Abstract
In Asia, rice is a staple cereal crop and the continent accounts for about 90 % of the global rice production and consumption. Statistics on the areas planted with rice or production of paddy rice are fundamental to agriculture-related decisions or policy-making. Asia-Rice Crop Estimation & Monitoring (Asia-RiCE) aims to develop rice-related information, such as paddy field maps, rice growing conditions, yield, and production, using remote sensing tools and disseminate the same at the local and global scales. In this paper, we propose a methodology for the identification of rice-planted areas by using multi-temporal SAR images; a software named INternational Asian Harvest mOnitoring system for Rice (INAHOR) was developed to manipulate the proposed algorithm. The INAHOR uses the imagery observed both at the time of planting of rice and grown-up stages. In this study, two thresholds needed for the INAHOR were optimized based on the detailed land cover data collected through a field survey. Rice-planted areas across the study area in Japan were identified by the INAHOR using the RADARSAT-2 Wide Fine beam mode data. The classification results of RADARSAT-2 VV and VH polarizations were compared. The data with VH polarization showed a higher total accuracy of 83 % with −20.5 dB and 3.0 dB for the minimum and range thresholds, respectively. The INAHOR is currently being used with the RADARSAT-2, ALOS, and ALOS-2 SAR data in the Southeast Asian countries to assess the robustness of the thresholds and classification accuracies under the framework of Asia-RiCE.
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Acknowledgments
The authors would like to express their gratitude to Mr. Takuma Anahara at the Earth Observation Research Center (EORC), Japan Aerospace Exploration Agency (JAXA) for conducting the field survey, and the Canadian Space Agency (CSA) for providing RADARSAT-2 data through the Science and Operational Applications Research (SOAR)—Joint Experiment of Crop Assessment and Monitoring (JECAM) project.
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Oyoshi, K., Tomiyama, N., Okumura, T. et al. Mapping rice-planted areas using time-series synthetic aperture radar data for the Asia-RiCE activity. Paddy Water Environ 14, 463–472 (2016). https://doi.org/10.1007/s10333-015-0515-x
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DOI: https://doi.org/10.1007/s10333-015-0515-x