ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語


 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.

MYU Research

(proofreading and recording)

(translation service)

The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Sensors and Materials, Volume 31, Number 10(3) (2019)
Copyright(C) MYU K.K.
pp. 3319-3326
S&M2013 Research Paper of Special Issue
Published in advance: September 25, 2019
Published: October 31, 2019

Analysis of Vegetation Infection Information Using Unmanned Aerial Vehicle with Optical Sensor [PDF]

Kap Yong Jung and Joon Kyu Park

(Received June 2, 2019; Accepted August 9, 2019)

Keywords: UAV, optical sensor, big data, ortho image, near-infrared image, infection information, forest management, Bursaphelenchus xylophilus

The forests (approx. 640000 ha) of Korea comprise coniferous forest (41%), broad-leaved forest (27%), and mixed stand forest (29%). They appear to be vulnerable to fire, diseases, and pests. The pine tree is one of the typical Korean species of trees. It was more than 50% of the whole forest area of the country in the 1960s, but the area of pine tree forests has been reduced to 30% because of recent changes in the forest ecosystem and damage caused by diseases and insect pests. In particular, pine wilt disease is currently spreading over Korea. In this study, an unmanned aerial vehicle (UAV) with an optical sensor was used to detect infected trees and to support big data on forest management. Red, green, and blue (RGB) images and near-infrared (NIR) images were acquired using UAV. The infected trees were detected using the RGB images, and the normalized difference vegetation index (NDVI) values were calculated using NIR images. The NDVIs of infected trees were lower than those of non-infected ones, and infected trees that were not detected as infected ones in the RGB images also have lower NDVIs than the neighboring trees that were detected as being infected. Through further research, if a distinct feature of the NDVI of infected trees is discovered, it will be helpful for the early detection of infected trees. Hence, this research is expected to be applied to the detection of infected trees and to support big data on forest management.

Corresponding author: Joon Kyu Park

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Kap Yong Jung and Joon Kyu Park, Analysis of Vegetation Infection Information Using Unmanned Aerial Vehicle with Optical Sensor, Sens. Mater., Vol. 31, No. 10, 2019, p. 3319-3326.

Forthcoming Regular Issues

Forthcoming Special Issues

Special Issue on Advanced Materials on Electronic and Mechanical Devices and their Application on Sensors (5)
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)

Special Issue on Advances in Shape Memory Materials
Guest editor, Ryosuke Matsui (Aichi Institute of Technology) and Hiroyuki Miki (Tohoku University)

Special Issue on Perceptual Deep Learning in Computer Vision and its Application
Guest editor, Chih-Hsien Hsia (National Ilan University)

Special Issue on Materials, Devices, Circuits, and Analytical Methods for Various Sensors (3)
Guest editor, Chien-Jung Huang (National University of Kaohsiung), Cheng-Hsing Hsu (National United University), Ja-Hao Chen (Feng Chia University), and Wei-Ling Hsu (Huaiyin Normal University)
Conference website

Special Issue on Sensing Technologies and Their Applications (1)
Guest editor, Rey-Chue Hwang (I-Shou University)
Call for paper

Special Issue on New Trends in Smart Sensor Systems
Guest editor, Takahiro Hayashi (Kansai University)
Call for paper

Copyright(C) MYU K.K. All Rights Reserved.