Biomass estimation based on simultaneous use of standwise forest inventory data, ASTER and MODIS satellite data

According to the Intergovernmental Panel on Climate Change Good Practice Guidance (IPCC GPG) (IPCC 2003), remote sensing methods are especially suitable for independent verifying the national Land Use, Land-Use Change, and Forestry (LULUCF) carbon pool estimates, especially the aboveground biomass. In the present study, we demonstrate the potential to integrate standwise inventory data, ASTER and MODIS satellite data for characterizing stand volume (m ha) and aboveground biomass of trees (t ha) in boreal forests landscape in the southern Finland. The simultaneous use of high and coarse resolution images is essential especially when estimating these forest characteristics for extensive areas where ground data are not available or are limited. In this study, the regression models computed using standwise forest inventory data and ASTER satellite images were utilized with the MODIS data.