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DSM generation and evaluation from QuickBird stereo imagery with 3D physical modelling

机译:利用3D物理建模从QuickBird立体影像生成和评估DSM

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摘要

A digital terrain model (DTM) extracted from QuickBird in-track stereo images using a three-dimensional (3D) multisensor physical model developed at the Canada Centre for Remote Sensing, Natural Resources Canada was evaluated. Firstly, the stereo photogrammetric bundle adjustment was set-up with about 10 accurate ground control points and 1-2m errors in the three axes were obtained over 48 independent checkpoints. The DTM was then generated using an area-based multi-scale image matching method and 3D semi-automatic editing tools and then compared to lidar elevation data with 0.2-m accuracy. An elevation error with 68% confidence level (LE68) of 6.4 m was achieved over the full area. Since the DTM is in fact a digital surface model where the height, or a part, of land cover (trees, houses) is included, the accuracy depends on the land cover types. Using 3D visual classification of the stereo QuickBird images, different classes (deciduous, conifer, mixed and sparse forests, residential areas, bare soils and lakes) were generated to take into account the height of the surfaces (natural and human-made) in the accuracy evaluation. LE68 values of 3.4m to 6.7m were thus obtained depending on the land cover types with biases representative of the surface heights. On the other hand, LE68 values of 0.5m and 1.3m with no bias were obtained for lakes and bare soils respectively. These last results are more representative of the real stereo QuickBird potential for DTM and 5-m contour line generation, compliant with the highest topographic standard. Since the images were acquired in wintertime and the lidar data in summertime, better results could thus be expected when using stereo images acquired in summertime, mainly in deciduous forests to integrate the full canopy height into the DSM.
机译:评估了使用加拿大自然资源加拿大遥感中心开发的三维(3D)多传感器物理模型从QuickBird轨道立体图像中提取的数字地形模型(DTM)。首先,建立了立体摄影测量束调节装置,该装置具有约10个准确的地面控制点,并且在48个独立的检查点上获得了三个轴上的1-2m误差。然后使用基于区域的多尺度图像匹配方法和3D半自动编辑工具生成DTM,然后将DTM与激光雷达高程数据进行比较,精度为0.2-m。 68%置信度(LE68)的高程误差为6.4 m。由于DTM实际上是一个数字表面模型,其中包括了土地覆盖物(树木,房屋)的高度或一部分,因此精度取决于土地覆盖物的类型。使用立体QuickBird图像的3D视觉分类,生成了不同的类别(落叶,针叶树,稀疏森林,居民区,裸露的土壤和湖泊),以考虑到自然表面和自然表面的高度准确性评估。因此,根据土地覆盖类型获得的LE68值为3.4m至6.7m,其偏差代表表面高度。另一方面,湖泊和裸土的LE68值分别为0.5m和1.3m,无偏差。这些最后的结果更能代表DTM和5米轮廓线生成的真正立体QuickBird潜力,符合最高的地形标准。由于图像是在冬季采集的,而激光雷达数据是在夏季采集的,因此,使用夏季采集的立体图像(主要是在落叶林中将整个冠层高度整合到DSM中)时,可以预期获得更好的结果。

著录项

  • 来源
    《International journal of remote sensing》 |2004年第22期|p.5181-5193|共13页
  • 作者

    T. TOUTIN;

  • 作者单位

    Canada Centre for Remote Sensing, Natural Resources Canada, 588 Booth Street, Ottawa, Ontario K1A 0Y7, Canada;

  • 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
  • 中图分类 遥感技术;
  • 关键词

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