首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >IMPROVED DISTRIBUTED RUNOFF MODELLING OF URBANISED CATCHMENTS BY INTEGRATION OF MULTI-RESOLUTION REMOTE SENSING
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IMPROVED DISTRIBUTED RUNOFF MODELLING OF URBANISED CATCHMENTS BY INTEGRATION OF MULTI-RESOLUTION REMOTE SENSING

机译:通过集成多分辨率遥感,改进了城市化集水区的分布式径流建模

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The runoff amount and intensity on catchment scale is strongly related to the spatial distribution of impervious area cover, which is the predominant cover type in urbanized area. This can only be taken effectively into account when a fully-distributed hydrological model is used. In this paper we investigate the assessment of imperviousness by a multi-resolution remote sensing technique. The remote sensing approach uses a classified high resolution (HR) Ikonos image that covers part of the research area to train a neural network based sub-pixel classification model that estimates impervious surface cover proportions within the pixels of a medium-resolution (MR) Landsat ETM+ image that covers the entire area. The GIS based distributed WetSpa model was used for studying the influence of different imperviousness scenarios on runoff generation with an hourly time step. It shows that estimates of imperviousness derived from satellite data may strongly improve those made by experts, as well as the necessity of application of fully-distributed grid-based hydrological models for urban runoff simulation.
机译:集水区径向量和强度与不透水区域覆盖的空间分布强烈相关,这是城市化区域的主要覆盖类型。只有在使用完全分布的水文模型时,才能有效地考虑到这一点。在本文中,我们通过多分辨率遥感技术调查了不透水的评估。遥感方法使用分类的高分辨率(HR)IKONOS图像,其涵盖了研究区域的一部分,以训练基于神经网络的子像素分类模型,该分类模型估计中分辨率(MR)Landsat的像素内的不透水表面覆盖比例ETM +图像覆盖整个区域。 GIS基于GIS的分布式WetsPA模型用于研究不同的不透明情景对径流生成的影响,每小时步骤。它表明,卫星数据的不受不足的估计可能强烈改善专家制造的估计,以及应用全分布式基于网格的水文模型进行城市径流模拟的必要性。

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