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NTIS 바로가기농촌계획 : 韓國農村計劃學會誌, v.28 no.1, 2022년, pp.57 - 69
정찬희 (충북대학교 농업생명환경대학 지역건설공학과) , 고승환 (충북대학교 농업생명환경대학 지역건설공학과) , 박종화 (충북대학교 농업생명환경대학 지역건설공학과)
Crop classification is very important for estimating crop yield and figuring out accurate cultivation area. The purpose of this study is to classify crops harvested in fall in Idam-ri, Goesan-gun, Chungcheongbuk-do by using unmanned aerial vehicle (UAV) images and support vector machine (SVM) model....
Antonarakis, A. S., Richards, K. S. and Brasington J., 2008, Object-Based Land Cover Classification Using Airborne LiDAR, Remote Sensing of Environment, 112(6): 2988-2998.
Choi, K. P., Yu, S. S. Yoo, N. H. and Oh, H. J., 2021, Pest Prediction and Prevention Model Visualization Using Farm Map for Ecological Smart Farm, Journal of Korean Institute of Information Technology, 19(2): 105-113.
Franklin, S. E. and Wulder, M. A., 2002, Remote Sensing Methods in Medium Spatial Resolution Satellite Data Land Cover Classification of Large Areas, Progress in Physical Geography-Earth and Environment, 26(2): 173-205.
Gouk, S. Y., Seo, H. S., Seo, D. J., Kwon, S. W. and Kim, K. J., 2021, Situation of Recent Agricultural Product Price Fluctuations and Implications, Korean Rural Economic Institute, Naju, KR, 1-25.
Haralick, R. M., Shanmugam, K. and Dinstein, I. H., 1973, Textural Features for Image Classification, IEEE Transactions on Systems, Man, and Cybernetics, SMC3(6): 610-621.
Ka, M. H., 2000, Application of Spaceborne Earth Remote Sensing Information, Journal of the Korean Society of Remote Sensing, 16(3): 261-279.
Kanan, C. and Cottrell, G. W., 2012, Color-to-Grayscale: Does the Method Matter in Image Recognition?, PloS one, 7(1): e29740.
Kim, S. E., 2013, The Performance Comparison of the Variable Selection Methods for SVMs, Masters thesis, Sungkyunkwan University.
KMA(Korea Meteorological Administration), https://data.kma.go.kr, Accessed on 26 June, 2021.
KOSTAT, 2020a, Crop Production Survey Statistical Information Report, 1-114.
KOSTAT, 2020b, Agriculture Area Survey Statistical Information Report, 1-52.
Kussul, N., Lavreniuk, M., Skakun, S. and Shelestov, A., 2017, Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data, IEEE Geoscience and Remote Sensing Letters, 14(5): 778-782.
Kwak, G. H. and Park, N. W., 2019, Impact of Texture Information on Crop Classification with Machine Learning and UAV Images, Applied Sciences-Basel, 9(4): 643.
Landis, J. R. and Koch, G. G., 1977, The Measurement of Observer Agreement for Categorical Data, Biometrics, 33(1): 159-174.
Lee, D. H., Kim, H. J. and Park, J. H., 2021, UAV, a Farm Map, and Machine Learning Technology Convergence Classification Method of a Corn Cultivation Area, Agronomy, 11(8): 1554.
McNairn, H., Kross, A., Lapen, D., Caves, R. and Shang, J., 2014, Early Season Monitoring of Corn and Soybeans with TerraSAR-X and RADARSAT-2, International Journal of Applied Earth Observation and Geoinformation, 28: 252-259.
Na, S. I., 2021, The Meaning of Agricultural and Forestry Satellites through Examples of Satellite Use in Agriculture, Magazine of the Korean Society of Agricultural Engineers, 63(2): 35-43.
Na, S. I., Park, C. W., So, K. H., Park, J. M. and Lee, K. D., 2017, Satellite Imagery based Winter Crop Classification Mapping using Hierarchica Classification, Korean Journal of Remote Sensing, 33(5): 677-687.
Rakotomamonjy, A., 2003, Variable Selection Using SVM-based Criteria, Journal of machine learning research, 3(Mar): 1357-1370.
R Core Team, R: A Language and Environment for Statistical Computing, https://www.R-project.org, Accessed on 26 September, 2021.
Sull, K. J., 2005, A Study on the Classification of High-Resolution Satellite Image by Texture Analysis: Focus on the Extracting Urban Area, Masters thesis, Sangmyung University.
Tassi, A. and Vizzari, M., 2020, Object-Oriented LULC Classification in Google Earth Engine Combining SNIC, GLCM, and Machine Learning Algorithms, Remote Sensing, 12(22): 3776.
Torbick, N., Huang, X. D., Ziniti, B., Johnson, D., Masek, J. and Reba, M., 2018, Fusion of Moderate Resolution Earth Observations for Operational Crop Type Mapping, Remote Sensing, 10(7): 1058.
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