CAJ | 학술논문

运用面向对象分类法中的基于监督分类和基于规则的滑坡识别方法,选择合适的特征属性,利用Aster和Geoeye的融合影像对构林坪流域进行滑坡信息提取,并对分类结果进行精度评价和比较.结果表明：基于监督分类的滑坡信息提取总体精度为66.58%, Kappa系数为0.65,具有较高的分类精度；基于规则的滑坡信息提取方法也取得了84.7%的识别结果,但是区域特殊地形地貌和引发滑坡因子的复杂性导致了72.6%的分歧因子.总体上基于面向对象分类法的高分辨率遥感滑坡信息提取在白龙江流域具有良好的适用性.
운용면향대상분류법중적기우감독분류화기우규칙적활파식별방법,선택합괄적특정속성,이용Aster화Geoeye적융합영상대구림평류역진행활파신식제취,병대분류결과진행정도평개화비교.결과표명：기우감독분류적활파신식제취총체정도위66.58%, Kappa계수위0.65,구유교고적분류정도；기우규칙적활파신식제취방법야취득료84.7%적식별결과,단시구역특수지형지모화인발활파인자적복잡성도치료72.6%적분기인자.총체상기우면향대상분류법적고분변솔요감활파신식제취재백룡강류역구유량호적괄용성.
Through a selection of appropriate attributes, two object-oriented classification methods (supervised classification method and rule-based method) were applied to extract landslide morphological information for Goulinping Basin based on the fused images of Aster and Geoeye. The accuracy of the classifications were evaluated and compared and the results showed that the accuracy of landslide information extraction based on the supervised classification is 66.58%and the Kappa coe?cient is 0.65. The recognition accuracy based on the rule-based method is 84.7%, but the difference of factor is 72.6% due to the special topography and the complexity of the influencing factors of the landslide. In summary, the two classification methods have good applicability in Bailong River Basin.