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2018 Vol.51, Issue 4 Preview Page
November 2018. pp. 522-529

Recent advanced UAV (Unmanned Aerial Vehicle) technology supply new opportunities for estimating crop condition using high resolution imagery. The objective of this study was to analyze the change of vegetation index in UAV imagery according to sun altitude. This study was conducted using a fixed-wing UAV, called Ebee, with Cannon S110 camera from November 2017 to September 2018 in the grass experiment of National Institute of Agricultural Sciences on a clear day. As a result, the NDVI (Normalized Difference Vegetation Index) of UAV imagery decreased after 9 a.m. and showed a minimum value at 13 a.m. and increased since then. The solar zenith angle and the NDVI of UAV imagery showed a positive linear relationship. Therefore, in order to quantitatively compare and analyze the time series vegetation index, it is necessary to establish a UAV flight plan considering the change of solar zenith angle. It is thought that it will be necessary to examine cloudy days with various crop in the future.

Relationship between solar zenith angle and NDVI calculated by UAV imagery.

  1. Cohen, W.B. 1991. Response of vegetation indices to change in three measures of leaf water stress. Photogrammetric Engineering and Remote Sensing. 57(2):195-202.
  2. Ishihara, M., Y. Inobe, K. Ono, M. Shimizu, and S. Matsuura. 2015. The impact of sunlight conditions on the consistency of vegetation indices in croplands—effective usage of vegetation indices from continuous ground-based spectral measurements. Remote Sensing. 7:14079-14098.10.3390/rs71014079
  3. Jensen, J.R. 2013. Remote sensing of the environment: an earth resource perspective. Pearson education limited. 620p.
  4. Kim, S.H. 2016. A study on the diffusion of Korean agricultural ICT and role of the agricultural cooperative federation using the theory of technology adoption life cycle and chasm. Cooperative management review. 45:1-27(in Korean).
  5. Lee, B.O., J.W. Yoon, J.H. Yang, and C.Z. Jin. 2016a. Strategies for the value innovation of agriculture in Korea. Journal of Agricultural, Life and Environment Sciences. 28(1):43-51 (in Korean).
  6. Lee, K.D., C.W. Park, K.H. So, and S.I. Na. 2017. Selection of optimal vegetation indices and regression model for estimation of rice growth using UAV aerial images. Korean J. Soil Sci. Fert. 50(5):409-421 (in Korean).
  7. Lee, K.D., S.I. Na, S.C. Baek, K.D. Park, J.S. Choi, S.J. Kim, H.J. Kim, H.S. Choi, and S.Y. Hong. 2015. Estimating the amount of nitrogen in hairy vetch on paddy fields using unmanned aerial vehicle imagery. Korean J. Soil Sci. Fert. 48(5):384-390.10.7745/KJSSF.2015.48.5.384
  8. Lee, K.D., Y.E. Lee, C.W. Park, S.Y. Hong, and S.I. Na. 2016b. Study on reflectance and NDVI of aerial images using a fixed-wing UAV "Ebee". Korean J. Soil Sci. Fert. 49(6):731-742.10.7745/KJSSF.2016.49.6.731
  9. Lyon, J.G., D. Yuan, R.S. Lunetta, and C.D. Elvidge. 1998. A change detection experiment using vegetation indices. Photogrammetric Engineering and Remote Sensing. 64(2):143-150.
  10. Na, S.I., C.W. Park, Y.K, Cheong, C.S. Kang, I.B. Choi, and K.D. Lee. 2016c. Selection of Optimal vegetation indices for estimation of barley & wheat growth based on remote sensing - an application of unmanned aerial vehicle and field investigation data. Korean Journal of Remote Sensing. 32(5):483-497 (in Korean).10.7780/kjrs.2016.32.5.7
  11. Na, S.I., S.Y. Hong, C.W. Park, K.D. Kim, and K.D. Lee. 2016a. Estimation of highland Kimchi cabbage growth using UAV NDVI and agro-meteorological factors, Korean J. Soil Sci. Fert. 49(5):420-428 (in Korean).10.7745/KJSSF.2016.49.5.420
  12. Na, S.I., S.Y. Hong, C.W. Park, K.D. Kim, and K.D. Lee. 2016b. Mapping the spatial distribution of IRG growth based on UAV. Korean J. Soil Sci. Fert. 49(5):495-502 (in Korean).10.7745/KJSSF.2016.49.5.495
  13. Park, J.K., H.J. Lee, J.W. Hwang. 2005. An analysis of adoption possibility for precision agriculture in Korean rice farms. Korean journal of economics. 46(4):1-23.
  14. Stark, B., T. Zhao, and Y.Q. Chen. 2016. An analysis of the effect of the bidirectional reflectance distribution function on remote sensing imagery accuracy from small unmanned aircraft systems. 2016 International Conference on Unmanned Aircraft Systems (ICUAS), 1342-1350.10.1109/ICUAS.2016.7502566
  15. Tomas, J.R. and H.W. Gausman. 1977. Leaf reflectance vs. leaf chlorophyll and carotenoid concentrations for eight crops. Agron. J. 69:799-802.10.2134/agronj1977.00021962006900050017x
  • Publisher :Korean Society of Soil Science and Fertilizer
  • Publisher(Ko) :한국토양비료학회
  • Journal Title :Korean Journal of Soil Science and Fertilizer
  • Journal Title(Ko) :한국토양비료학회 학회지
  • Volume : 51
  • No :4
  • Pages :522-529
  • Received Date :2018. 10. 01
  • Accepted Date : 2018. 11. 14