Multi-Scale Regional Forest Carbon Density Estimation Based on Sequential Gaussian Co-Simulation

Based on Forest Inventory （plot） data in Xianju County， Zhejiang in 2008 and the Landsat TM image data collected in the same region in 2007，the aboveground forest carbon density and its distributions at 30m × 30m and 270m×270m resolution was estimated and the results analyzed comparatively by applying sequential gaussian cosimulation The results showed that the aboveground forest carbon density of Xianju County was continuously distributed， which was surrounded by high carbon density of forest land and the intermediate region was filled with the majority of low carbon density of nonforest land. The total carbon is 5283789.63Mg based on the estimation by rardomly sampling method. With the sequential gaussian cosimulation， the sum of the carbon is 5692875.69 Mg and the square R of model is 06203 in 30m×30m resolution. Comparing with the result in 270m × 270m resolution， the former total carbon is larger， the range of distribution is wider and the model′s precision is higher. The result showed that sequential gaussian cosimulation which considers the spatial distribution of carbon density is closer to the estimation from the plot data， the carbon density distribution is more reasonable and the ability to represent the continuous changes of carbon distribution is better.