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Automatic Building Extraction with Multi-sensor Data Using Rule-based Classification

机译:基于规则分类的多传感器数据自动提取建筑物

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This paper presents a new approach for automatic building extraction using a rule-based classification method with a multi-sensor system that includes light detection and ranging (LiDAR), a digital camera, and a GPS/IMU positioned on the same platform. The LiDAR data (elevation and intensity) and ortho-image are used to develop a rule set defined by parameter analyses during the segmentation and fuzzy classification processes to improve the building extraction results. The proposed approach was tested using the data derived from a multi-sensor system in Sivas, Turkey. Moreover, analyses of completeness (81.71%) and correctness (87.64%) were performed by automatic comparison of the extracted buildings and reference data.
机译:本文提出了一种新的自动建筑提取方法,该方法使用基于规则的分类方法,该方法具有多传感器系统,包括光检测和测距(LiDAR),数码相机和位于同一平台上的GPS / IMU。 LiDAR数据(高程和强度)和正射影像用于在分割和模糊分类过程中开发由参数分析定义的规则集,以改善建筑物提取结果。使用从土耳其锡瓦斯(Sivas)的多传感器系统获得的数据对提出的方法进行了测试。此外,通过对提取的建筑物和参考数据进行自动比较,对完整性(81.71%)和正确性(87.64%)进行了分析。

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