Tree and building detection in dense urban environments using automated processing of IKONOS image and LiDAR data

JUNGRACK KIM; JAN-PETER MULLER

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Tree and building detection in dense urban environments using automated processing of IKONOS image and LiDAR data

机译：使用IKONOS图像和LiDAR数据的自动处理，在密集的城市环境中检测树木和建筑物

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The automated detection and reconstruction of artificial structures, larger than 10 m~2 in area using high resolution satellite images and Light Detection and Ranging (LiDAR) data through 3-dimensional shapes and/or 2-dimensional boundaries is described here. Additionally, it is demonstrated how individual tree crowns have been detected with more than 90% accuracy in very dense urban environments from very high-resolution images and range data. Pre-existing machine vision algorithms and techniques were modified and updated for this particular application to building detection within dense urban areas. All products from such procedures have not only been demonstrated with a significant areal coverage but have also been quantitatively assessed against manually obtained and third party mapping data. Accuracies of around 85% have been achieved for building detection and almost 95% for tree crown detection.

机译：本文介绍了使用高分辨率卫星图像和通过3维形状和/或2维边界的光检测和测距（LiDAR）数据对面积大于10 m〜2的人工结构进行自动检测和重建的方法。此外，它还演示了如何在非常密集的城市环境中从超高分辨率图像和距离数据中以90％以上的精度检测单个树冠。修改并更新了已有的机器视觉算法和技术，以用于在城市密集地区进行建筑物检测的特定应用。通过这种程序获得的所有产品不仅被证明具有明显的面积覆盖范围，而且还针对手动获取的数据和第三方制图数据进行了定量评估。建筑物检测的准确度约为85％，树冠检测的准确度约为95％。

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来源
《International journal of remote sensing》 |2011年第8期|p.2245-2273|共29页
作者
JUNGRACK KIM; JAN-PETER MULLER;
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作者单位

University College London, Milliard Space Science Laboratory, Holmbury St Mary,Dorking, Surrey RH5 6NT, UK;

University College London, Milliard Space Science Laboratory, Holmbury St Mary,Dorking, Surrey RH5 6NT, UK;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
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Tree and building detection in dense urban environments using automated processing of IKONOS image and LiDAR data

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