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首页> 外文会议>Fifth international workshop on the analysis of multi-temporal remote sensing images >QUANTIFYING CHANGES TO THE URBAN MORPHOLOGY OF DUBLIN WITH SPATIAL METRICS DERIVED FROM MEDIUM RESOLUTION REMOTE SENSING DATA
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QUANTIFYING CHANGES TO THE URBAN MORPHOLOGY OF DUBLIN WITH SPATIAL METRICS DERIVED FROM MEDIUM RESOLUTION REMOTE SENSING DATA

机译：基于中分辨率遥感数据的空间度量量化都柏林城市形态的变化

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Satellite images of medium resolution are cheap, widely available and are often part of extensive historic archives, which makes them ideally suited to study urban growth. Their lower resolution, on the other hand, hampers studying urban morphology and change processes at a more detailed, intra-urban level. In this paper, we develop spatial metrics for use on continuous sealed surface data produced by a sub-pixel classification of Landsat TM and ETM+ imagery. Three approaches are compared to derive the sealed surface fractions at sub-pixel level: linear regression analysis, linear spectral mixture analysis and a multi-layer perceptron (MLP). The metrics represent the shape of the cumulative frequency distribution of the estimated sub-pixel fractions within each spatial unit by fitting a transformed togistic function with a nonlinear least-squares approach. A MLP classifier is then used to relate the metric variables to combined urban land-use classes selected from the European MOLAND topology. In combination with density information derived from the sealed surface maps, our approach allows producing maps that show changes in urban morphology
机译：中等分辨率的卫星图像价格便宜，可广泛获得，并且通常是大量历史档案的一部分，这使其非常适合研究城市发展。另一方面，其较低的分辨率会阻碍在更详细的城市内部层面研究城市形态和变化过程。在本文中，我们开发了可用于由Landsat TM和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。比较了三种方法以得出亚像素级的密封表面分数：线性回归分析，线性光谱混合分析和多层感知器（MLP）。度量通过使用非线性最小二乘法拟合转换的Togistic函数来表示每个空间单位内的估计子像素部分的累积频率分布的形状。然后，使用MLP分类器将度量变量与从欧洲MOLAND拓扑结构中选择的组合城市土地利用类别相关联。结合从密封表面图获得的密度信息，我们的方法允许生成显示城市形态变化的图

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