Application Of Multi-dimensional Sphere Model On Forestry Monitoring And Trend Analysis

This paper introduces application of Arithmetic Series, Geometric Series, and the Multi-Dimensional Sphere Model (MDSM) to forestry monitoring program. This research uses DBH,height,volume,basal area,and canopy density as five axis to build a five dimensional Variable Space,5-Space. Thus an identity in the5-space can be used to expresse the forest state. The dynamics of the identity will indicate the changes and trend of the forest, and may discover the mechanics and speed, and environmental changes of the forest.In this research, the Arithmetic Series found the increasments of DBH,height,volume,basal area,and canopy density. The order of the increasements of the five components is:canopy density<DBH<height<basal area<volume. The Geometric Series discovered the increasing rate of the components, and they are in the order of: DBH<basal area<height<volume<canopy density. After filter out the system noise, the MDSM predicted theDBH,height and basal area are relatively decreasing,but volume and canopy density are relatively increasing. The five components of the trend vector are in the order of:DBH<basal area<height<volume<canopy density.Six samples of over-mature stands data collected in2003and repeated in2008from Great Xing an Mountain were applied in this research, to predict the2013forest state.The predicted values are close to an natural matured forest, and relatively matching with previous studies conducted by other scientists. Therefore, the paper considered the MDSM can relatively predict the future state of forest, or MDSM can be applied to forest monitoring program. However, much more work needs to be done before formal application.