Book Reviews

Books reviewed:
M. Steiner (ed.), Clusters and Regional Specialisation. On Geography,Technology, and Networks
Denis J.B. Shaw, Russia in the Modern World. A New Geography
Ron Martin, Money and the Space Economy     

青海古代文化遗址时空分布特征

本文对青海古代各历史时期的文化遗址及文物进行了分析与探讨,提出了青海古代文化遗址有着分布的集中性、石器时代的完整性以及多元结构的民族文化特点;论证了以上特点是由地理环境及历史的各民族文化活动所致。     

乡村振兴背景下农村基本公共服务与多维贫困的时空耦合特征研究

村级尺度上探索农村基本公共服务与区域贫困之间的关联特征以及二者耦合作用机理,是实现精准扶贫与乡村振兴战略有机结合的重要一环。本文分别建立农村基本公共服务和多维贫困综合发展监测模型,结合时空探索性分析和耦合协调分析方法,综合揭示两者的时空发展分布特征及其耦合关联关系。2015—2018年研究区内58个行政村的实证结果表明：①研究区内农村基本公共服务的发展呈中段高、南北段低的空间非均衡性分布,整体发展差异呈缩小趋势;②研究区内贫困村的多维贫困状况在空间分布上呈现出中北段地区贫困程度较轻、南段贫困程度较深的格局;③农村基本公共服务与多维贫困存在空间负相关性关联与明显耦合,且自实施乡村振兴战略以来,贫困村多转为同步型发展。研究结果可为现阶段乡村振兴战略的实施提供科学的决策依据和参考。     

Exploring the associations between cooling centre accessibility and marginalization in Montreal,Toronto, and Vancouver,Canada

Cooling centres provide respite, safety, and social support during extreme heat events for populations that do not have the resources to own or operate in-home air conditioning. The objective of this study was to measure the spatial accessibility of cooling centres and analyze the associations between cooling centre access and marginalization in Montreal, Toronto, and Vancouver, Canada. The potential spatial accessibility of cooling centres within a 15-minute walk was measured at the dissemination area scale using the two-step floating catchment area method. A two-stage modelling approach was used to analyze the associations between cooling centre access and marginalization. Approximately 62%, 58%, and 54% of the populations in Montreal, Toronto, and Vancouver had access to at least one cooling centre. In Montreal and Vancouver, high marginalization areas were more likely to have cooling centre access than low marginalization areas. Of the areas with cooling centre access, smaller access scores were observed in areas with high residential instability. Approximately one-fifth of the areas in each city had no cooling centre access and high marginalization, and may be considered for future cooling centres or programs that improve accessibility to existing centres.     

The ripple effects of large-scale transport infrastructure investment

We analyze the general equilibrium effects of an asymmetric decrease in transport costs, combining a large-scale spatial dynamic general equilibrium model for 267 European NUTS-2 regions with a detailed transport model at the level of individual road segments. As a case study, we consider the impact of the road infrastructure investments in Central and Eastern Europe of the European Cohesion Policy. Our analysis suggests that the decrease in transportation costs benefits the targeted regions via substantial increases in gross domestic product (GDP) and welfare compared to the baseline, and a small increase in population. The geographic information embedded in the transport model leads to relatively large predicted benefits in peripheral countries such as Greece and Finland, which hardly receive funds, but whose trade links cross Central and Eastern Europe, generating profit from the investments there. The richer, Western European nontargeted regions also enjoy a higher GDP after the investment in the East, but these effects are smaller. Thus, the policy reduces interregional disparities. There are rippled patterns in the predicted policy spillovers. In nontargeted countries, regions trading more intensely with regions where the investment is taking place on average benefit more compared to other regions within the same country, but also compared to neighboring regions across an international border. We uncover that regions importing goods from Central and Eastern Europe enjoy the largest spillovers. These regions become more competitive and expand exports, to the detriment of other regions in the same country.     

AGGREGATION ERROR EFFECTS ON THE DISCRETE-SPACE p-MEDIAN MODEL: THE CASE OF EDMONTON, CANADA

The spatial analysis literature recognizes three sources of aggregation error, termed Source A, Source B, and Source C, which affect models relying on distance measurements between populations and facilities. We consider these effects with respect to aggregating from census enumeration areas to census tracts, on a popular location model. We identify a further source of aggregation error, which we dub Source D error, arising from the representation of facility sites by discrete points. Source D effects are of the same magnitude as Source A and B combined, much greater than Source C effects. Source D error is further significant, because, unlike Source A and B error, it can be eliminated only by disaggregating .
La littérature sur Vanalyse spatiale reconnaît trois sources d'erreur d'agrégation appelées erreurs de source A, B, et C. Ces erreurs influencent les modèles qui reposent sur des mesures de distance entre des populations et des installations. On considère les effets d'agrégation des secteurs de dénombrement en secteurs de recensement sur un modèle de localisation courant. On identifie une quatrième source d'erreur d'agrégation appelée erreur de source D. Cette erreur découle de la représentation des sites des installations par des points discrets. Ses effets sont du même ordre de grandeur que ceux des sources A et B combinées et beaucoup plus grands que les effets de source G. L'erreur de source D est d'autant plus significative à cause du fait que, contrairement aux erreurs de source A et B, elle ne peut être éliminée que par la désagrégation .     

SPATIAL DEPENDENCY OF SEGREGATION INDICES

A few researchers have mentioned the scale sensitivity of segregation index, D. In this paper, I discuss analytically and empirically why using large enumeration areal units usually results in low segregation measures, and using small areal units produces relatively high segregation measures. The discussion is also applicable to the multi-group variant of D. A major finding is that if people of the same ethnic groups are positively spatially auto-correlated, increasing the size of areal units of analysis may not lower D initially, because only people of the same group are added. But enlarging the areal units subsequently may include population of other ethnic groups, and therefore could lower D. However, if the boundaries of the larger enumeration units are drawn to include only population of the same group, then D will not change significantly. Both the spatial autocorrelation of ethnic group population and zonal pattern are critical factors in determining the scale sensitivity of D.     

多伦多都市区的居住空间结构研究

本文采用因子生态分析方法剖析多伦多都市区的居住空间结构。主成分分析表明,家庭构成、年龄构成、职业构成是形成城市居住分异的主要因素。聚类分析表明,家庭构成和年龄构成的分异呈同心园格局,职业构成的分异呈扇形格局。形成这种居住分异格局的机制包括动力机制、管理机制和行为机制三个方面。