Maximum likelihood classification of LIDAR data incorporating multiple co-registered bands
Maximum likelihood classification of LIDAR data incorporating multiple co-registered bands
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发表时间：
2006
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通讯作者：
M. Bartels;Hong Wei
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作者：
M. Bartels;Hong Wei
在过去的十年中，激光雷达（LIDAR）已被商业和公共部门公认为土地测量的可靠和准确的来源。激光雷达数据中的目标分类倾向于采用额外的同时记录的波段进行数据融合。本文提出了一种基于最大似然估计的监督分类算法，该算法利用高分辨率的LIDAR数据和共配准的线扫描波段（如航空照片和近红外照片），对LIDAR数据进行了初始、最终回波和强度的分类。本文讨论了特征和类的选择以及精度评估等问题。所提出的结果表明融合激光雷达数据集的分类方法的适用性。
In the past decade, LIght Detection And Ranging (LIDAR) has been recognised by both the commercial and public sector as a reliable and accurate source for land surveying. Object classification in LIDAR data tends towards data fusion by employing additional simultaneously recorded bands. In this paper, a supervised classification algorithm based on Maximum Likelihood is presented using high resolution first, last echo and intensity LIDAR data and co-registered line scanner bands such as aerial photos and near infra-red photos. The issues regarding feature and class selection as well as accuracy assessment are addressed in this paper. The presented results show the suitability of the classification approach for fused LIDAR data sets.