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Development of FMI and TMI by estimation of the fire spots in inaccessible areas
Journal of the Korean Data & Information Science Society 2019;30:1121-33
Published online September 30, 2019;  https://doi.org/10.7465/jkdi.2019.30.5.1121
© 2019 Korean Data and Information Science Society.

Suk Hee Yoon1 · Myoung Soo Won2 · Keun Chang Jang3 · Si Young Lee4

123Division of Forest Ecology and Climate Change, National Institute of Forest Science
14Professional Graduate School of Disaster Prevention, Kangwon National University
Correspondence to: Senior researcher, Division of Forest Ecology & Climate Change, National Institute of Forest Science, Seoul 02455, Korea. E-mail: forestfire@korea.kr
Received August 27, 2019; Revised September 11, 2019; Accepted September 11, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This study focuses on developing FMI and TMI through looking at the MODIS data on forest fires that occurred in inaccessible areas for 2011 to 2015 years. In order to do this, 1,469 fire ignition points were extracted from 3,637 fire spots. The ratio of forest fires for each of forest types showed 59.4% (deciduous), 21.7% (evergreen), and 18.9% (mixed). In terms of altitude and aspect, the fire frequency was the highest at 56.3% under 550m and 18.9% in the southeast. The results of calculating the FMI and the TMI by the weight of the fire frequency, the deciduous forest showed FMI 10, FMI 4 in evergreen forest and mixed forest showed FMI 3. The highest TMI of 10 has an altitude index of 5.0 under 550m and a southeast aspect index of 5.0. On the other hand, the altitude index of 1,537m or more was 0.5, and the aspect index of northeast, east, and south was 1.0, which was the lowest of FMI 1.5. Thus, this study results will be useful for decision-makers to prevent forest fires in accessible areas, and when coming up with system to do intensive monitoring of the fire risk areas.
Keywords : Forest fire, fuel model index (FMI), inaccessible area, topography model index (TMI).