Research on classification method of surveying and mapping remote sens-ing image information based on decision tree algorithm
At present,the layout of classification nodes of surveying and mapping remote sensing image information is generally independent,and the classification and recognition range is small,which leads to the increase of missing error of remote sensing image information.Ac-cording to the current information classification requirements and standards,remote sensing im-age information is preprocessed in the form of multi-objective,so as to expand the classification and recognition range,deploy multi-objective classification and recognition nodes,establish the classification matrix of surveying and mapping remote sensing image in formation,and on this basis,construct a decision tree to calculate the classification model of remote sensing image in-formation,and adopt multiple correction processing to achieve information classification.The test results show that:Compared with the test group,the leakage error ratio of remote sensing image information of the proposed method is better controlled below 2.5,indicating that with the aid and support of decision trees,the current classification efficiency of remote sensing image information is higher and the error is controllable.When it is applied to automatic classification of remote sensing images,it has good elasticity and robustness,and the classification structure is simple and clear,and better classification effect is achieved.A special data structure is defined and the classification system is realized.The practice shows that the system has good stability and interactivity,and has strong practicability.
Decision tree algorithmSurveying and mapping remote sensingRemote sensing imageInformation classification methodRemote sensing recognition
NETL
NSTL
万方数据
