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Remote sensing-based assessment of impact of Phailin cyclone on rice in Odisha, India

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Abstract

Assessing the nature and extent of damage due to natural calamities remains one of the thrust areas in monitoring resource inventory through remote sensing. The effect of the cyclone Phailin and the post-incessant rains during second fortnight of October 2013 on coastal Odisha was studied in terms of rice area flooded, submerged and damaged. Multi-temporal SAR data were analysed to obtain the rice mask, and from this rice mask, the flood affected rice area was determined. Taluka-wise and district-wise crop loss proportion was estimated, and the overall production loss has been estimated. SAR data aided in delineation of flooded regions, while AWiFS NDVI data of subsequent dates showed both continued inundation and crop vigour status post-flood time period. The ground truth indicated that a major portion of the inundated region was not rice but was typha grasses and harvested rice field which should not be accounted as damage to rice crop. The damage on crop yield was difficult to assess; however, the inundation of the crop at panicle initiation and flowering would have impact on grain filling (results in chaffiness) and was considered as completely damaged. Most of the current inundated rice regions fall in this category. It was estimated that a total of 0.167 million hectares and 0.37 million tons of rice crop was lost in the cyclone and floods. The district-level percentage area of rice flooded was communicated to State Remote Sensing Centre in four days timeframe. The overall accuracy obtained for the validation of the ground truth sites was 91.5 %.

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References

  • Boschetti M, Stroppiana D, Brivio PA, Bocchi S (2009) Multi-year monitoring of rice crop phenology through time series analysis of MODIS images. Int J Remote Sens 30:4643–4662

    Article  Google Scholar 

  • Bouman BAM (1995) Crop Modelling and remote sensing for yield prediction. Netherlands J Agric Sci 43:143–161

    Google Scholar 

  • Casanova D, Epema GF, Goudriaan J (1998) Monitoring rice reflectance at field level for estimating biomass and LAI. Field Crop Res 55:83–92

    Article  Google Scholar 

  • Chakraborty M, Panigrahy S (2000) A processing and software system for rice crop inventory using multi-date RADARSAT ScanSAR data. ISPRS J Photogramm Remote Sens 55:119–128

    Article  Google Scholar 

  • Chakraborty M, Panigrahy S, Sharma SA (1997) Discrimination of rice crop grown under different cultural practices using temporal ERS-1 synthetic aperture radar data. Photogramm Remote Sens 52:183–191

    Article  Google Scholar 

  • Chang KW, Shen Y, Lo JC (2005) Predicting rice yield using canopy reflectance measured at booting stage. Agronomy J 97:872–878

    Article  Google Scholar 

  • Chen C, McNairn H (2006) A neural network integrated approach for rice crop monitoring. Int J Remote Sens 27:1367–1393

    Article  Google Scholar 

  • Choudhary I, Chakraborty M, Santra SC, Parihar JS (2012) Methodology to classify rice cultural types based on water regimes using multi-temporal RADARSAT-1 data. Int J Remote Sens 33(13):4135–4160

    Article  Google Scholar 

  • Fairhurst T, Dobermann A (2002) Rice in the Global Food Supply. Better Crops International 16(Special Supplement):3–6

    Google Scholar 

  • FAO (2004a) International Year of Rice, Rice and Environment. http://www.fao.org/rice2004/en/rice4.htm. Accessed 27 June 2012

  • FAO (2004b) International year of rice, rice and us. http://www.fao.org/rice2004/en/rice-us.htm. Accessed 27 June 2012

  • Inoue Y, Penuelas Y, Miyata A, Mano M (2008a) Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice. Remote Sens Environ 112:156–172

    Article  Google Scholar 

  • Inoue Y, Penuelas Y, Miyata A, Mano M (2008b) Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice. Remote Sens Environ 112:156–172

    Article  Google Scholar 

  • Kurosu T, Fujita M, Chiba K (1995) Monitoring of rice crop growth from space using the ERS-1 C-Band SAR. IEEE Trans Geosci Remote Sens 33:1092–1096

    Article  Google Scholar 

  • Kurosu T, Fujita M, Chiba K (1997) The identification of rice fields using multi-temporal ERS-1 C Band SAR data. Int J Remote Sens 18:2953–2965

    Article  Google Scholar 

  • Lam-Dao N, Apan A, Young F, Le-Van T, Le-Toan T, Bouvet A (2007) Rice monitoring using ENVISAT ASAR data: preliminary results of a case study in the Mekong river delta, Vietnam. 28th Asian Conference on Remote Sensing, November 12–16, Kuala Lumpur, Malaysia

  • Lim K-S, Tan C-P, Koay J-Y, Koo V-C, Ewe H-T, Lo Y-C, Ali A (2007) Multitemporal C B and radar measurement on rice fields Progress in Electromagnetics Research Symposium, Beijing, China, March 26–30, 36–39 PIERS. Eelectromagnetics Academy, Cambridge

  • Lim K-S, Koo V-C, Ewe H-T (2008) Multi-angular scatterometer measurements for various stages of rice growth. Progr Electromagn Res 83:385–396

    Article  Google Scholar 

  • Panigrahy S, Chakraborty M, Manjunath KR, Kundu N, Parihar JS (1998) Evaluation of RADARSAT Standard beam shallow and steep angle data for rice crop monitoring in India. Proc ADRO Final Symposium, Montreal, pp 13–15

    Google Scholar 

  • Patel NK, Medhavy TT, Patnaik C, Hussain A (1995) Multi temporal ERS-1 SAR data for identification of rice crop. J Indian Soc Remote Sens 23:33–39

    Article  Google Scholar 

  • Xue L-H, Cao W, Luo W, Dai T, Zhu Y (2004) Monitoring leaf nitrogen status in rice with canopy spectral reflectance. Agronomy J 96:135–142

    Article  Google Scholar 

  • Xue L-H, Cao W-X, Luo W-H, Yang L-Z (2005) Canopy spectral reflectance characteristics of rice with different cultural practices and their fuzzy cluster analysis. RiceScience 12:57–62

    Google Scholar 

  • Yang CM, Chen RK (2004) Modeling rice growth with hyperspectral reflectance data. Crop Sci Soc Am 44:1283–1290

    Article  Google Scholar 

  • Yang CM, Cheng CH (2001) Spectral characteristics of rice plants infested by brown planthoppers. Proc Natl Sci Council 25:180–186

    CAS  Google Scholar 

  • Yang CM, Cheng CH, Chen RK (2007) Changes in spectral characteristics of rice canopy infested with brown planthopper and leaffolder. Crop Sci 47:329–335

    Article  CAS  Google Scholar 

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Acknowledgement

The authors are highly grateful to Shri. Kiran Kumar, Chairman ISRO, Shri Tapan Misra, Director, SAC, Dr. P.K. Pal, Deputy Director, EPSA and Dr. J.S. Parihar, former Deputy Director, EPSA, Dr. Manab Chakraborty, former Group Director, GSAG/EPSA for their consistent encouragement in carrying out this study. Authors also duly acknowledge Shri K.R. Manjunath for the support provided in ground data collection and data analysis. Help provided during the analysis by Dr. S.S. Ray, Director, MNCFC, Mr. Suresh Singh, Project Scientist, MNCFC, New Delhi, Ms. V. Jain, former JRF, SAC, Shri S. Vyas, former JRF, SAC, Ms. S. Kundu, JRF, SAC, Shri. A.K. Mahapatra, Chief Executive, ORSAC, S.C. Maharana, A Kanungo, Scientists, ORSAC, Bhubaneshwar are duly acknowledged.

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Correspondence to Dipanwita Haldar.

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Haldar, D., Nigam, R., Patnaik, C. et al. Remote sensing-based assessment of impact of Phailin cyclone on rice in Odisha, India. Paddy Water Environ 14, 451–461 (2016). https://doi.org/10.1007/s10333-015-0514-y

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  • DOI: https://doi.org/10.1007/s10333-015-0514-y

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