A new technique for visualization of forest fire smoke plumes using MODIS data

Forest fire smoke detection by satellites is important and required for monitoring air pollution and human health. MODIS smoke detection algorithms are under development. The common problem is to separate smoke from clouds. To overcome this issue we propose a new visualization technique of a false-c...

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Bibliographic Details
Published in2012 IEEE International Geoscience and Remote Sensing Symposium pp. 2380 - 2383
Main Authors Nagatani, I., Kudoh, J., Kawano, K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2012
Subjects
Aerosols
Clouds
Fires
forest fire smoke
Image color analysis
image enhancement
Indexes
MODIS
Reflectivity
smoke plume detection
visualization
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Summary:Forest fire smoke detection by satellites is important and required for monitoring air pollution and human health. MODIS smoke detection algorithms are under development. The common problem is to separate smoke from clouds. To overcome this issue we propose a new visualization technique of a false-color composite image that composed of Smoke Reflectance Index (SARI), MODIS channel 7 reflectance, and Water Index (WI). The SARI and WI were developed in this study. The false-color composite image shows smoke in reddish and clouds in pink-white. Smoke pixels are easily identified and sampled. Overall smoke pixels are detected by their training dataset. In this paper, we present a case study of Russia and Mongolian forest fire in 2009. The result of smoke detection was compared to those of existing method. It was confirmed that the proposed method detected smoke pixels more accurately.
ISBN:9781467311601
146731160X
ISSN:2153-6996
2153-7003
DOI:10.1109/IGARSS.2012.6351016