Browse > Article
http://dx.doi.org/10.7780/kjrs.2019.35.6.3.4

A Feasibility Study on the Application of TVDI on Accessing Wildfire Danger in the Korean Peninsula  

Kim, Kwang Nyun (Department of Atmospheric Sciences, Chungnam National University)
Kim, Seung Hee (Center of Excellence in Earth Systems Modeling & Observations, Chapman University)
Won, Myoung Soo (Division of Forest Ecology and Climate Change, National Institute of Forest Science)
Jang, Keun Chang (Division of Forest Ecology and Climate Change, National Institute of Forest Science)
Choi, Won Jun (Environmental Satellite Center, National Institute of Environmental Research)
Lee, Yun Gon (Department of Atmospheric Sciences, Chungnam National University)
Publication Information
Korean Journal of Remote Sensing / v.35, no.6_3, 2019 , pp. 1197-1208 More about this Journal
Abstract
Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to improve TVDI performance over the study region. In-situ measured air temperature was employed to increase accuracy, regression line was generated using monthly data to include seasonal effect, and TVDI was calculated at each province level to consider vegetation type and local climate. The modified TVDI calculation method was evaluated in wildfire cases and showed significant improvement in wildfire danger estimation.
Keywords
Temperature Vegetation Dryness Index (TVDI); wildfire; remote sensing; vegetation index;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Seong, N., M. Seo, K. S. Lee, C. Lee, H. Kim, S. Choi, and K. S. Han, 2015. A water stress evaluation over forest canopy using NDWI in Korean peninsula, Korean Journal of Remote Sensing, 31(2): 77-83.   DOI
2 Shin, H., E. Chang, and S. Hong, 2014. Estimation of near surface air temperature using MODIS land surface temperature data and geostatistics, Journal of Korea Spatial Information Society, 22(1): 55-63.   DOI
3 Sung, M. K., G. H. Lim, E. H. Choi, Y. Y. Lee, M. S. Won, and K. S. Koo, 2010. Climate change over Korea and its relation to the forest fire occurrence, Atmosphere, 20(1): 27-35.
4 Vidal, A. and C. Devaux-Ros, 1995. Evaluating forest fire hazard with a Landsat TM derived water stress index, Agricultural and Forest Meteorology, 77(3-4): 207-224.   DOI
5 Xu, K., X. Zhang, Z. Chen, W. Wu, and T. Li, 2016. Risk assessment for wildfire occurrence in high-voltage power line corridors by using remote-sensing techniques: a case study in Hubei Province, China, International Journal of Remote Sensing, 37(20): 4818-4837.   DOI
6 Park, J. S. and K. T. Kim, 2009. Evaluation of MODIS NDVI for drought monitoring: Focused on comparison of drought index, Journal of Korea Spatial Information Society, 17(1): 117-129.
7 Akther, M. S. and Q. K. Hassan, 2011. Remote sensingbased assessment of fire danger conditions over boreal forest, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4(4): 992-999.   DOI
8 Baek, S. G., H. W. Jang, J. S. Kim, and J. H. Lee, 2016. Agricultural drought monitoring using the satellite-based vegetation index, Journal of Korea Water Resources Association, 49(4): 305-314.   DOI
9 Bisquert, M. M., J. M. Sanchez, and V. Caselles, 2011. Fire danger estimation from MODIS Enhanced Vegetation Index data: application to Galicia region (north-west Spain), International Journal of Wildland Fire, 20(3): 465-473.   DOI
10 Chowdhury, E. H. and Q. K. Hassan, 2015. Development of a new daily-scale forest fire danger forecasting system using remote sensing data, Remote Sensing, 7(3): 2431-2448.   DOI
11 Chuvieco, E., D. Cocero, D. Riano, P. Martin, J. Martinez-Vega, J. de la Riva, and F. Perez, 2004. Combining NDVI and surface temperature for the estimation of live fuel moisture content in forest fire danger rating, Remote Sensing of Environment, 92(3): 322-331.   DOI
12 Lee, S.Y., 2010. Review of wildfire occurrences from 1960 to 2009, Journal of the Korean Society of Hazard Mitigation, 10(3): 51-55.
13 Gu, Y., B. K. Wylie, and N. B. Bliss, 2013. Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA, Ecological Indicators, 24: 31-36.   DOI
14 Guo, G. and M. Zhou, 2004. Using MODIS land surface temperature to evaluate forest fire risk of northeast China, IEEE Geoscience and Remote Sensing Letters, 1(2): 98-100.   DOI
15 Kang, J. M., C. Zhang, J. K. Park, and M. G. Kim, 2010. Forest fire damage analysis using satellite images, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 28(1): 21-28.
16 Kong, I., K. Kim, and Y. Lee, 2017. Sensitivity Analysis of Meteorology-based Wildfire Risk Indices and Satellite-based Surface Dryness Indices against Wildfire Cases in South Korea, Journal of Cadastre & Land InformatiX, 47(2): 107-120.   DOI
17 Korea Forest Service, 2018. 2017 Statistical Yearbook of forest fires, Korea Forest Service, Daejeon, Republic of Korea (in Korean).
18 Myoung, B., S. H. Kim, S. V. Nghiem, S. Jia, K. Whitney, and M. C. Kafatos, 2018. Estimating Live Fuel Moisture from MODIS Satellite Data for Wildfire Danger Assessment in Southern California USA, Remote Sensing, 10(1): 87.   DOI
19 Oldford, S., B. Leblon, L. Gallant, and M. E. Alexander, 2003. Mapping Pre-Fire Forest Conditions with NOAA-AVHRR Images in Northern Boreal Forests, Geocarto International, 18(4): 21-32.   DOI
20 Onderka, M. and I. Melichercik, 2010. Fire-prone areas delineated from a combination of the Nesterov Fire-risk Rating Index with multispectral satellite data, Applied Geomatics, 2(1): 1-7.   DOI
21 Sandholt, I., K. Rasmussen, and J. Andersen, 2002. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status, Remote Sensing of Environment, 79(2-3): 213-224.   DOI