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http://dx.doi.org/10.7848/ksgpc.2022.40.2.135

Evaluation of vegetation index accuracy based on drone optical sensor  

Lee, Geun Sang (Dept. of Cadastre & Civil Engineering, Vision College of Jeonju)
Cho, Gi Sung (Dept. of Civil Engineering, Jeonbuk National University)
Hwang, Jee Wook (Dept. of Urban Engineering, Dept. of Urban Engineering, Jeonbuk National University)
Kim, Pyoung Kwon (Dept. of Civil Engineering, Jeonbuk National University)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.40, no.2, 2022 , pp. 135-144 More about this Journal
Abstract
Since vegetation provides humans with various ecological spaces and is also very important in terms of water resources and climatic environment, many vegetation monitoring studies using vegetation indexes based on near infrared sensors have been conducted. Therefore, if the near infrared sensor is not provided, the vegetation monitoring study has a practical problem. In this study, to improve this problem, the NDVI (Normalized Difference Vegetation Index) was used as a reference to evaluate the accuracy of the vegetation index based on the optical sensor. First, the Kappa coefficient was calculated by overlapping the vegetation survey point surveyed in the field with the NDVI. As a result, the vegetation area with a threshold value of 0.6 or higher, which has the highest Kappa coefficient of 0.930, was evaluated based on optical sensor based vegetation index accuracy. It could be selected as standard data. As a result of selecting NDVI as reference data and comparing with vegetation index based on optical sensor, the Kappa coefficients at the threshold values of 0.04, 0.08, and 0.30 or higher were the highest, 0.713, 0.713, and 0.828, respectively. In particular, in the case of the RGBVI (Red Green Red Vegetation Index), the Kappa coefficient was high at 0.828. Therefore, it was found that the vegetation monitoring study using the optical sensor is possible even in environments where the near infrared sensor is not available.
Keywords
Optical Sensor; Vegetation Index; Drone; Threshold Value;
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