首页> 外文会议>2010 IEEE International Geoscience and Remote Sensing Symposium >DSM generation from very high optical and radar sensors: Problems and potentialities along the road from the 3D geometric modeling to the Surface Model
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DSM generation from very high optical and radar sensors: Problems and potentialities along the road from the 3D geometric modeling to the Surface Model

机译:高度光学和雷达传感器产生的DSM:从3D几何建模到曲面模型的整个过程中存在的问题和潜力

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摘要

The availability of new high resolution optical and radar spaceborne sensors offers new interesting potentialities for the acquisition of data useful for the generation of Digital Surface Models (DSMs). The accuracy level of DSM is strictly related both to the image orientation and to the matching process. As regards the image orientation, remote sensing community usually adopts two different types of models for High Resolution Satellite Imagery (HRSI): the physical sensor models and the generalized sensor models also called rigorous and Rational Polynomial Functions (RPFs) models respectively. In a scientific software developed by the research group of Geodesy and Geomatic Area of the University of Rome "La Sapienza" both rigorous and RPFs models are implemented, with a specific tool for the terrain-independent Rational Polynomial Coefficients (RPCs) generation; the software manages the imagery acquired by several optical sensors (EROS A, Ikonos, QuickBird, Cartosat-1, WorldView-1, GeoEye-1) and by the Italian SAR constellation COSMO-SkyMed. In the same software a facility for image matching is embedded. The Area Base Matching (ABM) is used, combined with the orientation model re-parametrized in terms of RPCs. In the present work some examples of models application and DSM generation are analyzed and discussed.
机译:新型高分辨率光学和雷达星载传感器的可用性为获取有用的数据提供了新的有趣潜力,这些数据可用于生成数字表面模型(DSM)。 DSM的准确性水平与图像方向和匹配过程都紧密相关。关于图像方向,遥感界通常对高分辨率卫星图像(HRSI)采用两种不同类型的模型:物理传感器模型和广义传感器模型,分别分别称为严格和有理多项式函数(RPF)模型。由罗马大学“ La Sapienza”大地测量学与地理区域研究小组开发的科学软件,同时实现了严格的模型和RPF模型,并使用了一种特定的工具来生成与地形无关的有理多项式系数(RPCs);该软件管理由多个光学传感器(EROS A,Ikonos,QuickBird,Cartosat-1,WorldView-1,GeoEye-1)和意大利SAR星座COSMO-SkyMed采集的图像。在同一软件中,嵌入了用于图像匹配的工具。使用区域基础匹配(ABM),并结合根据RPC重新参数化的定向模型。在本工作中,将分析和讨论模型应用和DSM生成的一些示例。

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