Shunsuke Shimizu, T. Nakajima, Katsutoshi Takezoe, S. Tatsuhara
{"title":"不成功长尾杉人工林的林型分类","authors":"Shunsuke Shimizu, T. Nakajima, Katsutoshi Takezoe, S. Tatsuhara","doi":"10.5638/THAGIS.24.13","DOIUrl":null,"url":null,"abstract":": We classified unsuccessful 60-year-old forests, planted mainly with hinoki cypress ( Chamaecyparis obtusa ), into types based on the species composition of invading trees, and determined the change of each forest type. Thematic maps of topographic factors were derived from a digital elevation model generated from LiDAR data. The study area was classified into four forest types, based on tree regression analysis of species composition and the topographic factors. Then the dominance of C. obtusa and invading trees was determined from the distribution maps of their top heights created based on tree regression analyses of them and the topographic factors. The relationship between the dominance of them and forest types was shown. Finally, changes in the stand volume of each forest type were determined. Based on the results, we suggest the following three future management policies for each forest type, taking into consideration the timber price of invading hardwood trees, the growth of C. obtusa , and the increase in stand volume: no operations, reinforcement planting, or switching to mixed conifers and hardwood forests.","PeriodicalId":177070,"journal":{"name":"Theory and Applications of GIS","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification of unsuccessful Chamaecyparis obtusa plantations into forest types\",\"authors\":\"Shunsuke Shimizu, T. Nakajima, Katsutoshi Takezoe, S. Tatsuhara\",\"doi\":\"10.5638/THAGIS.24.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": We classified unsuccessful 60-year-old forests, planted mainly with hinoki cypress ( Chamaecyparis obtusa ), into types based on the species composition of invading trees, and determined the change of each forest type. Thematic maps of topographic factors were derived from a digital elevation model generated from LiDAR data. The study area was classified into four forest types, based on tree regression analysis of species composition and the topographic factors. Then the dominance of C. obtusa and invading trees was determined from the distribution maps of their top heights created based on tree regression analyses of them and the topographic factors. The relationship between the dominance of them and forest types was shown. Finally, changes in the stand volume of each forest type were determined. Based on the results, we suggest the following three future management policies for each forest type, taking into consideration the timber price of invading hardwood trees, the growth of C. obtusa , and the increase in stand volume: no operations, reinforcement planting, or switching to mixed conifers and hardwood forests.\",\"PeriodicalId\":177070,\"journal\":{\"name\":\"Theory and Applications of GIS\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theory and Applications of GIS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5638/THAGIS.24.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory and Applications of GIS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5638/THAGIS.24.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of unsuccessful Chamaecyparis obtusa plantations into forest types
: We classified unsuccessful 60-year-old forests, planted mainly with hinoki cypress ( Chamaecyparis obtusa ), into types based on the species composition of invading trees, and determined the change of each forest type. Thematic maps of topographic factors were derived from a digital elevation model generated from LiDAR data. The study area was classified into four forest types, based on tree regression analysis of species composition and the topographic factors. Then the dominance of C. obtusa and invading trees was determined from the distribution maps of their top heights created based on tree regression analyses of them and the topographic factors. The relationship between the dominance of them and forest types was shown. Finally, changes in the stand volume of each forest type were determined. Based on the results, we suggest the following three future management policies for each forest type, taking into consideration the timber price of invading hardwood trees, the growth of C. obtusa , and the increase in stand volume: no operations, reinforcement planting, or switching to mixed conifers and hardwood forests.