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Toward Near Real Time Forest Fire Monitoring in Thailand Honda Kiyoshi and Veerachai Tanpipat

Toward Near Real Time Forest Fire Monitoring in Thailand Honda Kiyoshi and Veerachai Tanpipat Space Technology Applications and Research, School of Advanced Technologies, Asian Institute of Technology, Km 42 Phaholyothin Road, P.O. Box 4,Klong Luang, Pathumthani 12120, Thailand. Contents.

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Toward Near Real Time Forest Fire Monitoring in Thailand Honda Kiyoshi and Veerachai Tanpipat

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  1. Toward Near Real Time Forest Fire Monitoring in Thailand Honda Kiyoshi and Veerachai Tanpipat Space Technology Applications and Research, School of Advanced Technologies, Asian Institute of Technology, Km 42 Phaholyothin Road, P.O. Box 4,Klong Luang, Pathumthani 12120, Thailand

  2. Contents • Objectives • Background of Forest Types and Forest Fire in Thailand • Fire Experiment Results • Conclusion of Fire Experiment • The summary of MODIS and ground truth of the experiment area • The MODIS NDVI values of burned and unburned pixels where the burned pixel is detected in 29 March 2002 MODIS image • MODIS Scatter Plot • The linear equation which can separate burned and un-burned pixels MODIS Time series of the of the experiment area • Results combination method • MODIS and LANDSAT Comparison • 12 Conclusion

  3. Objectives To improve the forest fire burn scars detection in near real time To improve the estimation of high resolution imageries (LANDSAT) by using the low resolution imageries, Moderate Resolution Imaging Spectroradiometer (MODIS).

  4. Background Forest Fire in Thailand Forest fires in Thailand annually occur during the dry season from December to May with their peak in March. Fires, mostly classified as surface fires, mainly take place in; Dry Dipterocarp and Mixed Deciduous Forest and Forest Plantation, and to some extent in Dry Evergreen Forest, Hill Evergreen Forest or even in some parts of Tropical Rain Forest.

  5. The Cause of Forest Fire The main human activities which cause forest fire are gathering of forest non-timber products, agricultural debris burning, incendiary fire, hunting, and carelessness where the gathering forest non-timber products is the main cause.

  6. Forest and Forest Fire Types Thailand has two dominate vegetation types, Evergreen and Deciduous. The Evergreen Forest is composed of a great proportion of the non-leaf shedding species and covered about 40 percent of the total forested area. It can be classified into Tropical Rain Forest, Dry Evergreen Forest, Hill Evergreen Forest, Coniferous Forest, Mangrove Forest, Swamp Forest, and Beach Forest. On the other hand, the remaining 60 percent, the Deciduous Forest is composed of species with leafless periods.

  7. Fire Experiment

  8. Conclusion of Fire Experiment There are two results that can be concluded from this study.The first is that the afternoon temperature difference between burnt and un-burnt area can be detected by a thermal sensor within 70 days after forest fires.The second is that the reflectance value of vegetations will drop right after the fire and start to increase and reach its healthy condition around 80 days after with normal seasoning.Moreover, the results form the field experiment can improve the usage of multi-temporal satellite remote sensing to improve the typical LANDSAT 16 days revisit cycle of burned scars detection and monitoring.

  9. The summary of MODIS and ground truth of the experiment area

  10. The MODIS NDVI values of burned and unburned pixels where the burned pixel is detected in 29 March 2002 MODIS image

  11. The summary of the collective burned (1037 samples) and unburned (879 samples) pixels

  12. The linear equation which can separate burned and un-burned pixels is Band 2 = 3212 + 1.277 (Band1). MODIS 21 April 2002 burned scar detection applying Band 2 = 3212 + 1.277 (Band1) where the red is the burned area and the blue is water boundary

  13. MODIS Time series of the of the experiment area with 1-2-NDVI band combination, from the top left to right are 9 February, 16 February, 11 March, 29 March, 21 April, and 9 May.The big fire occurred late evening of 11 March 2002

  14. 29 Mar 21 Apr 9 May 9 Feb The preliminary results from equation Y = 3212 + 1.277 Band1. Where Band2 – Y > 0 is Unburned and < 0 is Burned area.

  15. 21 Apr Predicted, Feb9 & Mar29 Two Date Results Accept Negative Only 21 Apr Band2 21 Apr Y = 3212 + 1.277 X Masking by Negative

  16. 16 February 02 LANDSAT 7 ETM+ 5 April 02 LANDSAT 7 ETM+ 4 March 02 LANDSAT 7 ETM+ LANDSAT Products

  17. MODIS 9 Feb MODIS29 Mar MODIS9 May MODIS 21 Apr MODIS and LANDSAT Comparison LS 16 Feb LS 4 Mar LS 5 Apr

  18. Conclusions In conclusion, the proposed method is the burned and unburned linear threshold equation Y = 3212 + 1.277 X; where Band2 – Y < 0 is potential burned area; combining with the 2-date linear extrapolation method. This method is near-real-time burned scars detection which will be better in order to monitor burn scars movement and forest fire activities. Burned scars locations validation confirms that it works well to detect MODIS burned scars of Dry Dipterocarp and Mixed Deciduous Forest in Huai-Kha-Kaeng Wildlife Sanctuary as can be evidenced from the results presented.

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