Abstract
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.
Original language | English |
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Pages | 2380-2383 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2012 Dec 1 |
Event | 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany Duration: 2012 Jul 22 → 2012 Jul 27 |
Other
Other | 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 |
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Country/Territory | Germany |
City | Munich |
Period | 12/7/22 → 12/7/27 |
Keywords
- MODIS
- forest fire smoke
- image enhancement
- smoke plume detection
- visualization
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- Computer Science Applications