| Forest fire, as a main factor in forest ecosystem, played an important role in atmospheric chemical cycles and the carbon cycle. The high frequency of forest fire will not only detory the ecosystem but also result in massive release of carbon greenhouse gases. The forest fire estmissions is mainly in the form of CO2and CO, and others being emitted into atmosphere as CH4, multi-carbon hydrocarbons and volatile organic oxides. This will be breaking the balance of carbon in atmosphere, and then making a critical effect on the global climate environment. The research on the relationship between forest fire and carbon emission will contribute to understanding of how the impact that fire on global carbon cycle is and improvement of strategies of fire management. The estimation of composition and release of fire gas is a basic work for the research of atmosphere environment.There are four main research aspects (RA) in this study based on MODIS, TM remote sensing data, historical fire and forest survey data RA (1) estimating the consumption of forest fuel, and emission of polluting gas emission; RA (2) establishing the estimation and consumption model of forest fuel load; RA (3) developing the model of emission of forest fire; RA (4) evaluating the loss of forest fire and estimating the emission of polluting gases. The detailed work as follows:Preprocessed the remote sensing data,Which includes geometic and radiometric correction. Smooth processed the multi-temporal remote sensing data and completed the basic work of getting remote sensing information.Completed forestfuel classification based on MODIS and proved that appropriate classi-ficationmethodsand the participation of other necessary data can obtain more satisfact-ory resolution of classification. The results showed that the resolution based ondecision tree methodis83.2%, higher than supervised classification in terms of TM data.This resolution can meet the production needs. The keys ofdecision tree method are getting the threshold of surface features and developing a suitable rule of classification.However, accessibility and quantity of TM and MODIS images are able to affect the classification accuracyofthe com-bustibles.In this study, we estimated the burned area using mixed-pixel decomposition techni-que based on MODIS data. After pixel decomposition, the resolution of pixel can reach about92%, and the total precision can get90%, basically putting an end to the problem that extracting pixel accuracy of non-vegetated areas and the fire edge is low. Compared with conventionalaircraft, this method is more convenient in operation on large spatial scales and more time-sensitive also. Furthermore, it has high level of timeliness and can meet the production needs better than high-resolution data.Estimated the burned area of forest fire in798highland of Songling, which is242,030hectares totally, including severe fire (23,781ha), moderate fire (145,408ha) and low-intensity fire (72,964ha) and the percentage is9.82%.60.05%,30.13%correspondingly.Established a TM image-based estimation model of forest fuel load, then deducted the fuel load of entire Daxing'an mountains based on the model. We obtained a resasonable resolution; however, a further improvement is still needed. The Partial Least Squares and Second-order Least Squares models have been used to deduct the forest fuel load in this study.We made a comparison between these two models in terms of different statistics and the results indicated that Second-order Least Squares model is superior over Partial Least Squares and the function of estimation models of thearbor, shrub layer, surface fuel are as follows:Y=4.542-3.226×B2+2.126×B3-1.524×B5+0.432×Prin2+0.469×ent2+39.706×sec2+70.628×corr4+0.179×DBH,Y=8.975+0.043×B3-0.008×54-0.256×homo1+0.144×cont6+0.692×DBH.Completed the estimation the consumption of forest fuel in798high-land of Songling. The total loss of fuel load of canopy shrub is2946805.78t in different fire severity, in which Larch canopy shrub is1503946.10t accounting for51.04%;Mixed coniferous canopy shrub is872662.73t (29.73%);Broad-leaved mixed canopy shrub is566631.95t (19.23%).Besides, there is a significant distinction between different severity of fires, such as sever fire caused a667515.03t fuel load loss occupied22.65%; meanwhile,moderatefire and low intensity fire lead to1962732.38t and316557.36t respectively fuel load loss and accouting to66.61%.10.74%of total loss of fuel load. The consumption of surface fuel load in798high-land of Songling is2083668.65t, in which the number of burned fuel load by high intensity fire, moderate fire,low intensity fire is226286.75t,1427932.29t,429450.04t respectively.This paper, the emission factor wasused to estimate the emission of gases from forest fires. The results revealed that there were149187.66tCO2emitted from forest fire, in which88110.43t come from canopy shrub fuel,61077.23tfrom surface fuel. The total amount of CO was12010.07t and canopy shrub fuel and surface fuel12010.07t and occupied9177.63trespectively.The total amount of CH was1925.41t, canopy shrub fuel1512.15t and surface fuel413.26t. The total amount of NO was470.76t, canopy shrub fuel272.19t and surface fuel198.57t. The total amount of SO2was658.77t, canopy shrub fuel301.07t and surface fuel357.70.
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