[논문]Drone 영상을 이용한 논 필지 볏짚 환원-동계 재배 확인 및 CH4 배출량 산정

장성주; 박진석; 홍록기; 홍주표; 권채린; 송인홍

doi:10.7851/ksrp.2021.27.3.021

Drone 영상을 이용한 논 필지 볏짚 환원-동계 재배 확인 및 CH4 배출량 산정
Estimation of Paddy CH4 Emissions through Drone-Image-Based Identification of Paddy Rice Straw Application & Winter Crop Cultivation 원문보기

농촌계획 : 韓國農村計劃學會誌, v.27 no.3, 2021년, pp.21 - 33

장성주 (서울대학교 생태조경.지역시스템공학부) , 박진석 (서울대학교 생태조경.지역시스템공학부) , 홍록기 (서울대학교 생태조경.지역시스템공학부) , 홍주표 (서울대학교 생태조경.지역시스템공학부) , 권채린 (서울대학교 생태조경.지역시스템공학부) , 송인홍 (서울대학교 생태조경.지역시스템공학부)

Abstract ▼ AI-Helper

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.

주제어

표/그림 (13)

그림 Figure 1. Location and investigation time of the study sites
그림 Figure 2. Example images of (a)drone photograph in summer and (b)the resulting paddy area(Gangwon-do Wonju-si, site 8)
표 Table 1. Drone-image-based identification of rice straw application & winter cropping areas
그림 Figure 3. Example images of (a)drone photograph in winter and (b)the identified organic amendment (Gangwon-do Wonju-si, site 8)
표 Table 2. Water regime scaling factor for the CH4 emission estimation(ME, 2014; KOSTAT, 2018; KOSTAT, 2019)
표 Table 3. Organic amendment scaling factor for the CH4 emission estimation(ME, 2014; 2020)
표 Table 4. Organic matter application amount and scaling factors for the CH4 emission estimation
표 Table 5. Total photographed area and paddy area for study sites unit : ha
그림 Figure 4. Box plot of (a)paddy area and (b)their percentage to respective study area
그림 Figure 5. Percentage of rice straw application and winter crop culitvation areas over the study sites
표 Table 6. Rice straw application and winter crop cultivation area for the study sites unit : ha
그림 Figure 6. Box plot of the estimated yearly methane emissions over the study sites
표 Table 7. Yearly CH4 emissions for the study sites unit : ha

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