Abstract
Wet-season and dry-season rice production systems in Thailand covered approximately 9.5 and 2.0 million hectares, respectively. The areas under both systems depended on the annual water resources of the previous rainy season, which fluctuated and caused pressure to compensate budget. Ministry of Agriculture and Cooperatives (MOAC) issued a policy process to support rice production to match supply-based water availability. Satellite data sets were used to issue official rice planted areas and Geo-Informatics and Space Technology Development Agency (GISTDA) is the leading organization responsible for this activity. The biweekly rice planted area was released in shapefile format, and Rice Department (RD) analyzed these data for specific rice variety distribution. We found that satellite data sets estimated wet season rice planted areas in 2017/18, 2018/19, 2019/20 and 2020/21 seasons were similar to the actual planted areas. We concluded the importance of satellite datasets to support the policy process and to establish efficient communication and planning with local officials, farmers’ groups, and stakeholders for effective rice map** and monitoring efforts. The implementation will offer opportunities for collaboration to adapt to the risky nature of rainfed wet season rice production in Thailand and elsewhere.
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References
Buddhaboon, C., Varinruk, B., Sansen, K., Rossopa, B., Phinchongsakuldit, A., Pornprommin, P., Taprab, S., & Suwannarat, A. (2018). Development of suitability production area map for rice commodity groups (in Thai). Thai Rice Research Journal, 9(1), 88–104.
Geo-Informatics and Space Technology Development Agency. (2021). Rice data: Shape files (*.ZIP). Retrieved January 3, 2021, from https://rice.gistda.or.th/
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.
Kaeomuangmoon, T., **trawet, A., Chotamonsak, C., Singh, U., Buddhaboon, C., Naoujanon, P., Kongton, S., Kono, Y., & Hoogenboom, G. (2019). Estimating seasonal fragrant rice production in Thailand using a spatial crop modelling and weather forecasting approach. The Journal of Agricultural Science, 157, 566–577. https://doi.org/10.1017/S0021859619000881
Kuenzer, C., & Knauer, K. (2013). Remote sensing of rice crop areas. International Journal of Remote Sensing, 34(6), 2101–2139.
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.
Lasko, K., Vadrevu, K. P., Tran, V. T., & Justice, C. (2018). Map** 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.
Lasko, K., Vadrevu, K. P., Bandaru, V., Nguyen, T. N. T., & Bui, H. Q. (2021). PM2.5 emissions from biomass burning in South/Southeast Asia–Uncertainties and trade-offs. In Biomass burning in South and Southeast Asia (pp. 149–169). CRC Press.
Ministry of Agriculture and Cooperatives. (2020). Level of suitability area for rice production. Retrieved January 2, 2021, from http://agri-map-online.moac.go.th/ [in Thai].
Motohka, T., Nasahara, K. N., Miyata, A., Mano, M., & Tsuchida, S. (2009). Evaluation of optical satellite remote sensing for rice paddy phenology in monsoon Asia using a continuous in situ dataset. International Journal of Remote Sensing, 30(17), 4343–4357.
NABC (National Agricultural Big Data Center). (2020). Assessing drought impact. Accessed on February 17, 2021, from https://www.nabc.go.th/disaster/ [in Thai].
Nelson, A., Setiyono, T., Rala, A. B., Quicho, E. D., Raviz, J. V., Abonete, P. J., Maunahan, A. A., Garcia, C. A., Bhatti, H. Z. M., Villano, L. S., & Thongbai, P. (2014). Towards an operational SAR-based rice monitoring system in Asia: Examples from 13 demonstration sites across Asia in the RIICE project. Remote Sensing, 6(11), 10773–10812.
Office of Agricultural Economics. (2020a). Dry season rice: Planted and harvested, product and yield at 15% of moisture content. Retrieved January 3, 2021, from http://www.oae.go.th/view/1/ตารางแสดงรายละเอียดข้าวนาปรัง/TH-TH [in Thai].
Office of Agricultural Economics. (2020b). Dry season rice: Planted and harvested, product and yield at 15% of moisture content. Retrieved January 3, 2021, from http://www.oae.go.th/view/1/ตารางแสดงรายละเอียดข้าวนาปี/TH-TH [in Thai].
Rice Department. (2020). Rice knowledge bank: Rice variety. Retrieved, January 5, 2021, from http://www.ricethailand.go.th/rkb3/Varieties.htm [in Thai].
Royal Irrigation Department. (2020). Irrigated area. http://thaisdi.gistda.or.th/dataset/rid0005 [in Thai].
Tennakoon, S. B., Murty, V. V. N., & Eiumnoh, A. (1992). Estimation of cropped area and grain yield of rice using remote sensing data. International Journal of Remote Sensing, 13(3), 427–439.
Vadrevu, K. P., Ellicott, E., Badarinath, K. V. S., & Vermote, E. (2011). MODIS derived fire characteristics and aerosol optical depth variations during the agricultural residue burning season, North India. Environmental Pollution, 159(6), 1560–1569.
Vadrevu, K. P., Giglio, L., & Justice, C. (2013). Satellite based analysis of fire–carbon monoxide relationships from forest and agricultural residue burning (2003–2011). Atmospheric Environment, 64, 179–191.
Vadrevu, K., & Lasko, K. (2018). Intercomparison of MODIS AQUA and VIIRS I-band fires and emissions in an agricultural landscape—Implications for air pollution research. Remote Sensing, 10(7), 978.
Vadrevu, K. P., Dadhwal, V. K., Gutman, G., & Justice, C. (2019a). Remote sensing of agriculture–South/Southeast Asia research initiative special issue. International Journal of Remote Sensing, 40(21), 8071–8075.
Vadrevu, K., Heinimann, A., Gutman, G., & Justice, C. (2019b). Remote sensing of land use/cover changes in South and Southeast Asian countries. International Journal of Digital Earth, 12(10), 1099–1102.
** paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images. Remote Sensing of Environment, 100(1), 95–113.
Acknowledgements
We thank all authors of data sets, information, and journals who support this study. In addition, we acknowledge the Ministry of Agriculture and Cooperatives and Ministry of Commerce, for providing valuable official data sets. Finally, we also convey sincere thanks to the Bureau of Rice Policy and strategy staff, Rice Department, Ministry of Agriculture and cooperatives hel** us collect various sources of data sets to fulfill this study.
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Buddhaboon, C., Nueangjumnong, P., Kaeomuangmoon, T., **trawet, A. (2022). The Utilization of Satellite Data to Support Wet Season Rice Production Policy in Thailand: A Review of Practices and Opportunities. 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_15
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