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Journal of the Indian Society of Remote Sensing, Vol 35, No. 4, 2007
METHANE EMISSION MODELLING USING MODIS THERMAL AND O P T I C A L DATA: A CASE S T U D Y ON G U J A R A T RESHU AGARWAL @AND J.K. G A R G Space Applications Center (ISRO), Ahmedabad-380015, India @Corresponding author :
[email protected]
ABSTRACT
Wetlands are one of the most important sources of atmospheric methane (CIt4) contributing about 22% to the global methane budget. But to improve estimates of CH4 emission at regional and global scales there is a need to observe the sources such as wetlands frequently and develop process-based models. In this regard, wetland inventory using satellite remote sensing data has conventionally been carried out by analysis of optical data. Due to thermal inertia differences emittive thermal channels data has shown protmse to provide highly critical intbrmation about wetlands such as water spread, aquatic vegetation and mud flats etc. Thermal channels data of MODIS (Moderate Resolution Imaging Spectroradiometer) sensor with a spatial resolution of 1km and swath of 2330 km is emerging as the key source of remote sensing data for global/ regional wetland estimation and assessment of green house gas emission. In the present study MODIS thermal channels (31 and 32) and optical channels (1, 2, and 3) data have been used lbr evaluating methane emission from wetlands in Gujarat. An empirical model based on temperature and productivity has been used to investigate the response of methane emission from different sources Model has the potential to estimate country level methane emission based on salellite remote sensing in conjunction w~th collateral data/information In this study, MODIS data of two dates pertaining to Gujarat have been analyzed and results compared with respect to methane emission.
Introduction
Methane is considered as the most significant natural greenhouse gas due to its global warming potential. Methane has a large radiative effect with one unit m a s s o f CH 4 p r o d u c i n g 21 t i m e s the Recewed 17 Aprd, 2007, in final forn3 28 .lune, 2007
radiative effect o f one unit mass o f CO2 According to International Panel on Climate Change (IPCC, 1998) since 1750 a t m o s p h e r i c c o n c e n t r a t i o n o f methane has increased by 150 per cent (as o f 1998) from approximately 700 to 1,745 parts per billion by v o l u m e ( p p b v ) . W e t l a n d s are one o f the most
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Reshu Agarwal and J.K. Garg
important terrestrial sources of C H 4 because of the presence of anaerobic conditions, high organic matter content, and large area. Methane emission from wetlands is dependent on climate/weather conditions such as temperature and humidity besides water spread. Objective global estimates of methane from wetlands are still not available due to non-availability of temporal data on "extent and types of wetlands". Problem is further compounded by absence of wetland type/condition specific methane emission factors. There have been several attempts to use measured rates of emission from wetlands for global total CH 4 emission (Matthews et al., 1987 and Sheppard et al., 1982). Quite a few studies have also used process-based models (Cao et al., 1996, Walter et al, 2000 and Walter et al., 2001). In the present study an effort has been made to estimate methane emission from different sources using remotely sensed thermal data and other collateral information from literature. Ill this regard, MODIS (Moderate Resolution Imaging Spectroradiometer), an EOS instrument, has shown promise for global/regional wetlands assessment. The objective of the present work is to develop a methodology that can be applied to simulating methane emission from different methane emitting classes (water, mud flats, swamp/marsh and salt flats). The objective is to have a tool that can be used to study seasonal distribution of methane emission.
regions namely north Gujarat, south Gujarat, Saurashtra peninsula and Kachchh. Out of total geographical area of Gujarat, wetlands cover 27.17 lakh ha (Garg et al., 1998). The average maximum temperature is 39.9~ and average minimum temperature is 12.5~
Data Used MODIS ( M o d e r a t e Resolution lmaging Spectroradiometer) data has 36 bands with spatial resolutions 250 m (I and 2 bands), 500 m (3-7 bands) and 1000 m (remaining bands). MODIS provides images o f daylight reflection and day/night emission o f the earth, repeating global coverage every one or two days. MODIS data of January [6, 2005 and February 16, 2005 have been used in the present study. Bands 31(10.28-11.72 jam) and 32(11.78-12.28 p,m) are used for land surface temperature (LST) estimation. MODIS LST product is used for the validation of land surface temperature retrieved by constant emissivity method (Kahle, 1987).
Methodology Methane emission from tropical wetlands has been modeled using a two factor empirical model. The two factors are temperature and productivity. The summary of the adopted methodology for this study is shown in Fig. I. Estimation o f M e t h a n e E m i t t i n g A r e a
Study Area Gujarat State, covering an area of 1,95,980 km 2 (6% of the total area of India), situated on the west coast of India between 2002 ' and 24041 ' N latitude and 6808 ' and 74~ ' E longitude has been chosen for this study. The tropic of cancer passes through the districts of Kacbchh, the northern tips of Surendranagar and Ahmedabad and the district of Mahesana and Sabarkantha. On the basis of geographical features, Gujarat is divided into four
Optical bands (1,2, and 3) of MODIS data have been utilized for delineation of methane emitting sources. Hierarchical classification has been carried out over georeferenced optical MODIS images. Four methane-emitting classes viz. water, mud flats, swamp/marsh and salt flats have been delineated and area estimated. Remaining classes have been clubbed t o g e t h e r and labeled non-methane producing area. Classified images of two different dates (16 January 2005 and 16 February 2005) are shown in Fig.2 (a) and 2(b).
Methane Emission Modelhng using MODIS Thermal and Opncal Data...
325
[ MODIS l] DATA
LSTproduct
Thermalbands (31 and 32)
i Comparlsonand ) I LST(constant 1 vahdanon ~ emlsswltymethod) T factor
Ophcalbands (I,2 and 3) Literature
Hmrarchal classllicatmn Extracnonof classes
Producnwty
Observed methane
M e t h a n e Emission Model
Estimated CH4 emission Fig. I. Methodology Framework L S T Estimation and Validation
Land surface temperature (LST) is one of the important parameters for studying land surface. In the present study LST has been used as one of the major parameters for estimation of emitted methane. Many methods of LST determination such as Spectral ratio method (Watson, 1982), reference channel method, emissivity normalization method, alpha residue method (Li, 1999) and Split window method (Wan and Dozier, 1996 and Wan, 1997) have been propounded by various researchers. However, one of the major-problems encountered in estimating kinetic temperature of various land cover types is the emissivity. Split window method (SWM) corrects for atmosphere's effects based on the differential absorption in adjacent infrared band, but requires the exact emissivity for each type of feature. In the present research constant emissivity method (CEM) given by Kahle (1987) has been used for estimating the temperature of areas of interest.
MODIS thermal channels data (31, 32) have been used as input. First the DN values are converted into radiance values using the following relation: Radiance = offset + bsf* DN
(1)
where bsf is band scale factor available in header file) and DN is Digital Number Assuming constant emissivity, as per different land uses in 31 ~t band (10.28-11.77gm), temperature (T) is calculated for each pixel using Planck's Law: T-
Where, C~ = Ci = = )v = R =
C,
2~hc2=3.74183 x 10-~6wm 2 1.4388• 10 ZmK Emissivity Wavelength Radiance
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Reshu Agarwal and J.K. Garg
Fig. 2. (a) Classified image of 16 January 2005
Fig. 2. (b) Classified image of 16 February 2005
Methane Emission Modclhng using MODIS Thermal and Optical Data.. Using these t e m p e r a t u r e s , pixel-wise emissivities have been calculated in 32 ''d band (I 1 77-12.28 lain) using the relation
g=--e
(3)
cI
These emissivities have been used to rectify the temperature in 31 st band. A program by Agarwal et al. (2005) using CEM has been used to calculate plxel-wise land surface temperature from MOD1S thermal data. In order to validate the restllts using constant emissivity method in areas of interest, MODIS LST product of the same date has been used. The variation between two methods is given in Table 1. T a b l e 1 : Comparison of temperature derived using
SWM and CEM method SWM
("C)
CEM
(,C)
LOCATION
327
from 30~ to 40~ (Liu, 1996). Inclusion of productivity factor is based on the fact that methane emission is mainly driven by photosynthetic activity. Methane emission from wetlands is described by the following equation: ECH4 :
Eo[~ 9 Fi-A. P
(4)
Where gobs is the observed methane flux from different classes, F t is T factor, A is area and P is productivity factor. Productivity and observed methane, shown in Table 2 for all the four wetlands have been used from Sheppard et al. (1982). T a b l e 2: Productivity and Methane emission
fluxes for different classes S o u rces
Productivity
Flux
(g/mS/year) Water
0.25
3.5
Mud flats
1.00
2.25
Swamp/marsh
0.25
25.1
Salt flats
1.00
1.4
28.2
28.3
28.1
284
T factor is defined as follows (Liu, 1996):
40.4
40.6
30.6
31 3
F(Ts) F, - F(Ts)
39. l
39.4
o0.~
o0.o
30.8
31.3
32.1
32.6
41.7
41.6
Nal sarovar
,}
Mud fiats
(5)
Where, F(Ts)Salt fiats
Estimation o f M e t h a n e E m i s s i o n
Methane emission has been estimated using a two-factor empirical l,nodel. T factor (temperature related factor) is used to model the change in methanogenic activity as a function of temperature. E x p e r i m e n t s have shown that the optimal temperature for the majority of methanogens ranges
e 0334(Ts-23) 1 + e 0 334(Ts-23)
(6)
In the above equation Ts is the temperature in ~ which has been calculated for each pixel using constant emissivity method. F(Ys) is the mean o f F(Ts) o v e r land. Coefficients of this exponential equation have been taken from Liu (1996). Optical bands of MODIS data (1,2 and 3) and NDVI layer have been used for hierarchical classification to classify different classes, which are responsible for emission of
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Reshu Agarwal and J.K. Garg
methane. Subsequently, classified image and F t image have been used for getting the class statistics for all the four classes. A semi-automated procedure incorporating all steps required for data analysis and methane estimation has been developed. Results and Discussion
In the present study, emission of methane from different sources has been modeled based on temperature and productivity. Two date MODIS data have been processed for the state of Gujarat for obtaining temperature and methane emitting pixels for four classes viz. water, mud flats, swamp/marsh and salt flats. Emissive bands (band 31 and band 32) of M O D I S data h a v e been a n a l y z e d for estimating temperature using CEM while optical bands (1,2 and 3) are used for delineating methaneemitting pixels using hierarchical classification.
A comparative study has also been done for two dates separated by a month (16 January 2005 and 16 February 2005) to study the variation in the emission of methane. Figure 3 (a) and Fig.3 (b) are the p r o c e s s e d i m a g e s through model, which pictorially indicate the emission of methane from various sources. Results of methane emission on two dates are given in Table 3. Annual methane flux (Sheppard et al., 1982) has been used to model methane emission and thus the values give an indication of the total amount of annual methane emission. It assumes that the same environmental conditions persist throughout the year. However, weather conditions do change in various parts of the year and in view of this segmentation has been done to have an idea about monthly methane emission estimates. The amount of emitted methane in January 2005 was 618 kg with 4832 km 2 methane emitting area while in the month
Fig. 3. (a) Methane emission on 16 January 2005
Methane Emission Modelling using MODIS Thermal and Optical Data...
329
Fig. 3. (b) Methane emission on 16 February 2005
Table 3: Methane emitting areas and estimates in Gujarat Classes
Area (km 2) 16 January 2005
Water Mud flats Swamp/marsh Salt flats
Total
Estimated Ch 4 Emission (kg)
16 February 2005
16 January 2005
16 February 2005
414
384
35
24
1383
1898
118
169
472
458
42
35
2563
1959
423
300
4832
4699
618
528
of February 2005 this amount was 528 kg with 4699 km 2 methane emitting area.
Conclusion As assessment o f monthly global/regional methane budget is required for estimating annual
methane emission from wetlands and other sources. In this regard MODIS data holds a great potential in bridging the existing lacuna and accordingly an attempt has been made to model methane from wetlands and other sources for the state of Gujarat as a test study. An empirical model has been developed using temperature, productivity, area and
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Reshu Agarwal and J.K Garg
observed methane fluxes for estimation of methane emissions. Based on this approach an assessment of methane emission from Gujarat for two dates has been made. Temperature has been derived using Constant Emissivity Method and validated with the MODIS LST product. It has been found that for wetland features in Gujarat, temperature estimated using CEM is very close than that of MODIS LST product as given in Table 1. Productivity and methane fluxes have been used from the work of Sheppard et al. (1982). Results show that emitted methane in January 2005 was 618 kg with 4832 km 2 methane emitting area while in the month of February 2005 this amount was 528 kg with 4699 km 2 methane emitting area. It may be mentioned here that data on daily methane fluxes from different sources in India" is not available and it is planned to develop model(s) sensitive to variations/changes in daily temperature and other meteorological variables.
Acknowledgements Authors express thanks to R.R. Navalgund, Director SAC (Space Applications Centre) for his keen interest and encouragement. Thanks are also due to J.S. Parihar, G r o u p Director, AFEG (Agricultural, Forestry and Environment Group) and S. Panigrahy, Head, EFD (Environment and Forest Ecosystem Division) for guidance and critical evaluation. We also thank Ajai, Group Director, MESG (Marine and Earth Sciences Group) and Shiv Mohan, Head, ATDD ( A d v a n c e Techniques Development Division) in the initial phase of the work. Thanks are also due to Ritesh Agarwal and J. Antony for useful suggestions and help in carrying out the work.
Constant Emissivity Method and its utility in land surface delineation MODIS Data Utilization Workshop, held at Space Applications Center (ISRO), Ahmedabad from April 19-20, 2005. Cao, M, Marshell, S. and Gregson, K. (1996). Global carbon exchange and methane emissions from natural wetlands: Application of a process based model. Journal of Geophyszcal Research, 101(14) 39914,414. Garg, J.K., Singh, T.S. and Murthy, T.VR. (1998). Wetlands of India Project Report: RSAM/SAC/ RESA/PR/01/98.239p. IPCC (1998). The regional impacts of climate change. An assessment of vulnerability, Cambridge University Press. Kahle, A.B. (1987) Surface emlttance, temperature and thermal inertia derived from thermal infrared multispectral scanner (TIMS) data for Death Valley, California. Geophysics, 52: 858-874. Li, Z.L., Becker, F., Stoll, M.P. and Wan, Z (1999). Evaluation of six methods for extracting relative emissivity spectra from thermal infrared images. Remote sensing of Env:ronment, 69:197-214. Liu, Y. (1996). Modelling the emission of nitrous oxide (NzO) and methane (CH4) from the Terrestrial biosphere to the atmosphere. MITjoint Program on the Science and Policy of Global Change, Report No.10. Matthews, E and Fung, 1. (1987). Methane emission from natural wetlands' Global distribution, area and environmental characteristics of sources, Global Bzogeochemlcal Cycles, 1: 61-86, Sheppard, J.C., Westberg, H., Hopper, J.F., Ganesan, K., and Zimmerman, P. (1982). Inventory of global methane sources and their production rates. J Geo Res., 87:1305-1312
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