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http://dx.doi.org/10.7780/kjrs.2020.36.6.1.8

Analysis of UAV-based Multispectral Reflectance Variability for Agriculture Monitoring  

Ahn, Ho-yong (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
Na, Sang-il (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
Park, Chan-won (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
Hong, Suk-young (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
So, Kyu-ho (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
Lee, Kyung-do (Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration)
Publication Information
Korean Journal of Remote Sensing / v.36, no.6_1, 2020 , pp. 1379-1391 More about this Journal
Abstract
UAV in the agricultural application are capable of collecting ultra-high resolution image. It is possible to obtain timeliness images for phenological phases of the crop. However, the UAV uses a variety of sensors and multi-temporal images according to the environment. Therefore, it is essential to use normalized image data for time series image application for crop monitoring. This study analyzed the variability of UAV reflectance and vegetation index according to Aviation Image Making Environment to utilize the UAV multispectral image for agricultural monitoring time series. The variability of the reflectance according to environmental factors such as altitude, direction, time, and cloud was very large, ranging from 8% to 11%, but the vegetation index variability was stable, ranging from 1% to 5%. This phenomenon is believed to have various causes such as the characteristics of the UAV multispectral sensor and the normalization of the post-processing program. In order to utilize the time series of unmanned aerial vehicles, it is recommended to use the same ratio function as the vegetation index, and it is recommended to minimize the variability of time series images by setting the same time, altitude and direction as possible.
Keywords
UAV; Reflectance; Multispectral Camera; Agriculture Monitoring;
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Times Cited By KSCI : 11  (Citation Analysis)
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