Acknowledgement
본 연구는 농촌진흥청 연구개발사업(과제명 : 드론 이용 동계 사료작물 정밀재배 및 초지조성 관리기술 개발, 과제번호 : PJ0141232019)의 지원에 의해 연구되었습니다.
References
- Ahmed, K., Marco, S., Simone, G., Francesco, M. and Francesco, P. 2019. Monitoring within-field variability of corn yield using sentinel-2 and machine learning techniques. Remote Sensing. 11(23):2873-2892. https://doi.org/10.3390/rs11232873
- Bendig, J., Bolten, A., Bennertz, S., Broscheit, J., Eichfuss, S. and Bareth, G. 2014. Estimating biomass of barley using crop surface models(CSMs) derived from UAV-based RGB imaging. Remote Sensing. 6(11):10395-10412. https://doi.org/10.3390/rs61110395
- Fan, X., Kawamura, K., Lim, J., Yoshitoshi, R., Yuba, N., Lee, H.J. and Tsumiyama, Y. 2016. Spring growth stage detection in Italian ryegrass field using a ground-based camera system. Grassland Science. 62(3):188-193. https://doi.org/10.1111/grs.12122
- Gitelson, A.A., Kaufman, Y.J. and Merzlyak, M.N. 1996. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment. 58:289-298. https://doi.org/10.1016/S0034-4257(96)00072-7
- Korea Rural Economic Institute. 2014. Statistical survey technique development and application method. pp. 1-65.
- Lee, H.J., Lee, H.W. and Go, H.J. 2016. Estimating the spatial distribution of rumex acetosella L. on hill pasture using UAV monitoring system and digital camera. Journal of the Korean Society of Grassland and Forage Science. 36(4):365-369. https://doi.org/10.5333/KGFS.2016.36.4.365
- Lee, H.W., Lee, H.J., Jung, J.S. and Ko, H.J. 2015. Mapping herbage biomass on a hill pasture using a digital camera with an unmanned aerial vehicle system. Journal of the Korean Society of Grassland and Forage Science. 35(3):225-231. https://doi.org/10.5333/KGFS.2015.35.3.225
- Lee, K.D., Lee, Y.E., Park, C.W., Hong, S.Y. and Na, S.I. 2016. Study on reflectance and NDVI of aerial images using a fixed-wing UAV "Ebee". Korean Journal of Soil Science and Fertilizer. 49:731-742. https://doi.org/10.7745/KJSSF.2016.49.6.731
- Lee, K.D., Park, C.W., So, K.H. and Na, S.I. 2017. Selection of optimal vegetation indices and regression model for estimation of rice growth using UAV aerial images. Korean Journal of Soil Science and Fertilizer. 50:409-421. https://doi.org/10.7745/KJSSF.2017.50.5.409
- Lee, K.D., Park, C.W., So, K.H., Kim, K.D. and Na, S.I. 2017. Estimating of transplanting period of highland kimchi cabbage using UAV imagery. Journal of the Korean Society of Agricultural Engineers. 59(6):39-50. https://doi.org/10.5389/KSAE.2017.59.6.039
- Na, S.I., Park, C.W., Cheong, Y.K., Kang, C.S., Choi, I.B. and Lee, K.D. 2016. Selection of optimal vegetation indices for estimation of barley & wheat growth based on remote sensing. Korea Journal of Remote Sensing. 32(5):483-497. https://doi.org/10.7780/KJRS.2016.32.5.7
- Na, S.I., Park, C.W., Cheong, Y.K., Kang, C.S., Choi, I.B. and Lee, K.D. 2017. Monitoring onion growth using UAV NDVI and meteorological factors. Korean Journal of Soil Science and Fertilizer. 50(4):306-317. https://doi.org/10.7745/KJSSF.2017.50.4.306
- NIPA. 2017. ICT convergence in-depth report. pp. 1-5.
- Park, J.K. and Park, J.H. 2017. Analysis of rice field drought area using Unmanned Aerial Vehicle (UAV) and Geographic Information System (GIS) methods. Journal of the Korean Society of Agricultural Engineers. 59(3):21-28. https://doi.org/10.5389/KSAE.2017.59.3.021
- Shin, J.Y., Lee, J.M., Yang, S.H. and Lee, H.J. 2020. Selection of optimal vegetation indices for predicting winter crop dry matter based on unmanned aerial vehicle. Journal of the Korean Society of Grassland and Forage Science. 40(4):196-202. https://doi.org/10.5333/KGFS.2020.40.4.196
- Torres-Sanchez, J., Pena, J.M., Castro, A.I. and Lopez-Granados, F. 2014. Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV. Computers and Electronics in Agriculture. 103:104-113. https://doi.org/10.1016/j.compag.2014.02.009
- Xiang, H. and Tian, L. 2011. Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV). Biosystems Engineering. 108(2):174-190. https://doi.org/10.1016/j.biosystemseng.2010.11.010