摘要
在分析支持向量机(Support Vector Machine,SVM)分类技术和机载激光雷达(LIDAR)数据、航空影像特征的基础上,提出了基于SVM的LIDAR数据和航空影像的面向对象建筑物提取方法。结果表明,该方法充分利用了多源影像的互补信息,能够得到更高的信息提取精度,准确而快速地更新地理空间数据库,是一种有效的面向对象建筑物提取方法。
On the basis of analyzing the Support Vector Machine （SVM） classification technique and the features of LIDAR data and aerial imagery, this paper has put forward a new building extraction method based on object -oriented SVM, which integrates multi - source information of aer/al imagery and Light Detection and Ranging （ LI- DAR） data. Tests show that the extraction accuracy is improved by using this method. Moreover, the proposed object -oriented building extraction method not only proves to be effective but also can update GIS database quickly and accurately.
出处
《国土资源遥感》
CSCD
2008年第2期27-29,47,共4页
Remote Sensing for Land & Resources
基金
地理空间信息工程国家测绘局重点实验室项目(200720)
广西自然科学基金项目(052204)共同资助
