. P. (2015b). Development of decadal (1985–1995–2005) land use and land cover database for India. Remote Sens., 7, 2401–2430. https://doi.org/10.3390/rs70302401.

    Article  Google Scholar 

  140. SAC. (2016). Desertification and land degradation Atlas of India. http://www.sac.gov.in/SACSITE/Desertification_Atlas_2016_SAC_ISRO.pdf.

  141. Sahai, B., Bhattacharya, A., & Hegde, V. S. (1991). IRS 1A applications for groundwater targeting. Current Science, 61(3&4), 172–179.

    Google Scholar 

  142. Sarabhai, V. (1974). Remote Sensing in the service of developing countries. In Kamala Chowdhary (Ed.), Science policy and national development—Vikram Sarabhai (pp. 66–81). Delhi: Macmillan.

    Google Scholar 

  143. Sarangi, R. K., Chauhan, P., & Nayak, S. (2001). Phytoplankton bloom monitoring in the offshore water of Northern Arabian Sea using IRS P4 OCM satellite data. Indian Journal of Marine Science, 30, 214–221.

    Google Scholar 

  144. Sathyanadh, A., Karipot, A., Ranalkar, M., & Prabha, T. V. (2016). Evaluation of soil moisture data products over Indian region and analysis of spatio-temporal characteristics with respect to monsoon rainfall. Journal of Hydrology, 542, 47–62.

    Google Scholar 

  145. Shah, H. L., & Mishra, V. (2016). Development of an experimental near real time drought monitor in India. Journal of Hydrometeorology, 17(2), 615–636.

    Google Scholar 

  146. Sharma, S., Babu, K. N., Mathur, A. K., & Ali, M. M. (2002). Identification of large-scale atmospheric and oceanic features from IRS P4 multifrequency scanning microwave radiometer on board Oceansat-1. Journal of Atmospheric and Oceanic Technology, 19, 1127–1134.

    Google Scholar 

  147. Simon, B., Joshi, P. C., Thapliyal, P. C., & Pal, P. K. (2001). Monsoon onset 2000 monitored using multi-frequency microwave radiometer on board Oceansat-1. Current Science, 81(6), 647–651.

    Google Scholar 

  148. Simon, A., & Shanmugam, P. (2012). An algorithm for classification of algal blooms using MODIS-Aqua data in oceanic waters around India. Advance Remote Sensing, 1, 35–51.

    Google Scholar 

  149. Singh, R. P., & Gupta, P. K. (2016). Development in Remote Sensing techniques for hydrological Studies. Proc. Ind. National Science Academy, 82(3), 773–786. https://doi.org/10.16943/ptinsa/2016/48484.

    Article  Google Scholar 

  150. Singh, R., Kumar, P., & Pal, P. K. (2011). Assimilation of Oceansat-2scatterometer- derived surface winds in the weather research and forecasting model. IEEE Transactions on Geoscience and Remote Sensing, 50(4), 1015–1021.

    Google Scholar 

  151. Singh, R., Ojha, S. P., Kishtawal, C. M., & Pal, P. K. (2013). Quality assessment and assimilation of MEGHATROPIQUE SAPHIR radiance into WRF assimilation System. Journal of Geophysical Research: Atmosphere, 118(13), 6957–6969.

    Google Scholar 

  152. Singh, R., Ojha, S. P., Kishtawal, C. M., & Pal, P. K. (2014). Impact of various observing systems on weather analysis and forecast over the Indian region. Journal of Geophysical Research: Atmosphere, 119(17), 10232–10246.

    Google Scholar 

  153. Singh, R., Ojha, S. P., Kishtawal, C. M., Pal, P. K., & Kiran Kumar, A. S. (2016). Impact of the assimilation of INSAT 3D radiances on short-range weather forecast. Quarterly Journal of the Royal Meteorological Society, 142, 120–131. https://doi.org/10.1002/go.2636.

    Article  Google Scholar 

  154. Singh, S. S., & Prasad, V. S. (2017). Impact of Megha-Tropiques SAPHIR radiances in T574L64 global data assimilation and forecasting system at NCMRWF. International Journal of Remote Sensing, 38(16), 4587–4610. https://doi.org/10.1080/01431161.2017.1323279.

    Article  Google Scholar 

  155. Singh, A. K., Singh, V., Singh, K. K., Tripathi, J. N., Kumar, A., Sateesh, M., et al. (2018). Validation of INSAT 3D derived rainfall estimates (HE & IMSRA), GPM (IMERG) and GLDAS2.1 model rainfall product with IMD gridded rainfall & NMSG Data over IMD’s meteorological subdivisions during monsoon. Mausam, 69, 177–192.

    Google Scholar 

  156. Solanki, H. U., Dwivedi, R. M., & Nayak, S. (1998). Relationship between IRS MOS-B derived chlorophyll and NOAA AVRR SST: a case study in the NW Arabian Sea, India. In Proceedings of the 2nd International Workshop on MOS-IRS and Ocean Colour (pp. 438–442). Institute of Space Technology, Berlin.

  157. Sreejith, K. M., Agrawal, R., & Rajawat, A. S. (2016). Crystal deformation Studies using Synthetic Aperture Interferometry. Proceedings of the Indian National Science Academy, 82(3), 737–746. https://doi.org/10.16943/pitsaid/2016/48481.

    Article  Google Scholar 

  158. Srivastav, S. K., Bhattacharya, A., Kamaraju, M. V. V., & Sreenivasa Reddy, G. (2000). Remote Sensing and GIS for locating favourable zones of land-zinc-copper mineralisation in Rajpura-Dariba area, Rajasthan, India. International Journal of Remote Sensing, 21(7), 3253–3267.

    Google Scholar 

  159. Thenkabail, P. S., Mitchell, S., & Turral, H. (2005). Ganges and Indus River basin landuse/landcover (LULC) and irrigated area mapping using continuous stream of MODIS data. Remote Sensing of Environment, 95, 317–341.

    Google Scholar 

  160. Tiwari, V. M., & Srinivas, N. (2019). Satellite observations of terrestrial water. In Water resources of Indiastatus of science and technology (pp. 145–180). Indian National Science Academy.

  161. Tiwari, V. M., Wahr, J., & Swenson, S. (2009). Dwindling groundwater resources in northern India from satellite gravity observations. Geophysical Research Letters, 36, L18401.

    Google Scholar 

  162. Tiwari, V. M., Wahr, J. M., Swenson, S., & Singh, B. (2011). Land water storage variation over Southern India from space gravimetry. Current Science, 101(4), 536–540.

    Google Scholar 

  163. Tripathi, P., Behera, M. D., & Roy, P. S. (2019). Spatial heterogeneity of climate explains plant richness distribution at the regional scale in India. PLoS ONE, 14(6), 0218322. https://doi.org/10.1371/journal.pone.0218322.

    Article  Google Scholar 

  164. Tyagi, A., Sikkiam, D. R., Goyal, S., & Bhowmick, M. (2012). A satellite-based study of pre-monsoon thunderstorms (Nor’westers) over eastern India and their organisation into mesoscale convective complexes. Mausam, 63, 29–54.

    Google Scholar 

  165. Velloth, S., Mupparthy, R. S., Raghavan, B. R., & Nayak, S. (2014). Coupled correction and classification of hyperspectral imagery for mapping coral reefs of Agatti and Flat Islands, India. International Journal of Remote Sensing, 35(14), 5544–5561.

    Google Scholar 

  166. Venkateshwar Rao, V., Sharma, J. R., & Dadhwal, V. K. (2013). Water resources of India—critical issues and satellite technology option. NNRMS Bulletin, 38, 1–9.

    Google Scholar 

  167. Verma, A. K. (2018). Measurements of precipitation from satellite radiometers (Visible, Infrared and microwave): Physical basis, Methods and Limitation. Remote Sensing of Aerosols, Clouds and Precipitation (pp. 223–248). Amsterdam: Elsevier.

    Google Scholar 

  168. Yadav, R., Puviarasan, N., Giri, R. K., Tomar, C. S., & Singh, V. (2020). Comparison of GNSS and INSAT 3D sounder retrieved precipitable water vapour and validation with GPS sonde data over Indian sub-continent. Mausam, 71(1), 1–10.

    Google Scholar 

Download references

Acknowledgements

I am extremely indebted to Dr. George Joseph, ISRO Honorary Professor, who encouraged me to convert my presidential address at IGU into a review article, and for also evaluating the manuscript. My grateful thanks to Dr. A. S. Kiran Kumar, Vikram Sarabhai Distinguished Professor, ISRO, for giving me an opportunity to Chair Vikram Sarabhai Centenary Celebration Committee which led to me to read about Dr. Sarabhai. Shri Pramod Kale, former director, SAC-ISRO, who narrated his early discussions with Dr Sarabhai about remote sensing development in the country, and Dr. Kartikeya Sarabhai, Director, Centre for Environment Education, who provided text of Dr. Sarabhai's presidential address at 8th IGU Annual Convention, are thankfully acknowledged. My sincere gratitude to Dr. V. S. Hegde, Satish Dhawan Professor, ISRO, and Dr. A. Senthil Kumar, Professor, Kongu Engineering College, Erode, for meticulously going through the manuscript and making very useful comments. Thanks are due to Dr. M. Mohapatra, Director General, ESSO-IMD, Dr. E. N. Rajagopal, Director, ESSO-NCMRWF, Dr. M. Ravichandran, Director, ESSO-NCPOR, Dr. P. S. Roy, Hyderabad University, Dr. A. V. Kulkarni, Divecha Centre for Climate Change, IISc, Dr. Prakash Chauhan, Director, IIRS-ISRO, Dr. Raj Kumar, Deputy Director, SAC-ISRO, Dr. Shibendu Ray, Director, MNCFC, and Prof. D. Ramakrishnan, IIT, Bombay, for useful discussions and Ms V. B. Mariyammal, NIAS, for supporting in preparing the manuscript.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Shailesh Nayak.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Based on the presidential address delivered at the 55th annual convention, Indian Geophysical Union, Bhopal, 2018.

About this article

Verify currency and authenticity via CrossMark

Cite this article

Nayak, S. Remote Sensing for National Development: The Legacy of Dr. Vikram Sarabhai. J Indian Soc Remote Sens 48, 1101–1120 (2020). https://doi.org/10.1007/s12524-020-01156-x

Download citation

Keywords

  • Remote sensing
  • Applications
  • Services
  • Societal benefits
  • National system