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http://dx.doi.org/10.7780/kjrs.2021.37.5.1.7

Comparative Analysis of Rice Lodging Area Using a UAV-based Multispectral Imagery  

Moon, Hyun-Dong (Department of Applied Plant Science, Chonnam National University)
Ryu, Jae-Hyun (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
Na, Sang-il (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
Jang, Seon Woong (IREMTECH, Co., Ltd)
Sin, Seo-ho (Food Crop Research Center, Agricultural Research & Extension Services)
Cho, Jaeil (Department of Applied Plant Science, Chonnam National University)
Publication Information
Korean Journal of Remote Sensing / v.37, no.5_1, 2021 , pp. 917-926 More about this Journal
Abstract
Lodging rice is one of critical agro-meteorological disasters. In this study, the UAV-based multispectral imageries before and after rice lodging in rice paddy field of Jeollanamdo agricultural research and extension servicesin 2020 was analyzed. The UAV imagery on 14th Aug. includesthe paddy rice without any damage. However, 4th and 19th Sep. showed the area of rice lodging. Multispectral camera of 10 bands from 444 nm to 842 nm was used. At the area of restoration work against lodging rice, the reflectance from 531 nm to 842 nm were decreased in comparison to un-lodging rice. At the area of lodging rice, the reflectance of around 668 nm had small increases. Further, the blue and NIR (Near-Infrared) wavelength had larger. However, according to the types of lodging, the change of reflectance was different. The NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge) shows dome sensitivities to lodging rice, but they were different to types of lodging. These results will be useful to make algorithm to detect the area of lodging rice using a UAV.
Keywords
Rice lodging; Multi-spectral camera; UAV; Canopy Structure; Red-Edge; NIR;
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1 Dunford, R., K. Michel, M. Gagnage, H. Piegay, and M.L. Tremelo, 2009. Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest, International Journal of Remote Sensing, 30(19): 4915-4935.   DOI
2 Ju, Y.C., G.J. Lim, S.W. Han, J.S. Park, Y.C. Cho, and S.J. Kim, 2000. Yield Response of Rice Affected by Adverse Weather Conditions Occurred in 1999, Korean Journal of Agricultural and Forest Meteorology, 2(1): 1-8 (in Korean with English abstrsct).
3 Liu, T., R. Li, X. Zhong, M. Jiang, X. Jin, P. Zhou, and W. Guo, 2018. Estimates of rice lodging using indices derived from UAV visible and thermal infrared images, Agricultural and Forest Meteorology, 252: 144-154.   DOI
4 Moon, I.J., E.S. Choi, J.S. Shim, and K.S. Park, 2007. Changes in Typhoon Intensity on the Korean Peninsula by Climate Change, Proc. of 2007 KMS Spring Meeting, Incheon, KR, Apr. 21, pp. 312-313.
5 Potgieter, A.B., B. George-Jaeggli, S.C. Chapman, K. Laws, L.A. Cadavid Suarez, J. Wixted, J. Watson, M. Eldridge, D.R. Jordan, and G.L. Hammer, 2017. Multi-Spectral Imaging from an Unmanned Aerial Vehicle Enables the Assessment of Seasonal Leaf Area Dynamics of Sorghum Breeding Lines, Frontiers in Plant Science, 8: 1532.   DOI
6 Lee, M.-H., Y.-J. Oh, and R.-K. Park, 1991. Lodging mechanisms and reducing damage of rice plant, Korean Journal of Crop Science, 36(5): 383-393 (in Korean with English abstract).
7 Yang, H., E. Chen, Z. Li, C. Zhao, G. Yang, S. Pignatti, R. Casa, and L. Zhao, 2015. Wheat lodging monitoring using polarimetric index from RADARSAT-2 data, International Journal of Applied Earth Observation and Geoinformation, 34: 157-166.   DOI
8 Yang, M.D., H.H. Tseng, Y.C. Hsu, and H.P. Tsai, 2020. Semantic segmentation using deep learning with vegetation indices for rice lodging identification in multi-date UAV visible images, Remote Sensing, 12(4): 633.   DOI
9 Somers, B., G.P. Asner, L. Tits, and P. Coppin, 2011. Endmember variability in spectral mixture analysis: a review, Remote Sensing of Environment, 115(7): 1603-1616.   DOI
10 Jeong, E.G., K.J. Kim, A.R. Cheon, C.K. Lee, S.L. Kim, S.B. Darshan, and J.R., Son, 2006. Characterization of Grain Quality under Lodging Time and Grade at Ripening, Korean Journal of Crop Science, 51(5): 440-444 (in Korean with English abstrsct).
11 Lee, K.D., S.I. Na, S.C. Baek, and C.W. Park, 2016. Estimating of rice plant lodging area using UAV aerial images, 2016 Korea Society of Soil Sciences And Fertilizer Fall Conference Abstract, Korean Society of Soil Sciences and Fertilizer, Muju, JeollaNamde, Korea, p. 80.
12 Lee, G.S. and Y.W. Choi, 2019. Analysis of Cropland Spectral Properties and Vegetation Index Using UAV, Journal of the Korean Association of Geographic Information Studies, 22(4): 86-101 (in Korean with English abstract).   DOI
13 Merrick, T., M.L.S.P. Jorge, T.S.F. Silva, S. Pau, J. Rausch, E.N. Broadbent, and R. Bennartz, 2020. Characterization of chlorophyll fluorescence, absorbed photosynthetically active radiation, and reflectance-based vegetation index spectroradiometer measurements, International Journal of Remote Sensing, 41(17): 1-26.   DOI
14 Sims, D.A., H. Luo, S. Hastings, W.C. Oechel, A.F. Rahman, and J.A. Gamon, 2006. Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem, Remote Sensing of Environment, 103(3): 289-303.   DOI
15 Tu, YH., K. Johansen, S. Phinn, and A. Robson, 2019. Measuring Canopy Structure and Condition Using Multi-Spectral UAS Imagery in a Horticultural Environment, Remote Sensing, 11(3): 269.   DOI
16 Vina, A., A.A. Gitelson, A.L. Nguy-Robertson, and Y. Peng, 2011. Comparison of different vegetation indices for the remote assessment of green leaf area index of crops, Remote Sensing of Environment, 115(12): 3468-3478   DOI
17 Ryu, J.H., 2021. Evaluation of Measurement Accuracy for Unmanned Aerial Vehicle-based Land Surface Temperature Depending on Climate and Crop Conditions, Korean Journal of Remote Sensing, 37(2): 211-220 (in Korean with English abstrsct).   DOI
18 Yang, M.D., K.S. Huang, Y.H. Kuo, H.P. Tsai, and L.M. Lin, 2017. Spatial and spectral hybrid image classification for rice lodging assessment through UAV imagery, Remote Sensing, 9(6): 583.   DOI
19 Zhang, C. and J.M. Kovacs, 2012. The application of small unmanned aerial systems for precision agriculture: A review, Precision Agriculture, 13(6): 693-712.   DOI