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http://dx.doi.org/10.7780/kjrs.2019.35.6.2.10

Derivation and Evaluation of Surface Reflectance from UAV Multispectral Image for Monitoring Forest Vegetation  

Lee, Hwa-Seon (Department of Geoinformatic Engineering, Inha University)
Seo, Won-Woo (Department of Geoinformatic Engineering, Inha University)
Woo, Choongshik (Forest Disaster Management Division, National Institute of Forest Science)
Lee, Kyu-Sung (Department of Geoinformatic Engineering, Inha University)
Publication Information
Korean Journal of Remote Sensing / v.35, no.6_2, 2019 , pp. 1149-1160 More about this Journal
Abstract
In this study, two radiometric correction methods deriving reflectance from UAV multispectral image for monitoring forest vegetation were applied and evaluated. Multispectral images were obtained from a small multispectral camera having 5 spectral bands. Reflectance were derived by applying the two methods: (1) the direct method using downwelling irradiance measurement and (2) the empirical line correction method by linking a set of field reflectance measured simultaneous with the image capture. Field reflectance were obtained using a spectroradiometer during the flight and used for building the linear equation for the empirical method and for the validation of image reflectance derived. Although both methods provided the high correlations between field reflectance and image-derived reflectance, their distributions were somewhat different. While the direct method provided rather stable and consistent distribution of reflectance all over the entire image area, the empirical method showed very unstable and inconsistent reflectance distribution. The direct method would be more appropriate for relatively wide area that requires more time to acquire image and may vary in downwelling irradiance and atmospheric conditions.
Keywords
UAV; multispectral image; reflectance; radiometric correction; forest;
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Times Cited By KSCI : 3  (Citation Analysis)
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