| Based on the field survey subcompartments data,the paper took the Pinus massoniana of the Hetian and Sanzhou in Changting county in Fujian Province as the research object, and used the factor between volume and biomass to obtain the unit biomass of standard plot. Based on the data processing and the matching of remote sensing images,DEM and forest resource data for subcompartments, to extract the vegetation index and terrain factors as the independent variables, which were confirmend to the model through the correlation analysis with biomass.According to the different methods, the independent variables were improted to the retrieval model building of Pinus massoniana plot biomass, then the accuracy verification and evalution were analyzed. We selected NDVI,GVI,MSAVI,PC1,PC2,PC3,PVI and RVI to establish the retrieval model of biomass=-75.714-624.524*NDVI+1.398*GVI+340.518*MSAVI+0.022*PC1-0.366*PC2-0.474*PC3-0.560*PVI+57.362*RVI, the multiple corelation coefficient of which was 0.999 and could be used to estimate the Pinus massoniana biomass.By estimating the biomass which was using the TM remoting sensing data and based on the retrieval model of Pinus massoniana biomass, the temporal and spatial change regulation were analyzed. The research showed that the Pinus massoniana biomass increased from 2004 to 2009,which increased from 34160.522t to 646698.450t. The Pinus massoniana biomass was scattered in the semi-sunny and sunny slope, the slope of 5～35°, and increased with the rising of slope. The Pinus massoniana biomass was scattered in the altitude of 250～800 meters and increased with the rising of altitude. As the factors of soil,LAI,temperature and precipitation and so on were not considered, the model and analysis of results were not perfect. So in the future work, we can optimize the model and analyse the driviing force, and raise the further suggestions in the environmental protection and controlling soil and water loss. |
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