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논문 기본 정보

자료유형
학술저널
저자정보
장성주 (서울대학교 생태조경ㆍ지역시스템공학부 석사과정) 박진석 (서울대학교 생태조경ㆍ지역시스템공학부 박사과정) 홍록기 (서울대학교 생태조경ㆍ지역시스템공학부 학부과정) 홍주표 (서울대학교 생태조경ㆍ지역시스템공학부 학부과정) 권채린 (서울대학교 생태조경ㆍ지역시스템공학부 학부과정) 송인홍 (서울대학교)
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한국농촌계획학회 농촌계획 농촌계획 제27권 제3호
발행연도
2021.8
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21 - 33 (13page)

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Rice straw management and winter crop cultivation are crucial components for the accurate estimation of paddy methane emissions. Field-based extensive investigation of paddy organic matter management requires enormous efforts however it becomes more feasible as drone technology advances. The objectives of this study were to identify paddy fields of straw application and winter crop cultivation using drone images and to apply for the estimation of yearly methane emission. Total 35 sites of over 150ha in area were selected nationwide as the study areas. Drone images of the study sites were taken twice during summer and winter in 2018 through 2019: Summer images were used to identify paddy cultivation areas, while winter images for straw and winter crop practices. Drone-image-based identification results were used to estimate paddy methane emission and compared with conventional method. As the result, mean areas for paddy, straw application and winter crop cultivation were 118.9ha, 12.0ha, and 11.3ha, respectively. Overall rice straw application rate were greater in Gyeonggi-do(20%) and Chungcheongnam-do(12%), while winter crop cultivation was greatest in Gyeongsangnam-do(30%) and Jeolla-do(27%). Yearly mean methane emission was estimated to be 226.2kg CH4/ha/yr in this study and about 32% less when compared to 331.8kg CH4/ha/yr estimated with the conventional method. This was primarily because of the lower rice straw application rate observed in this study, which was less than quarter the rate of 55.62% used for the conventional method. This indicates the necessity to use more accurate statistics of rice straw application as well as winter crop practices into paddy methane emission estimation. Thus it is recommended to further study to link drone technology with satellite image analysis in order to identify organic management practices at a paddy field level over extensive agricultural area.

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