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Quantifying intra-urban morphology of the Greater Dublin area with spatial metrics derived from medium resolution remote sensing data

机译：使用从中等分辨率遥感数据得出的空间指标来量化大都柏林地区的城市内部形态

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Spatial metrics derived from satellite imagery are useful measures to quantify structural characteristics of expanding cities, and can provide indications of functional land use types. Images of medium resolution are cheap, widely available and are often part of extensive historic archives. Their lower resolution, on the other hand, inhibits studying urban morphology and change processes at a more detailed, intra-urban level. In this study, we develop spatial metrics for use on continuous sealed surface data produced by a sub-pixel classification of Landsat ETM+ imagery. The metrics characterise the shape of the cumulative frequency distribution of the estimated sub-pixel fractions within a building block by fitting an exponential and a sigmoid function with a least-squares approach. A classification tree is then used to relate the metric variables to urban land-use classes selected from the European MOLAND topology. This approach shows promising results, but still needs improvement which may be achieved by including spatially explicit metrics in the analysis.
机译：从卫星图像得出的空间度量是有用的措施，可以量化扩展中的城市的结构特征，并且可以提供功能性土地利用类型的指示。中等分辨率的图像价格便宜，可广泛获得，并且经常是大量历史档案的一部分。另一方面，它们的较低分辨率会阻止在更详细的城市内部层面研究城市形态和变化过程。在这项研究中，我们开发了可用于由Landsat ETM +图像的亚像素分类产生的连续密封表面数据的空间度量。度量通过使用最小二乘法拟合指数函数和S形函数来表征构建块内估计子像素分数的累积频率分布的形状。然后使用分类树将度量标准变量与从欧洲MOLAND拓扑结构中选择的城市土地利用类别相关联。这种方法显示出令人鼓舞的结果，但仍需要改进，可以通过在分析中包括空间明确的指标来实现。

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