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Rice Growth Stage Monitoring and Yield Estimation in the Vietnamese Mekong Delta Using Multi-temporal Sentinel-1 Data

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Remote Sensing of Agriculture and Land Cover/Land Use Changes in South and Southeast Asian Countries

Abstract

Rice is one of the major staple food crops in the world, so monitoring rice production to support agricultural management to ensure food security is essential. Managers need important decision-making information such as regularly updated rice acreage, growth stage, and yield. This study aims to propose applying radar remote sensing data in extracting this information. Synthetic Aperture Radar (SAR) data from Sentinel-1 satellite is provided free of charge by the European Space Agency (ESA), with large coverage, high spatio-temporal resolution. It also has the advantage of observing in cloudy, foggy, and rainy weather conditions, regardless of solar radiation. Therefore, this data is suitable for monitoring rice in countries with tropical monsoon climates like Vietnam. This paper presents the results of extracting growth stage information and yield estimation of Winter-Spring rice crops in 2018 in the Mekong Delta using C-band Sentinel-1 data. The results demonstrate the utility of SAR Sentinel-1 data to monitor the distribution of rice-growing areas, the growth stage in the Mekong Delta, and the estimation of rice yield in An Giang province, the Mekong Delta.

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References

  • Bouvet, A., & Le Toan, T. (2011). Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta. Remote Sensing of Environment, 115(4), 1090–1101. https://doi.org/10.1016/j.rse.2010.12.014

    Article  Google Scholar 

  • Bouvet, A., Thuy, L. T., & Lam-Dao, N. (2009). Monitoring of the rice cropping system in the mekong delta using ENVISAT/ASAR dual polarization data. IEEE Transactions on Geoscience and Remote Sensing, 47(2), 517–526. https://doi.org/10.1109/TGRS.2008.2007963

    Article  Google Scholar 

  • Chen, C., & Mcnairn, H. (2006). A neural network integrated approach for rice crop monitoring. International Journal of Remote Sensing, 27(7), 1367–1393. https://doi.org/10.1080/01431160500421507

    Article  Google Scholar 

  • Choudhury, I., & Chakraborty, M. (2006). SAR signature investigation of rice crop using RADARSAT data. International Journal of Remote Sensing, 27(3), 519–534. https://doi.org/10.1080/01431160500239172

    Article  Google Scholar 

  • Clauss, K., et al. (2018). Estimating rice production in the Mekong Delta, Vietnam, utilizing time series of Sentinel-1 SAR data. International Journal of Applied Earth Observation and Geoinformation, 73(March), 574–585. https://doi.org/10.1016/j.jag.2018.07.022

    Article  Google Scholar 

  • GSO. (2018). General Statistics Office of Vietnam, General Statistics Office of Vietnam. Available at: https://www.gso.gov.vn/default_en.aspx?tabid=778. Accessed 4 Mar 2020.

  • Hoang-Phi, P., et al. (2020). Sentinel-1 SAR time series-based assessment of the impact of severe salinity intrusion events on spatiotemporal changes in distribution of rice planting areas in coastal provinces of the Mekong Delta, Vietnam. Remote Sensing, 12(19), 3196. https://doi.org/10.3390/rs12193196

    Article  Google Scholar 

  • Justice, C., Gutman, G., & Vadrevu, K. P. (2015). NASA land cover and land use change (LCLUC): An interdisciplinary research program. Journal of Environmental Management, 148(15), 4–9.

    Article  Google Scholar 

  • Lam-Dao, N., et al. (2012). Estimation of the rice yield in the Mekong Delta using SAR dual polarisation data. VNU Journal of Science Earth Sciences, 28(1), 20–28. Available at: https://js.vnu.edu.vn/EES/article/view/1152

    Google Scholar 

  • Lasko, K., & Vadrevu, K. (2018). Improved rice residue burning emissions estimates: Accounting for practice-specific emission factors in air pollution assessments of Vietnam. Environmental Pollution, 236, 795–806.

    Article  Google Scholar 

  • Lasko, K., Vadrevu, K. P., Tran, V. T., Ellicott, E., Nguyen, T. T., Bui, H. Q., & Justice, C. (2017). Satellites may underestimate rice residue and associated burning emissions in Vietnam. Environmental Research Letters, 12(8), 085006.

    Article  Google Scholar 

  • Lasko, K., Vadrevu, K. P., Tran, V. T., & Justice, C. (2018a). Mapping double and single crop paddy rice with Sentinel-1A at varying spatial scales and polarizations in Hanoi, Vietnam. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(2), 498–512.

    Article  Google Scholar 

  • Lasko, K., Vadrevu, K. P., & Nguyen, T. T. N. (2018b). Analysis of air pollution over Hanoi, Vietnam using multi-satellite and MERRA reanalysis datasets. PLoS One, 13(5), e0196629.

    Article  Google Scholar 

  • Le Toan, T., et al. (1997). Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results. IEEE Transactions on Geoscience and Remote Sensing, 35(1), 41–56. https://doi.org/10.1109/36.551933

    Article  Google Scholar 

  • Li, S., et al. (2016). Estimation of rice biophysical parameters using multitemporal RADARSAT-2 images. IOP Conference Series: Earth and Environmental Science, 34(1), 012019. https://doi.org/10.1088/1755-1315/34/1/012019

    Article  Google Scholar 

  • Manfron, G., et al. (2013). Application of an automatic rice mapping system to extract phenological information from time series of MODIS imagery in African environment: First results of Senegal case study. In R. Lasaponara, N. Masini, & M. Biscione (Eds.), EARSeL.

    Google Scholar 

  • Miyaoka, K., et al. (2013). Rice-planted area mapping using small sets of multi-temporal SAR data. IEEE Geoscience and Remote Sensing Letters, 10(6), 1507–1511. https://doi.org/10.1109/LGRS.2013.2261049

    Article  Google Scholar 

  • Nguyen, L. D. (2009). Rice crop monitoring using new generation Synthetic Aperture Radar (SAR) imagery. University of Southern Queensland. Available at: https://core.ac.uk/download/pdf/11039403.pdf.

  • Pazhanivelan, S., et al. (2015). Rice crop monitoring and yield estimation through COSMO Skymed and TerraSAR-X: A SAR-based experience in India. In International archives of the photogrammetry, remote sensing and spatial information sciences – ISPRS Archives. International Society for Photogrammetry and Remote Sensing, pp. 85–92. https://doi.org/10.5194/isprsarchives-XL-7-W3-85-2015.

  • Phung, H. P., & Nguyen, L. D. (2020). Rice crop monitoring in the Mekong Delta, Vietnam using multi-temporal sentinel-1 data with C-band. In J. N. Reddy et al. (Eds.), ICSCEA 2019, Lecture notes in civil engineering (Vol. 80, pp. 979–986). Springer. https://doi.org/10.1007/978-981-15-5144-4_94

    Chapter  Google Scholar 

  • Phung, H.-P., et al. (2020). 'Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data. Journal of Applied Remote Sensing, 14(01), 1. https://doi.org/10.1117/1.JRS.14.014518

    Article  Google Scholar 

  • Quegan, S., & Jiong Jiong Yu. (2001). Filtering of multichannel SAR images. IEEE Transactions on Geoscience and Remote Sensing, 39(11), 2373–2379. https://doi.org/10.1109/36.964973

    Article  Google Scholar 

  • Quegan, S., et al. (2000). Multitemporal ERS SAR analysis applied to forest mapping. IEEE Transactions on Geoscience and Remote Sensing, 38(2), 741–753. https://doi.org/10.1109/36.842003

    Article  Google Scholar 

  • Shao, Y., et al. (2001). Rice monitoring and production estimation using multitemporal RADARSAT. Remote Sensing of Environment. https://doi.org/10.1016/S0034-4257(00)00212-1

  • Shen, S., et al. (2009). A scheme for regional rice yield estimation using ENVISAT ASAR data. Science in China Series D: Earth Sciences, 52(8), 1183–1194. https://doi.org/10.1007/s11430-009-0094-z

    Article  Google Scholar 

  • Silvestro, P. C., et al. (2017). Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications. PLOS ONE, 12(11), e0187485. https://doi.org/10.1371/journal.pone.0187485

    Article  Google Scholar 

  • Small, D., & Schubert, A. (2008). Guide to ASAR Geocoding. RSL, University of Zürich.

    Google Scholar 

  • Son, N. T., et al. (2013). Prediction of rice crop yield using MODIS EVI−LAI data in the Mekong Delta, Vietnam. International Journal of Remote Sensing, 34(20), 7275–7292. https://doi.org/10.1080/01431161.2013.818258

    Article  Google Scholar 

  • Vadrevu, K., Heinimann, A., Gutman, G., & Justice, C. (2019a). Remote sensing of land use/cover changes in South and Southeast Asian Countries. International Journal of Digital Earth, 12(10), 1099–1102.

    Article  Google Scholar 

  • Vadrevu, K. P., Dadhwal, V. K., Gutman, G., & Justice, C. (2019b). Remote sensing of agriculture–South/Southeast Asia research initiative special issue. International Journal of Remote Sensing, 40(21), 8071–8075.

    Article  Google Scholar 

  • Wang, J., et al. (2015). Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS and PALSAR images. Scientific Reports, 5(1), 10088. https://doi.org/10.1038/srep10088

    Article  Google Scholar 

  • Wu, F., et al. (2011). Rice crop monitoring in South China With RADARSAT-2 quad-polarization SAR data. IEEE Geoscience and Remote Sensing Letters, 8(2), 196–200. https://doi.org/10.1109/LGRS.2010.2055830

    Article  Google Scholar 

Download references

Acknowledgments

The study has been carried out within the framework of the research project “Applied research on optical and radar remote sensing data for rice planted area monitoring and rice yield and production estimation in the Mekong Delta and Red River Delta”, the project number: VT-UD-08/17-20, which belongs to the National program on space science and technology (2016–2020).

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Correspondence to Nguyen Lam-Dao .

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Hoang-Phi, P., Lam-Dao, N., Nguyen-Van-Anh, V., Nguyen-Kim, T., Le Toan, T., Pham-Duy, T. (2022). Rice Growth Stage Monitoring and Yield Estimation in the Vietnamese Mekong Delta Using Multi-temporal Sentinel-1 Data. In: Vadrevu, K.P., Le Toan, T., Ray, S.S., Justice, C. (eds) Remote Sensing of Agriculture and Land Cover/Land Use Changes in South and Southeast Asian Countries. Springer, Cham. https://doi.org/10.1007/978-3-030-92365-5_17

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