A Comparative Study of Image Classification Method to Classify Onion and Garlic Using Unmanned Aerial Vehicle (UAV) Imagery

Kyung­Do  Lee; Ye-Eun  Lee; Chan-Won   Park; Sang­Il  Na

doi:10.7745/KJSSF.2016.49.6.743

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A Comparative Study of Image Classification Method to Classify Onion and Garlic Using Unmanned Aerial Vehicle (UAV) Imagery

December 2016. pp. 743-750

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Abstract

Recently, usage of UAV (Unmanned Aerial Vehicle) has increased in agricultural part. This study was conducted to classify onion and garlic using supervised classification of a fixed-wing UAV (Model : Ebee) images for evaluation of possibility about estimation of onion and garlic cultivation area using UAV images. Aerial images were obtained 11~12 times from study sites in Changryeng-gun and Hapcheon-gun during farming season from 2015 to 2016. The result for accuracy in onion and garlic image classification by R-G-B and R-G-NIR images showed highest Kappa coefficients for the maximum likelihood method. The result for accuracy in onion and garlic classification showed high Kappa coefficients of 0.75~0.97 from DOY 105 to DOY 141, implying that UAV images could be used to estimate onion and garlic cultivation area.

Keywords

UAV

Supervised classification

Kappa coefficient

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Information

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 : 49
No :6
Pages :743-750
Received Date : 2016-10-24
Revised Date : 2016-11-15
Accepted Date : 2016-11-15
DOI :https://doi.org/10.7745/KJSSF.2016.49.6.743

Korean Journal of Soil Science and Fertilizer ISSN:0367-6315(Print) 2288-2162(Online) 한국토양비료학회 학회지

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