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Toward Near Real Time Forest Fire Monitoring in Thailand Honda Kiyoshi and Veerachai Tanpipat Space Technology Applications and Research, School of Advanced.

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Presentation on theme: "Toward Near Real Time Forest Fire Monitoring in Thailand Honda Kiyoshi and Veerachai Tanpipat Space Technology Applications and Research, School of Advanced."— Presentation transcript:

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 1.Objectives 2. Background of Forest Types and Forest Fire in Thailand 3. Fire Experiment 4. Conclusions of Fire Experiment 5. NDVI of MODIS and Ground Truth at Fire Experiment 6.MODIS Scatter Plot and Results 7.Linear Extrapolation Concept 8.Results of Combination Method 9.LANDSAT Burnt Scars Products 10. MODIS and LANDSAT Burnt Scars Comparison 11.Conclusions

3 Objectives To improve the forest fire burnt 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 Causes 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. On the other hand, the remaining 60 percent, the Deciduous Forest is composed of species with leafless periods.

7 Forest TypesSurface Fire Undergroun d Fire Crown Fire Evergreen 1.Tropical Rain Forest 2.Dry Evergreen 3.Coniferous 4.Mangrove 5.Swamp 6.Beach XXXXXXXX X X Deciduous 1.Mixed Deciduous 2.Dry Dipterocarp 3.Savanna XXXXXX Plantation 1.Pine 2.Teak 3.Eucalyptus XXXXXX X

8 Fire Experiment

9

10 Fire Experiment Results

11 Conclusion of Fire Experiment There are two results that can be concluded from this experiment. The first is that the afternoon temp. difference between burnt and un-burnt area can be detected by a portable 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 burnt scars detection and monitoring.

12 NDVI of MODIS and Ground Truth of the Fire Experiment 10 Feb

13 The MODIS NDVI values of burnt and un-burnt pixels where the burnt pixel is detected in 29 March 2002 MODIS image 11 Mar

14 The Scatter Plot of Collective Burnt (1037 samples) and Un-burnt (879 samples) Pixels

15 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

16 Linear Extrapolation Concept Diagram

17 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

18 The preliminary results from equation Y = 3212 + 1.277 Band1. Where Band2 – Y > 0 is Unburned and < 0 is Burned area. 9 Feb 29 Mar21 Apr9 May

19 21 Apr Band2 21 Apr Predicted, Feb9 & Mar29 Accept Negative Only 21 Apr Y = 3212 + 1.277 X Masking by Negative Results of Combination Method

20 16 February 02 LANDSAT 7 ETM+ 4 March 02 LANDSAT 7 ETM+ 5 April 02 LANDSAT 7 ETM+ LANDSAT Burnt Scars Products

21 MODIS 9 Feb MODIS 21 Apr MODIS 9 May LANDSAT 16 Feb LANDSAT 4 Mar LANDSAT 5 Apr MODIS and LANDSAT MODIS 29 Mar

22 Burnt Area Accumulated from Satellite Images

23 Conclusions The proposed method is the burnt and un- burnt linear threshold equation; Y = 3212 + 1.277 Band 1; where Band2-Current – Y < 0 is potential burned area; combining with the 2-date linear extrapolation method. This method is near-real-time burnt scars detection which will be better use in order to monitor burnt scars movement and forest fire activities.

24 Conclusions Continue New burnt scars locations of MODIS and LANDSAT are matching well. Burnt area accumulation numbers of both MODIS and LANDSAT are closed, so it works well to detect MODIS burnt 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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