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Preparation Of Koelreuteria Paniculata Volume Table And Carbon Measurement Table In Middle Areas Of Shandong Province

Posted on:2022-11-13Degree:MasterType:Thesis
Country:ChinaCandidate:Y WuFull Text:PDF
GTID:2493306749496244Subject:Ecology
Abstract/Summary:PDF Full Text Request
Standing wood volume,as an important indicator to characterize the growth status of trees during their growth and development,is an important part of the basic forest management table.As an important part of the city,urban green space system is not only the key to regulate the carbon and oxygen balance of the city,but also the basis of sustainable urban development.How to select high ornamental and high carbon tree species in the construction of urban green space has become the focus of people’s attention.With the continuous promotion of urban forestry reform in China,forestry operation is developing in a more intensive direction,and there is an urgent need to compile a more accurate standing timber volume table for carbon sink assessment of urban tree species.Koelreuteria paniculata is the deciduous tree of Sapindaceae Juss.,with a deep and long root system,strong sprouting ability,strong resistance to pollution and adaptability,which is increasingly important for maintaining the carbon balance in cities and strengthening the urban ecological environment,and has become an indispensable part of the landscaping species,but there is a lack of research on the timber table of Koelreuteria paniculata in China In this study,three cities in middle areas of Shandong Province(Jinan,Zibo and Tai’an)in China were used as the research object,and their Diameter at Breast Hight(DBH),Tree Height(H),and height under branches were measured in the field,and six one-element wood volume equations and nine two-element wood volume equations were selected as alternative equations,and parametric regression(Ordinary Least Squares,Bayesian Regression)and nonparametric regression(Random Forest,Artificial Neural Network)were used to fit Koelreuteria paniculata respectively.The best model for expressing wood volume was obtained by comparing and selecting the best model according to the fit test indexes,and then compiling the unity and binary wood volume tables,and estimating the biomass and carbon content of individual wood plants according to the biomass equation and carbon measurement formula.The main results of the study are as follows:(1)Using the principles of maximum R2 and minimum RMSE,the most suitable model for compiling timber volume table was selected as random forest model by comparing parametric and nonparametric regression methods,with R2 of 0.9558 and RMSE of 0.0101 for the best-fitting one-element timber volume model and R2 of 0.9217 and RMSE of 0.0147 for the best-fitting binary timber volume model,and the model was tested using mean square;(2)Based on the previously constructed timber volume model,the timber volume was calculated according to different diameter at breast height and tree height diameter classes,and the unity and binary wood volume tables of Koelreuteria paniculata timber volume were compiled,and the correctness of the results of the timber volume tables was verified by combining the actual measured data,and the error values were all less than 5%;(3)Using the biomass model to relate wood volume to biomass,the biomass calculation model of its was B=1250.22 Vi,and based on this model and the above-mentioned volume,a unity and binary biomass table of Koelreuteria paniculata in middle areas of Shandong Province region was prepared;(4)The biomass of a single tree was related to its carbon content,and the relationship between carbon content and volume was obtained as C=625.11 Vi,a generalized table of unity and binary carbon content in middle areas of Shandong Province region was prepared.The preparation of Koelreuteria paniculata volume table through the above study further enriches the study of volume table in China,while linking its individual biomass and carbon content with wood volume,which facilitates the rapid estimation of Koelreuteria paniculata carbon stock in actual production practice and provides reference for future the tree growth studies and biomass and carbon stock estimation.
Keywords/Search Tags:Koelreuteria paniclata, Volume table, Random Forest, Artificial Neural Network, Carbon measurement
PDF Full Text Request
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