Forest vegetation carbon patterns are significant for evaluating carbon emission and accumulation. Many methods were used to simulate patterns of forest vegetation carbon stock in previous studies, however, uncertaint...Forest vegetation carbon patterns are significant for evaluating carbon emission and accumulation. Many methods were used to simulate patterns of forest vegetation carbon stock in previous studies, however, uncertainty apparently existed between results of different methods, even estimates of same method in different studies. Three previous methods, in- cluding Atmosphere-vegetation interaction model 2 （AVIM2）, Kriging, Satellite-data Based Approach （SBA）, and a new method, High Accuracy Surface Modeling （HASM）, were used to simulate forest vegetation carbon stock patterns in Jiangxi Province in China. Cross-valida- tion was used to evaluate methods. The uncertainty and applicability of the four methods on provincial scale were analyzed and discussed. The results showed that HASM had the high- est accuracy, which improved by 50.66%, 33.37% and 28.58%, compared with AVIM2, Kriging and SBA, respectively. Uncertainty of simulation of forest biomass carbon stock was mainly derived from modeling error, sampling error and statistical error of forest area. Total forest carbon stock, carbon density and forest area of Jiangxi were 288.62 Tg, 3.06 kg/m2 and 94.32×109 m2 simulated by HASM, respectively.展开更多
基金National Fundamental R&D Program of the Ministry of Science and Technology of the People’s Republic of China,No.2013FY111600-4
文摘Forest vegetation carbon patterns are significant for evaluating carbon emission and accumulation. Many methods were used to simulate patterns of forest vegetation carbon stock in previous studies, however, uncertainty apparently existed between results of different methods, even estimates of same method in different studies. Three previous methods, in- cluding Atmosphere-vegetation interaction model 2 （AVIM2）, Kriging, Satellite-data Based Approach （SBA）, and a new method, High Accuracy Surface Modeling （HASM）, were used to simulate forest vegetation carbon stock patterns in Jiangxi Province in China. Cross-valida- tion was used to evaluate methods. The uncertainty and applicability of the four methods on provincial scale were analyzed and discussed. The results showed that HASM had the high- est accuracy, which improved by 50.66%, 33.37% and 28.58%, compared with AVIM2, Kriging and SBA, respectively. Uncertainty of simulation of forest biomass carbon stock was mainly derived from modeling error, sampling error and statistical error of forest area. Total forest carbon stock, carbon density and forest area of Jiangxi were 288.62 Tg, 3.06 kg/m2 and 94.32×109 m2 simulated by HASM, respectively.
