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http://dx.doi.org/10.5658/WOOD.2020.48.6.917

A Study on a Development of Automated Measurement Sensor for Forest Fire Surface Fuel Moistures  

YEOM, Chan-Ho (Professional Graduate School of Disaster Prevention, Kangwon National University)
LEE, Si-Young (Professional Graduate School of Disaster Prevention, Kangwon National University)
PARK, Houng-Sek (Graduate School of Forestry, Dongguk University)
WON, Myoung-Soo (Forest Resource Management and Restoration Division, National Institute of Forest Science)
Publication Information
Journal of the Korean Wood Science and Technology / v.48, no.6, 2020 , pp. 917-935 More about this Journal
Abstract
In this study, an automated sensor to measure forest fire surface fuel moistures was developed to predict changes in the moisture content and risk of forest fire surface fuel, which was indicators of forest fire occurrence and spread risk. This measurement sensor was a method of automatically calculating the moisture content of forest fire surface fuel by electric resistance. The proxy of forest fire surface fuel used in this sensor is pine (50 cm long, 1.5 cm in diameter), and the relationship between moisture content and electrical resistance, R(R:Electrical resistance)=2E(E:Exponent of 10)+13X(X:Moisture content)-9.705(R2=0.947) was developed. In addition, using this, the software and case of the automated measurement sensor for forest fire surface fuel moisture were designed to produce a prototype, and the suitability (R2=0.824) was confirmed by performing field monitoring verification in the forest. The results of this study would contribute to develop technologies that can predict the occurrence, spread and intensity of forest fires, and are expected to be used as basic data for advanced forest fire risk forecasting technologies.
Keywords
forest fires; forest fuel humidity; forest fire prediction; Surface fuel; electrical resistance;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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