期刊
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
卷 6, 期 2, 页码 -出版社
MDPI AG
DOI: 10.3390/ijgi6020055
关键词
regional phenomena; remote sensing; global urban footprint; settlement pattern; urban nodes; Europe; mega-region; urban corridor; spatial analysis
The spatial patterns of landscapes are complex. Highly dense urban centers are not just mirrowed in a dichotomic sense by rural environments; landscapes are a spatially variable continuum. In this logic, nation-states (or any political or administrative unit) spatially integrate different types and physical appearances of land cover. Understanding regions in the sense that similar physical characteristics may construct alternative (natural) spatial entities which may sub-divide or cross-over adminstrative boundaries allows us to overcome common map projections. However, which indicators and which regional logics define and delimit regions is conceptually vague. With this paper we aim to add an empirical study to identify regional phenomena in Europe. To do so, we take advantage of a new data set from remote sensing, the Global Urban Footprint. It features European-wide consistent spatial information on settlement patterns. We use density and distribution of settlements as indicators for delimiting regions by similar characteristics. Our methodological approach classifies urban nodes (by settlement density and size), spans an unbounded soft space by the classification of spatial connectivity between nodes (by continuous settlement) and maps territorial entities (by density around nodes); the approach is following a space of place logic. From a geographic perspective we identify uneven development across Europe. The corridor streching from England via the Benelux areas via Germany, Switzerland, France to Northern Italy is mapped as the European backbone; however, new focal areas such as, e.g., towards eastern Europe are also detected. Applying a plausibility check reveals that the proxy settlement pattern corresponds well with regional conceptions presented in other studies.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据