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

Izumi Nagatani, Jun-Ichi Kudoh, Koichi Kawano

研究成果: Paper査読

3 被引用数 (Scopus)

抄録

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.

本文言語English
ページ2380-2383
ページ数4
DOI
出版ステータスPublished - 2012 12 1
イベント2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany
継続期間: 2012 7 222012 7 27

Other

Other2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
CountryGermany
CityMunich
Period12/7/2212/7/27

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)
  • Computer Science Applications

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