Measuring Spatial Dynamics in Metropolitan Areas
Measuring Spatial Dynamics in Metropolitan Areas
复制标题
测量大都市地区的空间动态
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
L. Interlante
中科院分区：
文献类型：
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作者：
S. Rey;L. Anselin;D. Folch;Daniel Arribas;Myrna L. Sastré Gutiérrez;L. Interlante
本文介绍了一种新的方法来衡量邻里变化。与传统的先验识别“社区”然后研究居民属性如何随时间变化的方法不同，这种方法将社区更本质地视为一个既有地理足迹又有社会经济组成的单元。因此，当邻域的两个方面从一个周期变换到下一个周期时，变化被识别。该方法是基于一个空间聚类算法，确定在两个时间点的一个城市的街区。作者还制定了宏观（城市）和地方（邻里）尺度的空间变化指标。作者说明了这些方法在应用程序中的时间一致的人口普查区的359个最大的大都市地区在美国的1990-2000年期间的一个广泛的数据库。
This article introduces a new approach to measuring neighborhood change. Instead of the traditional method of identifying “neighborhoods” a priori and then studying how resident attributes change over time, this approach looks at the neighborhood more intrinsically as a unit that has both a geographic footprint and a socioeconomic composition. Therefore, change is identified when both aspects of a neighborhood transform from one period to the next. The approach is based on a spatial clustering algorithm that identifies neighborhoods at two points in time for one city. The authors also develop indicators of spatial change at both the macro (city) level and the local (neighborhood) scale. The authors illustrate these methods in an application to an extensive database of time-consistent census tracts for 359 of the largest metropolitan areas in the United States for the period 1990-2000.