| dc.description.abstract | Spatial interpolation is a calculation process to estimate the value at unmeasured areas with the assumption that the data attributes have continuos spatial relationships. The use of IHMB sample data for estimating standing stock and biomass distribution is an interesting challenge of task, particularly in supporting the REDD+ program. In this study, several interpolation methods were examined to obtain the best method to be used in estimating the standing stock and biomass based on IHMB data in dry land forests. The IDW (Inverse Distance Weight) and Kriging method were tested for interpolating all size timber class (D>10 cm), commercial tree species (D>40 cm). The spatial analysis performed includes isolines development, construction of TIN (Triangulated irregular network), conversion to grid, grid to vector conversion and calculating the mean. This study shows that the IDW of power 3 provides the best estimation for interpolating all tree size from all species (D>10 cm), comerciall species (D>40 cm) and biomass, respectively. For the Kriging Method, the best estimation was derived from spherical and circular approaches. In general, the IDW method gives slightly better estimation than the Kriging method on estimating spatial distribution of standing stock and biomass. | en |
