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Cartographic Elements Extraction using High Resolution Remote Sensing Imagery and XML Modeling

机译:使用高分辨率遥感影像和XML建模提取制图要素

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At the present time, the remote sensing community will have to deal with new data type; very high spatial resolution and IKONOS and Quickbird data give an excellent reference of them. For some topics that are directly implied like environment or urban areas analysis, this new data will be very important. Indeed, the arrival of these images enables a new capability and the study of a range of non-observable objects until now. Using high resolution imagery should make it possible to detect man made features such as buildings, rivers or roads in an easier way than conventional data. This research presents and proposes an automatic system of cartographic elements extraction from space images, using very high spatial resolution images. This system can be adapted to others types of remote sensing images. This research work is focus on the extraction of four types of cartographic elements: water areas, urban areas, wooded areas and linear features such as roads or railways. Each type of cartographic element is extracted detecting its own characteristics, using image analysis, applying a segmentation process and knowledge extraction.
机译:目前,遥感界将不得不处理新的数据类型。非常高的空间分辨率以及IKONOS和Quickbird数据为它们提供了很好的参考。对于直接隐含的某些主题(例如环境或城市区域分析),此新数据将非常重要。的确,这些图像的到来使人们有了新的能力,并且可以研究直到现在为止的一系列不可观测的物体。使用高分辨率图像应该可以比传统数据更容易地检测到人造特征,例如建筑物,河流或道路。这项研究提出并提出了一种使用非常高的空间分辨率图像从空间图像中提取制图要素的自动系统。该系统可以适用于其他类型的遥感图像。这项研究工作集中在四种类型的制图要素的提取上:水域,市区,林木区和线性要素(例如道路或铁路)。使用图像分析,应用分段过程和知识提取来提取每种类型的制图要素,以检测其自身的特征。

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