CAJ | 학술논문

本文利用HJ－1A星HSI2级产品数据对大兴安岭塔河地区的森林优势树种组进行识别研究。通过对影像数据进行一阶微分变换、对数变换、对数变换后的导数变换、二阶微分变换、三阶微分变换以后，分别对原始数据和5种变换后数据进行MNF（最小噪声分离变换）变换。用SVM（支持向量机）分类器分别对6种数据监督分类后，进行精度的验证及评价。结果表明：影像数据经过5种变换后，分类总精度均高于未经变换的原始数据，精度提高幅度为1．5％～4．8％，二阶微分变换分类精度最高（精度为89．5％，Kappa系数为0．802）；二阶微分变换下的4个优势树种组各自的制图精度和用户精度均高于其他变换方法，平均精度分别为90．4％和90．7％，总平均精度为90．5％。
본문이용HJ－1A성HSI2급산품수거대대흥안령탑하지구적삼림우세수충조진행식별연구。통과대영상수거진행일계미분변환、대수변환、대수변환후적도수변환、이계미분변환、삼계미분변환이후，분별대원시수거화5충변환후수거진행MNF（최소조성분리변환）변환。용SVM（지지향량궤）분류기분별대6충수거감독분류후，진행정도적험증급평개。결과표명：영상수거경과5충변환후，분류총정도균고우미경변환적원시수거，정도제고폭도위1．5％～4．8％，이계미분변환분류정도최고（정도위89．5％，Kappa계수위0．802）；이계미분변환하적4개우세수충조각자적제도정도화용호정도균고우기타변환방법，평균정도분별위90．4％화90．7％，총평균정도위90．5％。
We classified the dominate forest tree species group by one image data of the HJ-1A satellite Level2 HSI product in the Tahe area.We analyzed the image data by first derivative , log, first derivative of log, the second derivative and the third derivative methods , and deposed the original data and five kinds transformed data by MNF ( Minimum Noise Frac-tion) , then verified and appraised them with the SVM ( Support Vector Machine ) after combining with the ground data computing confusion matrix for validation .The classification accuracy with five kinds of transformation was higher than that without any transformation , and the accuracy increased by from 1.5%to 4.8%.The accuracy of second derivative was 89.5%, which was the best with Kappa of 0.802.The mapping accuracy and user accuracy of four dominate forest tree species groups deposed by the second derivative was better than others , and the average accuracies were 94.7%and 91.2%, re-spectively , with the total average accuracy of 90.5%.