1. School of Engineering and Technology Asian Institute of Technology, Thailand Examination Committee: Dr. Nitin Kumar Tripathi (Chairperson) Dr. Roland Cochard Dr. I. V. Murali Krishna Dr. Taravudh Tipdecho BY MD. AHASANUL HOQUE RS&GIS May 2011

2. Introduction  CO 2 is 390 ppm (NASA, 2010).  Increasing by 1.9 ppm/yr (BBC, 2010).  Surface temperature raised by 0.74 ± 0.18 °C (IPCC, 2007)  CO 2 is a prominent greenhouse gas but fundamental for photosynthesis

3. Statement of the Problem  Kyoto protocol : reduce GHGs emission to 5.2% below 1990 levels by 2012. => only 1 year left  About 20 countries – 80% CO 2 world’s emissions.  32 countries and 10 US states - started emission trading scheme.  Countries need to know terrestrial sequestration capacity but conventional method is destructive.  Remote sensing approach - for larger area in quick turn around time and cost effective.

4. Objective of the Study Developing a grid based model for CO 2 absorption by different land cover classes.

5. Methodology Multispectral Satellite Images ASTER 15m Band 321 ASTER 15m Band 321 LANDSAT 30m Band 432 LANDSAT 30m Band 432 MODIS 250m Ref. Image (124) DN to Reflectance Conversion Layer Stacking Subset Image by AOI Atmospheric Correction using FLAASH Model Image Enhancement Contrast Stretching - Histogram Modification Image Enhancement Contrast Stretching - Histogram Modification Re-projection by MRT Supervised Classification Nearest Neighborhood Supervised Classification Nearest Neighborhood Accuracy Assessment Ground Truth data Land Cover Classes Overlay Field Vegetation Inventory Biomass measurement CarbonFix Standard 3.1 Validation Volume Calculation by Allometric Eqn. Generate NDVI Computation of NPP using CASA & SEABAL model Generate NPP/ CO2 Image Masking by Land Covers Above Ground Carbon stock image by land covers Output CO 2 Map

6. NPP = APAR. LUE = NDVI. PAR. LUE LUE = ε 0 * T1 * T2 * Λ (Field et al., 1995) Λ = the evaporative fraction from SEBAL. (Bastiaanssen and Ali, 2001) = 0.5+ (EET/PET) (Field et al., 1995) Where, ε° = globally uniform maximum (2.5g/MJ) and T 1 & T 2 relate to plant growth regulation (acclimation) by temperature Where, NPP=net primary production APAR=Absorbed Photo-synthetically Active Radiation LUE=Light Use Efficiency factor PAR= Photo-synthetically Active Radiation T 2 = 1.185*{1+exp (0.2Topt-10-Tmon)} -1 * {1+exp(-0.3Topt-10+Tmon)} -1 T 1 = 0.8 + 0.02 * T opt – 0.0005 * (T opt ) 2 APAR/PAR~NDVI (Daughtry et al., 1992) CASA (Carnegie-Ames-Stanford Approach) model, to calculate NPP

7. Mathematical Representation of Model Algorithms NDVI = ƒ( NIR, RED) PAR = ƒ (K↓) (W/m2) = 0.51 for Tropical countries (Christensen and Goudriaan, 1993) T 2 = 1.185 *{1+exp (0.2 * 28 -10 – 25 )} -1 * {1+exp(-0.3* 28 -10 + 25)} -1 = 0.0016098 T 1 = 0.8 + (0.02*28) - 0.0005 * (28) 2 = 0.968 Where PET = is potential evapotranspiration = 119.5 mm/month for Thailand (Vudhivanikh V., 1996) and 124.62 mm in December for Nakhon Nayok (Cropwat-FAO, 2006) EET = is the estimated evapotranspiration = 1.6 mm/day for Evergreen Forest in Thailand (Tanaka, N., et al, 2008) and 110.52 mm in December (RID, 2006) LUE = 3.49 for Forest & 3.45 for Open Scrubs

8. Study area  Geographical coordinates 14° 12' 11" North 101° 12' 53" East.  Area of 2,122 km 2

9. Data Used ASTER 15m No. of Cells: 8774320 Area : 197422.2 ha LANDSAT 30m No. of Cells: 2332260 Area : 209903.4 ha MODIS 250m No. of Cells: 32684 Area : 204275 ha

10. Field Data Collection Number of Sample Points : 31 5m 5m Tree Layer 5m 5m Tree Layer Shrubs Layer 1m Shrubs Layer 1m Herb layer Herb layer 15m

11. Tree Volume Measurement Angle Measure (%) Ground Distance Collector ’s height 1.8 m DBH Measurement V T = (DBH/200) 2 x 3.142 x Ht / 3 ( FarmForest Line, 2010) Ht = [Angle(%) x Ground Distance/100] + Collector’s Height (1.8 m)

12. CO 2 sink measurement: Field Method  CFS was created by 60 country organizations in 1999 & released at the Climate Conference in Bali in December 2007.  According to CarbonFix Standard 3.1 (CFS), 2010 Above Ground Woody Biomass = Tree Volume x Biomass expansion Factor x Wood Density x Carbon Fraction x C to CO2 factor Above Ground non woody biomass = Fresh biomass x Dry to wet ratio x Carbon Fraction x C to CO2 factor

13. Normalized Difference Vegetation Index (NDVI) Results & Discussion ASTER 15m No. of pixel : 8774320 LANDSAT 30m No. of pixel : 2332260 MODIS 250m No. of pixel : 32684

14. Landcover classification images ASTER 15m Accuracy: 89.36 % LANDSAT 30m Accuracy: 82.98 % MODIS 250m Accuracy: 72.34 %

15. Model Results of NPP ASTER 15m Sinked CO 2 = 6.12 ml. ton LANDSAT 30 m Sinked CO 2 = 8.83 mil. ton MODIS 250m Sinked CO 2 = 10.39 mil. ton

16. CO 2 sink = 3.25 mil. ton CO 2 sink = 1.85 mil.tonCO 2 sink = 3.23 mil.ton LANDSAT Primary Forest LANDSAT Sparse Forest LANDSAT Open Scrubs CO 2 sinking by landcovers

17. Validation of the Model Results big treesnew trees large healthy vegetation Crop residuals

18. R² = 0.754 R² = 0.697R² = 0.029 Validation of the Model Results

19. R² = 0.615R² = 0. 657R² = 0.058

20. Normalizing LANDSAT & MODIS to ASTER Converting value to Same Unit area 15m x 15m multiplied By 4 to Landsat & 277 to Modis

21.  LANDSAT 30m & MODIS 250m Image acquisition date is same  LANDSAT 30m NDVI & MODIS 250m NDVI 41 points correlation is 0.739  Therefore, assuming LANDSAT 30m result is actual CO 2 sink value  Actual CO 2 sink = 0.801 x MODIS 250m sink (ton)

22. Downscaling MODIS 250m to MODIS 30m MODIS 30m NDVI MODIS 30m Land Cover Classes No. of pixel = 2332116 Sinked CO2 =2.66 mil. ton

23. Downscaling MODIS 250m to MODIS 15m No. of Cells = 9515056 Sinked CO2 = 10.85 mil. ton MODIS 15m NDVI MODIS 15m Land Cover Classes

24. Comparison among downscaled image and other images sink Pixel based Value of each images sink Normalized sink value of each image

25. MODIS 250m to LANDSAT 30m sink ASTER 15m, LANDSAT 30m & downscaled MODIS sink comparison  LANDSAT 30m sink = 0.79 x downscaled MODIS 30m sink NDVI correlation between LANDSAT 30m and MODIS 30m R² = 0.719

26. Conclusion  CASA algorithms can give the precise and accurate result if SEBAL data are of same time  The finer the satellite resolution the more accurate CO 2 result.  Medium resolution LANDSAT provided net CO 2 sink stock estimate as 8.33 million tonnes of CO 2 in Nakhon Nayok.  Scale factor 0.801 for MODIS 250m for achieving the amount of LANDSAT 30m sequestered CO 2.  A general average stock can be assumed to meet Kyoto Protocol or CDM target of carbon quantities.  MODIS data can be used to find terrestrial sink accurately.

27. Recommendations  Proposed methodology with MODIS can be used for regional, or global scale carbon sequestration measuring and monitoring tool.  Research to measure the CO 2 emission data of the study area & required afforestation for remaining CO 2. MODIS 250m CO 2 Map

28. With deep gratitude to Govt. of Japan for supporting to study in AIT. Thanks to all Let us use MODIS free data to find more CO 2 sinks & make a healthier and green environment.