Study On Site Quality Evaluation And Suitability Of Eucalyptus

Site conditions have an important impact on the growth of trees.Site quality evaluation and tree species suitability research are hot topics in affborestation decision-making and matching species with the site.This paper takes Eucalyptus artificial forest in Guangxi as the research object,based on Class ?continuous inventory data and Class ? survey of forest resources data,constructs site quality evaluation model of Eucalyptus with difference equation method,and carries out the tree species suitability study by machine learning method.Finally,using model analysis and software development technology,an expert system for site quality evaluation based on GIS is constructed.The main research contents and results are as follows:(1)Aiming at the Eucalyptus artificial forest,a study on site quality evaluation of forest land was carried out,and a site quality evaluation model of Eucalyptus was constructed.By using the difference equation methods as the prototype,10 differential equations are derived as the expression of the forest land site quality evaluation model.Using non-linear regression technology,the parameters of 10 forest site quality evaluation models were fitted.The accuracy of 10 models was validated by using the test data.The results show that compared with the other 9 models,the model of Eucalyptus quality evaluation based on Richards equation has better prediction effect.The base age of Eucalyptus was brought into Eucalyptus site quality evaluation model,which was used to evaluate the site quality of Eucalyptus forest land.This model is of great practical significance for site quality evaluation of Eucalyptus forest land.(2)This research studied the application of machine learning classification algorithms in Eucalyptus suitability analysis,and explored the relationship between Eucalyptus suitability and site factors.Three machine learning classification algorithms,Naive Bayesian,Support Vector Machine and Random Forest,were used to evaluate the suitability of tree species,and three suitability evaluation models of Eucalyptus were constructed.When using the above three algorithms to construct the model,the input of the model is 11 site factors,including landform type,elevation,aspect,slope position,slope,litter layer thickness,humus layer thickness,soil layer thickness,gravel content,parent material,and soil type.The output of the model is suitable for Eucalyptus growth or not suitable for Eucalyptus growth.The generalization ability of the model is compared with the test data.The results show that the Random Forest algorithm has better classification effect than Naive Bayesian and Support Vector Machine.In the study area.the area between 200?350 m above sea level and 80?100 cm in soil thickness is more suitable for Eucalyptus growth.Machine learning classification algorithm can better evaluate whether the site is suitable for the growth of Eucalyptus,and can be applied to the study of tree species suitability to provide support for scientific afforestation.(3)On the basis of the above research,the work flow,system functional structure,system architecture and system database of the expert system for site quality evaluation based on GIS are designed.The key algorithm of system implementation is studied and designed.By integrating the above technologies and methods,the functions of site quality evaluation,such as forest land site quality evaluation,tree species suitability evaluation and so on,are realized.An expert system for site quality evaluation based on GIS is developed,and an operation example of the system is given.