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Competition between cities and regions in Europe. Can smart spatial planning interact with gravitational site location models for external investment?

机译:欧洲城市和地区之间的竞争。智能空间规划能否与重力场地位置模型相互作用以进行外部投资?

摘要

However smart a city or a region might be, a wide range of companies (eg in retail and services) use a gravitational model for site location for new investments. If the primary choice model is a gravitational one, being smart will only matter for site location within a region. From a spatial planning point of view, the right question is ‘can we influence gravitational site location choice while applying intelligent and consistent long term planning?’. udFirst we implement a multi-scalar gravitational analysis of the EU-28 area, allowing to define a gravitational central area. We use the population density dataset (inhabitants per hectare calculated from Corine Land Cover 2006) provided by the European Environmental Agency and Joint Research Center. Spatial statistics allow us to define areas that have significantly more inhabitants and are thus ‘gravitational centers’. By applying different influence ranges, we get four different perceptions of centrality. With an influence distance of 100km we see the european core area, while on the opposite end a 10km distance gives us a wide range of central places for services of proximity. This provides every city or region with insight in the way the gravitational choice model influences investment in regions. For spatial planning, it is almost impossible to influence this with traditional planning instruments. Competition between regions and states on the European level is mostly defined by national (tax) policy and cultural differences. udIn a second part, we take a closer look at the regional level. For an equal area around (1) Brussels, (2) Milano-Venezia, and (3) Wien-Bratislava we apply the same spatial statistics calculations with different influence zones. The analysis on a regional level shows clear differences in regional development and in the position of cities within the region. For the Flemish region we confront the pattern of central areas with the statistical analysis of the actual location of firms.
机译:无论城市或区域多么聪明,各种各样的公司(例如零售和服务业)都使用重力模型来确定新投资的地点。如果主要选择模型是万有引力模型,那么聪明只会与区域内的站点位置有关。从空间规划的角度来看,正确的问题是“在应用智能且一致的长期规划时,我们能否影响重力站点的位置选择?”。 ud首先,我们对EU-28区域执行多尺度重力分析,从而定义了重力中心区域。我们使用了由欧洲环境署和联合研究中心提供的人口密度数据集(每公顷居民数,根据2006年科林土地覆盖量计算)。空间统计数据使我们能够定义人口明显更多的地区,因此是“引力中心”。通过应用不同的影响范围,我们得到了四种不同的中心观。在100公里的影响距离内,我们看到了欧洲核心区域,而在另一端,则有10公里的距离为我们提供了广泛的邻近服务中心。这为每个城市或地区提供了有关重力选择模型影响地区投资方式的见解。对于空间规划,几乎不可能用传统的规划工具来影响它。欧洲地区和国家之间的竞争主要由国家(税收)政策和文化差异决定。在第二部分中,我们将仔细研究区域级别。对于(1)布鲁塞尔,(2)米兰-威尼斯和(3)维也纳-布拉迪斯拉发周围相等的区域,我们将相同的空间统计计算应用于不同的影响区域。区域层面的分析表明,区域发展和区域内城市的位置存在明显差异。对于佛兰芒地区,我们通过对企业实际所在地的统计分析来应对中部地区的格局。

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