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首页> 外文期刊>GIScience & remote sensing >Quality assessment of digital surface models extracted from WorldView-2 and WorldView-3 stereo pairs over different land covers
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Quality assessment of digital surface models extracted from WorldView-2 and WorldView-3 stereo pairs over different land covers

机译:从不同土地覆盖范围的WorldView-2和WorldView-3立体对中提取的数字表面模型的质量评估

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摘要

Digital surface models (DSMs) extracted from very high resolution (VHR) satellite stereo images are becoming more and more important in a wide range of geoscience applications. The number of software packages available for generating DSMs has been increasing rapidly. The main goal of this work is to explore the capabilities of VHR satellite stereo pairs for DSMs generation over different land-cover objects such as agricultural plastic greenhouses, bare soil and urban areas by using two software packages: (i) OrthoEngine (PCI), based on a hierarchical subpixel mean normalized cross correlation matching method, and (ii) RPC Stereo Processor (RSP), with a modified hierarchical semi-global matching method. Two VHR satellite stereo pairs from WorldView-2 (WV2) and WorldView-3 (WV3) were used to extract the DSMs. A quality assessment on these DSMs on both vertical accuracy and completeness was carried out by considering the following factors: (i) type of sensor (i.e., WV2 or WV3), (ii) software package (i.e., PCI or RSP) and (iii) type of land-cover objects (plastic greenhouses, bare soil and urban areas). A highly accurate light detection and ranging (LiDAR) derived DSM was used as the ground truth for validation. By comparing both software packages, we concluded that regarding DSM completeness, RSP produced significantly (p0.05) better scores than PCI for all the sensors and type of land-cover objects. The percentage improvement in completeness by using RSP instead of PCI was approximately 2%, 18% and 26% for bare soil, greenhouses and urban areas respectively. Concerning the vertical accuracy in root mean square error (RMSE), the only factor clearly significant (p0.05) was the land cover. Overall, WV3 DSM showed slightly better (not significant) vertical accuracy values than WV2. Finally, both software packages achieved similar vertical accuracy for the different land-cover objects and tested sensors.
机译:从高分辨率(VHR)卫星立体声图像中提取的数字表面模型(DSM)在广泛的地球科学应用中变得越来越重要。可用于生成DSM的软件包数量正在迅速增加。这项工作的主要目标是通过使用两个软件包,探索VHR卫星立体声对在不同土地覆盖物体(如农用塑料温室,裸露的土壤和城市区域)上生成DSM的功能,这些软件包括:(i)OrthoEngine(PCI),基于层次化亚像素均值归一化互相关匹配方法,以及(ii)RPC立体处理器(RSP),具有改进的层次化半全局匹配方法。 WorldView-2(WV2)和WorldView-3(WV3)的两个VHR卫星立体声对用于提取DSM。通过考虑以下因素,对这些DSM的垂直准确性和完整性进行了质量评估:(i)传感器的类型(即WV2或WV3),(ii)软件包(即PCI或RSP)和(iii )类型的土地覆盖物(塑料温室,裸露的土壤和城市地区)。高度精确的光检测和测距(LiDAR)衍生的DSM被用作验证的基础。通过比较两个软件包,我们得出结论,就DSM完整性而言,RSP在所有传感器和土地覆盖物类型上的得分均显着高于PCI(p <0.05)。对于裸露的土壤,温室和城市地区,使用RSP代替PCI的完整性提高的百分比分别约为2%,18%和26%。关于均方根误差(RMSE)的垂直精度,唯一明显有意义的因素(p <0.05)是土地覆盖率。总体而言,WV3 DSM的垂直准确度值略高于WV2。最后,两个软件包对于不同的土地覆盖物和经过测试的传感器都实现了相似的垂直精度。

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