关键词: 自动阈值, 决策树分类, 桉树, 多种指数, 样本集, 遥感影像处理

Abstract:

Eucalyptus of different ages and growth characteristics were selected to form the sample set,and the statistical analysis of the sample set of 8 kinds of NDVI was carried out by using Landsat 8 as the data source.Therefore,an automatic threshold decision tree classification method based on the law of exponential distribution is proposed,which is applied to the Eucalyptus forest classification in the study area through GEE.Results show that:1) from 2013 to 2019,the indexes of the sample set of planting eucalyptus follow certain rules,each index presents a minimum value every three years,which accords with the periodicity of planting and felling of Eucalyptus;2) compared with the classification result of random forest algorithm,the accuracy of classification result of automatic threshold decision tree is improved by about 4%,the average total accuracy of classification is 0.88,the average Kappa Coefficient is 0.83;3) Google historical image is applied to verify the classification result of automatic decision tree,and the coincidence rate of eucalyptus distribution area is 88.4% .All the above results show that the automatic threshold decision tree classification method proposed in this paper can effectively achieve information extraction of Eucalyptus.

Key words: automatic threshold, decision tree classification, eucalyptus, multi-index, sample set, remote sensing image processing