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Mapping urban impervious surfaces from an airborne hyperspectral imagery using the object-oriented classification approach

机译：使用面向对象的分类方法将城市渗透表面映射到空中高光谱图像中

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The objective of this research is to explore the capabilities of the hyperspectral imagery in mapping the urban impervious objects and identifying the surface materials using an object-oriented approach. The application is conducted to Toulouse city (France) within the HYEP research project in charge of using hyperspectral imagery for the environmental urban planning. The method uses the multi-resolution segmentation and classification algorithms. The first results highlight a high potential of the hyperspectral imagery in land cover mapping of the urban environment, especially the extraction of impervious surfaces. They, also, illustrate, that the object-oriented approach by means of the fuzzy logic classifier yields promising results in distinguishing the mean roofing materials based only on the spectral information. Conversely to the red clay tiles and metal roofs, which are easily identified, the concrete, gravel and asphalt roofs are still confused with roads.
机译：本研究的目的是探讨高光谱图像在映射城市不透水物体并使用面向对象的方法识别表面材料的能力。该申请由Hyeps Country（法国）进行，负责使用高光谱图像进行环境城市规划。该方法使用多分辨率分段和分类算法。第一个结果突出了城市环境的陆地覆盖映射中高光谱图像的高潜力，尤其是渗透表面的提取。它们还示出了借助于模糊逻辑分类器的面向对象的方法产生了有希望仅基于光谱信息区分平均屋顶材料。相反，易于识别的红色粘土瓷砖和金属屋顶，混凝土，砾石和沥青屋顶仍然与道路混淆。

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