Crop Water Stress Index (CWSI) Mapping for Evaluation of Abnormal Growth of Spring Chinese Cabbage Using Drone-based Thermal Infrared Image |
Na, Sang-il
(Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, Rural Development Administration)
Ahn, Ho-yong (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, Rural Development Administration) Park, Chan-won (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, Rural Development Administration) Hong, Suk-young (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, Rural Development Administration) So, Kyu-ho (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, Rural Development Administration) Lee, Kyung-do (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, Rural Development Administration) |
1 | Jones, H.G., 1992. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology, 2nd edition, Cambridge University Press, New York, NY, USA. |
2 | Kim, M.C., Y.H. Choi, J.G. Cho, S.K. Yun, J.H. Park, Y.J. Kim, J.K. Jeon, and S.B. Lee, 2019. Response of Crop Water Stress Index (CWSI) and Canopy Temperature of Apple Tree to Irrigation Treatment Schemes, Journal of the Korean Society of Agricultural Engineers, 61(5): 23-31 (in Korean with English abstract). DOI |
3 | Korea Rural Economic Institute (KREI) Homepage. http://www.krei.re.kr/, Accessed on Jun. 2, 2020. |
4 | Korean Statistical Information Service (KOSIS) Homepage. https://www.kosis.kr/, Accessed on Jul. 8, 2020. |
5 | Lee, H.S., S.K. Kim, H.J. Lee, J.H. Lee, S.W. An, and S.G. Lee, 2019. Development of Crop Water Stress Index for Kimchi Cabbage Precision Irrigation Control, Korean Journal of Horticultural Science & Technology, 37(4): 490-498 (in Korean with English abstract). |
6 | Lee, S.G., H.J. Lee, S.K. Kim, C.S. Choi, S.T. Park, Y.A. Jang, and K.R. Do, 2015. Effects of Vernalization, Temperature, and Soil Drying Periods on the Growth and Yield of Chinese Cabbage, Korean Journal of Horticultural Science & Technology, 33(6): 820-828 (in Korean with English abstract). DOI |
7 | Martinez, J., G. Egea, J. Aguera, and M. Pirez-Ruiz, 2016. A cost-effective canopy temperature measurement system for precision agriculture: A case study on sugar beet, Precision Agriculture, 18(1): 95-110. |
8 | Na, S.I., K.D. Lee, S.C. Baek, and S.Y. Hong, 2015. Estimation of Chinese cabbage growth by RapidEye imagery and field investigation data, Korean Journal of Soil Science and Fertilizer, 48(5): 556-563 (in Korean with English abstract). DOI |
9 | Na, S.I., C.W. Park, and K.D. Lee, 2016. Application of highland kimchi cabbage status map for growth monitoring based on unmanned aerial vehicle, Korean Journal of Soil Science and Fertilizer, 49(5): 469-479 (in Korean with English abstract). DOI |
10 | Na, S.I., C.W. Park, K.H. So, H.Y. Ahn, and K.D. Lee, 2018. Development of Biomass Evaluation Model of Winter Crop Using RGB Imagery Based on Unmanned Aerial Vehicle, Korean Journal of Remote Sensing, 34(5): 709-720 (in Korean with English abstract). DOI |
11 | Na, S.I., C.W. Park, K.H. So, H.Y. Ahn, and K.D. Lee, 2019a. Selection on Optimal Bands to Estimate Yield of the Chinese Cabbage Using Drone-based Hyperspectral Image, Korean Journal of Remote Sensing, 35(3): 375-387 (in Korean with English abstract). DOI |
12 | Na, S.I., C.W. Park, K.H. So, H.Y. Ahn, and K.D. Lee, 2019b. Photochemical Reflectance Index (PRI) Mapping using Drone-based Hyperspectral Image for Evaluation of Crop Stress and its Application to Multispectral Imagery, Korean Journal of Remote Sensing, 35(5-1): 637-674 (in Korean with English abstract). DOI |
13 | Yun, S.K., S.J. Kim, E.Y. Nam, J.H. Kwon, Y.S. Do, S.Y. Song, M.Y. Kim, Y.H. Choi, G.S. Kim, and H.S. Shin, 2020. Evaluation of Water Stress Using Canopy Temperature and Crop Water Stress Index (CWSI) in Peach Trees, Protected Horticulture and Plant Factory, 29(1): 20-27 (in Korean with English abstract). DOI |
14 | Pou, A., M.P. Diago, H. Medrano, J. Baluja, and J. Tardaguila, 2014. Validation of thermal indices for water status identification in grapevine, Agricultural Water Management, 134: 60-72. DOI |
15 | Torres-Sanchez, J., J.M. Pena, A.I. de Castro, and F. Lopez-Granados, 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. DOI |
16 | Woebbecke, D.M., G.E. Meyer, K. Von Bargen, and D.A. Mortensen, 1995. Color indices for weed identification under various soil, residue, and lighting conditions, Transactions of the ASAE, 38(1): 259-269. DOI |
17 | Choi, Y.H., M.Y. Kim, W.H. Oh, J.G. Cho, S.K. Yun, S.B. Lee, Y.J. Kim, and J.K. Jeon, 2019. Statistical Analysis of Determining Optimal Monitoring Time Schedule for Crop Water Stress Index (CWSI), Journal of the Korean Society of Agricultural Engineers, 61(6): 73-79 (in Korean with English abstract). |
18 | Zhang, Z., J. Bian, W. Han, Q. Fu, S. Chen, and T. Cui, 2018. Cotton moisture stress diagnosis based on canopy temperature characteristics calculated from UAV thermal infrared image, Transactions of the Chinese Society Agricultural Engineers, 34(15): 77-84. |
19 | Agricultural Weather Information Service Homepage. http://weather.rda.go.kr/, Accessed on Jul. 15, 2020. |
20 | Bellvert, J., J. Marsal, J. Girona, and P.J. Zarco-Tejada, 2015. Seasonal evolution of crop water stress index in grapevine varieties determined with high-resolution remote sensing thermal imagery, Irrigation Science, 33(2): 81-93. DOI |
21 | DeJonge, K.C., S. Taghvaeian, T.J. Trout, and L.H. Comas, 2015. Comparison of canopy temperature-based water stress indices for maize, Agricultural Water Management, 156: 51-62. DOI |
22 | Han, M., H. Zhang, K.C. DeJonge, L.H. Comas, and T.J. Trout, 2016. Estimating maize water stress by standard deviation of canopy temperature in thermal imagery, Agricultural Water Management, 177: 400-409. DOI |
23 | Idso, S.B., R.D. Jackson, P.J.J. Pinter, R.J. Reginato, and J.L. Hatfield, 1981. Normalizing the stress degree-day parameter for environmental variability, Agricultural Meteorology, 24: 45-55. DOI |
24 | Idso, S.B., R.D. Jackson, and R.J. Reginato, 1977. Remote sensing of crop yields, Science, 196(4285): 19-25. DOI |
25 | Jackson, R.D., S.B. Idso, R. Reginato, and P.J. Pinter, 1981. Canopy temperature as a crop water stress indicator, Water Resources Research, 17(4): 1133-1138. DOI |