Study On The Stand Spatial Structure Simulation Of Cunninghamia Lanceolata Ecological Forest

In recent years, the rapid development of computer technology provides conditions for the simulation of stand in forestry science field, how more true express the actual situation of stand is the current research focus, this paper took the Cunninghamia lanceolata non-commercial forest in Fushou State-owned Forest Farm as the study area, realized the expression of growth prediction and forest spatial structure of forest trees, through discussing competitive relationships between the trees, the main contents and conclusions were as follows:(1) The W_V_Hegyi competition index was proposed. It revealed that it was negative correlation according to the correlation analysis between competition index and the diameter at breast height (DBH). Based on the negative correlation, it could be confirmed that the reciprocal of DBH is the weight of weighted Voronoi diagram and competition unit by using weighted Voronoi diagram tool in Arcgis, and the W_V_Hegyi could be proposed, based on Voronoi diagram. Finally, The comparative analysis among Hegyi, V_Hegyi and W_V_Hegyi revealed that:1) The correlative intensity sequence between competition index and DBH was W_V_Hegyi> V_Hegyi> Hegyi; 2)According to the power function relationship, the three competition indexes were curve fitted with DBH respectively, and the order of imitative effect was:W_V_Hegyi> V_Hegyi> Hegyi; 3) The average sorting of them in sample plots was:V_Hegyi> W_V_Hegyi> Hegyi. The above comparative analysis which could be proved that W_V_Hegyi competition index was more accurate than Hegyi and V_Hegyi in reflecting the competitive relationship among trees.(2)The diameter class growth model was constructed based on W_V_Hegyi competition index. First, constructed the individual tree model based on the correlation analysis between DBH growth and W_V_Hegyi competition index. Second, tried to use the weighted average tree height to weight DBH growth by using the geostatistics method, then rebuilded the individual tree model. Third, quantitative analysis was carried out on the competition index of the diameter class, using the regression analysis method to build diameter class growth model. The results show that:1) W_V_Hegyi competition index and DBH had the strongest correlation; 2) The fitting results of the model based on weight DBH growth was obvious higher than the above one, that explained the necessity of the weighting; 3) This diameter class growth model based on weight DBH growth includes four demanded elements of diameter class:average DBH, mean age, mean competition index and the number of trees. The multiple correlation coefficient of it was 0.886, and its regression effect is remarkable. This paper presents a new method of constructing the diameter class growth model based on the weight DBH growth and W_V_Hegyi competition index, provides a new way from individual to stand for Simulation.(3)The three-dimensional simulation of stand spatial structure. Based on the attribute data and spatial location information of measured samples, the simulation of stand spatial structure came true by using software of visualized software, and combined with 3d terrain, then it reflected more actual situation of the forest stand spatial structure.(4)The simulation of structure optimization based on the constructed competitive growth model. Based on the proposed optimization method, the forest stand was adjusted, then compared the change of spatial structure index between before and after adjustment, and realized more intuitive effect between before and after adjustment by using visualized software; the stand growth forecasts was also realized based on the constructed competitive growth model.