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Brian G. Lees
4School of Physical, Environmental and Mathematical Sciences, University of New South Wales at Australian Defence Force Academy. Northcott Drive, Canberra ACT 2600. Australia
Astronomy Chemistry Earth & Planetary Sciences Mathematics Physics

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Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia Dyah R. Panuju; Bambang H. Trisasongko; Budi Susetyo; Mahmud A. Raimadoya; Brian G. Lees
Journal of Mathematical and Fundamental Sciences Vol. 42 No. 1 (2010)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.sci.2010.42.1.5

Abstract

In addition to forest encroachment, forest fire is a serious problem in Indonesia. Attempts at managing its widespread and frequent occurrence has led to intensive use of remote sensing data. Coarse resolution images have been employed to derive hot spots as an indicator of forest fire. However, most efforts to verify the hot spot data and to verify fire accidents have been restricted to the use of medium or high resolution data. At present, it is difficult to verify solely upon those data due to severe cloud cover and low revisit time. In this paper, we present a method to validate forest fire using NDVI time series data. With the freely available NDVI data from SPOT VEGETATION, we successfully detected changes in time series data which were associated with fire accidents.
Co-Authors Bambang H. Trisasongko Budi Susetyo Dyah R. Panuju Mahmud A. Raimadoya