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http://dx.doi.org/10.11108/kagis.2020.23.2.021

Drone-based Vegetation Index Analysis Considering Vegetation Vitality  

CHO, Sang-Ho (Dept. of Mineral Resources and Energy Engineering, Jeonbuk National University)
LEE, Geun-Sang (Dept. of Cadastre & Civil Engineering, Vision College of Jeonju)
HWANG, Jee-Wook (Dept. of Urban Engineering, Jeonbuk National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.23, no.2, 2020 , pp. 21-35 More about this Journal
Abstract
Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.
Keywords
Vegetation Vitality; Drone; Vegetation Index; Threshold Value;
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