Patterns and scale relations among urbanization measures in Stockholm, Sweden
Patterns and scale relations among urbanization measures in Stockholm, Sweden
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DOI：
10.1007/s10980-009-9385-1
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发表时间：
2009-12-01
影响因子：
5.2
通讯作者：
Elmqvist, Thomas
中科院分区：
文献类型：
--
作者：
Andersson, Erik;Ahrne, Karin;Elmqvist, Thomas
在这项研究中，我们衡量城市化的基础上，从景观指数的人口因素，如收入和土地所有权的数据从斯德哥尔摩，瑞典的21个变量。主要目的是测试变量之间的关系，以及这些模式在各个尺度上是否一致。这些变量主要是从文献中确定的，并限于容易获得的数据。我们使用GIS对变量进行采样，然后进行主成分分析以寻找其中的模式，在四个不同的尺度（250 x 250，750 x 750，1，250 x 1，250和1，750 x 1，750，均以米为单位）重复采样和分析。在最小的尺度上，大多数变量似乎大致结构沿沿着两个轴，一个景观指数和一个主要与人口因素，但也不透水的表面和针叶林。其他土地覆被类型与这两条轴线并不十分吻合。当增加规模时，这种模式就不那么明显了，相反，变量被分成几个高度相关的变量的小束。一些对或束的变量相关的所有规模，从而互换，而其他协会改变规模。在选择衡量城市化的指标时，尤其是在衡量指标是基于若干变量的指数时，必须牢记这一点。将我们的研究结果与其他城市的研究结果进行比较，我们认为，由于城市的形状和大小以及可用信息差异很大，因此很难找到普遍的梯度。我们还认为，如果您不仅希望比较城市，而且还希望了解城市化如何影响城市不同地区的生态特征，则需要多变量梯度。
In this study we measure urbanization based on a diverse set of 21 variables ranging from landscape indices to demographic factors such as income and land ownership using data from Stockholm, Sweden. The primary aims were to test how the variables behaved in relation to each other and if these patterns were consistent across scales. The variables were mostly identified from the literature and limited to the kind of data that was readily accessible. We used GIS to sample the variables and then principal component analyses to search for patterns among them, repeating the sampling and analysis at four different scales (250 x 250, 750 x 750, 1,250 x 1,250 and 1,750 x 1,750, all in meters). At the smallest scale most variables seemed to be roughly structured along two axes, one with landscape indices and one mainly with demographic factors but also impervious surface and coniferous forest. The other land-cover types did not align very well with these two axes. When increasing the scale this pattern was not as obvious, instead the variables separated into several smaller bundles of highly correlated variables. Some pairs or bundles of variables were correlated on all scales and thus interchangeable while other associations changed with scale. This is important to keep in mind when one chooses measures of urbanization, especially if the measures are indices based on several variables. Comparing our results with the findings from other cities, we argue that universal gradients will be difficult to find since city shape and size, as well as available information, differ greatly. We also believe that a multivariate gradient is needed if you wish not only to compare cities but also ask questions about how urbanization influences the ecological character in different parts of a city.