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Assessment of paddy performance under BGREI initiative using RISAT SAR data

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Abstract

Bringing Green Revolution in Eastern India (BGREI) is a large-scale Department of Agriculture and Co-operation, Ministry of Agriculture (MoA), Government of India funded project with the aim to increase crop productivity through improved package of practices in low-productivity zones of eastern India. Assessment of the BGREI plots with respect to crop vigour variability using space-based observations was planned for 2011–2014 years. A new approach based on Synthetic Aperture Radar (SAR) data was used to assess the rice crop growth pattern and crop vigour. A methodology was developed to evaluate the effect of BGREI programme in the state of Odisha, India. The peak green biomass estimated from SAR data was found to be 10–30% higher in BGREI plots compared to the controlled plots during 2012–2013 and 2013–2014. The improvement was higher in traditionally low productive rainfed zones in coastal and southern Odisha as compared to the irrigated tracts of the northern plateau. Uniformity in growth in terms of growth rate, transplantation time and duration was observed in BGREI plots in both the years, but magnitude was found to be higher in 2012–2013. The impact of the BGREI programme in Odisha indicates that the scheme proved to be a breakthrough in improving rice productivity in low-productivity pockets of eastern India and the SAR-based methodology was able to pickup this with high accuracy.

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References

  • Aschbacher J, Pongsrihadulchai A, Karnchanasutham S, Rodprom C, Paudya DR, Le Toan T (1995) Assessment of ERS-1 SAR data for rice crop mapping and monitoring. IEEE T Geosci Remote GE-23:2183–2185

    Google Scholar 

  • Chakraborty M (2002) Manual of procedures for rice crop monitoring using SAR Data, for ESCAP/SAC (ISRO) regional seminar and group training on capacity building for monitoring and assessment of rice crop in the ESCAP, ISRO/EOS/M/01/02, p 47

  • Chakraborty M, Manjunath KR, Panigrahy S, Kundu N, Parihar JS (2005) Rice crop parameter retrieval using multi-temporal, multi-incidence angle Radarsat SAR data. ISPRS J Photogramm 59:310–322

    Article  Google Scholar 

  • Chakraborty M, Panigrahy S, Rajawat AS, Kumar R, Murthy TVR, Haldar D, Chakraborty A, Kumar T, Rode S, Kumar H, Mahapatra M, Kundu S (2013) Initial results using RISAT-1 C-band SAR data. Curr Sci 104(4):490–501

    Google Scholar 

  • Chakraborty M, Patnaik C, Haldar D, Jain V (2014) Kharif rice biomass and grain yield estimation. 2013 and 2014. RISAT-UP project closure document

  • Foody GM, Curran P, Groom GB, Munro DC (1989) Multi-temporal airborne synthetic aperture radar data for crop classification. Geocarto Int 4:19–29

    Article  Google Scholar 

  • Haldar D, Patnaik C, Mohan S, Chakraborty M (2010) Rice crop identification using dual- polarization C-band data. Presented in international conference on microwave, antenna, propagation and remote sensing (ICMARS) held at Jodhpur during 14–17 Dec 2010

  • Haldar D, Chakraborty M, Jain V, Parihar JS (2013) BGREI paddy monitoring status in Orissa- comparative evaluation of 2011 and 2012. SAC/EPSA/FASAL- R&D/ATDG/SR/01/2013

  • Haldar D, Das A, Yadav M, Hooda RS, Mohan S, Chakraborty M (2014a) Analysis of temporal polarization phase difference for major crops in India. Prog Electromagn Res (PIER B) 57:299–3094

    Article  Google Scholar 

  • Haldar D, Manjunath KR, Panigrahy S, Jain V, Gopalan RS, Khullar M, Chakraborty M, Parihar JS (2014b) Monsoon paddy monitoring and assessment using synthetic aperture radar data under BGREI programme in Odisha, India. Paddy Water Environ. http://link.springer.com/article/10.1007/s10333-014-0452-0

  • Hoogeboom P (1983) Classification of agricultural crops in radar images. IEEE Trans Geosci Remote Sens GE-23:329–336

    Article  Google Scholar 

  • Inoue Y, Sakaiya E (2013) Relationship between X-band backscattering coefficients from high resolution satellite SAR and biophysical variables in paddy rice. Remote Sens Lett 4(3):288–295

    Article  Google Scholar 

  • Kuenzer C, Knauer K (2013) Review article. Remote sensing of rice crop areas. Int J Remote Sens 34(6):2101–2139

    Article  Google Scholar 

  • Kuroso T, Suitz M, Fujita K, Chiba, Moriya T (1993) Rice crop monitoring with ERS-1 SAR—a first year result. In: Proceedings of 2nd ERS-1 Symposium, , Hamburg, Germany, October 11–14, ESA SP-361, vol 1, pp 97–102

  • Le Toan T, Ribbes F, Floury N, Wang L, Kong JA, Kurosu T, Fujita M (1997) Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results. IEEE Trans Geosci Remote Sens 35(1):41–56

    Article  Google Scholar 

  • McNairn H, Decker V, Murnaghan K (2002) The sensitivity of C-band polarimetric SAR to crop condition. In: IEEE international geoscience and remote sensing symposium 0-7803-7536-X, pp 1471–1473.s4

  • Panigrahy S, Chakraborty M, Sharma SA, Kundu N, Ghose SC, Pal M (1997) Early estimation of rice acreage using temporal ERS-1 synthetic aperture radar data—a case study for Howrah and Hughly districts of West Bengal, India. Int J Remote Sens 18:1827–1833

    Article  Google Scholar 

  • Panigrahy S, Manjunath KR, Chakraborty M, Kundu N, Parihar JS (1999) Evaluation of RADARSAT standard beam data for identification of potato and rice crops in India. ISPRS J Photogramm 54(4):254–262

    Article  Google Scholar 

  • Parihar JS, Panigrahy S, Chakraborty M (1997) ADRO document. Paddy rice monitoring with Radarsat 1

  • Premlatha M, Nageshwara Rao PP (1994) Crop acreage estimation using ERS-1 SAR data. J Indian Soc Remote Sens 22:139–147

    Article  Google Scholar 

  • Wang C, Wu J, Zhang Y, Pan G, Qi J, Salas WA (2009) Characterizing L-band scattering of paddy rice in southeast China with radiative transfer model and multitemporal ALOS/PALSAR imagery. IEEE Trans Geosci Remote Sens 47(4):988–998. doi:10.1109/TGRS.2008.2008309

    Article  Google Scholar 

  • Zhang Y, Wang C, Zhang Q (2011) Identifying paddy fields with dual-polarization ALOS/PALSAR data. Can J Remote Sens 37(1):103–111

    Article  Google Scholar 

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Acknowledgements

The authors are grateful to Shri Tapan Misra, Director SAC, for his support and encouragement. The authors are also grateful to Shri A.S. Kiran Kumar, then Director SAC, currently Chariman, ISRO, for his inspiration and encouragement. The authors are also grateful to Dr. Manab Chakraborty for technical guidance and Shri K.R. Manjunath for encouragement during the period of investigation. The authors are highly grateful to State Department of Agriculture, Odisha, for providing ground data and BGREI point locations. This project was a part of FASAL research activity; thus, support from MoA is duly acknowledged.

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Authors and Affiliations

  1. Building-40, Earth, Ocean, Atmosphere, Planetary Sciences and Applications Area (EPSA), Space Applications Centre, Ahmedabad, 380 015, India

    Dipanwita Haldar

  2. Department of Agriculture, Bhubaneswar, Odisha, India

    R. S. Gopalan

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  1. Dipanwita Haldar
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  2. R. S. Gopalan
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Correspondence to Dipanwita Haldar.

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Haldar, D., Gopalan, R.S. Assessment of paddy performance under BGREI initiative using RISAT SAR data. Paddy Water Environ 15, 761–771 (2017). https://doi.org/10.1007/s10333-017-0589-8

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  • DOI: https://doi.org/10.1007/s10333-017-0589-8

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