The effects of environmental factors on the site indexes of Sugi (Cryptomeria japonica) and Hinoki (Chamaecyparis obtusa) manmade coniferous forest stands were analyzed in the Shikoku National Forest using GIS. Rock type had a significant relationship with the site index, while soil type did not. Temperature had a positive relationship and radiation had a negative relationship with the site index data of Sugi and Hinoki. On the other hand, precipitation had a positive relationship with the site index of Sugi, but no significant relationship with the site index of Hinoki. Snow depth had a negative relationship with the site index of Hinoki, while it had no significant relationship with the site index Sugi. These results correspond well with the species' characteristics.

抄録全体を表示

Traditional parameters of forest structure could not meet the need of modern forest management completely. In order to know change law of forest structure in a given period, based on the survey on forest status, spatial structure characteristics of the forest dominated by Pinus densiflora and Chamaecyparis obtusa in 1999 and 2009 were studied by four spatial structure indices of mingling, angle index, neighborhood comparison and opening degree. The results indicated that: Species richness increased somewhat with seven species in 2009 while four species in 1999. The diameter class of Pinus densiflora was not continuous due to lack of small trees, whereas other species were small trees except for Chamaecyparis obtusa. The average mingling was 0.316 and 0.567 respectively in 1999 and 2009, indicating that mixed degree between species from middle-mixed developed into high-mixed level. The distribution pattern of all trees from regular became random. However, neighborhood comparison was 0.456 and 0.474 respectively in the two periods, showing the ratio of the trees whose growth was in oppressed status increased somewhat. And the average opening degree decreased from 0.393 to 0.304, indicated that growth space of most trees were in inadequate condition in 2009. From succession, Pinus densiflora will disappear from the stand finally, while Chamaecyparis obtusa will continue to be in dominance in competition between species. Most of broad-leaved species are in disadvantage at present, and effective measures need to take to protect successful growth of them. Finally, possible operation plan for the forest was discussed.

抄録全体を表示

Porter's Industrial Cluster Theory has been applied to Scotland's forestry industries since 2000, and this paper analyses the relevance of this experience for prefectural forestry policies in Japan, based on Nagano Prefecture as a case study. First, the paper discusses the key contributions to industry competitiveness resulting from clusters and their networks. Next, the current situation in Nagano is considered together with emerging prefecture policies to increase timber supply and encourage its forestry industry. Strengths and weaknesses in the prefecture's forestry system are identified and the extent to which Nagano's policies already reflect experience in Scotland is summarised. While many of the overall aims are similar to those of Scotland's forestry cluster, Nagano Prefecture has some weaknesses including the fragmented ownership structure and the multiple stages in the distribution chain. Based on Scotland's experience, potential remains to develop and manage effective cluster networks, and to stimulate cooperation across the supply chain between timber producers and users to improve productivity and develop markets, thereby 'co-creating' value.

抄録全体を表示

The purpose of this article is to attempt classification of leaf images using a self-organizing map (SOM) and tree-based model. The number of samples was 420 (84 species), which were collected at the Kyoto Prefectural University campus. Data input into the models were used as 10 dimensions: circularity, ratio of minor axis to major axis, four capacity dimensions and four information dimensions. Both the capacity and information dimensions were calculated from the distance feature, which was calculated as the distance from the center of gravity in the figure to the circumference and was shown as the function of an angle, using the fractal dimensions of states with ε-entropy. As a classification method, SOM illustrated the 10 dimensions data on a two-dimensional plane as a nonlinear map. Moreover, the classification accuracy of decision trees derived from tree-based models was examined. Additionally, the samples were divided into five groups based on differences in leaf shape, as follows: simple leaves with leaf teeth, simple leaves without leaf teeth, lobed leaves, needle leaves and compound leaves. It was found that: (1) The fractal dimension showed different values, and this dimension was found to be effective as a factor for estimating and classifying; (2) when the number of leaning times and map sizes of SOM increases, all tree species were clearly classified on SOM map; and (3) as for classification by tree-based models, the correct ratios of each model varied widely, ranging from 42.1% (REPTree) to 100.0% (RandomTree) without cross-validation, and ensemble learning can improve the estimation accuracy of the models.

抄録全体を表示