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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.8
- 수록면
- 306 - 317 (12page)
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초록· 키워드
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Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, NDVIUAV and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And NDVIUAV in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to NDVIUAV and other meteorological factors were well reflected in the model.
목차
ABSTRACT
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
참고문헌 (14)
참고문헌 신청
Agricultural Weather Information Service Homepage. http://weather.rda.go.kr/ Accessed 7 Nov. 2016.
Choi, S.C. and J.S. Baek. 2016. Onion yield estimation using spatial panel regression model. Korean J. Appl. Stat. 29(5):873-885 (in Korean with English abstract).
Dieter, H., Z. Werner, S. Gunter, and S. Peter. 2005. Monitoring of gas pipelines - a civil UAV application. Aircr. Eng. Aerosp. Technol. 77:352-360.
Herwitz, S.R., L.F. John, S.E. Dunagan, R.G. Higgins, D.V. Sullivan, J. Zheng, B.M. Lobitz, J.G. Leung, B.A. Gallmeyer, M. Aoyagi, R.E. Slye, and J.A. Brass. 2004. Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support. Comput. Electro. Agric. 44:49-61.
Jung, K.S., Y.S. Kim, and S.R. Oh. 2015. Technical development of flood damage estimation using UAV. Mag. Korea Water Resour. Assoc. 48(1):51-59 (in Korean with English abstract).
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UCI(KEPA) : I410-ECN-0101-2018-523-001256761